text:
\section{Introduction}\label{intro}

The most important rule of power systems is that demand and generation should be balanced at all times.  In order to fit into the secure operational framework of today's power grid, generators need to be able to forecast and control their output power for the next day and commit to generating the amount of electricity that they are scheduled to produce by the independent system operator (ISO). Failure to do so will result in system reliability issues; therefore, to ensure compliance, stiff penalties are imposed on those not able to meet their schedule. This favors the predictable and controllable power which can be generated from fossil fuels. With today's mostly price-inelastic demand, incorporating considerable amounts of renewable generation, given the volatility and unpredictability of such sources, is a challenge  \cite{eric}.

 One way to overcome the dispatch issues associated with renewable resources is through a cyber system in support of making energy demand both observable and controllable. One embodiment of the so-called Smart Grid is a model for \textit{smart} devices to become flexible agents, distributed across the grid, whose demand can be modified, either in a centralized or a distributed manner, via programs that produce market efficiency. These flexible agents could, among other things, modulate the demand to more easily integrate volatile renewable generation sources in the system, especially those available locally, at the edge of the distribution network.

To help this remarkable transition, utility companies are introducing smart meters, whose deployment is referred to as the Advanced Metering Infrastructure (AMI) \cite{AMI}). The AMIs are currently used to improve the prediction accuracy of the load and curtail demand during emergencies. The question is {\it when, how and with what incentives} load control could be performed on a regular basis.

\vspace{-.4cm}
\subsection{Previous Work
Previous work on demand management techniques can be categorized into either price-based load control techniques, which fall under the class of Demand Response (DR) methods, or direct load control (typically through curtailment), which is classified as Demand Side Management (DSM).

Price-based load control strategies include Time Of Use (TOU), Critical Peak Pricing (CPP), or Real-Time Pricing (RTP) techniques, all of which require customers to make energy usage decisions individually based on pricing signals.
In TOU pricing strategies, the price data is usually delivered months or years before the actual time of use. There have been several studies on determining these rates, which requires a dynamic model for the price response of customers, typically derived based on experiments \cite{TOU1,TOU2}. TOU can ameliorate customer behavior and smoothen the daily demand profile, but has little chance of aiding the integration of volatile resources. In RTP, instead, price information is provided only hours before consumption. With RTP, there is a need for an automated system to help the customer make energy usage decisions; generally they are referred to as Home Energy Management Systems (HEMS) (see e.g., \cite{amirhamed,Han}). HEMS plan the customers consumption given pricing data, appliance power profiles, job deadlines, and user preferences.  RTP strategies are appealing since they correct inefficiencies with a decentralized market driven control, but raise some concerns in terms of safety. Real-time prices are not actually real-time since they have to be delivered to the customer beforehand, to allow some planning time. Also, the presence of a feedback loop due to customer response may result in rebound peaks that can worsen the situation \cite{kishore} and can also lead to physical and price instability \cite{mitter}. An important question is how to compute the optimum price for each end-use customer without introducing economic and physical safety issues. Can these prices be equal for every customer, or type of appliance, in a neighborhood, or should they change? Should they be updated continuously, or in an event-driven fashion? Determining pricing also requires extensive knowledge about customer behavior: on pre-determined rates, customers are much more predictable.

Demand Side Management strategies are, in contrast, built for safety. They are usually applied directly by a control center, and require customer subscription to an economic incentive program. The first techniques emerged in the 60's and are currently employed through the so-called \textit{Interruptible Load} programs, where some of the customers appliances, upon receiving a notice, are  automatically turned off for a pre-determined amount of time (15-30 minutes).  Several methods have been proposed to determine the best load curtailment strategy \cite{LC1,LC2}.  These schemes have the benefit of aggregating several load assets but  their pitfall is that it is hard to determine off-line the degree to which they inconvenience the customers. Thus, these programs are normally used only in emergency situations.

In recent years, the deployment of advanced two-way communication links are leading to rethink \textit{centralized load control}. Rather than the utility, an aggregator could directly control end-use appliances and tap not only customers HVAC (heating, ventilation, and air conditioning) systems but also on their electric vehicle (EV) batteries \cite{maxzhang}. Next, we explain that EVs and HVAC have significant differences and, in our view, require separate treatment.

\subsection{Classification of Loads and research on Deferrable Loads}
There are three main classes of appliances used by residential customers. A first class of automata is one whose load profile, once on, is predictable. This class includes, for example, EVs, dishwashers, washers/dryers etc. Given that their cycles last for a long time, their starting time can be easily shifted, but their operation should not be interrupted. In this paper we specifically target this first class of {\it deferrable loads}. A second class of loads has a predictable profile except for an unknown duration. This class includes lighting, television sets, stereos etc. The service these loads deliver is extremely time sensitive, and so is their electricity demand. Therefore, the demand due to this type is not very flexible (except for dimmable lights).  Last but not least, the third class of loads includes, for example, thermostatically controlled appliances. These loads can be both interrupted and turned on earlier, but their load profile and the time sensitivity of the service depend non-linearly on a local state. Most centralized load control programs interrupt this class of appliances. Here we argue that there is an additional layer of complexity in capturing digitally their service model, and therefore, to avoid incorrect generalization, we currently exclude them from our treatment.

Specifically, we will name as {\it D-loads} those deferrable loads which, if enabled by embedded logic and two way communications, can specify their energy request to a remote control center and wait to be dispatched.

The most important {\it D-loads} are Electric Vehicles (EV). Researchers have proposed algorithms that control the energy use of EVs under dynamic pricing \cite{poor,korea}. Examples of direct control are the work in \cite{caramanis}, where the charging rate of EVs drawing from a single feeder is oprimized by dividing them into service queues depending on their desired time of departure; the work in \cite{somayeh}, instead, optimizes the charging rate of EVs by including them in the optimal power flow problem solved by the system operator.  The inclusion of deferrable loads in the energy market in the presence of renewables is the subject of \cite{homer,oren1}. In this line of work, the demand response assets are modeled as an aggregate tank/storage capacity that needs to be filled by a certain deadline. The DSM model we propose in this paper can provide a more accurate description of the load modification capability of an aggregator, and for the information flows to support the service.

\vspace{-0.1in}
\subsection{Contribution}
In this paper, we propose a direct load management scheme that mediates between the central control model of DLC and the {\it laissez faire} nature of RTP.
The scheme we propose in this paper is a direct control architecture that can be implemented as a voluntary program in which customers release the control of the time at which their D-loads start functioning to their associated neighborhood controller or {\it aggregator}.  They turn over this control in return for a financial reward for the inconvenience they experience, as their energy use is manipulated to follow a desired demand profile closely. We envision that the scheduling decisions are made at several distributed control centers that aggregate energy requests from many customers and make energy usage decisions that are relayed back to them.  Anticipating that aggregating energy requests up to a certain level will give us the benefits of scale, our model allows us to explore to what degree cooperation among customers benefits the efficiency of the system.
In fact, our scheme can be viewed as a model for building up {\it reservoirs of D-loads requests}, like a virtual water dam for loads, which can be dispatched optimally to follow the generation, thereby reversing the traditional roles played by generators and loads.

Our contribution is the introduction of a Digital Direct Load Scheduling (DDLS) model to manage D-loads and the network architecture that incorporates it. The model includes 1) an {\it encoding component} for controllable load, generation and for the feedback signals, 2) a {\it load scheduler} and 3) a {\it generation market interface}.  The encoding component allows deferrable appliances to become D-loads, which means that through the DDLS these appliances become capable of specifying their request for energy and release the control of their starting time to the scheduler, which determines their activation time in such a way to shape the load profile to follow available green generation. In this paper, we present the encoding component and the load scheduler aspects of our proposed model.  The proposed feedback mechanism informs the D-loads that need to be activated about the time they can start their job.  The description of how the proposed management system interacts with the electricity market and the extension of the DDLS to thermostatically controlled appliances is left as future research.

\section{The load model}\label{sec.model}\label{basic}

The load in the power grid is a mixture of random requests. In our model we separate the D-loads portion from the remaining part of the load. In fact, the load is:
\begin{equation}\label{loadeq}
L(t) = L^N(t) + L^{S}(t),
\end{equation}
where $L^N(t)$ represents the base load, which we presumably have no control over, while $L^{S}(t)$ is the {\it controllable part of the load} due to the D-loads.  Here, we consider $L^N(t)$  predictable using standard load forecasting methods (e.g., \cite{m1,m2,m3}).

The next step is to further fragment $L^S(t)$ into contributions from individual appliances. In the model, D-loads arrive in the system randomly following a non-stationary  arrival process:
\begin{eqnarray}\label{arrival}
a(t)=\sum_{i=1}^{\infty}u(t-t_{i}^a),
\end{eqnarray}
with $u(t)$ the unit step, $t_{i}^a$ the arrival time of the $i^{th}$ D-load of any type, and an arrival rate of $\lambda(t)$ for these appliances. Each arrival event $i$ has an associated parameter vector $C_{i}$ that determines uniquely the time evolution of the load contribution when that appliance is turned on. In fact, we assume that, if turned on at time zero, the D-load injection is the complex phasor signal $g(t;C_i)$, one to one with $C_{i}$. In general, $C_{i}\in \mathbb{C}^{N}$ can be the Nyquist samples, or the Fourier or Wavelet coefficients of the known load evolution after activation. A simple example is that of EVs, for which $C_i$ is a two-dimensional vector,
representing the charging rate and the fraction of battery capacity needed by the car upon its arrival.
 $C_{i}$'s are assumed to be i.i.d. random vectors with a known stationary probability distribution $f_C(c)$, independent of the arrival times. Thus, the $i$th arrival event is modeled by a tuple $(t^a_{i},C_{i})$.
If every arriving D-load is allowed in the system without any delay, the unscheduled demand profile would be:
\begin{equation}\label{lus}
L^{US}(t) =  \sum_{i=1}^{\infty} g(t - t_{i}^a;C_{i}).
\end{equation}
The degrees of freedom we will use in shaping the load is to delay the switch-on time for each D-load. Hence, the process of D-loads switching on is a {\it departure process}, in which the departure time $t_{i}^d>t_i^a$ is the time instant when the $i^{th}$ appliance is scheduled to switch on:
\begin{equation}\label{departure}
d(t)=\sum_{i=1}^{\infty}u(t-t_{i}^d),~~~t_{i}^d\geq t_{i}^a.
\end{equation}
In addition, it is convenient to include in $L^N(t)$ the load due to previously scheduled D-loads, since scheduled tasks are non-preemptable and we cannot reschedule them.  \footnote{This assumption is not as restrictive as it seems, since one could potentially impose an upper-bound to the request made, effectively breaking down the transaction in parts. We believe that this option would be much more practical than assuming jobs can be interrupted arbitrarily. }

Thus, the future values of $L^{S}(t)$ can be written as the following function of future departures
\begin{equation}\label{lev}
L^{S}(t) = \sum_{i\in I} g(t - t_i^d;C_i),~~~~t_i^d\geq t_i^a,
\end{equation}
where the set $I$ includes all D-loads that have yet not been scheduled, including those that have already arrived in the system at time $t$ but have not yet been authorized to function or the future arrivals.

\section{The Encoding Component of the DDLS}\label{commmod}\label{datarep}
To enable the optimal scheduling, the $i$th D-load communicates the tuple $(t_i^a,C_i)$ to the scheduler, upon its arrival.
Naturally, this information has to be digitized.

First, the charging codes $C_i$ are quantized through a mapping $\Psi(C_i)$ onto $Q$ codes $C_q,~q=1,\ldots,Q$, forming the codebook ${\mathcal C}=\{C_1,\ldots,C_Q\}$. The effect of this mapping is twofold: 1) it obviously
provides a digital representation of the incoming request that can be communicated; 2) it separates the  D-loads in $Q$ classes of service (queues), one per quantization code.
The arrival rate for the $q$-th queue is:
\begin{equation*}
\lambda_{q}(t) = \lambda(t) \int_{x \in \Psi^{-1}(C_{q})}f_C(x)dx,~~~q=1,\ldots,Q.
\end{equation*}

Since arrivals in different queues are independent processes, the arrival process $a(t)$ can be divided into $Q$ separate processes whose state can be represented by a vector $\bar{a}(t) = [a_1(t) \ldots a_Q(t)]^T$ of length $Q$ with the property that $\Vert \bar{a}(t)\Vert_1 = a(t)$. Each element of this vector is given by,
\begin{equation}
a_q(t)=\sum_{i=1}^{\infty} \delta(\Psi(C_i) - C_q) u(t-t_{i}^a),
\end{equation}
where $\delta(.)$ here represents the Kronecker delta function. The corresponding departure processes can also be represented by a vector $\bar{d}(t) = [d_1(t) \ldots d_Q(t)]^T$, also satisfying $\Vert \bar{d}(t)\Vert_1 = d(t)$. Each $d_q(t)$ is:
\begin{equation}
d_q(t)=\sum_{i=1}^{\infty} \delta(\Psi(C_i) - C_q) u(t-t_{i}^d).
\end{equation}
 We also know that $\bar{a}(t) \succeq \bar{d}(t)$, where $\succeq$ represents element by element inequality. This is simply due to the fact that the the number of departures from each queue can never be larger than the number of arrivals.
The quantization of the charge codes allows a simple system representation of the relationship between the individual queue departure processes and the total D-load, that is equivalent to \eqref{lev} for $Q\rightarrow \infty$. In fact, since the $C_{q}$'s are discrete values, the synthesis formula for the quantized load reconstruction is:
\begin{eqnarray}\label{conv}
\hat L^{S}(t)&= &\sum_{q=1}^{Q} \sum_{i\in I} \delta(\Psi(C_i) - C_q) g(t - t_i^d;C_q)\\
& =& \sum_{q=1}^{Q} \frac{\partial}{\partial t}d_q(t)\star g({t};{C_{q}}),
\end{eqnarray}
where  $\frac{\partial}{\partial t}{d}_q(t)$ will produce a Kronecker delta at each $t_i^d$ in the $q$-th queue and $\star$ is the convolution sign.

In order to work online and compute feasible schedules, the second step is to operate in discrete time intervals. Thus, we assume that the departure process $\bar{d}(t)$ can only have increments at discrete times:
\begin{equation}
t_{i}^d \in \lbrace \ell\triangle |\ell \in \mathbb{N}\rbrace.
\end{equation}
 Given the fact that both $t_{i}^d$'s and $C_q$'s are chosen from a discrete set, we can alternately represent the future D-loads contribution in \eqref{lev} for $t\geq \ell_0\triangle = \lceil\frac{t}{\triangle}\rceil\triangle$ as
\begin{equation}
\hat L^{S}(t)= \sum_{q=1}^{Q} \sum_{\ell=\ell_0}^{\infty} [{d}_q(\ell\triangle)-{d}_q((\ell-1)\triangle)] g({t-\ell\triangle};{C_{q}}).
\end{equation}
One can further assume that $\triangle^{-1}$ is higher than the Nyquist rate needed to sample the charge profile  $g(t;C)$ for all possible $\Psi(.)$ and that $g(t;C)$ is roughly constant over intervals of length $\triangle$. In this case, not only can the load be uniquely reconstructed from its samples but the arrival processes can also be represented in discrete time. From this point on we use a discrete model for arrivals, departure processes and for the load profile, and replace the previous quantities with their discrete-time counterparts:
\begin{equation} \left. \begin{array}{ll}
a_q(\ell\triangle)\rightarrow a_q(\ell),~~~d_q(\ell\triangle)\rightarrow d_q(\ell),~~~ \\
g({\ell\triangle};{C_{q}}) \rightarrow g_q(\ell),~~~~
\hat L^S(\ell\triangle) \rightarrow L^S(\ell).
\end{array} \right.
\end{equation}
The discrete-time load synthesis formula  from the decisions $d_{q}(\ell)$ and samples of the pulses $g_{q}(\ell)$ is:
\begin{eqnarray}\label{disload}
 L^{S}(\ell)&=& \sum_{q=1}^{Q} \sum_{k=\ell_0}^{\infty}[d_q(k)-d_{q}(k-1)]g_{q}(\ell-k) \nonumber\\
&=&  \sum_{q=1}^{Q} J d_{q}(\ell) \star g_{q}(\ell), ~~~~~~\ell\geq \ell_0,
\end{eqnarray}
where $J$ is the first difference operator. Fig. \ref{model} relates the queues states with the synthesis formula \eqref{disload}.

\begin{figure}
\centering
\includegraphics[scale=0.1]{dig2.pdf}
\caption{Diagram of the Load Synthesis Equation}
\label{model}
\end{figure}

\subsection{The Inconvenience Cost: Average Delay Model}\label{dci}
In order to measure the customers rewards, another quantity that requires modeling is the delay experienced by participants in the DDLS program. Scheduling the energy use of appliances is typically accompanied by deadlines preferred by the consumer, similar to most job scheduling algorithms. But, as in many other scheduling problems that handle diverse job profiles, incorporating deadlines will make the algorithm increasingly complex and not scalable. Specifically, with a random and non-stationary task arrival and resource model, incorporating deadlines would make our problem definition not suitable to handle a large scale customer base. Hence, we follow the path of many scalable computing and communication systems existing today that provide best-effort scheduling services without providing guarantees about the timing of resource delivery to an individual transaction (a great example of which would be the Internet, which currently provides one single class of {\it best-effort} service to voice and video traffic, which are typically severely degraded by delay). Thus, our algorithm will tolerate occasional deadline misses and will provide the maximum average QoS to the entire population and in return, with much lower communication and computational requirements. This is reasonable since we imagine that DDLS will be voluntary program and only customers with enough degrees of flexibility in their demand will participate in it. Customers with stricter deadlines shall resort to conventional service providers or be charged more than those accepting best-effort services.

It is a well known result in traffic flow theory that the total delay experienced by the customers in a queue, i.e. $\sum_i (t_i^d - t_i^a)$, is equal to the area of the queue polygon, that represents the state of the queue $s(t)$ versus time, and is obtained by superimposing the departure and arrival profiles, i.e.,
\begin{equation}
s(t) = a(t) - d(t).
\end{equation}
The delay experienced in the past by the D-loads currently present in the system is not amendable and so, it is not useful in the formulation of the optimization. Hence, for the purpose of optimal scheduling in the future, one can replace the total delay cost with the total delay experienced by all the customers from now on, which we call the {\it Delay Cost Increment} (DCI):
\begin{equation}\label{delay}
\mbox{DCI}(t) \triangleq C_I \int_t^{\infty} s(\tau)d\tau = C_I \int_t^{\infty} (a(\tau) - d(\tau))d\tau,
\end{equation}
where $C_I$ is the cost per unit of time delay\footnote{For a time-dependent delay cost
$\mbox{DCI}(t) = \int_t^{\infty} C_I (\tau) s(\tau)d\tau.$}.

 With quantization, it is also possible to define different delay costs $C_{I,q}$  for each service queue, allowing to offer higher QoS to customers in return for higher subscription rates.  To do so, we define a matrix $C_T = \mbox{diag}[C_{I,1}, \ldots C_{I,Q}]$:
\begin{equation}\label{delay5}
\mbox{DCI}(t)= \int_t^{\infty}\left\Vert\ C_T(\bar{a}(\tau)-\bar{d}(\tau)) \right\Vert_1 d\tau.
\end{equation}
In addition, when using a discrete set of decision epochs,
\begin{equation}\label{delay4}
\mbox{DCI}(\ell_0)=\left\Vert \sum_{\ell=\ell_0}^{\infty}C_T[\bar{a}(\ell)-\bar{d}(\ell)]\right\Vert_1,
\end{equation}
Where $\ell_0\triangle = \lceil\frac{t}{\triangle}\rceil\triangle$. Note that the interchangeability of integration and the $\mathcal{L}_1$ norm is possible since $\bar{a}(\tau) - \bar{d}(\tau) \succeq 0$.

\subsection{Network model}\label{datagat}

The communication network supports two directions of communication: the uplink towards the scheduler, and the downlink activation feedback from the scheduler to the loads.
We assume that the scheduler aggregates arrivals over a large number of customer premises, each of which pools the requests in a local Home Energy Management System (HEMS), interacting with the scheduler, which we refer as the Community Energy Management System (CEMS). While the CEMS gathers information and schedules the D-loads, another entity provides the interface to the market of generation assets.
We call this agent, the Green Energy Management System (GEMS).
The architecture is shown in Fig. \ref{fig.architecture}.

\begin{figure}
\centering
\includegraphics[scale=0.21]{mag.pdf}
\caption{The GEMS Architecture}
\label{fig.architecture}
\end{figure}

The encoding component we laid out above provides a clear basis to compute exactly the rate requirements associated with the DDLS, and in this section we measure the communication rate requirements necessary to enable the control mechanism.
\subsubsection{The Scheduler Uplink (HEMS to CEMS)}
To reconstruct and optimize the demand, the CEMS needs to know the increments of $\bar{a}(\ell \triangle)$, i.e., the arrivals in the queues.

We envision the HEMS as a software application run by non-dedicated hardware (a personal computer, or a smart-phone) and assume that the individual D-loads have a sensor network interface that allows them to convey their request to the HEMS in a local area network (via Bluetooth, Zigbee or new emerging standards for sensor network communications \cite{sensornetworks}).
HEMS locally compute the accrued inconvenience cost, and total consumption of D-loads in the premise over long time intervals. This information is communicated offline to track the quality of service delivered and for billing purposes.
However, given that the scheduler only cares about $\bar{a}(\ell  \triangle)$, the data communicated for real time scheduling can be both anonymized, as well as aggregated as they flow towards the CEMS.
The time sensitive bits correspond to the digital communication of the tuple $(t_{i}^a,q)$. Clearly, this requires $\log Q$ bits for the charging class.
The arrival time $t_{i}^a\approx \ell_i^{a} \triangle$, where $\ell_i^{a}$ represents its finite precision representation.
Let $\ell_{i}^n>\ell_{i}^a$ be the {\it notification} time index of the arrival, i.e., the time when the event is first recorded and added to the corresponding queue.
Let $D$ be the maximum network delay in units $\triangle$,  such that with overwhelming probability,
$\ell_{i}^n-\ell_{i}^a<D$; then, denoting by $\lfloor x\rfloor$ the floor function, this implies that $\lfloor  \ell_{i}^n/D\rfloor =\lfloor  \ell_{i}^a/D\rfloor$. Thus, the code
$$p_i^a=\ell_{i}^a-\lfloor  \ell_{i}^a/D\rfloor$$
allows to reconstruct the arrival time as
$\ell_{i}^a=\lfloor  \ell_{i}^n/D\rfloor+p_i^a.$
In this case, since $p_i^a\in \{0,\ldots,D-1\}$ clearly, encoding  $t_{i}^a$ only requires $\log_2 D$ bits.
Hence, considering that $\lambda(\ell\triangle)$ is the traffic of D-loads arriving in the system, the HEMS access channel needs to support an aggregate traffic of
\begin{equation}\label{eq.Rhems}
R_{\rm HEMS}(\ell)=\frac {1} {\triangle}\lambda(\ell\triangle)\log_{2}(DQ).
\end{equation}

As we discussed before, the traffic can be aggregated at the first network relay, acting as a base station (BS); for example a BS could map one to one with each area transformer or to a ISP node, by coalescing the arrival times into information about  $\bar{a}(\ell\triangle)$. If the arrivals follow a Poisson arrival process, $E\{\bar{a}(\ell\triangle)\}= \lambda(\ell\triangle)$ and the communication rate of the aggregate arrival vector is bounded by:
\begin{equation}\label{eq.Rcems}
R_{\rm CEMS}(\ell)= \frac 1 2 Q \log(2\pi e \lambda(\ell\triangle)).
\end{equation}

\subsubsection{Communicating the decisions back}
Consistent with our uplink model, we envision a downlink message structure that preserves the anonymity of the scheduled user. Once the CEMS decides the optimum schedule, it sends a feedback record, to let the vector $\bar d^{\rm opt}(\ell\triangle)$ of D-loads in. This feedback consists of a $Q \times 1$ vector $\bar{T}(\ell)$, which alerts all appliances in the corresponding classes $q=1,\ldots,Q$ that arrived before times $T_{q}(\ell)$ to enter the system.
The calculation of these vectors is performed as indicated in Fig. \ref{figdec}, i.e.,
\begin{equation}\label{alpha2}
T_{q}(\ell)=\max\lbrace \tau\leq \ell: a_{q}(\tau) \leq d_{q}^{\rm opt}(\ell)\rbrace.
\end{equation}

\begin{figure}
\centering
\includegraphics[width = 2.7in,height=1.5in]{decision3.pdf}
\caption{\small Mapping decisions into feedback messages}
\label{figdec}
\end{figure}

This system makes sure that the departures match the desired value, while guaranteeing the anonymity of the information about the access.
Also in this case it is not necessary to transmit absolute times $T_{q}(\ell)$.
Considering that the delay is an explicit cost for the optimization, and that the optimum decisions are correlated since the queue states are correlated,  $T_{q}(\ell)$ can be differentially encoded with a relatively modest rate requirement. More specifically, assuming that $\rho_q$ is the minimum correlation coefficient among the decisions $d_q(\ell)$ for D-loads in any class and at any time, and that the variance of the delay for appliances is bounded by $\sigma_{T_q}^2$, then each feedback vector requires a number of bits per second:
$$R_{\mathrm{feedback}}={\cal O}\left(\frac 1 \triangle \sum_{q=1}^Q\frac 1 2 \log_2(e (1-\rho_q^2)\sigma_{T_q}^2)\right).$$

\subsection{Optimal Quantization Rate}
Suppose that $\gamma\left(g\left({t};{C}\right),g\left({t};{Q(C)}\right)\right)$ is a distortion metric, measuring the quantization error in the reproduction of the individual load profile.
The average per queue and per load distortion $\chi_q$ caused by the load reconstruction technique is,
\begin{align*}
		\chi_q	= \int_{t=0}^{\infty}
			\int_{x\in Q^{-1}(C_{q})}\gamma\left(g\left({t};{x}\right),g\left({t};{C_{q}})\right)\right)f_C(x)dt dx.
\end{align*}
Weighting the relative contributions of each queue by the corresponding arrival rate $\lambda_q^{\max}=\sup_t \lambda_q(t)$, the  average distortion per unit time $\chi_{tot}$ is bounded by
\begin{equation}\nonumber
\chi_{tot} \leq \sum_{q=1}^{Q}\lambda_q^{\max}\chi_q.
\end{equation}
Hence, the number of codes/queues $Q$ can be chosen based on an appropriate rate-distortion optimization. For example:

1)~Minimize $Q$ (and, thus, the rate) while meeting a desired maximum distortion $\chi*$ in load reconstruction, i.e.,

\begin{equation*}\left. \begin{array}{ll}\label{detq}
{\min}~Q~~\mbox{s.t.}~~\sum_{q=1}^{Q}\lambda_q^{\max}\chi_q\leq \chi*.
\end{array} \right.
\end{equation*}

2)~Minimize the distortion, limiting the maximum bit rate,
\begin{equation*}\left. \begin{array}{ll}
\min_{{\cal C}} \sum_{q=1}^{Q}\lambda_q^{\max}\chi_q\\
\mbox{s.t.} ~~\underset{\lambda}\max ~R_{\rm HEMS} \leq R^{\max}_1~\underset{\lambda}\max ~ R_{\rm CEMS} \leq R^{\max}_2
\end{array} \right.
\end{equation*}
where the rate functions $R_{\rm HEMS}$ and $R_{\rm CEMS}$ are defined in \eqref{eq.Rhems}-\eqref{eq.Rcems} respectively. It is clear that the optimum in both cases is reached when the constraints are tight.

Next we sketch a few necessary elements of the market interface of our aggregator. We leave the complete development and analysis of this market interface to future work.

\section{The Electricity Market Interface}\label{sec.elmarket}
We assume that the GEMS cannot use its local renewables to export power to the upstream distribution grid and its generated electricity can only be used locally. The overall system including  the customers, renewables, CEMS and GEMS, needs to behave as a single retailer in the wholesale power market and it can also provide ancillary services. The various operational costs that the cell may have include:
\vspace{.2cm}
\\ {1) \bf Wholesale market day-ahead bidding cost}: by looking on the day-ahead forecasts of its local generation units and its demand pattern, the market interface issues a bid in the day-ahead wholesale market to purchase a certain amount of power for every hour of the next day, so that it can safely serve all of its load reliably.
\\ {2) \bf Wholesale market real-time bidding cost}: if local generation and day-ahead bid are insufficient to meet the demand, the market interface requests more energy from the central grid in the spot market. Also, if it has purchased extra amount of energy that it cannot consume, it can either sell it back to the grid or pay for negative spinning reserve, in case there is no demand for it. To model this cost, we assume that there is what we call the {\it supply curve} $B(t)+R(t)$, which includes the day-ahead bid plus  the the cell local renewable generation and that  there is a per unit cost of $C_{up}(t)$ for deviating upward and a per unit cost of $C_{dn}(t)$ for a downward deviation with respect to the supply curve. Subtracting the uncontrollable load $L^N(t)$ from the supply curve, we denote the Zero Incremental Cost (ZIC) power profile for D-loads by $P(t)$:
\begin{equation}\label{eq.zic}
P(t) = B(t) + R(t) - L^N(t).~~~~(\mathrm{ZIC-profile})
\end{equation}
For short look-ahead horizons, we assume that a reasonably accurate estimate of $R(t)$ is available and thus, $P(t)$ can be considered a deterministic function.
Also, we assume that near perfect estimates of the upward and downward balancing prices are available. For results on market clearing price forecasting techniques see \cite{olsson}.
\\ {3) \bf Inconvenience cost paid to customers:} This cost is paid either directly or indirectly to the customer, as an incentive to participate in DDLS programs.
We will model this cost using the concept of DCI introduced in \ref{dci}. The inconvenience cost per unit time can be variable with time of day and the queue in which the D-load is placed.

The cell should also purchase energy from its local renewable resources (if they are not owned by the cell). To cover the above mentioned costs, the cell bills its customers for the electricity it purchases from the wholesale market and on-sells to them. Also, a retailer with a DDLS program is in fact capable of providing several types of ancillary services with different dynamics and can provide peak shaving and price control services to the utility or the ISO in return for appropriate reimbursements to cover its costs. We leave a detailed discussion of these issues to our subsequent papers and instead, we will mainly focus on the scenario in which the cell has already bid in the day-ahead market $B(t)$ and has access to the information to determine the ZIC profile in \eqref{eq.zic}, and wants to minimize its costs in real-time.

\section{DDLS: The Real-time Scheduling Problem}\label{micrort}
The GEMS, which is in charge of the market interface of the cell, needs to purchase energy from the central wholesale market in order to satisfy the cell demand.
Thus, each day, the GEMS solves an optimization problem to determine the optimal day-ahead bid $B^*(\ell), \ell = 1,\ldots,24$ to be placed in the wholesale market for each hour of the next day. For the rest of this paper, we will assume that the day-ahead bidding process is done and focus on the real-time operation of the cell scheduler. The discussion on how to place these bids based on predictions of the wholesale market price, local generation resources and taking the DDLS ability into account requires considerable amount of space and will be presented in future works (for preliminary results, see \cite{ISCCSP}).

In real-time, the goal is to minimize the accumulated cost of operation over time. This can be accomplished through a sequential decision maker. In order to derive scheduling decisions that are foresighted, we choose to use a Model Predictive Control (MPC) model. Following our previous notation,  $P(\ell)$ , $R(\ell)$, $L^{S}(\ell)$, $C_{up}(\ell)$ and $C_{dn}(\ell)$ are samples of their continuous counterparts at $t=\ell\triangle$ (the costs are also multiplied by the interval length $\triangle$).
 Assuming a look-ahead horizon of $T$ units of time, and denoting by $u_q$ the duration of the jobs of appliances in the $q$-th queue, we can formulate the general real-time scheduling problem for the cell as,
\begin{align}\label{mainopt1}
D^{*} = \mbox{argmin}
_{D}~ &\operatorname{E}_A[\mbox{Cost of retail entity in real time}]\nonumber\\
 \mbox{argmin}_{D}~ &\sum_{\ell=\ell_0}^{\ell_0+T}\operatorname{E}_A \lbrace C_\ell(L^N(\ell) + L^S(\ell,D),B^*(\ell),R(\ell)) \nonumber\\ &~~~~~+ \mbox{DCI}(\ell_0,D)\}
\end{align}
$$\mbox{s.t.}~~~ \forall \ell \leq \ell_0+T, q\in \{1,\ldots,Q\}:~~ d_{q}(\ell-1) \leq d_{q}(\ell) \leq a_{q}(\ell)$$
$$~~~d_{q}(\ell) \in  \mathbb{N},~~~ d_{q}(\ell+T-u_q) = a_{q}(\ell+T-u_q),$$
where $C_\ell(.)$ represents a prediction of the \textit{real-time} cost that the cell incurs at epoch $\ell$ when purchasing electricity equal to $L^N(\ell) + L^S(D,\ell) - (B^*(\ell)+R(\ell))$ from the local intermittent resources or a central wholesale market (if negative, the retail utility may have to pay for negative spinning reserve). The matrix $D$ represents the set of scheduling decisions that will be made  in the look-ahead horizon, i.e. $D = [\bar{d}(\ell),\ldots,\bar{d}(\ell_0+T)]$ and $D^{*}$ represents its optimal value. The matrix $A=[\bar{a}(\ell),\ldots,\bar{a}(\ell_0+T)]$ represents the arrival process. $\mathcal{D}$ is the entire decision space, i.e., $D \in \mathcal{D}$ and $\mathcal{A}$ is the space defined by the arrival process, i.e., $A \in \mathcal{A}$.  $\mbox{DCI}(\ell_0,D)$ is the cumulative cost of delaying the customers, calculated in a finite horizon $T$. The first and second constraints are due to causality and the third constraint requires that all the arriving appliances finish their jobs by time $\ell_0+T$. Stricter deadlines can be imposed to provide higher QoS to certain queues.

Considering the costs defined in the Section \ref{sec.elmarket}, and denoting respectively by $P_{up}(\ell) $ and $P_{dn}(\ell)$ the upward and downward deviations from the ZIC power supply $P(\ell)$ in \eqref{eq.zic} for the D-loads, the scheduling problem in \eqref{mainopt1} can be formulated as the following mixed integer optimization problem,
\begin{align}\label{mainopt2}
 &\min_{D}  ~ \operatorname{E}\lbrace \sum_{\ell=\ell_0}^{\ell_0+T} [C_{up}(\ell)P_{up}(\ell)+ C_{dn}(\ell)P_{dn}(\ell)\nonumber \\&~~~~~~~~~+\sum_{q=1}^QC_{I,q}(a_q(\ell) - d_q(\ell))  ]\rbrace
\end{align}
$$\mbox{s.t.}~~~ \forall \ell \leq \ell_0+T, q\in \{1,\ldots,Q\}:~~ d_{q}(\ell-1) \leq d_{q}(\ell) \leq a_{q}(\ell)$$
$$~~~d_{q}(\ell) \in  \mathbb{N},~~~ d_{q}(\ell+T-u_q) = a_{q}(\ell+T-u_q),$$
$$\forall \ell \leq \ell_0+T:~~P_{up}(\ell) \geq 0,~~~P_{dn}(\ell) \geq 0,~~~P_{dn}(\ell)P_{up}(\ell) = 0,$$
$$P_{up}(\ell) - P_{dn}(\ell) + P(\ell) = \Re\{L^{S}(\ell,D)\},$$
where $\Re[ L^{S}(\ell,D)]$ represents the active (real) part of the D-load for $\ell>\ell_0$.

After solving the above optimization problem at time $\ell_0$, the scheduler informs the D-loads about its decisions on the optimum departure process $d_q(\ell_0)$ for each queue, and discards the decisions made for the future (the dummy variables). Afterwards, it needs to solve the optimization at time $\ell_0+1$ again. Since we assume that scheduled tasks are not interruptible, the load due to D-loads that were scheduled to start their job at time $\ell_0$ is added to the non-controllable part of the load at and after time $\ell_0+1$, i.e.,for $\ell \geq \ell_0+1$:
$$L^N(\ell) \rightarrow L^N(\ell) + \sum_{q=1}^{Q} [d_q(\ell_0)-d_{q}(\ell_0-1)]g_{q}(\ell-\ell_0).$$

 \begin{remark} The finite horizon assumption is made since ${P}(\ell)$ is non-stationary and our knowledge about it cannot be considered perfect in an infinite horizon. Also, forecast errors for the arrival pattern of customers increases with time.\end{remark}

 \begin{remark} In the following, we will ignore the reactive power load due to the scheduled D-loads and assume that the pulses $g_q(\ell)$ will represent active power requests only (i.e., $\Re[ L^{S}(\ell)] = L^{S}(\ell)$. But, if desired, one can easily incorporate reactive power requirements in the above optimization problem as a constraint:
$$
\Im [L^{S}(\ell)] = \sum_{q=1}^{Q} \sum_{i=\ell_0}^{\ell} (d_q(i)-d_q(i-1))\Im[g_q(\ell-i)]  \leq \epsilon .
$$\end{remark} For brevity, from this point on we omit the dependency on $D$ of both $L^{S}(\ell;D)$ and $\mbox{DCI}(\ell_0,D) $. Next, we relax the problem \eqref{mainopt2}, considering two scenarios for the arrival process.

\vspace{-0.3cm}
\subsection{Scenario I}\label{scen3}
In this scenario, we look at the case where the arrival process is deterministic but the rate $\lambda_q(t)$ is not constant in time. This problem can be formulated as \eqref{mainopt2} without the expected value operator.

\begin{lemma}If we ignore the case where $C_{dn}(\ell) < 0$, the constraint $P_{dn}(\ell)P_{up}(\ell) = 0$ can be eliminated from \eqref{mainopt2}.\end{lemma}
\begin{proof} (by contradiction). Assume that for epoch $\ell$, the optimum solution to \eqref{mainopt2}  is such that $P^*_{dn}(\ell)P^*_{up}(\ell) > 0$. One can replace these values by setting the smaller number to 0 and the larger one to $|P^*_{dn}(\ell) - P^*_{up}(\ell)|$. The constraints will all still hold while the cost will be reduced. Thus, the optimization problem without the constraint $ P^*_{dn}(\ell)P^*_{up}(\ell) = 0$ is equivalent to  \eqref{mainopt2}.
\end{proof}

To continue, we define the following matrices,
\begin{eqnarray}\label{defv}
D &=& [\bar{d}(\ell_0),\ldots , \bar{d}(\ell_0+T)]\nonumber\\ A&=&[\bar{a}(\ell_0),\ldots , \bar{a}(\ell_0+T)]\nonumber\\P&=& [P(\ell_0),\ldots ,P(\ell_0+T)]\nonumber\\
P_{up}&=& [P_{up}(\ell_0),\ldots ,P_{up}(\ell_0+T)]\nonumber\\
P_{dn}&=& [P_{dn}(\ell_0),\ldots ,P_{dn}(\ell_0+T)]\nonumber\\
C_{up} &=& [C_{dv}(\ell_0),\ldots,C_{up}(\ell_0+T)]\nonumber\\
C_{dn} &=& [C_{dn}(\ell_0),\ldots,C_{dn}(\ell_0+T)]\nonumber\\
C_{T} &=&  [C_{I,1},\ldots,C_{I,Q}].
\end{eqnarray}
\begin{lemma} \eqref{mainopt2} can be cast in the following constrained mixed-integer  linear programming problem:
\begin{equation} \label{opt7}
\min_{D,P_{up},P_{dn}} C_{up}P_{up}^T + C_{dn}P_{dn}^T - (C_T\otimes\mathbf{1}_{1\times L})\mbox{vec}(D^T)
\end{equation}
$$\mbox{s.t.}~~~  0 \preceq \mbox{vec}(D^T) \preceq \mbox{vec}(A^T),~ (I\otimes J^T)\mbox{vec}(D^T) \succeq 0,$$
$$ P_{up}\succeq 0, ~~ P_{dn}\succeq 0,~~\Gamma \mbox{vec}(D^T) + P^T + P_{up}^T - P_{dn}^T = 0, $$
$$ D \in  \mathbb{N}^{Q\times (T+1)}$$
where $\mbox{vec}$ denotes the vectorization operation. The matrix $\Gamma = [\Gamma_1~,\Gamma_2,~\ldots ~,\Gamma_Q](I\otimes J^T)$, where $J$ is the first difference operator,
and the matrices $\Gamma_q$ are the Toeplitz matrices associated with each $g_q(\ell) = g(\ell;C_q)$, with first row equal to
$[g_q(1), 0, \ldots , 0 ]$ and first column equal to $[g_q(1),g_q(2),\ldots,g_q(T)]$.
\end{lemma}
\begin{proof} We showed that the load due to D-loads is the sum of the following $Q$ functions:
\begin{equation}\left. \begin{array}{ll}
\forall q: ~L^{S}_q(\ell)= \sum_{i=\ell_0}^{\ell_0+T}  (D(q,i) - D(q,i-1))g_q(\ell-i)
\end{array} \right.
\end{equation}
which is basically the convolution of first difference of the $q^{th}$ row of $D$ with the vector $[g_q(1) ,\ldots, g_q(T)]$. Thus, using $Q$ Toeplitz matrices, each associated with one of the $g_q(\ell)$'s, and considering that $\mbox{vec}((DJ)^T)=(I\otimes J^T) \mbox{vec}(D^T)$, we can rewrite the load due to D-loads as the following vector
\begin{eqnarray}
L^{S} &=& [\Gamma_1~,\Gamma_2,~\ldots ~,\Gamma_Q](I\otimes J^T) \mbox{vec}(D^T). \nonumber
\end{eqnarray}
On the other hand, the DCI in \eqref{delay5} can be rewritten as
\begin{equation}\left. \begin{array}{ll}
\Vert C_T (A - D) \Vert_1 = (C_T\otimes\mathbf{1}_{1\times L}) (\mbox{vec}(A^T)-\mbox{vec}(D^T)). \end{array} \right.
\end{equation}
With the first term independent of the decision variables and thus, not contributing to the objective function minimization, we can add only the second term to the cost to represent the delay cost. The rest of the constraints in \eqref{opt7} are just transformations of the constraints in \eqref{mainopt2} to vector form.
\end{proof}

Since large-scale integer programs like \eqref{opt7} are complex to solve, we may choose to relax the problem by omitting the integrality constraints for the decision variables. The linear program obtained gives a lower bound on the optimal value of the integer linear programming problem (the feasible
region of the integer program is a subset of its corresponding LP relaxation problem) After solving the relaxed problem, we can round the fractional values to obtain integral solutions. A possible modification is to try relaxations based branch and bound algorithms and recurse into several relaxed subproblems until a good solution is found. Due to the large size of our problem, we resort to the simpler rounding solution.

\vspace{-0.4cm}
\subsection{Scenario II}
In this scenario, customers arrive according to a random arrival process with a non-homogeneous rate $\lambda(t)$, e.g. a Poisson process. Since we no longer have deterministic information about future arrivals and only the past is fully observable for us, we need to solve a stochastic shortest path problem:
\begin{eqnarray} \label{opt12}
C^{*}_{\ell_0}(\bar{x}(\ell_0)) =
\min_{\bar{d}} \sum_{\ell=\ell_0}^{\infty}  \operatorname{E}_{\bar{a}} \left\{c(\bar{x}(\ell),\bar{d}(\ell),\bar{a}(\ell))\right\}
\end{eqnarray}
where the vector $\bar{x}(\ell)$, representing the state (expanded to include previous decisions), and the function $c(.)$ representing the cost incurred at time $\ell$ are defined as
$$\bar{x}(\ell) = [P(\ell),\bar{d}(\ell-\min\lbrace \ell-\ell_0, S\rbrace),\ldots,\bar{d}(\ell-1)]^T,$$
\begin{eqnarray}
c(\bar{x}(\ell),\bar{d}(\ell),\bar{a}(\ell))&=& C_{up}(\ell)P_{up}(\ell)+ C_{dn}(\ell)P_{dn}(\ell)\nonumber\\&+& \sum_{q=1}^QC_{I,q}(a_q(\ell) - d_q(\ell)).\nonumber
\end{eqnarray}
A state variable is the minimal history that is
necessary and sufficient to compute the decision function \cite{castlelab}. For our case, this includes all the decisions made in the past that can affect the current load of the system and the ZIC power profile in \eqref{eq.zic}. If we assume that the appliances can be on for a maximum duration of $S\triangle$ units of time, the last $S$ decisions should be included in the state variable.

As our knowledge about the intermittent resources and the arrival trends of D-loads will degrade significantly with time, solving \eqref{opt12} is not practical. Based on this fact, we divide our look-ahead horizon into the categories below:
\\[0.1cm]
1) Full statistical knowledge interval: in this interval, we have full statistical information about the arrival process and the amount of available resource and thus, we exploit this knowledge in our decision strategy.
\\[0.1cm]
2) Imperfect information interval: during this interval, we have some information about the arrival and generation processes but our knowledge is not as accurate as the first interval and thus, we will only use the expected value of predictions.
\\[0.1cm]
3) No useful knowledge interval: after a certain amount of time, our knowledge about the arrival process and the resource will degrade so significantly that we would rather not incorporate them in our decision.

Hence, we redefine our optimized scheduling problem as:
\begin{equation} \label{opt10}
\min_{D\in \mathcal{D}} \operatorname{E}_{\bar{x}}\left\{ \sum_{\ell=\ell_0}^{\ell_0+T-1} c(\bar{x}(\ell),\bar{d}(\ell),\bar{a}(\ell)) +\hat{C}_{\ell_0+T}(\bar{x}(\ell_0+T))\right\}
\end{equation}
where $\hat{C}_{\ell_0+T}(x(\ell_0+T))$ is the approximation of the true cost-to-go function $C^{*}_{\ell_0+T}(x(\ell_0+T))$ after $T$ stages (the length of the full statistical knowledge interval). This approximation is found using a base suboptimal policy that we solve for assuming that the uncertain quantities in the imperfect information interval are fixed at their typical values. Thus, this is an $T$-step lookahead policy, with the optimal cost-to-go approximated by the cost-to-go of a certainty equivalent controller. Note that we have already discussed the possible strategies to solve this problem in scenario III. Also, we can reduce the number of possible states by using state aggregation strategies in the complete statistical knowledge interval in order to construct a more simple and tractable problem. This will make the computation much less demanding.

\begin{remark} We solved the scheduling problem by ignoring flow constraints of the distribution network. Since we do not take individual D-load delays into account and we only care about the total delay experienced by the customers, these flow constraints can be incorporated in the design with a simple modification using the following suboptimal policy: If the BS knows that it does not have distribution capacity to let any more appliances start functioning, it sends a full capacity message to the CEMS, which can be incorporated into  \eqref{alpha2}.\end{remark}

\vspace{-0.2cm}
\section{Numerical Results}\label{numerical}
In this section, we compare the effectiveness of the introduced scheduling policies exercised at a cell that controls the charging of a fleet of around 15,000 vehicles to the following two scenarios: the case where no control mechanism is provided over the load and the case where the control is applied in a more distributed fashion with 500 local schedulers spread across the area where the program is implemented. We assumed that the following information are available to the scheduler: 1) perfect predictions of the mean arrival rate of vehicles $\lambda(t)$;
2) causal observability of the arrival process $a(t)$;
3)  predictions of the ZIC power profile \eqref{eq.zic} in the lookahead horizon;
4) predictions of the upward and downward clearing prices in the lookahead horizon; and
5) accurate estimates of the load injections $g_q(t)$.
To avoid computational complexities and to make the resulting demand profiles more meaningful to the reader, we assumed that the charging duration of the vehicles has a maximum of 8 hours and is quantized in 15 minute intervals, which is equal to the frequency with which the scheduler solves the optimization problem. The appliances arrive in the system following a Poisson arrival process with a mean arrival rate $\lambda = 12$ per hour for each of the 32 queues, assumed to be constant, in order for the results to be interpretable. The optimizers solve the scheduling problem with a certainty equivalent controller that uses a relaxed linear programming approach to determine the best scheduling strategy. After each step, the scheduled D-loads are added to the uncontrollable load term for future epochs.  The upward and downward balancing prices were chosen to be equal and the charging pulses were assumed to be square pulses scaled to match the duration of charging.

Fig. \ref{sim} compares the demand in the following two scenarios: coordinated charging of all vehicles by one scheduler unit and uncontrolled charging.  The look-ahead horizon in these simulations is assumed to be 8 hours and to be fair, no appliance is allowed to be delayed beyond 8 hours after it's arrival, which in reality can differ for different queues. Thus, the number of appliances receiving service is equal in the two scenarios. The results show that the average delay experienced by customers if everybody participates in the DDLS  program is less than one unit of time and due to the considerable decrease in the deviation costs, there is a relative 41 percent reduction in operational costs compared to the uncontrolled case.
\begin{figure}
\centering
\includegraphics[scale=0.37]{test1.pdf}
\caption{\small DDLS allows to follow a certain generation profile}
\label{sim}
\end{figure}

Fig. \ref{sim2} compares the case where instead of a single scheduler unit, several schedulers are distributed across the area where the DDLS program is carried out (20 schedulers in our case, each scheduling around 20 EVs per hour). To showcase the more subtle differences in this comparison, we have scaled down our simulation horizon to 16 hours and decreased the arrival rate by half. The savings that resulted from the distributed schedulers were still considerable (21 percent).

\begin{figure}
\centering
\includegraphics[scale=0.34]{scenario2.pdf}
\caption{\small Higher level of aggregation leads to greater savings}
\label{sim2}
\end{figure}
In Fig. \ref{price}, we compare the load directly controlled by the DDLS scheduler to the case where a single price signal is broadcast to every vehicle, using which they locally minimize their cost for charging. Due to a lack of work that examines how to optimally design the pricing signal and, since the comparison is based on how well the controlled load can follow the day-ahead bid, the price signals were chosen to be a function of excess or shortfall of generation from the uncontrolled load profile (which is close to flat). Individual customers are provided with the price for the whole day. Several price functions were tested but they all led to similar results. Since customers act selfishly to minimize their own costs, this technique results in very high rebound peaks, occurring at times when the price is lower even by a small amount (due to small increases in the ZIC power profile in \eqref{eq.zic}). The conclusion that can be drawn from this result is that implementing pricing techniques, irrespective of how good the individual HEMS work, needs much more research. Also, sending a single price signal to all the customers can endanger the stability of the grid.
\begin{figure}
\centering
\includegraphics[scale=0.36]{pricing.pdf}
\caption{\small A single pricing signal for everybody results in rebound peaks}
\label{price}
\end{figure}

\vspace{-0.3cm}
\section{Conclusions and future work}
\vspace{-0.1cm}
In this paper, we introduced a novel DSM model for direct load scheduling. We provided a communication framework to defer the time at which loads turn on, after informing the control center about their arrival in the grid and service request. We described a cellular architecture that we consider suitable to integrate Digital Direct Load Scheduling programs into the grid. Finally, we formulated and solved the problem of managing the energy demand from loads that can be deferred during the real-time operation of the cell. Simulations showed that such a program can alleviate the problem of matching demand and generation considerably with minimal inconvenience to the customers and parsimonious communication needs. In our future work, we will study architectures to incorporate these large reservoirs of storable demand in the electricity market. We will also look more closely at the statistical information that is required to solve the scheduling problems, e.g. the arrival patterns of D-loads, their requests and the availability of renewables. Another major area for future work would be to look at how to integrate the degrees of freedom offered by thermostatically controlled appliances in a neighborhood DSM program (maybe with smaller coverage areas than what was considered in this paper).
\renewcommand{\baselinestretch}{1}

\bibliographystyle{IEEEtran}
\small

redpajama_set_name: RedPajamaArXiv


Not unusually, the western mainstream media have treated it as a total surprise, a shocking bolt from the blue. Their surprise is not surprising. They've been listening to the wrong people.
The Workers' Advice Centre is little known in Israel, even to most peace and human rights activists I met. But if ever a just peace is to grow in Palestine-Israel, WAC will have played a unique role in creating the grounds for it, by fighting steadily for the universal right to a life that's worth living. In any context these days, I'd say that qualifies as revolutionary.
By my reading of history, this is a long, steep uphill battle. Since Michal Shwartz has been at it for more than half a century, I asked her how she reads history.
In such a long view of history, Egypt's intifada is thrilling, but no surprise.


text:
Richard Clarkin
Captain Nemo
Richard Clarkin has been an established presence on Canadian stages and screens for thirty years. Recently he starred as John A. MacDonald in the Confederation plays for VideoCab at Soulpepper for which he received a Best Actor Dora nomination. For Mirvish Productions he starred as Scar in The Lion King, Biff in Death of a Salesman and appeared in The Heart of Robin Hood. Richard originated the role of Jacob Mercer in David French's Salt-Water Moon and has performed in numerous productions for Toronto's most innovative theatre companies including the Company Theatre and Necessary Angel. Richard is a graduate of the National Theatre School of Canada and a co-founder of the landmark theatre group Primus. He has performed across Canada especially in Winnipeg for MTC, PTE and MTYP. He recently starred in the film adaptation of The Drawer Boy for which he received a Best Actor ACTRA Award nomination. Richard is best known onscreen as Gord Ogilvey from the Goon hockey films. He appears regularly in Murdoch Mysteries as Chief Inspector Davis.
Jamie Mac
Captain Nemo (Persephone Theatre, Saskatoon)
Jamie Mac simply loves to tell a story; whether it's busking for change in his home downtown St. John's, Newfoundland, or playing Macbeth at Stratford, he just wants to be involved in all things passion. To perform at the Persephone Theatre is a deep honour for him, as it is the furthest from home he has ventured through theatre. Jamie is a graduate of Ryerson Theatre Acting, where he and Jesse Nerenberg (Jules Verne) became lifelong friends. He's also a former member of the National Art's Centre's English Theatre Company, and a graduate of the Stratford Festival Birmingham Conservatory. At the N.A.C. Jamie took much critical acclaim as Jacob Mercer in Salt-Water Moon, and after 4 seasons at Stratford boasts 12 shows, and five Stratford HD Shakespeare films. Most notably at Stratford, being the youngest actor to ever play Macbeth at the prestigious festival - for one show as the second understudy - after a string of unfortunate events. Recently Jamie played Petruchio in Taming of the Shrew at the St. Lawrence Festival, and guest starred in the season 11 finale of Murdoch Mysteries. Other notable credits include: Benvolio (Romeo & Juliet), Wickers (The Breathing Hole), Silvius (As You Like It), Lennox (Macbeth) at Stratford; Laurie (Vimy), Adam (Creation), Charley Bates (Oliver!) at Canada's National Arts Centre; Clown (39 Steps) at Stage West; David Jung (Rockbound) at Two Planks And A Passion; Michael (Elephant Song) Beothuk Street Players; Jerry (Zoo Story) Reid Theatre. His film credits include: Played, Beauty And The Beast, Republic Of Doyle, Covert Affairs, and Life With Derek. You can follow him on instagram or twitter @jamiemaclive
Katie Melby
Professor Aronnax
Katie Melby is very excited to be joining the amazing team and cast of Twenty Thousand Leagues Under the Sea. She is co-Artistic Director of 3 Sticks, a physical theatre company dedicated to making new work, that she co-founded with fellow graduates of the Lecoq-based London International School of Performing Arts in 2005. Their work has been presented across the US, Canada, and Japan. Her credits include Rite of Spring (Lincoln Center), Sister's Follies (Abrons Art Center), La Davina Caricatura (La Mama), The Cat Who Went to Heaven (Brooklyn Academy of Music), l'Arbre Enchanté (Fire Island Opera Festival), Firebird(Chilean Tour), American Weather (HERE Arts Center), and The Disappearing Man (Musical Theatre Factory). She is also a co-founder of Cloud City, a multi-disciplinary art space in Brooklyn, and a graduate of the American Musical and Dramatic Academy.
Jesse Nerenberg
Originally from Montreal, Jesse is an actor based in Toronto.
Selected Theatre: Julius Caesar, Antony & Cleopatra, Much Ado About Nothing, As You Like It, The Taming of the Shrew, The Three Musketeers (St. Lawrence Shakespeare Festival); Perfect Wedding (Magnus Theatre), A Midsummer Night's Dream (Chekhov Collective); The Whipping Man (Winnipeg Jewish Theatre); Twelfth Night (Repercussion Theatre); Romeo & Juliet (Citadel Theatre); Twelfth Night, Hamlet, Love's Labour's Lost, Macbeth (Shakespeare Bash'd); Casimir & Caroline(Howland Company); Birth (Pandemic Theatre); Journey's End (Empty Room); The SantaLand Diaries (Frosty Co-op); Equus (Hart House); Mary's Wedding (Brantbury Fair); Serious Money (RTS/Nightwood).
Film, TV, Voice-Over: Murdoch Mysteries (CBC), Fare Trade (Bell Media), Slasher Digital (Shaftesbury), Private Eyes(Global), Touring T.O. (Bell Media), Warehouse 13 (SyFy), The Transporter (HBO Canada), Canadian Made and Storming Juno (History Television), Trust, INC. (CBC Radio).
Other: Graduate of the Ryerson Theatre School and participant in the 2014 Citadel/Banff Professional Theatre Program.
Creative Crew
Rick Miller
Co-Creator/Director
Rick Miller is a Dora and Gemini award-winning writer/director/actor/musician/educator who has performed in five languages on five continents and who Entertainment Weekly called "one of the 100 most creative people alive today". He has created and toured solo shows such as the hit sensation BOOM, MacHomer, and (w. Daniel Brooks) Bigger Than Jesus and HARDSELL. With Robert Lepage, he has collaborated on Geometry of Miracles, Zulu Time, Lipsynch, and on the film Possible Worlds. As the artistic director of WYRD Productions and co-creative director of the Kidoons Network, Rick has most recently developed BOOM and BOOM X, and (w. Craig Francis) Twenty Thousand Leagues Under The Sea, GAME of CLONES, Jungle Book, and (w. Craig Francis and Paul Van Dyck) Frankenstein; as well as animated series that educate, enlighten, empower and entertain young people. He often teaches an interdisciplinary class at the University of Toronto called The Architecture of Creativity. Rick is from Montreal, and lives in Toronto with his wife Stephanie Baptist and their two daughters.
craig.francis@kidoons.com
Co-Creator/Stage Manager
Craig Francis is a writer, performer, visual artist and storyteller whose works have been enjoyed by millions of children worldwide. Co-creative director of the Kidoons Network and an accomplished cartoonist, he is the creator of animated series including Jerry Muskrat's The Greatest Lakes Adventure, Grandfather Frog's Water Wonderful World with museums and historic sites nationwide. He is a co-producer and Stage Manager with the hit show BOOM (Kidoons / WYRD Productions) and the co-creator with Rick Miller of new theatrical productions: Twenty Thousand Leagues Under The Sea, the Star Wars / Game of Thrones parody GAME of CLONES, Frankenstein (with Paul Van Dyck), and the upcoming Jungle Book and Rose Red. Craig has developed marketing for performing arts centres, illustrated several books, appeared as a guest on CBC, CTV, Global, and Showtime. His voices can be heard in animated series and video games.
Deco Dawson
Projection Designer
Deco Dawson is an international award winning filmmaker from Winnipeg, Canada. His 15 innovative short films remain at times unclassifiable, continually blurring the lines between dramatic, documentary, animation and experimental film, often creating fantastical worlds with miniatures, archival footage, meticulous set design, in-camera effects and grainy, textured filmstock. Dawson is a Canadian Screen Award nominee, and a two-time winner of the Best Short Film Award from the Toronto International Film Festival for his films KEEP A MODEST HEAD in 2012 and FILM(dzama) in 2001, which also won the Best Technical Innovation award at the 2002 Ann Arbor Film Festival. In addition to screening at major festivals worldwide, Dawson has been host to solo retrospectives of his work in France, Spain, USA and Canada.
Itai Erdal
Itai Erdal has designed over 200 shows in over 40 cities around the world. Some of the companies he worked for include: The Stratford Festival, Vancouver Opera, Vancouver Playhouse, Arts Club Theatre, Bard on the Beach, Citadel, Factory, Tarragon, Soulpepper, Volcano, ATP, Touchstone, Electric Company and Theatre Replacement. He received the Jack King award in 2005, a Dora Mavor Moore award in 2007, the Dublin Fringe Design award in 2008, Jessie Richardson awards in 2003, 2009 & 2011, Victoria's Critics' Choice Spotlight award in 2012 and a Guthrie Award in 2013. Itai's one-man show How to Disappear Completely (The Chop) has toured to 17 cities in North America and Europe and continues to tour nationally and internationally. It won the best director award at the 2013 Summerworks Festival. Itai is the artistic director of The Elbow Theatre in Vancouver and a member of Associated Designers of Canada. www.itaierdal.com
Richard Feren
Composer & Sound Designer
Richard has been creating soundscores and music for Canadian theatre, dance and film since 1992. Over the years, he has worked with many prominent theatre figures including Daniel MacIvor, Michael Hollingsworth, Peter Hinton, Sarah Garton Stanley, Daniel Brooks, Darren O'Donnell, Chris Abraham, Ann-Marie MacDonald, Albert Schultz, Guillermo Verdecchia; and companies across Canada, such as the Citadel in Edmonton, Theatre Calgary, Canadian Stage, Soulpepper, Buddies In Bad Times, Neptune Theatre, and the Shaw Festival. His work has been heard around the world, in cities like Budapest, Sydney Australia, Tel Aviv, Dublin, New York, Manchester, Amsterdam, Tehran, and Prague. He has also composed music scores for films by Daniel MacIvor, Robert Lepage, Valerie Buhagiar, and others. Richard has won seven Dora Mavor Moore Awards, the 1999 Pauline McGibbon Award, and was shortlisted for the 2012 Siminovitch Prize. www.haemorrhage-music.com/richard-feren
Irina Litvinenko
Multimedia Designer
Irina Litvinenko is an accomplished creative artist, graphic designer, and video production artist. Irina has been a longstanding collaborator with Rick Miller and Craig Francis, including as Multimedia Designer for Jungle Book and BOOM X; assisting on onscreen media and DVD production for MacHomer and its educational Animated Shakespeare videos, brand design for BOOM and BOOM X, and video sequences and design elements for Twenty Thousand Leagues Under The Sea. As a web and video artist, Irina is a designer, animator, and production editor of the Kidoons Network animated series. She has worked on advertising and multimedia campaigns for Performing Arts Centers across Canada and the US; for shows from BOWFIRE to Carol Burnett; and campaigns including TELUS, Cirque Musica, and the University of Kentucky Opera.
Andraea Sartison
Andraea Sartison is a theatre artist and event producer in Winnipeg, MB. She is the founding Artistic Producer of One Trunk Theatre, captaining the creation of 15 original productions and one festival, since the company's inception in 2012, including A Dollhouse of Commons, I Dream of Diesel, Mission Potluck, Taste and 204FM. She is known for boldly creative performance concepts, interdisciplinary collaboration, devised theatre and integrating technology into live performance. Andraea has travelled internationally as a performer and director of new Canadian plays, from the fringe circuit to Broadway. Notable collaborations include with Ghost River Theatre on their production of Last Voyage of Donald Crowhurst at Alberta Theatre Projects as Assistant Director to Eric Rose, and Twenty Thousand Leagues Under the Sea on international tours as Assistant Director to Rick Miller. She is Associate Artistic Director of Theatre Projects Manitoba and is Co-Owner of Event Production and Arts Consultation Company Fête Jockey.
Shawn Kettner
Puppet Designer
Puppet designer/builder Shawn Kettner has been creating puppets of all kinds for over 40 years. Her work includes everything from tiny 4" high Moomins to giant 10' dragons and dinosaurs. Shawn is pleased to once again have her puppet creations at The New Victory Theatre, last seen here in Comet in Moomin Land. Shawn's work has appeared in numerous productions, most recently The House of Pooh Corner, The Hobbit, Rapa Nui and The Cat Came Back. She is the artistic coordinator for Many Voices, One World; an artist collective focused on promoting peace and community building through storytelling and art projects in the schools. Her company Patient Puppets Inc. has produced over 2200 medical demonstration puppets for use in hospitals and clinics around the world.
Marcus Jamin
Marcus Jamin is an actor, puppeteer and designer. His puppetry work has been featured at Theatre Passe Muraille, the SummerWorks Festival, the Fresh Ideas Festival, the Lab Cab Festival and Les Trois Jours de Casteliers in Montreal. He has had the privilege of acting as the Workshop Assistant to Ronnie Burkett on his productions of Penny Plain and The Daisy Theatre. Most recently he designed and built the puppets for Outside the March's Mr. Burns, a Post-electric Play. Marcus is a graduate of the National Theatre School of Canada.
Hanna Puley
Additional prop design
Hanna Puley is a Toronto based theatre and film designer. Credits include design for Henri Faberge's Heligoland Follies, and Feint of Hart, costume design for Digits' music video Street Violence as well as costume design on the Canadian Screen Award winning webseries Space Riders. Season 2 finished shooting at the end of May. Recent credits include design of the short film She Stoops to Conquer starring Julian Richings and the world premier of John Patrick Shanley's A Woman is a Secret.
Laura Johnson-Sherratt
Associate Lighting Designer
Laura Johnson is a Canadian lighting designer, stagehand, and jack of all trades in the theatre world. She graduated from York University with a BFA in Theatre Production and Design. In 2011, she volunteered at the Prague Quadrennial and had her work showcased in the Dublin Fringe Festival. Since then, she has been predominantly working in the Kitchener-Waterloo / Toronto regions. In 2015, Laura was Associate Lighting Designer for Canada 300, a National Conversation piece that traveled to 21 predominant Canadian cities, and has assisted with Twenty Thousand Leagues Under The Sea through its process, in both Toronto and Quebec City.
Production Crew
Gabriel Cropley
Production Manager / Technical Director
Gabriel Cropley is a Toronto based lighting designer and three-time Dora Mavor Moore award nominee.
Recent credits include King Arthur Panto for Port Hope Theatre Festival, Kickstart for CanAsian Dance, Return of the Dead for NAfro Dance, Styll (Nuit Blanche Scarborough exhibits) for the City of Toronto, Sounding Thunder for Festival of the Sound, Llandovery Castle for Bicycle Opera, Category E for Coal Mine Theatre, and Tales of China for Little Pear Garden Dance.
Gabriel has had the privilege of collaborating with Alias Dance Projects, Young Voices Toronto, Ballet Creole, Expect Theatre, Lark and Whimsy Theatre, Julia Sasso Dance, dreamwalker dance, Angela Blumberg, Simcoe Contemporary Dancers, Avinoam Silverman Dance, Deviation Dance, Newton Moraes Dance Theatre, Danny Grossman, Sook-Yin Lee & Jennifer Goodwin, Cadence Contemporary Ballet, Ontario School of Ballet, Theatre Gargantua, Peggy Baker Dance Projects, Martha Hicks School of Ballet, Sampradaya Dance Creations, Hamilton Children's Choir, Tracey Norman, Sabina Perry, Forcier StageWorks, Soulpepper Global Cabaret, RAW Taiko Drummers, Ritmo Flamenco, Teatron Theatre, JDdance, Tribal Crackling Wind, Toronto Dance Theatre, Art of Time Ensemble, and the School of Toronto Dance Theatre.
Guifré Bantjes-Ràfols
Assistant Technical Director
Guifré Bantjes-Ràfols is a Catalan-Canadian actor and creator based in Toronto, ON. A member of both ACTRA and IATSE, he grew up in the theatre and has been a professional working on both sides of the industry since 2009; He has produced a number of projects, including the upcoming short film; Laundro, which he also wrote and acted in. On the technical side, he is an Electric with IATSE 873 but prior credits include: Venue Technician for the Saskatoon Fringe, ASM for Visió Ardent/Burning Vision in Barcelona (Tant per Tant), and Technical Director for TO WebFest 2018.
Jeff Lord
Jeff has a lifelong passion and vision for combining art and technology to develop original works. His projects are inspired by a love of storytelling and innovation. Through Kidoons theatrical productions and digital works on the Kidoons Network, Jeff's artist collaborators help organizations to tell their stories onstage and online. He works with Not-for-Profits and corporate clients across Canada and the United States with a vision to inspire and empower all generations.
Kidoons and WYRD Productions engages under the terms of the Independent Theatre Agreement, professional Artists who are members of Canadian Actors' Equity Association.
Twenty Thousand Leagues Under The Sea has been a journey for us, and we owe thanks to the following for helping us to explore, including:
Jeff Lord of Kidoons
Don, Iris, and Chris of PANAMANIA team for the initial commission.
We would like to acknowledge funding support from the Ontario Arts Council, an agency of the Government of Ontario.
Produced with the support of the City of Toronto through the Toronto Arts Council.
We acknowledge the support of the Canada Council for the Arts, which last year invested $153 million to bring the arts to Canadians throughout the country. Nous remercions le Conseil des arts du Canada de son soutien. L'an dernier, le Conseil a investi 153 millions de dollars pour mettre de l'art dans la vie des Canadiennes et des Canadiens de tout le pays.
Our talented workshop & performance casts: Raoul Bhaneja, Colin Doyle, Stephanie Baptist, Rob McLaughlin, Stefanie Wiens, Carson Nattrass, Toby Hughes, Gil Garratt, Andrew Shaver, Mary-Lee Picknell, Marco Poulin, Eric Leblanc, Marie-Ève Perron, Suzy Jane Hunt; Serafín Falcón; and Richard Clarkin.
The Francis, Miller, and Baptist families
Ravi Jain, Jason Knight, Michael Levine, Jung-Hye Kim, and Leslee Silverman
Manitoba Theatre for Young People
Allen MacInnis and Young People's Theatre
Andy McKim and Theatre Passe Muraille
The teams at La Caserne and Ex Machina
Deborah Knight and DKPR, Toronto
Our ever-expanding network of web series partner organizations across the continent... and to water heroes and New Atlanteans everywhere!
- Rick Miller and Craig Francis, co-creators
Thanks for support from
Panamania TO2015 Arts and Culture Festival
Kidoons

redpajama_set_name: RedPajamaCommonCrawl


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Palmarès

Olimpiadi
2 medaglie:
1 oro ( nel C1 1000 metri)
1 argento ( nel C1 500 metri)

Mondiali
4 medaglie:
1 oro (Belgrado 1978 nel C1 500 metri)
1 argento (Duisburg 1979 nel C1 1000 metri)
2 bronzi (Duisburg 1979 nel C1 500 metri; Nottingham 1981 nel C2 500 metri)

Collegamenti esterni

redpajama_set_name: RedPajamaWikipedia


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Monday Politics Chat: With Mandel Gone, Who Will GOP Senate Candidate Be?
91.7 WVXU | By Howard Wilkinson
WVXU-FM
Howard Wilkinson
WVXU politics reporter Howard Wilkinson spoke with New Director Maryanne Zeleznik Monday morning about the sudden withdrawal of State Treasurer Josh Mandel, a Republican, from Ohio's U.S. Senate race. It might have been a re-match between Mandel and Democratic incumbent Sherrod Brown - a 2012 race that Brown won by six percentage points. But now the picture on Republican side is muddled, at best. Will the GOP nominee be Cleveland banker Mike Gibbons or will a better-known GOP figure step forward?
Howard Wilkinson joined the WVXU News Team after 30 years of covering local and state politics for The Cincinnati Enquirer. A native of Dayton, Ohio, Wilkinson has covered every Ohio governor's race since 1974 as well as 12 presidential nominating conventions. His streak continued by covering both the 2012 Republican and Democratic conventions for 91.7 WVXU. Along with politics, Wilkinson also covered the 2001 Cincinnati race riots; the Lucasville Prison riot in 1993; the Air Canada plane crash at the Cincinnati/Northern Kentucky International Airport in 1983; and the 1997 Ohio River flooding. The Cincinnati Reds are his passion. "I've been listening to WVXU and public radio for many years, and I couldn't be more pleased at the opportunity to be part of it," he says.
See stories by Howard Wilkinson


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Opinion|An American in Paris
Opinion | Op-Ed Columnist
THOMAS L. FRIEDMAN JAN. 20, 2005
Watching George Bush's second inaugural from a bistro in Paris is like watching the Red Sox win the World Series from a sports bar in New York City. Odds are that someone around you is celebrating - I mean, someone, somewhere in Europe must be happy about this - but it's not obvious.
Why are Europeans so blue over George Bush's re-election? Because Europe is the world's biggest "blue state." This whole region is a rhapsody in blue. These days, even the small group of anti-anti-Americans in the European Union is uncomfortable being associated with Mr. Bush. There are Euro-conservatives, but, aside from, maybe, the ruling party in Italy, there is nothing here that quite corresponds to the anti-abortion, anti-gay, anti-tax, anti-national-health-care, anti-Kyoto, openly religious, pro-Iraq-war Bush Republican Party.
If you took all three major parties in Britain - Labor, Liberals and Conservatives - "their views on God, guns, gays, the death penalty, national health care and the environment would all fit somewhere inside the Democratic Party," said James Rubin, the Clinton State Department spokesman, who works in London. "That's why I get along with all three parties here. They're all Democrats!"
While officially every European government is welcoming the inauguration of President Bush, the prevailing mood on the continent (if I may engage in a ridiculously sweeping generalization!) still seems to be one of shock and awe that Americans actually re-elected this man.
Before Mr. Bush's re-election, the prevailing attitude in Europe was definitely: "We're not anti-American. We're anti-Bush." But now that the American people have voted to re-elect Mr. Bush, Europe has a problem maintaining this distinction. The logic of the Europeans' position is that they should now be anti-American, not just anti-Bush, but most Europeans don't seem to want to go there. They know America is more complex. So there is a vague hope in the air that when Mr. Bush visits Europe next month, he'll come bearing an olive branch that will enable both sides to at least pretend to hold this loveless marriage together for the sake of the kids.
"Europeans were convinced that Kerry had won on election night and were telling themselves that they knew all along that Americans were not all that bad - and then suddenly, as the truth emerged, there was a feeling of slow resignation: 'Oh well, we've been dreaming,' " said Dominique Moisi, one of France's top foreign policy analysts. "In fact, real America is moving away from us. We don't share the same values. ... In France it was a very emotional issue. It was as if Americans were voting for the president of France as much as for president of the United States."
That sense that America is now so powerful that it influences everyone else's politics more than their own governments - so everyone wants to vote in our elections - is something you hear more and more these days.
Elizabeth Angell, a 23-year-old American studying at Oxford, told me that a Pakistani friend at school had asked her if he could just watch her fill out her absentee ballot for the U.S. election. "He said to me, 'It's the closest thing I am going to get to voting. ... I wish I could vote in your election because your government affects my daily life more than my own.' "
The one concrete result of the U.S. election will probably be to reinforce Europe's focus on its own efforts to build a United States of Europe, and to further play down the trans-Atlantic alliance. "When it comes to emotions, the re-election of Bush has reinforced the feeling of alienation between Europe and the U.S.," Mr. Moisi said. "It is not that we are so much against America, it is that we cannot understand the evolution of that country. ... This election has weakened the concept of 'the West.' "
Funnily enough, the one country on this side of the ocean that would have elected Mr. Bush is not in Europe, but the Middle East: it's Iran, where many young people apparently hunger for Mr. Bush to remove their despotic leaders, the way he did in Iraq.
An Oxford student who had just returned from research in Iran told me that young Iranians were "loving anything their government hates," such as Mr. Bush, "and hating anything their government loves." Tehran is festooned in "Down With America" graffiti, the student said, but when he tried to take pictures of it, the Iranian students he was with urged him not to. They said it was just put there by their government and was not how most Iranians felt.
Iran, he said, is the ultimate "red state." Go figure.


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package pl.droidsonroids.rockpaperscissors.engine;

import java.util.List;

public interface ClientView {
    void showLastResults(List<UserChoice> results);
    void showCurrentResults(List<UserChoice> results);
    void setOnChoiceListener(OnUserChoiceListener listener);
}

redpajama_set_name: RedPajamaGithub


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Articoli correlati a Common Sense, Science and Scepticism: A Historical...
Musgrave, Alan Common Sense, Science and Scepticism: A Historical Introduction to the Theory of Knowledge
Common Sense, Science and Scepticism: A Historical Introduction to the Theory of Knowledge
Musgrave, Alan
Can we know anything for certain? Dogmatists think we can, sceptics think we cannot, and epistemology is the great debate between them. Some dogmatists seek certainty in the deliverances of the senses. Sceptics object that the senses are not an adequate basis for certain knowledge. Other dogmatists seek certainty in the deliverances of pure reason. Sceptics object that rational self-evidence is no guarantee of truth. This book is an introductory and historically-based survey of the debate, siding for the most part with scepticism to show that the desire to vanquish it has often led to doctrines of idealism or anti-realism. Scepticism, science and common sense produce another view, fallibilism or critical rationalism: although we can have little or no certain knowledge, as the sceptics maintain, we can and do have plenty of conjectural knowledge. Fallibilism incorporates an uncompromising realism about perception, science, and the nature of truth.
"The treatment of basic issues in epistemology is quite nicely done, and although the book is intended as an introduction, it is not confined to the coverage of elementary topics. Musgrave does devote a good deal of space to the discussion of such standard epistemological material as skepticism, but he also includes interesting, elegant, and informative summaries of problems and theories in logic, semantics, and the philosophy of mathematics. The book can be read profitably by anyone with an interest in epistemology and its history." Douglas M. Jesseph, Isis
An introductory and historically-based survey of the debate between epistemological scepticism and the opposing dogmatism, out of which a third view, fallibilism, or critical rationalism, is developed.
1. Common Sense, Science and Scepticism: A Historical Introduction to the Theory of Knowledge (Paperback)
Professor Alan Musgrave
Descrizione libro CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 1993. Paperback. Condizione: New. Language: English. Brand new Book. Can we know anything for certain? Dogmatists think we can, sceptics think we cannot, and epistemology is the great debate between them. Some dogmatists seek certainty in the deliverances of the senses. Sceptics object that the senses are not an adequate basis for certain knowledge. Other dogmatists seek certainty in the deliverances of pure reason. Sceptics object that rational self-evidence is no guarantee of truth. This book is an introductory and historically-based survey of the debate, siding for the most part with scepticism to show that the desire to vanquish it has often led to doctrines of idealism or anti-realism. Scepticism, science and common sense produce another view, fallibilism or critical rationalism: although we can have little or no certain knowledge, as the sceptics maintain, we can and do have plenty of conjectural knowledge. Fallibilism incorporates an uncompromising realism about perception, science, and the nature of truth. Codice articolo AAV9780521436250
2. Common Sense, Science and Scepticism
Descrizione libro Cambridge University Press, 1993. PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice articolo LQ-9780521436250
3. Common Sense, Science and Scepticism: A Historical Introduction to the Theory of Knowledge
Alan Musgrave
GoldBooks
(Austin, TX, U.S.A.)
Descrizione libro Cambridge University Press. Condizione: new. Codice articolo think0521436257
4. Common Sense, Science and Scepticism : A Historical Introduction to the Theory of Knowledge
Descrizione libro Condizione: New. Codice articolo 434180-n
Descrizione libro Cambridge University Press, 1993. Paperback. Condizione: BRAND NEW. Codice articolo 0521436257_abe_bn
Immagini fornite dal venditore
7. Common Sense, Science and Scepticism: A Historical Introduction to the Theory of Knowledge (Paperback or Softback)
Editore: Cambridge University Press 2/19/1993 (1993)
Nuovo Paperback or Softback Quantità: 10
Descrizione libro Cambridge University Press 2/19/1993, 1993. Paperback or Softback. Condizione: New. Common Sense, Science and Scepticism: A Historical Introduction to the Theory of Knowledge. Book. Codice articolo BBS-9780521436250
Editore: Cambridge University Press 1993-02-11 (1993)
Descrizione libro Cambridge University Press 1993-02-11, 1993. Paperback. Condizione: New. Codice articolo 6666-LSI-9780521436250
10. Common Sense, Science and Scepticism: A Historical Introduction to the Theory of Knowledge


text:
Le sora-be ou sorabe est un alphabet d'origine arabe adapté pour transcrire les langues du sud-est de Madagascar, en particulier l'antemoro. Plusieurs centaines de manuscrits anciens nous sont parvenus bien que les plus vieux d'entre eux ne semblent pas remonter au-delà du . La plupart des textes comportent des formules magiques mais on y trouve aussi quelques récits à caractères historiques rapportant l'origine de certains groupes humains de la région. Des origines que l'on fait parfois remonter jusqu'à La Mecque ou même à Mahomet, bien qu'en règle générale, la pratique même de l'islam fasse ici défaut, ce qui constitue un fait assez exceptionnel.

La connaissance du sora-be s'est répandue un peu partout à Madagascar dès le  et le roi merina Andrianampoinimerina fit venir auprès de lui des scribes antemoro pour initier à l'écriture des enfants de la cour. C'est ainsi que dès son enfance, le futur roi Radama savait lire et écrire.

Relevons enfin que l'appellation de sora-be, signifiant littéralement « écriture de grosse taille » a pu faire émettre l'hypothèse de l'existence auparavant d'un autre type d'écriture, aux caractères plus petits, que l'on pense être d'origine indienne, comme celle largement utilisée en Asie du Sud-Est.

Alphabet

Notes et références

Voir aussi

Bibliographie

Articles connexes
 `ajami'', nom qui, pour les locuteurs arabes, qualifiait les peuples non-arabes qui utilisaient l'alphabet arabe.

Variante de l'alphabet arabe
Langue à Madagascar
Système d'écriture en Afrique
Langue malgache


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Home»Devotees Experiences»With the grace of Sadhguru, I got M.S. seat.
By aumaujaya December 24, 2022 Updated: January 10, 2023 No Comments3 Mins Read
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Aumaujayaa: My name is Prashanthi. Ours is Kaikaluru. Jaimahavibhoshri: I saw them for the first time in a satsang held in my village. I can tell you that life is different before meeting Guru and life is different after meeting Guru. Before meeting Guru, my life was restless, searching, and unsatisfied. Whenever the Guru entered my life, it was replaced by complete satisfaction. At any moment of pain or fear, Aumaujayaa once from the heart: That is enough, all who were enemies till then become friends. Every moment is wonderful. After meeting Swami, I had many experiences and sensations. I am telling an example of it. I got married right after I finished in 2002. Later I did not do my P.G. due to any responsibility. But the desire to do UG remained in me. I.KG once said the same thing to Raju and said to ask Guru. When he was making a face to ask the Guru, he himself took him to the Guru and asked him. Immediately, the teacher said that you must read it. Then I asked my father if I want to study like that, I have to leave Kaikaluru. The teacher said that there is no need for that, mom, you can stay in Kaikaluru and study. I thought I could study because the teacher said so. But I failed at the entrance. Even if I fail in the exam, I am in government service so I will get one of the remaining bottom seats. Somehow I am satisfied that I also look like an M.D.
But every day at the center in Kaikaluru, sitting in front of Srimurthy, he told the Guru. I used to say every day that they should put Mr. Murthy in the hospital. I used to pray every day that the teacher would give me a good seat in Elur. In the meantime, the counseling for those who got the rank in the exam has been completed, everyone said that there are no seats left, and those who found them took them as they found them. Going for the remaining seats is called waste. This is what I heard from someone. I burdened the teacher and went to counseling. After some time I came to know that I am the first member of the Andhra region. Second in Stale is mine. I have 34 seats vacant. What kind of first rankers want are Ortho, Gyance, SPM, DGO, and Anastacia. But in Eluru, there is only one eye specialist seat and for a moment I did not understand what to do. I prayed even though I was alone for a long time. Jaimahavibhoshri: Then a flash flashed in Burra that this is a test for me and if I get a good seat I will have to leave Kaikaluru which means that I will not get corrupted from my sadhana. My father seemed to be asking me to decide whether I want the world or not. Aumaujayaa: Well, getting a seat in MS Ophthalmology is not an ordinary thing. To get this seat they study 24 hours for a year without any connection with the other world but all I did was pray to Aumaujayaa, and trust Aumaujayaa with Manasavacha Karmana. The thing that gave me the most joy was knowing that this word came from the mouth of the guru. There was a doctor in Kaikaluru in one of the Guru's satsangs and she could not get a seat. He said that he got this seat only because of my grace. Aumaujayaa:
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aumaujaya
Jai Mahavibhoshri solved all my problems
My body was balanced by Mahavibhoshree's suggestions.
I am really lucky to have met such a great guru.


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SEX-AS: TWO MORE TEACHERS BUSTED FOR LUST 101
ANGELA NEW
TWO more Texas teacher have been busted for having sex with their students, making that three in just over a month.
Cops picked up Angela New, 39, after she allegedly slept with an 18-year-old from her school a month before he was due to graduate.
And April Alexander, 26, was jailed after being accused of having sex with a 16-year old student on more than 25 occasions. This follows the jailing of randy Brittni "Gang Bang" Colleps, who allegedly staged a sex orgy at her home while her serviceman husband was away on duty.
Labels: Sex, Students, teachers, Texas
BUD WALLY RUIZ COULD GET LIFE IN DOG KILLING
HE'S on his third strike and it could well mean he serves a lifetime behind bars for the brutal killing of his pet chihuahua.
Bud Wally Ruiz threw his pet pooch at his wife Marcela after she objected to him taking it with him during a heated row with her at their Gilroy, CA home.
But he tossed the six-week-old puppy with such force the he killed it and now faces two felony counts for cruelty to animals.
He is also suspected of assaulting his wife before fleeing and was charged with a misdemeanor count of spousal battery.
Labels: Bud Wally Ruiz, Chihuahua, life sentence, Puppy
LINDSAY LOHAN 'FRIGHTENED' OF OBSESSED STALKER
FORMER actress Lindsay Lohan has taken out a restraining order against her last friend crazy stalker after he left chocolates at her house and sent bizarre text messages saying they are engaged.
David Corcodan, 38, has been contacting her for almost two years, court documents show, sending more then 100 texts including one describing in graphic detail having sex with the actress.
Another showed that he was in the courtroom last month when the 24-year-old actress was sentenced to 120 days in jail.
"Given this obsessive and harassing behavior, I am frightened of Mr. Cocordan and feel that my personal safety, and the safety of those around me, is in jeopardy," Lohan said in the legal filing.
Cocordan, who police believe is a schizophrenic and is not taking
Labels: jail, jewelry, Lindsay Lohan, Restraining Order, stalker, store, Theft
PIRATES PLEAD GUILTY TO AMERICAN DEATHS
AVAST YE. The Somalian pirates who shot and killed American's in a deadly high-seas attack have pleaded guilty to the killings.
But although they sent their innocent victims to Davy Jones' locker, they themselves are more likely to serve long sentences for the murders. In February, the four Americans were on a yacht in the waters off the Horn of Africa when more than a dozen Somali men and one Yemeni hijacked their vessel.
But in the midst of negotiations for their release some the hijackers
Labels: American murders, horn of Africa, Mohamud Hirs Issa Ali, Pirates, Somalia
MAD MARNI YANG GETS LIFE FOR 'COLD BLOODED' KILLING
MAD Marni Yang has been sentenced to life for the "cold and calculated" murder of the pregnant girlfriend of former Chicago Bears defensive back Shaun Gayle.
Rhoni Reuter "didn't stand a chance" after her bitterly jealous love rival plotted her death with the ruthless efficiency of a trained killer.
As we reported here, prosecutors said Yang who was "obsessed with" Gayle, feared that Reuter's pregnancy was a "game changer and he would leave her because of it.
So she started to plan her execution.
Buying a book on Amazon called "How to Make Disposable Silencers" she then bought all the parts needed to smother the sound of a gunshot, crime scene technicians testified here.
She also got shooting lessons from her ex boyfriend, Cook County Sheriff's deputy, Salvador Devera he testified here.
Labels: Marni Yang, murder, Rhoni Reuter, Shaun Gayle
MAD MARNI YANG GETS LIFE FOR 'COLD BLOODED' KILLIN...


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Law360 Quotes Goldberg Segalla Attorneys in Employment and Labor Articles
Caroline J. Berdzik
Goldberg Segalla attorneys Caroline J. Berdzik, Madeline S. Baio, and Michael S. Katzen recently offered analysis to Law360 on a range of issues in the employment and labor sphere.
Caroline commented on the Supreme Court's ruling in a case involving the Equal Employment Opportunity Commission (EEOC) and a dispute over attorneys' fees. As Law360 notes, the Supreme Court found that a defendant need not obtain a favorable Title VII judgment to be a prevailing party — but remanded the decision of whether the EEOC must pay close to $5 million in attorneys' fees back to the Eighth Circuit.
In doing so, the court "sends a clear signal to the EEOC that its failure to comply with its obligations in pre-suit investigations can result in a finding that a defendant is a prevailing party for purposes of being awarded attorneys' fees under Title VII," noted Caroline, who chairs the firm's Employment and Labor Practice Group. "This decision is a welcome to employers and should give pause to the EEOC in terms of how it comports itself in the charge and litigation process."
Another article examines the potential impact of the recent Supreme Court decision that set the filing period for a constructive discharge claim to begin when an employee resigns — instead of the employer's last act of discrimination. Madeline explained that the decision will impact federal and private-sector employees alike.
"As Justice [Sonia] Sotomayor noted, the EEOC treats federal and private-sector employee limitations period as identical in operations, citing the EEOC Compliance Manual," she told the publication. "The court's decision makes clear that the limitation period in these kinds of cases is not triggered by the last act of alleged discrimination by the employer nor is it triggered by the last day the employee actually works."
Mike told Law360 that the Department of Labor's final version of its overtime exemption rule goes into effect on Dec. 1 — giving employers "an opportunity to address any other wage and hour compliance issues that may be lurking in the workplace," he said. The rule raises the minimum salary threshold to qualify for the Fair Labor Standards Act's white collar exemption. As Mike said, "Businesses and organizations with currently exempt employees on the cusp of the annual salary level can take some solace in knowing that for the first time, employers may count nondiscretionary bonuses, incentive payments and commissions toward up to 10 percent of the required salary level so long as they are paid at least quarterly."
Read the articles here:
"Attorneys React to DOL's Final Overtime Exemption Rule," Law360, May 18, 2016
"Attorneys React to High Court's EEOC Attys' Fees Ruling," Law360, May 19, 2016
"Attorneys React to High Court's Constructive Discharge Ruling," Law360, May 23, 2016
Employment and LaborCaroline J. Berdzik
NYC Enacts Law Cracking Down on Use of Automated Screening Tools and Artificial Intelligence
New York State Department of Labor Adopts New York Paid Sick Leave Regulations and Proposes New York HERO Act Regulations
Sixth Circuit Court of Appeals Lifts Stay on OSHA ETS


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P is for Peril By Sue Grafton
P is for Peril
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P is for Peril Summary
In her latest adventure, Kinsey Millhone enters the world of noir. A shadowland in which the mysterious disappearance of a prominent physician leads Kinsey into a danger-filled maze of duplicity and double-dealing . . .It is now nine weeks since Dr Dowan Purcell vanished without trace. The sixty-nine-year-old doctor had said goodnight to his colleagues at the Pacific Meadows nursing home, had climbed into his car and driven away - never to be seen again. His embittered first wife Fiona is convinced he is still alive. His second wife, Crystal - a former stripper forty years his junior - is just as sure he is dead. Enter private investigator Kinsey Millhone, hired by Fiona to find out just what has happened to the man they loved. Enter also Tommy Hevener, an attractive flame-haired twenty-something who has set his romantic sights on Kinsey. And Tommy is a man with a very interesting past . . .'One of the more humane and empathetic sleuths on the block, Grafton's heroine is also genuinely believable, full of quirks and all too human foibles . . . Absolute top form' Time Out
About Sue Grafton
Sue Grafton was born in Louisville, Kentucky, in 1940, her father the mystery writer C.W. Grafton, whose own work gave his daughter the initial inspiration to write herself. She lives in Santa Barbara, California, with her husband Steven Humphrey.