  Many residential energy consumers have installed photovoltaic (PV) panels and
energy storage systems. These residential users can aggregate and participate
in the energy markets. A stochastic decision making model for an aggregation of
these residential units for participation in two-settlement markets is proposed
in this paper. Scenarios are generated using Seasonal Autoregressive Integrated
Moving Average (SARIMA) model and joint probability distribution function of
the forecast errors to model the uncertainties of the real-time prices, PV
generations and demands. The proposed scenario generation model of this paper
treats forecast errors as random variable, which allows to reflect new
information observed in the real-time market into scenario generation process
without retraining SARIMA or re-fitting probability distribution functions over
the forecast errors. This approach significantly improves the computational
time of the proposed model. A simulation study is conducted for an aggregation
of 6 residential units, and the results highlights the benefits of aggregation
as well as the proposed stochastic decision-making model.

Optimization and Control;Multiagent Systems;Systems and Control;Systems and Control