  In a power grid, the electricity supply and demand must be balanced at all
times to maintain the system's frequency. In practice, the grid operator
achieves this balance by procuring frequency reserves in an ahead-of-time
market setting. During runtime, these reserves are then dispatched whenever
there is an imbalance in the grid. Recently, there has been an increasing
interest in engaging electricity consumers, such as plug-in electric vehicles
or buildings, to offer such frequency reserves by exploiting their flexibility
in power consumption. In this work, we focus on an aggregation of buildings
that places a joint bid on a reserve market. The resulting shared decision is
modeled as a large-scale optimization problem. Our main contribution is to show
that the aggregation can make its decision in a computationally efficient and
conceptually meaningful way, using the alternating direction method of
multipliers (ADMM). The proposed approach exhibits several attractive features
that include (i) the computational burden is distributed between the buildings;
(ii) the setup naturally provides privacy and flexibility; (iii) the iterative
algorithm can be stopped at any time, providing a feasible (though suboptimal)
solution; and (iv) the algorithm provides the foundation for a reward
distribution scheme that strengthens the group.

Optimization and Control