Optimal Price-Energy Demand Bids for Aggregate Price-Responsive Loads

In this paper, we seek to optimally operate a retailer that, on one side, aggregates a group of price-responsive loads and on the other, submits block-wise demand bids to the day-ahead and real-time markets. Such a retailer/aggregator needs to tackle uncertainty both in customer behavior and wholesale electricity markets. The goal in our design is to maximize the profit for the retailer/aggregator. We derive closed-form solutions for the risk-neutral case and also provide a stochastic optimization framework to efficiently analyze the risk-averse case. In the latter, the price-responsiveness of the load is modeled by means of a non-parametric analysis of experimental random scenarios, allowing for the response model to be non-linear. The price-responsive load models are derived based on the Olympic Peninsula experiment load elasticity data. We benchmark the proposed method using data from the California ISO wholesale electricity market.