Abstract
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.
Info
Journal Article, 2018
UN SDG Classification
DK Main Research Area
Science/Technology
