Direct load control for electricity market risk management via risk-limiting dynamic contracts

Abstract

This paper proposes a new direct load control framework that provides financial risk management solutions for real-time electricity markets. In this program, a load-serving entity makes risk-limiting dynamic contracts with its customers to optimally manage its revenue and risk. This risk is generated by both price volatility and demand uncertainty regarding distributed renewable generation as negative load. The key feature of our contract method is its risk-limiting capability: the amount of risk transferred to each customer is less than or equal to a pre-specified threshold. This is achieved by formulating the contract design problem as mean-variance constrained risk-sensitive control. We develop a dynamic programming-based solution approach. We demonstrate the performance of the proposed contracts by using locational marginal price (LMP) data from the Electricity Reliability Council of Texas and data on the electric energy consumption of customers in Austin, Texas. The numerical experiments suggest that the proposed direct load control program efficiently manages the load-serving entity's and its customers' risks even when the load-serving entity passes the wholesale electricity price to the customers.