Dynamic Pricing and Distributed Energy Management for Demand Response

TL;DR

This paper models dynamic electricity pricing using a Stackelberg game, analyzing the trade-offs between consumer surplus and retail profit, and examines the impact of renewables and storage on these dynamics.

Contribution

It provides a complete characterization of the demand-price relationship and Pareto front in a demand response setting with renewables and storage integration.

Findings

Optimal demand is an affine function of prices.

Pareto front of trade-offs is concave.

Renewable benefits shift from retailer to consumers as capacity increases.

Abstract

The problem of dynamic pricing of electricity in a retail market is considered. A Stackelberg game is used to model interactions between a retailer and its customers; the retailer sets the day-ahead hourly price of electricity and consumers adjust real-time consumptions to maximize individual consumer surplus. For thermostatic demands, the optimal aggregated demand is shown to be an affine function of the day-ahead hourly price. A complete characterization of the trade-offs between consumer surplus and retail profit is obtained. The Pareto front of achievable trade-offs is shown to be concave, and each point on the Pareto front is achieved by an optimal day-ahead hourly price. Effects of integrating renewables and local storage are analyzed. It is shown that benefits of renewable integration all go to the retailer when the capacity of renewable is relatively small. As the capacity increases beyond a certain threshold, the benefit from renewable that goes to consumers increases.