A game-theoretic approach for optimal time-of-use electricity pricing

TLDR

Electricity demand fluctuates throughout the day, raising supply costs, and time‑of‑use pricing has been proposed to manage this variability. The paper proposes a game‑theoretic method (GT‑TOU) to optimize time‑of‑use electricity pricing. The authors model utility cost and user satisfaction, design utility functions for both parties, and compute a Nash equilibrium via backward induction, extending the analysis to multiple user types with distinct price sensitivities. Numerical simulations demonstrate that GT‑TOU levels demand, reduces utility costs, enhances user benefits, and improves social welfare, indicating higher market efficiency.

Abstract

Demand for electricity varies throughout the day, increasing the average cost of power supply. Time-of-use (TOU) pricing has been proposed as a demand-side management (DSM) method to influence user demands. In this paper, we describe a game-theoretic approach to optimize TOU pricing strategies (GT-TOU). We propose models of costs to utility companies arising from user demand fluctuations, and models of user satisfaction with the difference between the nominal demand and the actual consumption. We design utility functions for the company and the users, and obtain a Nash equilibrium using backward induction. In addition to a single-user-type scenario, we also consider a scenario with multiple types of users, each of whom responds differently to time-dependent prices. Numerical examples show that our method is effective in leveling the user demand by setting optimal TOU prices, potentially decreasing costs for the utility companies, and increasing user benefits. An increase in social welfare measure indicates improved market efficiency through TOU pricing.