The Impacts Of Energy Customers Demand Response On Real-Time Electricity Market Participants

In this paper, we consider the profit-maximizing demand response of an energy customer in the real-time electricity market. In a real-time electricity market, the market clearing price is determined by the random deviation of actual power supply and demand from the predicted values in the day-ahead market. An energy customer, which requires a total amount of energy over a certain period of time, has the flexibility of shifting its energy usage in time, and therefore is in perfect position to exploit the volatile real-time market price through demand response. We show that the profit-maximizing demand response strategy can be obtained by solving a finite-horizon continuous-state Markov decision process (MDP) problem. Through rigorous analysis, we show that the optimal actual demand policy exhibits a threshold structure, which can solve the MDP without the need of discretizing the state and action spaces. We demonstrate through extensive simulations that the proposed demand response strategy not only maximizes the profit of the energy customer, but also alleviates the supply-demand imbalance in the power grid, and even reduces the bills of other market participants. On average, the proposed demand response strategy increases the energy customer's profit by 53.8% and saves the bills of other utilities by 80.4% comparing with the benchmark algorithms.