Stochastic-multiobjective market equilibrium analysis of a demand response program in energy market under uncertainty

In the electricity market, demand response programs are designed to shift peak demand and enhance system reliability. A demand response program can reduce peak energy demand, power transmission congestion, or high energy-price conditions by changing consumption patterns. The purpose of this research is to analyze the impact of a demand response program in the energy market, under demand uncertainty. A stochastic-multiobjective Nash-Cournot competition model is formulated to simulate demand response in an uncertain energy market. Then, Karush-Kuhn-Tucker optimality conditions and a linear complementarity problem are derived for the stochastic Nash-Cournot model. Accordingly, the linear complementarity problem is solved and its stochastic market equilibrium solution is determined by using a general algebraic modeling system. Additionally, the case of the Taiwanese electric power market is taken up here, and the results show that a demand response program is capable of reducing peak energy consumption, energy price, and carbon dioxide emissions. The results show that demand response program decreases electricity price by 2-10%, total electricity generation by 0.5-2%, and carbon dioxide emissions by 0.5-2.5% in the Taiwanese power market. In the simulation, demand uncertainty leads to an 2-7% increase in energy price and supply risk in the market. Additionally, trade-offs between cost and carbon dioxide emissions are presented. (C) 2016 Elsevier Ltd. All rights reserved.