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

Ming-Che Hu, Su-Ying Lu and Yen-Haw Chen

Applied Energy, 2016, vol. 182, issue C, 500-506

Abstract: 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, tradeoffs between cost and carbon dioxide emissions are presented.

Keywords: Demand response; Stochastic; Multiobjective; Nash–Cournot model; Uncertainty analysis (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (17)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:182:y:2016:i:c:p:500-506

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DOI: 10.1016/j.apenergy.2016.08.112

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