Virtual Power Plant Operation Strategy Under Uncertainty With Demand Response Resources in Electricity Markets
Jeseok Ryu, Jinho Kim
Abstract
The importance of resources for balancing electricity supply and demand is increasing with the decentralization of power systems; the role of demand response is being emphasized to effectively deal with the volatility of renewable energy. In this study, a model to participate in the electricity market, especially energy and demand response, utilizing demand response resources by compensating for the uncertainty from renewable energy products is proposed. The probabilistic distribution of photovoltaic generation was derived based on stochastic programming and used as a framework for solving the optimization problem by reflecting the uncertainty of photovoltaic generation. Moreover, a demand response modeling approach to enhance flexibility was developed by estimating the maximum potential demand response capacity in an industrial load. The output of these models was used to derive an optimal operational strategy for participating in the day-ahead market. The results in a simulated Korean electricity market confirmed that the virtual power plant aggregator’s profits increased when using the suggested strategy for utilizing demand response resources.