Operational Benefits Assessment of Demand Response Based on Linearized Consumers Satisfaction Constraints and Stochastic Simulation Method

The aggregation of flexible resources in demand side demonstrates a great potential to address the challenges brought by wind power integration. In this paper, we presented a probabilistic method to assess the synthetic benefits of demand response (DR) programs for power system operation under wind power uncertainty. First, the price-based DR programs are described through the elaborated modeling of demand-price elasticity and consumers satisfaction. Then, a short-term stochastic simulation method is proposed, where the randomness of wind generation is captured by Latin Hypercube sampling, and a two-stage stochastic program framework is developed to simulate the consumption re-scheduling in response to dynamic electricity tariffs. Moreover, the linearization technique is introduced to convexity the consumers satisfaction constraints, so that the assessment model converts to a computationally friendly mixed integer linear program (MILP). The simulation outcomes yield the DR performance metrics in several aspects, e.g., economics, renewable energy utilization, and reserve capacity adequacy. Numerical results validate the effectiveness of the proposed method, which demonstrates the benefits of DR by significantly improving the wind power utilization with a reduced operational cost and guaranteed consumers satisfaction.