A Risk-constrained Two-stage Stochastic Model for Optimal Scheduling of Smart Autonomous Microgrids considering Demand Side Management

In this paper, a risk-constrained two-stage stochastic model is proposed for optimal scheduling of autonomous microgrids considering the participation of end-use customers in demand response programs. The goal of the proposed scheme is to maximize the profit of the microgrid operator in different conditions of the user's risk taking, so that customers pay the lowest cost for their energy consumption. Based on the proposed model, customers are able to provide part of the system's reserve capacity to deal with uncertainties by using smart and response loads capability. The uncertainties of the problem are due to the predicted error of renewable resources, energy prices and demand loads, modeled on scenario-based methods. In the proposed model, in order to deal with the effects of undesirable scenarios, an index for assessing the value of risk is employed to estimate the level of undesirable profits. In addition, in order to more accurately analyze the frequency and voltage limitations, an AC load flow is used in the problem-solving process that achieves more realistic result to the microgrid operation. Finally, the proposed model is implemented in a typical microgrid and the results are investigated in different cases.