Stochastic Unit Commitment in the Presence of Demand Response Program under Uncertainties

Abstract

In this paper, impacts of various uncertainties such as random outages of generating units and transmission lines, forecasting errors of load demand and wind power, in the presence of Demand response (DR) programs on power generation scheduling are studied. The problem is modelled in the form of a two-stage stochastic unit commitment (UC) which by solving it, the optimal solutions of UC as well as DR are obtained. Generating units' constraint, DR and transmission network limits are included. Here, DR program is considered as ancillary services (AS) operating reserve which is provided by demand response providers (DRPs. In order to implement the existent uncertainties, Monte Carlo (MC) simulation method is applied. In this respect, scenarios representing the stochastic parameters are generated based on Monte Carlo simulation method which uses the normal distribution of the uncertain parameters. Backward technique is used to reduce the number of scenarios. Then, scenario tree is obtained by combining the reduced scenarios of wind power and demand. The stochastic optimization problem is then modelled as a mixed-integer linear program (MILP). The proposed model is applied to two test systems. Simulation results show that the DR improves the system reliability and also reduces the total operating cost of system under uncertainties.