Day-ahead generation scheduling for variable energy resources considering demand response

Abstract

The presence of higher penetration of renewable energy generation (RES) requires more flexible scheduling resources to maintain the balance between demand side and generation side. In addition to traditional reserve resources, demand response (DR) programs have gained much attention recently to mitigate wind power's volatility and uncertainty. To better accommodate wind power, this paper proposes a chance-constrained day-ahead generation scheduling model for variable energy resources considering DR. The model considers hourly forecast errors of wind power output and DR. A chance-constrained stochastic programming formulation is presented for the day-ahead scheduling model. Operation risk chance constraints for load shedding and wind curtailment are formulated. Reserve requirements are formulated as chance constraints in which power system reliability requirements are to be satisfied with a presumed level of high probability. The loss of load probability and the probability of wind power curtailment is less than certain level. The formulation captures both wind power output and DR uncertainties. The chance-constrained stochastic programming formulation is converted into an equivalent linear deterministic problem. The proposed model is tested in PJM 5-bus system.