A Day-ahead Optimal RERs Scheduling Approach for Virtual Power Plants Considering Different Loading Conditions

Abstract

Virtual power plant (VPP) concept, based on smart grid technology, is an important tool to integrate dispatchable and stochastic generating units in addition to controllable or interruptible loads into a single unit. This collection maximizes power energy utilization and enhances energy supply reliability. This paper introduces a price-based unit commitment depending on probabilistic model to investigate the effect of consumers' participation in demand response program for optimal day-ahead scheduling of VPP. Electricity prices, uncertainties in renewable energy and load variation are considered in VPP scheduling framework. A new modeling strategy is proposed for uncertainties and an adaptive differential evaluation algorithm is developed to solve the scheduling problem. To validate the proposed methodology, many simulations for different loading levels are introduced. The results illustrate the capability of the proposed methodology for effective scheduling of VPP resources considering demand response with achieving obvious economical and technical merits.