Techno-economic assessment of consumers' participation in the demand response program for optimal day-ahead scheduling of virtual power plants

In this paper, the consumers' participation in the demand response program for virtual power plant (VPP) is proposed. A proposed price-based scheduling strategy for optimal day-ahead scheduling of VPP is investigated to maximize the profit of the VPP composed of a set of distributed generation, dispatchable load, and wind turbines. For solving the optimal scheduling problem, a modified differential evolution algorithm (MDEA) is proposed. To achieve the work target, 33-kV, 18-bus test system is selected as a test system. The proposed algorithm leads to effective scheduling of VPP resources, especially for reserve power. To investigate the proposed methodology, the load is increased and the scheduling of VPP is investigated at the best and worst boundaries of VPP resources uncertainty. The best case happens at maximum load, high prices and maximum energy from renewables, while the worst scenario occurs at minimum load, low prices and minimum energy from renewables. In addition, the algorithm ensures the importance of VPP in playing a dual role as a demand/generation unit from the perspective of the upstream network in some time periods and highlights the vital effect of dispatchable loads on the management process at different conditions of the dispatchable load.