M. Samakoosh, H., Jafari-Nokandi, M., Sheikholeslami, A. (2018). Coordinated resource scheduling in a large scale virtual power plant considering demand response and energy storages. Journal of Operation and Automation in Power Engineering, 6(1), 50-60. doi: 10.22098/joape.2018.3153.1257

H. M. Samakoosh; M. Jafari-Nokandi; A. Sheikholeslami. "Coordinated resource scheduling in a large scale virtual power plant considering demand response and energy storages". Journal of Operation and Automation in Power Engineering, 6, 1, 2018, 50-60. doi: 10.22098/joape.2018.3153.1257

M. Samakoosh, H., Jafari-Nokandi, M., Sheikholeslami, A. (2018). 'Coordinated resource scheduling in a large scale virtual power plant considering demand response and energy storages', Journal of Operation and Automation in Power Engineering, 6(1), pp. 50-60. doi: 10.22098/joape.2018.3153.1257

M. Samakoosh, H., Jafari-Nokandi, M., Sheikholeslami, A. Coordinated resource scheduling in a large scale virtual power plant considering demand response and energy storages. Journal of Operation and Automation in Power Engineering, 2018; 6(1): 50-60. doi: 10.22098/joape.2018.3153.1257

Coordinated resource scheduling in a large scale virtual power plant considering demand response and energy storages

^{1}Mazandaran University of Science and Technology

^{2}Noshirvani University of Technology

Abstract

Virtual power plant (VPP) is an effective approach to aggregate distributed generation resources under a central control. This paper introduces a mixed-integer linear programming model for optimal scheduling of the internal resources of a large scale VPP in order to maximize its profit. The proposed model studies the effect of a demand response (DR) program on the scheduling of the VPP. The profit of the VPP is calculated considering different components including the income from the sale of electricity to the network and the incentives received by the renewable resources, fuel cost, the expense of the purchase of electricity from the network and the load curtailment cost during the scheduling horizon. The proposed model is implemented in a large scale VPP that consists of five plants in two cases: with and without the presence of the DR. Simulation results show that the implementation of the DR program reduces the operation cost in the VPP, therefore increasing its profit.

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