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Energies 2018, 11(6), 1488; https://doi.org/10.3390/en11061488

Optimal Dispatch of a Virtual Power Plant Considering Demand Response and Carbon Trading

1
School of Electrical Engineering, Zhejiang University, No. 38 Zheda Rd., Hangzhou 310027, China
2
State Grid Zhejiang Electric Power Co., Ltd., No. 8 Huanglong Rd., Hangzhou 310007, China
3
State Grid Zhejiang Economic Research Institute, No.1 Nanfu Road, Hangzhou 310008, China
4
Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam
5
Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam
*
Author to whom correspondence should be addressed.
Received: 10 May 2018 / Revised: 31 May 2018 / Accepted: 5 June 2018 / Published: 7 June 2018
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Abstract

The implementation of demand response (DR) could contribute to significant economic benefits meanwhile simultaneously enhancing the security of the concerned power system. A well-designed carbon emission trading mechanism provides an efficient way to achieve emission reduction targets. Given this background, a virtual power plant (VPP) including demand response resources, gas turbines, wind power and photovoltaics with participation in carbon emission trading is examined in this work, and an optimal dispatching model of the VPP presented. First, the carbon emission trading mechanism is briefly described, and the framework of optimal dispatching in the VPP discussed. Then, probabilistic models are utilized to address the uncertainties in the predicted generation outputs of wind power and photovoltaics. Demand side management (DSM) is next implemented by modeling flexible loads such as the chilled water thermal storage air conditioning systems (CSACSs) and electric vehicles (EVs). On this basis, a mixed integer linear programming (MILP) model for the optimal dispatching problem in the VPP is established, with an objective of maximizing the total profit of the VPP considering the costs of power generation and carbon emission trading as well as charging/discharging of EVs. Finally, the developed dispatching model is solved by the commercial CPLEX solver based on the YALMIP/MATLAB (version 8.4) toolbox, and sample examples are served for demonstrating the essential features of the proposed method. View Full-Text
Keywords: virtual power plant (VPP); demand response (DR); carbon trading mechanism; uncertainty; electric vehicle (EV) virtual power plant (VPP); demand response (DR); carbon trading mechanism; uncertainty; electric vehicle (EV)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Liu, Z.; Zheng, W.; Qi, F.; Wang, L.; Zou, B.; Wen, F.; Xue, Y. Optimal Dispatch of a Virtual Power Plant Considering Demand Response and Carbon Trading. Energies 2018, 11, 1488.

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