Multi-Objective Optimal Power Flow Calculation Considering Carbon Emission Intensity

Gangfei Wang, Hengrui Ma (), Bo Wang, Abdullah M. Alharbi, Hongxia Wang and Fuqi Ma
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Gangfei Wang: College of Energy and Electrical Engineering, Qinghai University, Xining 810016, China
Hengrui Ma: College of Energy and Electrical Engineering, Qinghai University, Xining 810016, China
Bo Wang: Hubei Engineering and Technology Research Center for AC/DC Intelligent Distribution Network, School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
Abdullah M. Alharbi: Department of Electrical Engineering, College of Engineering at Wadi Addawasir, Prince Sattam bin Abdulaziz University, Wadi Addawasir 11991, Saudi Arabia
Hongxia Wang: School of Electrical and Automation, Wuhan University, Wuhan 430072, China
Fuqi Ma: Hubei Engineering and Technology Research Center for AC/DC Intelligent Distribution Network, School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China

Sustainability, 2023, vol. 15, issue 24, 1-20

Abstract: In keeping with China’s dual carbon goals, optimal low-carbon power system dispatch has become a necessary component of the greening of the power system. However, typically, research considers only the economics of such efforts. Based on our power flow analysis of the power grid and the correlation properties of carbon emission flow, an optimal power flow calculation model targeting the total carbon emission rate of the power system’s power generation cost, active network loss, and load and network loss was constructed. Next, the NSGA-III algorithm was used to solve the model, and the decision was to coordinate and optimize the output schemes of various types of power plants, such as wind, water, and thermal. The modified IEEE39 node simulation system was built with Matlab software (MATLAB R2020b). The results of the calculation showed that, compared to the traditional method of determining the optimal power flow, the proposed method reduced the system carbon emissions by 20% while the power generation cost increased by less than 2%, which proves the effectiveness and practicability of the proposed method.

Keywords: carbon emission flow; NSGA-III algorithm; optimal power flow; TOPSIS method (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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