Coordinated Optimization Model of Active Power and Reactive Power in Power and Gas Systems with the Objective of Carbon Neutrality

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  • College of Electrical Engineering, Shanghai University of Electrical Power, Shanghai 200090, China

Received date: 2021-07-01

  Online published: 2021-12-30

Abstract

With the objective of carbon neutrality, renewable energy resources gradually become the main power supply, whose variability poses great challenges to the operation and optimization of the system, especially to the power distribution network. In order to solve the problem of reactive power caused by high penetration of renewable energy sources, a centralized optimization model is proposed, which takes reactive power optimization and “generation-network-load-storage” multi-energy integration into account. The model aims at optimizing the operating cost and minimizing network losses and carbon emissions of the system. Reactive power compensation, regulation of energy storage, and energy conversion are considered to achieve safe and low-carbon economic dispatch of the power and gas systems. An improved second-order cone relaxation method is used for the convex relaxation of non-linear equality constraints concerned with the distribution network. The switching capacity produced by discrete reactive power compensators can be exactly linearized by the application of the big M approach. The simulation results demonstrate that the proposed method could effectively compensate the reactive power required by the grid-connection point of wind turbine, coordinate the energy interaction between the power and gas, thus improving the stability and elasticity of the distribution network after integration of large-scale renewable energy sources, which helps promote the consumption of renewable energy.

Cite this article

SUN Xin, YAN Jiajia, XIE Jingdong, SUN Bo . Coordinated Optimization Model of Active Power and Reactive Power in Power and Gas Systems with the Objective of Carbon Neutrality[J]. Journal of Shanghai Jiaotong University, 2021 , 55(12) : 1554 -1566 . DOI: 10.16183/j.cnki.jsjtu.2021.233

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