Analysis of Coordinated Operation of the Clean Energy System Based on the Multiobjective Optimization Model

Discrete dynamics in nature and society

Yongqiang Wang¹  Shien He²  Zhicheng Ma²  Chen Liang²  Xunyang Wang³ 

[1]College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, Gansu 730000, China, lut.cn

[2]Postdoctoral Research Station of State Grid Gansu Electric Power Research Institute, No. 249, Wanxin North Road, 730070 Anning District, Lanzhou 730000, Gansu, China

[3]Postdoctoral Research Station of State Grid Gansu Electric Power Research Institute, No. 249, Wanxin North Road, 730070 Anning District, Lanzhou 730000, Gansu, China

[4]Department of Applied Mathematics, Lanzhou University of Technology, Lanzhou 730050, Gansu, China, lut.cn

[5]College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, Gansu 730000, China, lut.cn

DOI  :  10.1155/2021/5583598

来源: Hindawi Publishing Corporation

【 摘 要 】

With the increase in the proportion of clean energy connected to the grid, the effective coordination of the operation of various energy power has become a new challenge facing the current power system scheduling. The coordinated operation of the clean energy power generation system can alleviate the contradiction between power generation and output power fluctuations and overcome the bottleneck of new energy development. Considering the natural characteristics of clean energy, this paper aims to make full use of clean energy, reduce system operating costs, increase system power generation, and reduce output fluctuations; we establish a multiobjective optimization model for coordinated scheduling of clean energy power systems. The model seeks to maximize power generation and minimize output fluctuations, power purchase costs, and maintenance costs under the constraints of the grid structure. In this paper, the GA_PSO joint algorithm has an accelerated effect on the target optimization calculation, and then the superiority of the GA_PSO algorithm is verified by the IEEE14 standard system. The standard IEEE39 node test system is used to verify the rationality and feasibility of the model built and provides a reference strategy for the coordinated operation mechanism of the clean energy system. According to the model, in the example in this paper, the maximum value of photovoltaic power prediction is 1290 MW, and the minimum value is 210 MW; the maximum value of wind power prediction is 780 MW, and the minimum value is 28 MW; the minimum cost of power purchase and maintenance is 56,950.395; the maximum generating capacity is 5.045 GW; the minimum output fluctuation is 0.120 GW.

【 授权许可】

CC BY