Intelligent optimal scheduling strategy of IES with considering the multiple flexible loads

被引:3
|
作者
Li, Qiuwen [1 ]
Mo, Dong [1 ]
Kong, Xiangyun [1 ]
Lu, Yufu [1 ]
Liang, Yangdou [1 ]
Liang, Zhencheng [1 ]
机构
[1] Guangxi Power Grid Dispatch & Control Ctr, Nanning 530000, Peoples R China
关键词
Intelligent optimal scheduling; Integrated energy system; Demand response; Renewable energy; Flexible load; INTEGRATED ENERGY SYSTEM; DEMAND RESPONSE; ELECTRICITY;
D O I
10.1016/j.egyr.2023.04.242
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
As the energy system continues to evolve and advance, a relatively single energy system gradually turns to the comprehensive energy system. With the advancement of technology related to electric vehicle networks progresses, the flexible load in the power system has been significantly improved, and there will be more and more schedulable resources in the power system. On this basis, the paper mainly studies the integrated energy system including the power station of electric driven vehicles and a variety of flexible loads. First, an intelligent energy system model is built, including wind power, ES, cogeneration units, gas boilers, etc. Secondly, according to the flexible load response of electricity, heat and gas, the dynamic response of flexible loads such as electricity, heat and natural gas is incorporated into the optimal scheduling of the integrated energy system, and a model has been created for optimizing the integrated energy system with the goal of minimizing the system operational expenses. Finally, YALMIP is utilized to formulate the problem during modeling, while CPLEX is employed as the solver to find a solution. Through the example calculation, the system operation cost is reduced by 13.04%, the wind power consumption rate is increased by 8.65%, and the peak valley difference is reduced by 24.58%. This approach has been demonstrated to lower the overall operational expenses of the system, as well as assist in smoothing out peak and off-peak electricity demand, and increase the utilization of wind power. (C) 2023 Published by Elsevier Ltd. This is an open access article under theCCBY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:1983 / 1994
页数:12
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