Optimal Allocation for Multi-energy Complementary Microgrid Based on Scenario Generation of Wind Power and Photovoltaic Output

被引：0
|
作者：
Bai K. [1 ]
Gu J. [1 ]
Peng H. [1 ]
Zhu B. [2 ]
机构：
[1] School of Electronic Information and Electrical Engineering, Research Center for Big Data Engineering and Technologies, Shanghai Jiao Tong University, Shanghai
[2] Electric Power Research Institute of State Grid Shanghai Municipal Electric Power Corporation, Shanghai
来源：
Gu, Jie (gujie@sjtu.edu.cn) | 2018年 / Automation of Electric Power Systems Press卷 / 42期
关键词：
Bi-level programming; Energy hub; Multi-energy complementarity; Relativity; Scenario generation; Uncertainty;
D O I：
10.7500/AEPS20170913008
中图分类号：
学科分类号：
摘要：
The structure and coupling relationships between devices in the multi-energy complementary system are complex. In order to improve the energy efficiency and operation benefit of the system with high penetration of renewable energy, this paper studies the optimal allocation of the multi-energy complementary microgrid (MECM) considering the uncertainty and relativity between wind power and photovoltaic outputs. Considering the randomness and relativity of the renewable energy during the planning stage, a scenario generation method of wind power and photovoltaic output based on the kernel density estimation and Copula theory is proposed, and the wind power and photovoltaic output sequences on the typical days are obtained. Besides, the multi-energy flow balance equations of the MECM with wind power and photovoltaic with complete structures are established based on the energy hub. Then, by combining the configuration and operation, this paper establishes a bi-level optimal allocation model of MECM for the purpose of acquiring the lowest total annual cost and the highest primary energy saving ratio. The intelligent optimization algorithms are applied to solve this optimal model. The simulation example and sensitivity analysis show that the proposed method is able to obtain the optimal allocation of MECM with complete structure based on the consideration of the uncertainty of wind power and photovoltaic output. Meanwhile, the proposed method can also effectively reduce the total cost of the system and improve the primary energy saving ratio. © 2018 Automation of Electric Power Systems Press.
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页码：133 / 141
页数：8
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