基于模型预测控制的多微电网系统能量管理

胡克用; 李文娟; 王李冬; 曹世华; 朱方明; 寿周翔

doi:10.1631/FITEE.1601826

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基于模型预测控制的多微电网系统能量管理

常规文章 | Updated：2022-05-19

- 基于模型预测控制的多微电网系统能量管理
- Energy management for multi-microgrid system based on model predictive control
- 信息与电子工程前沿（英文） 2018年19卷第11期页码：1340-1351
- Affiliations：
  
  Qianjiang College, Hangzhou Normal University, Hangzhou 310018, China
  MOE Key Laboratory of Special Purpose Equipment and Advanced Manufacturing Technology, Zhejiang University of Technology, Hangzhou 310014, China
  School of Information Science and Engineering, Hangzhou Normal University, Hangzhou 311121, China
- Author bio：
  
  [ "Ke-yong HU, E-mail: hukeyong@yeah.net" ]
- Funds：
  
  Project supported by the National Natural Science Foundation of China (No. 61702151), the First Group of Teaching Reform Research Project in the 13th Five-Year Plan of Higher Education of Zhejiang Province, China (No. jg20180509), the Natural Science Foundation of Zhejiang Province, China (Nos. LY17E070004, LY17F010010, LY19F020022 and LQ14F020008), and the Public Welfare Technology Application Research Project of Zhejiang Province, China (No. 2017C33219)
- DOI：10.1631/FITEE.1601826
  中图分类号： TP273
- 收稿：2016-12-17，
  
  修回：2018-11-27，
  
  纸质出版：2018-11
- Accepted：
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胡克用, 李文娟, 王李冬, 等. 基于模型预测控制的多微电网系统能量管理[J]. 信息与电子工程前沿（英文）, 2018,19(11):1340-1351.

Ke-yong HU, Wen-juan LI, Li-dong WANG, et al. Energy management for multi-microgrid system based on model predictive control[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(11): 1340-1351.
胡克用, 李文娟, 王李冬, 等. 基于模型预测控制的多微电网系统能量管理[J]. 信息与电子工程前沿（英文）, 2018,19(11):1340-1351. DOI： 10.1631/FITEE.1601826.

Ke-yong HU, Wen-juan LI, Li-dong WANG, et al. Energy management for multi-microgrid system based on model predictive control[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(11): 1340-1351. DOI： 10.1631/FITEE.1601826.

摘要

为降低多微电网能量管理优化算法计算复杂度，提出一种基于模型预测控制能量优化管理方法。首先，采用分解协调实现供需平衡，协调多微电网系统剩余能量，使供电成本最小化。然后，根据多微电网潮流特性，建立能量管理模型并提出能量优化问题。接着，采用对偶分解法将优化问题分为两部分，引入基于全局优化的分布式预测控制算法，经过算法迭代与协调实现最优解。仿真结果表明，该方法能实时向用户提供所需能源，提高可再生能源利用率。此外，与粒子群算法（particle swarm optimization，PSO）进行比较。比较结果表明，该算法具有更好性能、更快收敛速度和更高效率。

Abstract

To reduce the computation complexity of the optimization algorithm used in energy management of a multi-microgrid system

an energy optimization management method based on model predictive control is presented. The idea of decomposition and coordination is adopted to achieve the balance between power supply and user demand

and the power supply cost is minimized by coordinating surplus energy in the multi-microgrid system. The energy management model and energy optimization problem are established according to the power flow characteristics of microgrids. A dual decomposition approach is imposed to decompose the optimization problem into two parts

and a distributed predictive control algorithm based on global optimization is introduced to achieve the optimal solution by iteration and coordination. The proposed method has been verified by simulation

and simulation results show that the proposed method provides the demanded energy to consumers in real time

and improves renewable energy efficiency. In addition

the proposed algorithm has been compared with the particle swarm optimization (PSO) algorithm. The results show that compared with PSO

the proposed method has better performance

faster convergence

and significantly higher efficiency.

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references

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