Research on Optimal Dispatching of Multi-Microgrid Considering Economy

Li HE; Hongfang LÜ

doi:10.12096/j.2096-4528.pgt.2018.061

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Research on Optimal Dispatching of Multi-Microgrid Considering Economy

Energy Internet | 更新时间：2025-06-06

- Research on Optimal Dispatching of Multi-Microgrid Considering Economy
- Power Generation Technology Vol. 39, Issue 5, Pages: 397-404(2018)
- 作者机构：
  
  上海电机学院电气学院, 上海市浦东新区 201306
- 作者简介：
- 基金信息：
  
  Special Funds Project of Shanghai Economic and Information Committee(12AZ22)
- DOI：10.12096/j.2096-4528.pgt.2018.061
  CLC：
- Received：29 April 2018，
  
  Published：30 October 2018
- 稿件说明：
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Li HE, Hongfang LÜ. Research on Optimal Dispatching of Multi-Microgrid Considering Economy[J]. Power Generation Technology, 2018, 39(5): 397-404.
DOI：

Li HE, Hongfang LÜ. Research on Optimal Dispatching of Multi-Microgrid Considering Economy[J]. Power Generation Technology, 2018, 39(5): 397-404. DOI： 10.12096/j.2096-4528.pgt.2018.061.

摘要

多微电网并网方式主要有单独并网方式和联合协调并网方式，这2种并网方式下微电网内部的微电源工作状态不同导致发电成本不同。为了减少发电成本，在满足相关微电源约束条件的前提下，建立一种考虑经济性的多微电网能量优化调度模型和单微电网的优化调度模型。由于传统人工鱼群算法精度低，收敛速度慢，提出一种基于模拟退火算法改进的人工鱼群（the artificial fish swarm algorithm based on simulated annealing algorithm，SA_AFSA）算法，该算法克服了传统鱼群算法的缺点。结合具体算例，通过该算法来求解单微电网和多微电网经济性优化调度问题，并比较2种并网方式下的发电成本。实验结果表明，在仅考虑经济性的前提下，多微电网联合协调并网的发电成本低于单微电网单独并网。

Abstract

The mode of multi-micro-grid connection mainly has single grid connected mode and joint coordinated grid connection mode. The different working state of micro power supply inside the two types of grid connection leads to different generating cost. To reduce the cost of power generation

an optimal scheduling model of multi micro grid energy and an optimal scheduling model for single micro grid were established on the premise of satisfying the constraints of the related micro power supply. Due to the low accuracy and slow convergence rate of the traditional artificial fish swarm algorithm

an improved artificial fish swarm algorithm (SA_AFSA algorithm) based on simulated annealing algorithm was proposed

which overcomes the shortcoming of the traditional fish swarm algorithm. Combined with a specific example

the algorithm is used to solve the economic optimal scheduling problem of single micro-grid and multi-micro-grid

and the cost of power generation under two grid connection modes was compared. The experimental results show that under the premise of only considering the economy

the cost of generation and coordination of multi micro-grid is lower than that of single micro-grid.

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Keywords

references

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