Open Access
ARTICLE
Bi-Level Energy Management Model of Grid-Connected Microgrid Community
1 School of Economics and Management, North China Electric Power University, Beijing, China
2 School of Economics and Management, North China Electric Power University (Baoding), Baoding, China
3 State Grid Tianjin Economic Research Institute, Tianjin, China
* Corresponding Author: Yuqing Wang. Email:
(This article belongs to the Special Issue: Energy Systems Management and Climate Change)
Energy Engineering 2022, 119(3), 965-984. https://doi.org/10.32604/ee.2022.020051
Received 29 September 2021; Accepted 22 December 2021; Issue published 31 March 2022
Abstract
As the proportion of renewable energy power generation continues to increase, the number of grid-connected microgrids is gradually increasing, and geographically adjacent microgrids can be interconnected to form a Micro-Grid Community (MGC). In order to reduce the operation and maintenance costs of a single micro grid and reduce the adverse effects caused by unnecessary energy interaction between the micro grid and the main grid while improving the overall economic benefits of the micro grid community, this paper proposes a bi-level energy management model with the optimization goal of maximizing the social welfare of the micro grid community and minimizing the total electricity cost of a single micro grid. The lower-level model optimizes the output of each equipment unit in the system and the exchange power between the system and the external grid with the goal of minimizing the operating cost of each microgrid. The upper-level model optimizes the goal of maximizing the social welfare of the microgrid. Taking a microgrid community with four microgrids as an example, the simulation analysis shows that the proposed optimization model is beneficial to reduce the operating cost of a single microgrid, improve the overall revenue of the microgrid community, and reduce the power interaction pressure on the main grid.Keywords
Cite This Article
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.