Open Access

ARTICLE

Low-Carbon and Economic Dispatch Strategy Considering Optimal Multi-Machine Allocation and Power Control for Grid-Forming Energy Storage in Micro-Energy Grids

Yiqun Kang^1,*, Zhe Li¹, Li You¹, Haozhe Xiong², Yuxuan Hu³, Fei Wang^4,*

1 Electric Power Research Institute of State Grid Hubei Corporation, Wuhan, China
2 Hubei Key Laboratory of Regional New Power Systems and Rural Energy System Configuration, Wuhan, China
3 Hubei Engineering Research Center of the Construction and Operation Control Technology of New Power Systems, Wuhan, China
4 School of Electrical Engineering, Xi’an Jiao Tong University, Xi’an, China

* Corresponding Authors: Yiqun Kang. Email: ; Fei Wang. Email:

(This article belongs to the Special Issue: Construction and Control Technologies of Renewable Power Systems Based on Grid-Forming Energy Storage)

Energy Engineering 2026, 123(9), 4 https://doi.org/10.32604/ee.2026.078724

Received 06 January 2026; Accepted 28 February 2026; Issue published 06 August 2026

Abstract

As the world’s energy framework shifts towards a low-carbon model, the widespread incorporation of renewable energy (RE) sources, primarily wind power and photovoltaics (PV), into the power grid is an unavoidable development. The micro-energy grid (MEG), as an integrated system that combines distributed energy, energy storage (ES), and power loads, can achieve efficient consumption of RE by implementing multi-machine optimal allocation and unified coordinated power control for parallel operation of grid-forming energy storage (GFES). For this purpose, this paper puts forward a low-carbon and economic dispatch strategy for MEG that considers multi-machine optimal allocation of GFES and unified coordinated power control for parallel operation. The strategy constructs a multi-machine optimal allocation model for GFES in the outer layer, striving to achieve the lowest operational costs for the MEG. In the inner layer, based on the obtained optimal multi-machine allocation scheme for GFES, a unified coordinated power control model for parallel operation of GFES in the MEG is constructed, targeting the minimization of pollutant gas emissions and system voltage deviation. The plant growth simulation algorithm (PGSA) is employed to solve the established models for multi-machine optimal allocation of GFES and unified coordinated power control for parallel operation in the MEG. Through simulation analysis, it has been substantiated that the proposed method can effectively achieve multi-machine optimal allocation and unified coordinated power control for parallel operation of GFES, reduce the operational costs of the MEG system, while also decreasing pollutant gas emissions and stabilizing system operation, thereby offering robust and substantial backing for the attainment of a low-carbon economy and the pursuit of sustainable development.

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Keywords

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