Cooperative optimal operation of multi-microgrids and shared energy storage for voltage regulation of distribution networks based on improved Nash bargaining
The increasing penetration rate of distributed generation will bring serious voltage violation issues to the distribution networks (DNs). As an effective organization form of distributed generation, microgrids (MGs) have flexible adjustment ability, which can provide voltage support for DNs. To enha...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-05-01
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| Series: | International Journal of Electrical Power & Energy Systems |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0142061525000833 |
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| Summary: | The increasing penetration rate of distributed generation will bring serious voltage violation issues to the distribution networks (DNs). As an effective organization form of distributed generation, microgrids (MGs) have flexible adjustment ability, which can provide voltage support for DNs. To enhance the energy economy and scheduling flexibility of MGs, shared energy storage system (SESS) has received widespread attention as a new type of energy storage technology. To this end, this paper proposes a cooperative optimal operation strategy of MGs and SESS aimed at voltage regulation in DNs. A two-stage cooperative optimization model based on Nash bargaining theory is established for MGs and SESS. In the first stage, the DN is partitioned using an improved electrical distance approach that incorporates voltage regulation incentives, with the objective of minimizing the cooperation costs for MGs and SESS. The second stage involves quantifying the contributions of each participant through a nonlinear energy mapping function, followed by the development of the trading price based on asymmetric bargaining informed by improved Nash bargaining. The goal of this approach is to ensure that MGs and SESS share cooperative benefits fairly. The alternating direction method of the multiplier (ADMM) is used to solve the problems, effectively protecting the privacy of each participating subject. Finally, the effectiveness of the proposed method is demonstrated through an analysis of the improved IEEE 33-node system. |
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| ISSN: | 0142-0615 |