| Autor: |
Javad Goodarzi, Mohammad Tolou Askari, Meysam Amirahmadi, Majid Babaeinik |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
IEEE Access, Vol 12, Pp 183973-183990 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2024.3503275 |
| Popis: |
This paper introduces a comprehensive three-stage strategic framework designed to enable home microgrids (H-MGs) to collaborate effectively within multiple interconnected electrical and thermal grids. By forming coalitions, H-MGs can enhance their competitiveness in the energy market. The framework is supported by a bi-level optimization model that addresses the optimal management of both electrical and thermal energy within home microgrids, while also integrating electricity and heat distribution networks. A key aspect of this model is the incorporation of a specialized demand-side management strategy, which focuses on solving the optimization problem to maximize the overall system’s profit, despite the presence of variable uncertainties. The bi-level optimization model operates on two levels. The upper-level model focuses on maximizing the profit of the network operator, taking into account Combined Heat and Power (CHP) resources. The lower-level model, on the other hand, is designed to minimize the cost of electricity supply for H-MGs. To solve this complex optimization problem, the paper proposes a Multi-Stage Stochastic Programming approach based on the Golf Optimization Algorithm (MSSP-GOA). The effectiveness of the proposed method is demonstrated through a detailed simulation study. The results show that the method significantly reduces the market clearing price (MCP) for approximately 26% of the time intervals. Additionally, it leads to a 42% increase in the consumption of responsive loads within H-MGs and a threefold increase in local generation. The MSSP-GOA algorithm not only enhances market participation but also significantly boosts profits for all participants involved, underscoring its potential as a robust solution for optimizing energy management in collaborative microgrid environments. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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