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A Min-Max Approach for Energy Management of Renewable-Based Electricity-Hydrogen Microgrids with Demand Response | ||
| International Journal of Industrial Electronics Control and Optimization | ||
| مقاله 19، دوره 9، شماره 4، اسفند 2026، صفحه 471-479 اصل مقاله (914.12 K) | ||
| نوع مقاله: Research Articles | ||
| شناسه دیجیتال (DOI): 10.22111/ieco.2026.54338.1736 | ||
| نویسندگان | ||
| Hamid Karimi* ؛ Hamid Reza Sezavar | ||
| Department of Electrical and Computer Engineering, Qom University of Technology, Qom, Iran. | ||
| چکیده | ||
| This paper presents a multi-objective energy management strategy for a hybrid electricity-hydrogen microgrid (MG) aimed at improving economic and operational performance. The proposed framework simultaneously minimizes total operating cost and reduces peak load, which are conflicting objectives in MG operation. To address this challenge, the problem is formulated as a multi-objective optimization model using a normalized weighted sum approach, enabling an effective trade-off between objectives while preventing the creation of new peaks in the load profile. The studied hydrogen-based MGs includes renewable energy sources such as solar and wind power, a battery energy storage system (BESS), a diesel generator, and demand response programs. Hydrogen is also utilized as an energy carrier to enhance system flexibility and support improved integration of renewable generation. Coordinated scheduling of generation units, storage systems, and flexible loads improves system efficiency. To enhance model accuracy, a long short-term memory (LSTM) forecasting method is applied to predict solar irradiance and wind speed using historical data, supporting more reliable scheduling decisions. The proposed model is validated through a general case study. Simulation results show a peak load reduction of 442 kW and an improvement in the load factor of 16.75%, confirming the effectiveness of the proposed approach | ||
| کلیدواژهها | ||
| Renewable energy؛ Demand response؛ Microgrid؛ Hydrogen-based microgrid؛ Long short-term memory | ||
| مراجع | ||
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آمار تعداد مشاهده مقاله: 177 تعداد دریافت فایل اصل مقاله: 145 |
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