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Volume 14
Issue 5
10.3390/machines14050559
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Sustainable Multi-Energy Microgrid Operation: Birds of Prey-Based Day-Ahead Scheduling Under Seasonal Renewable Uncertainty

by
Hany S. E. Mansour
1,2,
Hassan M. Hussein Farh
3,
Abdullrahman A. Al-Shamma’a
3,*,
AL-Wesabi Ibrahim
4,
Abdullah M. Al-Shaalan
5,
Amira S. Mohamed
1 and
Honey A. Zedan
6
1
Electrical Engineering Department, Faculty of Engineering, Suez Canal University, Ismailia 41522, Egypt
2
Egypt-Japan KOSEN (EJ-KOSEN) Institute, 10th of Ramadan City 44629, Egypt
3
Electrical Engineering Department, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11564, Saudi Arabia
4
College of Electrical and Information Engineering, Hunan University, Changsha 410083, China
5
Electrical Engineering Department, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia
6
Electrical Engineering Department, Faculty of Engineering, Badr University in Cairo (BUC), Cairo 11829, Egypt
*
Author to whom correspondence should be addressed.
Machines 2026, 14(5), 559; https://doi.org/10.3390/machines14050559 (registering DOI)
Submission received: 22 April 2026 / Revised: 12 May 2026 / Accepted: 14 May 2026 / Published: 16 May 2026
(This article belongs to the Special Issue Sustainable Intelligent Design, Control and Optimization for Renewable-Integrated Power Systems)
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Abstract

The increasing integration of renewable energy resources into modern microgrids requires reliable scheduling methods capable of managing uncertainty, seasonal variability, operating cost, and environmental impact. This study proposes a stochastic day-ahead scheduling approach for a representative grid-connected multi-energy microgrid comprising photovoltaic generation, wind generation, a microturbine, a fuel cell, an energy storage system, and utility-grid exchange. The proposed model was implemented and simulated in a MATLAB (2024b) environment. The Birds of Prey-Based Optimization algorithm is applied to determine the optimal 24 h dispatch schedule by minimizing a weighted objective function that combines operating and emission costs. Uncertainties in solar irradiance, wind speed, electrical load, ambient temperature, and electricity prices are modeled using probabilistic distributions and Monte Carlo simulations. To improve computational efficiency, 1000 generated scenarios are reduced to 10 representative scenarios using Fast Forward Selection based on Kantorovich distance. Seasonal case studies for winter, spring, summer, and autumn are used to evaluate the proposed method. Compared with five metaheuristic algorithms, the proposed approach achieves the lowest fitness value in all seasons, with reductions of 15.2%, 26.5%, 6.8%, and 23.9%, respectively. The results confirm improved economic and environmental microgrid operation under seasonal renewable uncertainty.
Keywords: multi-energy microgrids; birds of prey optimization; day-ahead scheduling; stochastic optimization; renewable uncertainty; scenario reduction; seasonal variation multi-energy microgrids; birds of prey optimization; day-ahead scheduling; stochastic optimization; renewable uncertainty; scenario reduction; seasonal variation
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MDPI and ACS Style

Mansour, H.S.E.; Farh, H.M.H.; Al-Shamma’a, A.A.; Ibrahim, A.-W.; Al-Shaalan, A.M.; Mohamed, A.S.; Zedan, H.A. Sustainable Multi-Energy Microgrid Operation: Birds of Prey-Based Day-Ahead Scheduling Under Seasonal Renewable Uncertainty. Machines 2026, 14, 559. https://doi.org/10.3390/machines14050559

AMA Style

Mansour HSE, Farh HMH, Al-Shamma’a AA, Ibrahim A-W, Al-Shaalan AM, Mohamed AS, Zedan HA. Sustainable Multi-Energy Microgrid Operation: Birds of Prey-Based Day-Ahead Scheduling Under Seasonal Renewable Uncertainty. Machines. 2026; 14(5):559. https://doi.org/10.3390/machines14050559

Chicago/Turabian Style

Mansour, Hany S. E., Hassan M. Hussein Farh, Abdullrahman A. Al-Shamma’a, AL-Wesabi Ibrahim, Abdullah M. Al-Shaalan, Amira S. Mohamed, and Honey A. Zedan. 2026. "Sustainable Multi-Energy Microgrid Operation: Birds of Prey-Based Day-Ahead Scheduling Under Seasonal Renewable Uncertainty" Machines 14, no. 5: 559. https://doi.org/10.3390/machines14050559

APA Style

Mansour, H. S. E., Farh, H. M. H., Al-Shamma’a, A. A., Ibrahim, A.-W., Al-Shaalan, A. M., Mohamed, A. S., & Zedan, H. A. (2026). Sustainable Multi-Energy Microgrid Operation: Birds of Prey-Based Day-Ahead Scheduling Under Seasonal Renewable Uncertainty. Machines, 14(5), 559. https://doi.org/10.3390/machines14050559

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