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Optimal active and reactive energy management for a smart microgrid system under the Moroccan grid pricing code

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  • Gheouany, Saad
  • Ouadi, Hamid
  • El Bakali, Saida

Abstract

This article presents an innovative active and reactive energy management system (AR-EMS) specifically designed for residential buildings in Morocco, seamlessly integrated with a Smart Microgrid (SMG) and the Electrical Power Grid (EPG) supplier. The considered SMG incorporates a Photovoltaic system (PV) and an Energy Storage System (ESS). In Morocco, the EPG utilizes a Range Tariff System (RTS), where the tariff structure depends on the total energy consumed at the end of each month. Hence, the proposed AR-EMS is designed to computes optimal active and reactive power setpoints of each source at 15-minute intervals for the next 30 days, based on forecasts of energy consumption and PV power production. The AR-EMS consists of two distinct layers: the Long-Term Optimization Layer (LTOL) and the Short-Term Optimization Layer (STOL). The LTOL focuses on optimizing active and reactive power flow over an extended time horizon of 30 days, relying on forecasted data. In contrast, the STOL involves short-term forecasting and energy optimization over the next 24-hour horizon, addressing the LTOL forecasting uncertainties. The proposed strategy emphasizes a multi-objective problem aiming at minimizing both active and reactive energy bill, ESS degradation cost, Peak-to-Average Ratio (PAR) and carbon emissions. The considered problem is solved using a metaheuristic algorithm, specifically the Lexicographic approach within the Particle Swarm Optimization (PSO) method. To validate the effectiveness of the proposed approach, two comparative analyses are conducted. The first involves the impact of time horizons on the energy cost and the management performances within the Moroccan context. The second comparison, highlights the benefits and shortfalls of using simultaneous active and reactive power management, comparing it with a system exclusively managing active power (A-EMS). Both compared strategies are evaluated using the Moroccan tariff RTS and real world data. The comparative analysis highlights the advantages of the proposed AR-EMS, demonstrating benefits in terms of active and reactive energy bill reduction by 58.9% and 83.2%, respectively, and showcases a 49.3% reduction in carbon emissions while improving the EPG power factor by 6% compared to A-EMS, In conclusion, the optimization results are encouraging the Moroccan government to further develop the installation of SMGs.

Suggested Citation

  • Gheouany, Saad & Ouadi, Hamid & El Bakali, Saida, 2024. "Optimal active and reactive energy management for a smart microgrid system under the Moroccan grid pricing code," Energy, Elsevier, vol. 306(C).
    • Handle: RePEc:eee:energy:v:306:y:2024:i:c:s0360544224022369
    DOI: 10.1016/j.energy.2024.132462
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    References listed on IDEAS

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    1. Zhu, Xu & Sun, Yuanzhang & Yang, Jun & Dou, Zhenlan & Li, Gaojunjie & Xu, Chengying & Wen, Yuxin, 2022. "Day-ahead energy pricing and management method for regional integrated energy systems considering multi-energy demand responses," Energy, Elsevier, vol. 251(C).
    2. Guo, Tianyu & Guo, Qi & Huang, Libin & Guo, Haiping & Lu, Yuanhong & Tu, Liang, 2023. "Microgrid source-network-load-storage master-slave game optimization method considering the energy storage overcharge/overdischarge risk," Energy, Elsevier, vol. 282(C).
    3. Jiang, Tao & Dong, Xinru & Zhang, Rufeng & Li, Xue, 2023. "Strategic active and reactive power scheduling of integrated community energy systems in day-ahead distribution electricity market," Applied Energy, Elsevier, vol. 336(C).
    4. Chaduvula, Hemanth & Das, Debapriya, 2023. "Analysis of microgrid configuration with optimal power injection from grid using point estimate method embedded fuzzy-particle swarm optimization," Energy, Elsevier, vol. 282(C).
    5. Alharbi, Abdullah G. & Olabi, A.G. & Rezk, Hegazy & Fathy, Ahmed & Abdelkareem, Mohammad Ali, 2024. "Optimized energy management and control strategy of photovoltaic/PEM fuel cell/batteries/supercapacitors DC microgrid system," Energy, Elsevier, vol. 290(C).
    6. Elkazaz, Mahmoud & Sumner, Mark & Naghiyev, Eldar & Pholboon, Seksak & Davies, Richard & Thomas, David, 2020. "A hierarchical two-stage energy management for a home microgrid using model predictive and real-time controllers," Applied Energy, Elsevier, vol. 269(C).
    7. Carvalho, Diego B. & Bortoni, Edson da C., 2024. "Proposed model with weighted parameters for microgrid management: Incorporating diverse load profiles, assorted tariff policies, and energy storage devices," Energy, Elsevier, vol. 296(C).
    8. Bian, Yifan & Xie, Lirong & Ye, Jiahao & Ma, Lan & Cui, Chuanshi, 2024. "Peer-to-peer energy sharing model considering multi-objective optimal allocation of shared energy storage in a multi-microgrid system," Energy, Elsevier, vol. 288(C).
    9. Hasanien, Hany M. & Alsaleh, Ibrahim & Tostado-Véliz, Marcos & Zhang, Miao & Alateeq, Ayoob & Jurado, Francisco & Alassaf, Abdullah, 2024. "Hybrid particle swarm and sea horse optimization algorithm-based optimal reactive power dispatch of power systems comprising electric vehicles," Energy, Elsevier, vol. 286(C).
    10. Hassaballah, E.G. & Keshta, H.E. & Abdel-Latif, K.M. & Ali, A.A., 2024. "A novel strategy for real-time optimal scheduling of grid-tied microgrid considering load management and uncertainties," Energy, Elsevier, vol. 299(C).
    11. Zheng, Siqian & Jin, Xin & Huang, Gongsheng & Lai, Alvin CK., 2022. "Coordination of commercial prosumers with distributed demand-side flexibility in energy sharing and management system," Energy, Elsevier, vol. 248(C).
    12. Suryakiran, B.V. & Nizami, Sohrab & Verma, Ashu & Saha, Tapan Kumar & Mishra, Sukumar, 2023. "A DSO-based day-ahead market mechanism for optimal operational planning of active distribution network," Energy, Elsevier, vol. 282(C).
    13. Kassab, Fadi Agha & Celik, Berk & Locment, Fabrice & Sechilariu, Manuela & Liaquat, Sheroze & Hansen, Timothy M., 2024. "Optimal sizing and energy management of a microgrid: A joint MILP approach for minimization of energy cost and carbon emission," Renewable Energy, Elsevier, vol. 224(C).
    14. Garg, Harish, 2016. "A hybrid PSO-GA algorithm for constrained optimization problems," Applied Mathematics and Computation, Elsevier, vol. 274(C), pages 292-305.
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