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Assessing the value of forecast-based dispatch in the operation of off-grid rural microgrids

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  • Mazzola, Simone
  • Vergara, Claudio
  • Astolfi, Marco
  • Li, Vivian
  • Perez-Arriaga, Ignacio
  • Macchi, Ennio

Abstract

Hybrid microgrids are expected to play an important role in the expansion of access to electricity in developing countries. While most of these systems are operated with dispatch strategies which do not make use of predictions about the load or about the availability of renewable energy resources, forecast-based strategies have recently gained attention as an alternative to bring down operation costs. In this work, we develop a framework to assess this potential under a range of assumptions about the quality of load and photovoltaic generation forecasts. The application of the methodology to a village of 600 households reveals cost savings ranging between 2% and 7% depending on the forecast quality and the composition of the microgrid. We also show that sizing microgrid components under the assumption of a predictive operation strategy results in a design with a higher share of intermittent generation.

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  • Mazzola, Simone & Vergara, Claudio & Astolfi, Marco & Li, Vivian & Perez-Arriaga, Ignacio & Macchi, Ennio, 2017. "Assessing the value of forecast-based dispatch in the operation of off-grid rural microgrids," Renewable Energy, Elsevier, vol. 108(C), pages 116-125.
    • Handle: RePEc:eee:renene:v:108:y:2017:i:c:p:116-125
    DOI: 10.1016/j.renene.2017.02.040
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    2. Moretti, Luca & Astolfi, Marco & Vergara, Claudio & Macchi, Ennio & Pérez-Arriaga, Josè Ignacio & Manzolini, Giampaolo, 2019. "A design and dispatch optimization algorithm based on mixed integer linear programming for rural electrification," Applied Energy, Elsevier, vol. 233, pages 1104-1121.
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    9. Fontenot, Hannah & Dong, Bing, 2019. "Modeling and control of building-integrated microgrids for optimal energy management – A review," Applied Energy, Elsevier, vol. 254(C).
    10. Ahmed, Adil & Khalid, Muhammad, 2019. "A review on the selected applications of forecasting models in renewable power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 9-21.
    11. Agüera-Pérez, Agustín & Palomares-Salas, José Carlos & González de la Rosa, Juan José & Florencias-Oliveros, Olivia, 2018. "Weather forecasts for microgrid energy management: Review, discussion and recommendations," Applied Energy, Elsevier, vol. 228(C), pages 265-278.
    12. Jamal, Taskin & Carter, Craig & Schmidt, Thomas & Shafiullah, G.M. & Calais, Martina & Urmee, Tania, 2019. "An energy flow simulation tool for incorporating short-term PV forecasting in a diesel-PV-battery off-grid power supply system," Applied Energy, Elsevier, vol. 254(C).
    13. Yang, Yuqing & Bremner, Stephen & Menictas, Chris & Kay, Merlinde, 2022. "Modelling and optimal energy management for battery energy storage systems in renewable energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    14. Wu, Xiaomin & Cao, Weihua & Wang, Dianhong & Ding, Min & Yu, Liangjun & Nakanishi, Yosuke, 2021. "Demand response model based on improved Pareto optimum considering seasonal electricity prices for Dongfushan Island," Renewable Energy, Elsevier, vol. 164(C), pages 926-936.
    15. Mousavi, Seyed Ali & Toopshekan, Ashkan & Mehrpooya, Mehdi & Delpisheh, Mostafa, 2023. "Comprehensive exergetic performance assessment and techno-financial optimization of off-grid hybrid renewable configurations with various dispatch strategies and solar tracking systems," Renewable Energy, Elsevier, vol. 210(C), pages 40-63.
    16. Konneh, Keifa Vamba & Masrur, Hasan & Konneh, David A. & Senjyu, Tomonobu, 2022. "Independent or complementary power system configuration: A decision making approach for sustainable electrification of an urban environment in Sierra Leone," Energy, Elsevier, vol. 239(PD).
    17. Samu, Remember & Calais, Martina & Shafiullah, G.M. & Moghbel, Moayed & Shoeb, Md Asaduzzaman & Nouri, Bijan & Blum, Niklas, 2021. "Applications for solar irradiance nowcasting in the control of microgrids: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    18. Wang, Guang Chao & Ratnam, Elizabeth & Haghi, Hamed Valizadeh & Kleissl, Jan, 2019. "Corrective receding horizon EV charge scheduling using short-term solar forecasting," Renewable Energy, Elsevier, vol. 130(C), pages 1146-1158.
    19. Andrea Micangeli & Davide Fioriti & Paolo Cherubini & Pablo Duenas-Martinez, 2020. "Optimal Design of Isolated Mini-Grids with Deterministic Methods: Matching Predictive Operating Strategies with Low Computational Requirements," Energies, MDPI, vol. 13(16), pages 1-19, August.
    20. Chapaloglou, Spyridon & Nesiadis, Athanasios & Iliadis, Petros & Atsonios, Konstantinos & Nikolopoulos, Nikos & Grammelis, Panagiotis & Yiakopoulos, Christos & Antoniadis, Ioannis & Kakaras, Emmanuel, 2019. "Smart energy management algorithm for load smoothing and peak shaving based on load forecasting of an island’s power system," Applied Energy, Elsevier, vol. 238(C), pages 627-642.
    21. Bahramara, Salah & Sheikhahmadi, Pouria & Golpîra, Hêmin, 2019. "Co-optimization of energy and reserve in standalone micro-grid considering uncertainties," Energy, Elsevier, vol. 176(C), pages 792-804.
    22. Fioriti, Davide & Pintus, Salvatore & Lutzemberger, Giovanni & Poli, Davide, 2020. "Economic multi-objective approach to design off-grid microgrids: A support for business decision making," Renewable Energy, Elsevier, vol. 159(C), pages 693-704.
    23. Moretti, L. & Polimeni, S. & Meraldi, L. & Raboni, P. & Leva, S. & Manzolini, G., 2019. "Assessing the impact of a two-layer predictive dispatch algorithm on design and operation of off-grid hybrid microgrids," Renewable Energy, Elsevier, vol. 143(C), pages 1439-1453.

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