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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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    12. 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.
    13. 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).
    14. Moretti, Luca & Martelli, Emanuele & Manzolini, Giampaolo, 2020. "An efficient robust optimization model for the unit commitment and dispatch of multi-energy systems and microgrids," Applied Energy, Elsevier, vol. 261(C).
    15. Tatiana González Grandón & Fernando de Cuadra García & Ignacio Pérez-Arriaga, 2021. "A Market-Driven Management Model for Renewable-Powered Undergrid Mini-Grids," Energies, MDPI, vol. 14(23), pages 1-29, November.
    16. 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).
    17. Fausto Calderon-Obaldia & Jordi Badosa & Anne Migan-Dubois & Vincent Bourdin, 2020. "A Two-Step Energy Management Method Guided by Day-Ahead Quantile Solar Forecasts: Cross-Impacts on Four Services for Smart-Buildings," Energies, MDPI, vol. 13(22), pages 1-29, November.
    18. Thomas Schmitt & Tobias Rodemann & Jürgen Adamy, 2021. "The Cost of Photovoltaic Forecasting Errors in Microgrid Control with Peak Pricing," Energies, MDPI, vol. 14(9), pages 1-13, April.
    19. Mehra, Varun & Amatya, Reja & Ram, Rajeev J., 2018. "Estimating the value of demand-side management in low-cost, solar micro-grids," Energy, Elsevier, vol. 163(C), pages 74-87.
    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. Gandhi, Oktoviano & Zhang, Wenjie & Kumar, Dhivya Sampath & Rodríguez-Gallegos, Carlos D. & Yagli, Gokhan Mert & Yang, Dazhi & Reindl, Thomas & Srinivasan, Dipti, 2024. "The value of solar forecasts and the cost of their errors: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    23. 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.
    24. 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.
    25. 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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