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A virtual power plant optimal dispatch model with large and small-scale distributed renewable generation

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  • Naval, Natalia
  • Sánchez, Raul
  • Yusta, Jose M.

Abstract

Volatility and sharp increases in the price of electricity are serious economic problems in the primary sector because they affect modernization investments for irrigation systems in Spain. This paper presents a new virtual power plant (VPP) model that integrates all available full-scale distributed renewable generation technologies. The proposed VPP operates as a single plant in the wholesale electricity market and aims to maximize profit from its operation to meet demand. Two levels of renewable energy integration in the VPP were considered: first, a wind farm and six hydroelectric power plants that inject the generated electricity directly to the distribution network, and second, on-site photovoltaic plants associated with each of the electricity supply points in the system that are designed to prioritize self-consumption. The proposed technical-economic dispatch model was developed as a mixed-integer optimization problem that determines the hourly operation of distributed large-scale renewable generation plants and on-site generation plants. The model was applied to real data from an irrigation system comprising a number of water pumping stations in Aragon (Spain). The results of the VPP model demonstrate the importance of the technical and economic management of all production facilities to significantly reduce grid dependence and final electricity costs.

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  • Naval, Natalia & Sánchez, Raul & Yusta, Jose M., 2020. "A virtual power plant optimal dispatch model with large and small-scale distributed renewable generation," Renewable Energy, Elsevier, vol. 151(C), pages 57-69.
    • Handle: RePEc:eee:renene:v:151:y:2020:i:c:p:57-69
    DOI: 10.1016/j.renene.2019.10.144
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    Cited by:

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    3. Natalia Naval & Jose M. Yusta, 2020. "Water-Energy Management for Demand Charges and Energy Cost Optimization of a Pumping Stations System under a Renewable Virtual Power Plant Model," Energies, MDPI, vol. 13(11), pages 1-21, June.
    4. Miranda, Rodolfo Farías & Salgado-Herrera, Nadia Maria & Rodríguez-Hernández, Osvaldo & Rodríguez-Rodríguez, Juan Ramon & Robles, Miguel & Ruiz-Robles, Dante & Venegas-Rebollar, Vicente, 2022. "Distributed generation in low-voltage DC systems by wind energy in the Baja California Peninsula, Mexico," Energy, Elsevier, vol. 242(C).
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    6. Chang, Weiguang & Dong, Wei & Wang, Yubin & Yang, Qiang, 2022. "Two-stage coordinated operation framework for virtual power plant with aggregated multi-stakeholder microgrids in a deregulated electricity market," Renewable Energy, Elsevier, vol. 199(C), pages 943-956.
    7. Kanjanapon Borisoot & Rittichai Liemthong & Chitchai Srithapon & Rongrit Chatthaworn, 2023. "Optimal Energy Management for Virtual Power Plant Considering Operation and Degradation Costs of Energy Storage System and Generators," Energies, MDPI, vol. 16(6), pages 1-19, March.
    8. Oluwaseun Oladimeji & Álvaro Ortega & Lukas Sigrist & Luis Rouco & Pedro Sánchez-Martín & Enrique Lobato, 2022. "Optimal Participation of Heterogeneous, RES-Based Virtual Power Plants in Energy Markets," Energies, MDPI, vol. 15(9), pages 1-19, April.
    9. Hans Ole Riddervold & Ellen Krohn Aasg{aa}rd & Lisa Haukaas & Magnus Korp{aa}s, 2021. "Internal hydro- and wind portfolio optimisation in real-time market operations," Papers 2102.10098, arXiv.org.
    10. Akbas, Beste & Kocaman, Ayse Selin & Nock, Destenie & Trotter, Philipp A., 2022. "Rural electrification: An overview of optimization methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    11. Lin, Xiaojie & Lin, Xueru & Zhong, Wei & Zhou, Yi, 2023. "Predictive operation optimization of multi-energy virtual power plant considering behavior uncertainty of diverse stakeholders," Energy, Elsevier, vol. 280(C).
    12. Yukta Mehta & Rui Xu & Benjamin Lim & Jane Wu & Jerry Gao, 2023. "A Review for Green Energy Machine Learning and AI Services," Energies, MDPI, vol. 16(15), pages 1-30, July.
    13. Mei Cai & Suqiong Hu & Ya Wang & Jingmei Xiao, 2022. "A Dynamic Social Network Matching Model for Virtual Power Plants and Distributed Energy Resources with Probabilistic Linguistic Information," Sustainability, MDPI, vol. 14(22), pages 1-33, November.
    14. Andrés Felipe Buitrago-Velandia & Oscar Danilo Montoya & Walter Gil-González, 2021. "Dynamic Reactive Power Compensation in Power Systems through the Optimal Siting and Sizing of Photovoltaic Sources," Resources, MDPI, vol. 10(5), pages 1-17, May.
    15. Andres Annuk & Wahiba Yaïci & Matti Lehtonen & Risto Ilves & Toivo Kabanen & Peep Miidla, 2021. "Simulation of Energy Exchange between Single Prosumer Residential Building and Utility Grid," Energies, MDPI, vol. 14(6), pages 1-13, March.
    16. Dominika Kaczorowska & Jacek Rezmer & Michal Jasinski & Tomasz Sikorski & Vishnu Suresh & Zbigniew Leonowicz & Pawel Kostyla & Jaroslaw Szymanda & Przemyslaw Janik, 2020. "A Case Study on Battery Energy Storage System in a Virtual Power Plant: Defining Charging and Discharging Characteristics," Energies, MDPI, vol. 13(24), pages 1-22, December.

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