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Optimal Power Dispatch for Maximum Energy Community Welfare by Considering Closed Distribution Systems and Renewable Sources

Author

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  • Paulo M. De Oliveira-De Jesus

    (Department of Electrical and Electronic Engineering, School of Engineering, Universidad de Los Andes, Bogotá 111711, Colombia)

  • Jose M. Yusta

    (Department of Electrical Engineering, University of Zaragoza, María de Luna 3, 50018 Zaragoza, Spain)

Abstract

Regulatory boards are promoting closed distribution systems (CDSs), which are different from traditional public-access networks, that can be owned and managed by energy communities (ECs). The inclusion of local renewable energy potential and an adequate schedule of storage devices in a CDS allow cooperation among the EC’s members in order to reduce operational expenditure (OPEX), providing internally competitive electricity prices with respect to those provided by publicly regulated networks and electricity markets. The CDS operators can assume a new role as the centralized energy dispatchers of generation and storage assets in order to maximize the profits of the members of the EC. This paper proposes an innovative optimal active and reactive power dispatch model for maximum community welfare conditions. A key difference between this proposal and existing social-welfare-based dispatches on public-access networks is the exclusion of the profit of the external wholesale electricity market. The focus of the proposed method is to maximize the welfare of all community members. A remuneration framework based on a collective EC with a single frontier is adopted, considering agreements between members based on locational marginal pricing (CDS-LMP). Results from an illustrative case study show a reduction of 50% in the EC’s OPEX with a payback time of 6 years for investments in CDSs, renewable sources, and storage.

Suggested Citation

  • Paulo M. De Oliveira-De Jesus & Jose M. Yusta, 2024. "Optimal Power Dispatch for Maximum Energy Community Welfare by Considering Closed Distribution Systems and Renewable Sources," Energies, MDPI, vol. 17(18), pages 1-21, September.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:18:p:4707-:d:1482603
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    References listed on IDEAS

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    1. Nwulu, Nnamdi I. & Xia, Xiaohua, 2017. "Optimal dispatch for a microgrid incorporating renewables and demand response," Renewable Energy, Elsevier, vol. 101(C), pages 16-28.
    2. Fatin Ishraque, Md. & Shezan, Sk. A. & Ali, M.M. & Rashid, M.M., 2021. "Optimization of load dispatch strategies for an islanded microgrid connected with renewable energy sources," Applied Energy, Elsevier, vol. 292(C).
    3. Zhang, Xizheng & Wang, Zeyu & Lu, Zhangyu, 2022. "Multi-objective load dispatch for microgrid with electric vehicles using modified gravitational search and particle swarm optimization algorithm," Applied Energy, Elsevier, vol. 306(PA).
    4. Lu, Xinhui & Liu, Zhaoxi & Ma, Li & Wang, Lingfeng & Zhou, Kaile & Feng, Nanping, 2020. "A robust optimization approach for optimal load dispatch of community energy hub," Applied Energy, Elsevier, vol. 259(C).
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    Cited by:

    1. Susanna Mocci & Simona Ruggeri & Fabrizio Pilo, 2024. "Low-Voltage Renewable Energy Communities’ Impact on the Distribution Networks," Energies, MDPI, vol. 18(1), pages 1-20, December.

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