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Flexible Loads Scheduling Algorithms for Renewable Energy Communities

Author

Listed:
  • Tiago Fonseca

    (School of Engineering, Polytechnical Institute of Porto, 4249-015 Porto, Portugal)

  • Luis Lino Ferreira

    (School of Engineering, Polytechnical Institute of Porto, 4249-015 Porto, Portugal)

  • Jorge Landeck

    (LIBPhys, Department of Physics, University of Coimbra, 3004-516 Coimbra, Portugal)

  • Lurian Klein

    (Cleanwatts, 3040-574 Coimbra, Portugal)

  • Paulo Sousa

    (School of Engineering, Polytechnical Institute of Porto, 4249-015 Porto, Portugal)

  • Fayaz Ahmed

    (Cleanwatts, 3040-574 Coimbra, Portugal)

Abstract

Renewable Energy Communities (RECs) are emerging as an effective concept and model to empower the active participation of citizens in the energy transition, not only as energy consumers but also as promoters of environmentally friendly energy generation solutions, particularly through the use of photovoltaic panels. This paper aims to contribute to the management and optimization of individual and community Distributed Energy Resources (DER). The solution follows a price and source-based REC management program, in which consumers’ day-ahead flexible loads (Flex Offers) are shifted according to electricity generation availability, prices, and personal preferences, to balance the grid and incentivize user participation. The heuristic approach used in the proposed algorithms allows for the optimization of energy resources in a distributed edge-and-fog approach with a low computational overhead. The simulations performed using real-world energy consumption and flexibility data of a REC with 50 dwellings show an average cost reduction, taking into consideration all the seasons of the year, of 6.5%, with a peak of 12.2% reduction in the summer, and an average increase of 32.6% in individual self-consumption. In addition, the case study demonstrates promising results regarding grid load balancing and the introduction of intra-community energy trading.

Suggested Citation

  • Tiago Fonseca & Luis Lino Ferreira & Jorge Landeck & Lurian Klein & Paulo Sousa & Fayaz Ahmed, 2022. "Flexible Loads Scheduling Algorithms for Renewable Energy Communities," Energies, MDPI, vol. 15(23), pages 1-24, November.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:23:p:8875-:d:982785
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    References listed on IDEAS

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    1. Feuerriegel, Stefan & Neumann, Dirk, 2014. "Measuring the financial impact of demand response for electricity retailers," Energy Policy, Elsevier, vol. 65(C), pages 359-368.
    2. Torriti, Jacopo, 2012. "Price-based demand side management: Assessing the impacts of time-of-use tariffs on residential electricity demand and peak shifting in Northern Italy," Energy, Elsevier, vol. 44(1), pages 576-583.
    3. Gianluca Serale & Massimo Fiorentini & Alfonso Capozzoli & Daniele Bernardini & Alberto Bemporad, 2018. "Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities," Energies, MDPI, vol. 11(3), pages 1-35, March.
    4. Haider, Haider Tarish & See, Ong Hang & Elmenreich, Wilfried, 2016. "Residential demand response scheme based on adaptive consumption level pricing," Energy, Elsevier, vol. 113(C), pages 301-308.
    5. Pol Olivella-Rosell & Pau Lloret-Gallego & Íngrid Munné-Collado & Roberto Villafafila-Robles & Andreas Sumper & Stig Ødegaard Ottessen & Jayaprakash Rajasekharan & Bernt A. Bremdal, 2018. "Local Flexibility Market Design for Aggregators Providing Multiple Flexibility Services at Distribution Network Level," Energies, MDPI, vol. 11(4), pages 1-19, April.
    6. Sanya Carley & David M. Konisky, 2020. "The justice and equity implications of the clean energy transition," Nature Energy, Nature, vol. 5(8), pages 569-577, August.
    7. Kavita Surana & Sarah M. Jordaan, 2019. "The climate mitigation opportunity behind global power transmission and distribution," Nature Climate Change, Nature, vol. 9(9), pages 660-665, September.
    8. Nistor, Silviu & Wu, Jianzhong & Sooriyabandara, Mahesh & Ekanayake, Janaka, 2015. "Capability of smart appliances to provide reserve services," Applied Energy, Elsevier, vol. 138(C), pages 590-597.
    9. Zhengjie You & Michel Zade & Babu Kumaran Nalini & Peter Tzscheutschler, 2021. "Flexibility Estimation of Residential Heat Pumps under Heat Demand Uncertainty," Energies, MDPI, vol. 14(18), pages 1-19, September.
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