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SwarmGrid: Demand-Side Management with Distributed Energy Resources Based on Multifrequency Agent Coordination

Author

Listed:
  • Manuel Castillo-Cagigal

    (E.T.S. Ingenieros de Telecomunicación, Universidad Politécnica de Madrid, Av. Complutense 30, 28040 Madrid, Spain)

  • Eduardo Matallanas

    (E.T.S. Ingenieros de Telecomunicación, Universidad Politécnica de Madrid, Av. Complutense 30, 28040 Madrid, Spain)

  • Estefanía Caamaño-Martín

    (Instituto de Energía Solar, E.T.S. Ingenieros de Telecomunicación, Universidad Politécnica de Madrid, Av. Complutense 30, 28040 Madrid, Spain)

  • Álvaro Gutiérrez Martín

    (E.T.S. Ingenieros de Telecomunicación, Universidad Politécnica de Madrid, Av. Complutense 30, 28040 Madrid, Spain)

Abstract

This paper focuses on a multi-agent coordination for demand-side management in electrical grids with high penetration rates of distributed generation, in particular photovoltaic generation. This coordination is done by the use of swarm intelligence and coupled oscillators, proposing a novel methodology, which is implemented by the so-call SwarmGrid algorithm. SwarmGrid seeks to smooth the aggregated consumption by considering distributed and local generation by the development of a self-organized algorithm based on multifrequency agent coordination. The objective of this algorithm is to increase stability and reduce stress of the electrical grid by the aggregated consumption smoothing based on a frequency domain approach. The algorithm allows not only improvements in the electrical grid, but also increases the penetration of distributed and renewable sources. Contrary to other approaches, this objective is achieved anonymously without the need for information exchange between the users; it only takes into account the aggregated consumption of the whole grid.

Suggested Citation

  • Manuel Castillo-Cagigal & Eduardo Matallanas & Estefanía Caamaño-Martín & Álvaro Gutiérrez Martín, 2018. "SwarmGrid: Demand-Side Management with Distributed Energy Resources Based on Multifrequency Agent Coordination," Energies, MDPI, vol. 11(9), pages 1-16, September.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:9:p:2476-:d:170453
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    References listed on IDEAS

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    1. Masa-Bote, D. & Castillo-Cagigal, M. & Matallanas, E. & Caamaño-Martín, E. & Gutiérrez, A. & Monasterio-Huelín, F. & Jiménez-Leube, J., 2014. "Improving photovoltaics grid integration through short time forecasting and self-consumption," Applied Energy, Elsevier, vol. 125(C), pages 103-113.
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    Citations

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    Cited by:

    1. Álvaro Gutiérrez, 2022. "Optimization Trends in Demand-Side Management," Energies, MDPI, vol. 15(16), pages 1-3, August.
    2. Libor Dražan & René Križan & Miroslav Popela, 2021. "Design and Testing of a Low-Tech DEW Generator for Determining Electromagnetic Immunity of Standard Electronic Circuits," Energies, MDPI, vol. 14(11), pages 1-15, May.
    3. Pawan Kumar & Gagandeep Singh Brar & Surjit Singh & Srete Nikolovski & Hamid Reza Baghaee & Zoran Balkić, 2019. "Perspectives and Intensification of Energy Efficiency in Commercial and Residential Buildings Using Strategic Auditing and Demand-Side Management," Energies, MDPI, vol. 12(23), pages 1-31, November.
    4. Jie Ma & Xiandong Ma & Suzana Ilic, 2019. "HVAC-Based Cooperative Algorithms for Demand Side Management in a Microgrid," Energies, MDPI, vol. 12(22), pages 1-19, November.
    5. Pedro Faria & Zita Vale, 2019. "Distributed Energy Resources Management 2018," Energies, MDPI, vol. 13(1), pages 1-4, December.

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