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Management of renewable energy production and distribution planning using agent-based modelling

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  • Mohammed, Nooriya A.
  • Al-Bazi, Ammar

Abstract

The use of renewable energy sources is increasing worldwide to achieve energy production sustainability. To reach this goal and mitigate against climate changes all energy resources must be optimally managed. In this paper, an innovative multi agent-based heuristic optimisation system is developed to address renewable energy systems’ challenges associated with the management of renewables including storage devices, planning of energy distribution, and consumption flexibility. A new heuristic algorithm is developed to introduce an efficient and sustainable storage strategy of surplus energy generated by different renewable resource options. This leads to archiving optimised storage levels of energy across different located storage devices in order to face risk of production shortages due to weather conditions. In order to test the behaviour of the developed system and address its benefits, a case study in the Republic of IRAQ is developed. Twelve major cities (in order of population size) distributed in 5 main regions including North, South, East, West and Middle parts of the country are selected, and hybrid renewable power generation sources such as Wind, PV-solar and Hydro are implemented based on weather changes. The results highlight the effect of high suppliers’ rate on electricity exchange and production planning from differently used renewable technologies. A sensitivity analysis is conducted to verify the behaviour of the developed model on different demand behaviour types.

Suggested Citation

  • Mohammed, Nooriya A. & Al-Bazi, Ammar, 2021. "Management of renewable energy production and distribution planning using agent-based modelling," Renewable Energy, Elsevier, vol. 164(C), pages 509-520.
    • Handle: RePEc:eee:renene:v:164:y:2021:i:c:p:509-520
    DOI: 10.1016/j.renene.2020.08.159
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    References listed on IDEAS

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    1. Weitemeyer, Stefan & Kleinhans, David & Vogt, Thomas & Agert, Carsten, 2015. "Integration of Renewable Energy Sources in future power systems: The role of storage," Renewable Energy, Elsevier, vol. 75(C), pages 14-20.
    2. Kayal, Partha & Chanda, C.K., 2015. "Optimal mix of solar and wind distributed generations considering performance improvement of electrical distribution network," Renewable Energy, Elsevier, vol. 75(C), pages 173-186.
    3. Obara, Shin'ya & Ito, Yuji & Okada, Masaki, 2018. "Optimization algorithm for power-source arrangement that levels the fluctuations in wide-area networks of renewable energy," Energy, Elsevier, vol. 142(C), pages 447-461.
    4. Li, Rui & Wang, Wei & Wu, Xuezhi & Tang, Fen & Chen, Zhe, 2019. "Cooperative planning model of renewable energy sources and energy storage units in active distribution systems: A bi-level model and Pareto analysis," Energy, Elsevier, vol. 168(C), pages 30-42.
    5. Zaman, Forhad & Elsayed, Saber M. & Ray, Tapabrata & Sarker, Ruhul A., 2016. "Evolutionary algorithms for power generation planning with uncertain renewable energy," Energy, Elsevier, vol. 112(C), pages 408-419.
    6. Rui Li & Wei Wang & Zhe Chen & Jiuchun Jiang & Weige Zhang, 2017. "A Review of Optimal Planning Active Distribution System: Models, Methods, and Future Researches," Energies, MDPI, vol. 10(11), pages 1-27, October.
    7. Luz, Thiago & Moura, Pedro & de Almeida, Aníbal, 2018. "Multi-objective power generation expansion planning with high penetration of renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2637-2643.
    8. Xiong, Linyun & Li, Penghan & Wang, Ziqiang & Wang, Jie, 2020. "Multi-agent based multi objective renewable energy management for diversified community power consumers," Applied Energy, Elsevier, vol. 259(C).
    9. Jafari, Mohammad & Malekjamshidi, Zahra, 2020. "Optimal energy management of a residential-based hybrid renewable energy system using rule-based real-time control and 2D dynamic programming optimization method," Renewable Energy, Elsevier, vol. 146(C), pages 254-266.
    10. V. V Thang & Thanhtung Ha, 2019. "Optimal Planning of Energy Hubs Considering Renewable Energy Sources and Battery Energy Storage System," International Journal of Sustainable Energy and Environmental Research, Conscientia Beam, vol. 8(1), pages 36-47.
    11. V. V. Thang & Thanhtung Ha, 2019. "Optimal Planning of Energy Hubs Considering Renewable Energy Sources and Battery Energy Storage System," International Journal of Sustainable Energy and Environmental Research, Conscientia Beam, vol. 8(1), pages 36-47.
    12. Kebir, Anouer & Woodward, Lyne & Akhrif, Ouassima, 2019. "Real-time optimization of renewable energy sources power using neural network-based anticipative extremum-seeking control," Renewable Energy, Elsevier, vol. 134(C), pages 914-926.
    13. Emilio Ghiani & Andrea Giordano & Andrea Nieddu & Luca Rosetti & Fabrizio Pilo, 2019. "Planning of a Smart Local Energy Community: The Case of Berchidda Municipality (Italy)," Energies, MDPI, vol. 12(24), pages 1-14, December.
    14. Kasaei, Mohammad Javad & Gandomkar, Majid & Nikoukar, Javad, 2017. "Optimal management of renewable energy sources by virtual power plant," Renewable Energy, Elsevier, vol. 114(PB), pages 1180-1188.
    15. Ricardo Faia & Pedro Faria & Zita Vale & João Spinola, 2019. "Demand Response Optimization Using Particle Swarm Algorithm Considering Optimum Battery Energy Storage Schedule in a Residential House," Energies, MDPI, vol. 12(9), pages 1-18, April.
    16. Dominik Franjo Dominković & Greg Stark & Bri-Mathias Hodge & Allan Schrøder Pedersen, 2018. "Integrated Energy Planning with a High Share of Variable Renewable Energy Sources for a Caribbean Island," Energies, MDPI, vol. 11(9), pages 1-15, August.
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