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Smart integration of renewable energy resources, electrical, and thermal energy storage in microgrid applications

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  • Tooryan, Fatemeh
  • HassanzadehFard, Hamid
  • Collins, Edward R.
  • Jin, Shuangshuang
  • Ramezani, Bahram

Abstract

With changes in energy policies to increase renewable energy resources integration, reduce fossil fuel consumption, and mitigate the environmental impact, optimal management of distributed energy resources becomes one of the key factors in the design of microgrid systems. This paper presents an optimum design and operation of a microgrid consisting of wind turbine, photovoltaic array, battery energy storage system, thermal energy storage, fuel cells, and boilers with consideration of electrical, heating and cooling loads. To optimize energy management, the uncertainty of renewable energy resources is considered. Furthermore, the system waste is utilized to produce biogas for boilers to meet heating demands within the system. The optimum energy management problem of distributed energy resources in the microgrid is solved using a Particle Swarm Optimization algorithm. The optimization results are obtained via minimizing the objective function which includes total cost of the system, greenhouse gas emissions, and fuel consumption. The results are shown that there is about a 24.56% reduction in CO2 emission when the produced heat of FC units are employed. It is observed that the utilization of produced energy from system waste brought down fuel consumption by 7%. The simulation results verify the efficiency and effectiveness of the proposed approach.

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  • Tooryan, Fatemeh & HassanzadehFard, Hamid & Collins, Edward R. & Jin, Shuangshuang & Ramezani, Bahram, 2020. "Smart integration of renewable energy resources, electrical, and thermal energy storage in microgrid applications," Energy, Elsevier, vol. 212(C).
    • Handle: RePEc:eee:energy:v:212:y:2020:i:c:s0360544220318247
    DOI: 10.1016/j.energy.2020.118716
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    13. Àlex Alonso-Travesset & Helena Martín & Sergio Coronas & Jordi de la Hoz, 2022. "Optimization Models under Uncertainty in Distributed Generation Systems: A Review," Energies, MDPI, vol. 15(5), pages 1-40, March.
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