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Optimal sharing energy of a complex of houses through energy trading in the Internet of energy

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  • Lin, Chun-Cheng
  • Wu, Yi-Fang
  • Liu, Wan-Yu

Abstract

To increase utilization of distributed renewable energy and decrease dependence on conventional electrical grids, the Internet of energy integrates smart grids with battery energy storage systems and the Internet of things to utilize redundant energy, so that energy can be shared among users. However, few works considered sharing energy in the Internet of energy from a residential community scale. Therefore, this paper constructs a mixed-integer programming model for the optimal sharing energy of a complex of houses through the Internet of energy with an energy trading platform, by which houses with renewable energy facilities and battery energy storage systems can trade and share energy so that the total profit of the whole complex of houses is maximized. This paper further solves this problem by a hybrid algorithm of harmony search and variable neighborhood search, which are good at finding optimal solutions through population search and individual search, respectively. Additionally, a solution repairing scheme is proposed to guarantee solution feasibility during the algorithm. Through simulation, this algorithm can save energy consumption of 748.17 kW for one day, and shift the peak load. On the average, each house can make a profit above 70¢ for one day.

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  • Lin, Chun-Cheng & Wu, Yi-Fang & Liu, Wan-Yu, 2021. "Optimal sharing energy of a complex of houses through energy trading in the Internet of energy," Energy, Elsevier, vol. 220(C).
    • Handle: RePEc:eee:energy:v:220:y:2021:i:c:s0360544220327201
    DOI: 10.1016/j.energy.2020.119613
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    7. Kühnbach, Matthias & Bekk, Anke & Weidlich, Anke, 2022. "Towards improved prosumer participation: Electricity trading in local markets," Energy, Elsevier, vol. 239(PE).
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