Development of the business feasibility evaluation model for a profitable P2P electricity trading by estimating the optimal trading price

JOURNAL OF CLEANER PRODUCTION

卷:295

Article

An, Jongbaek¹  Hong, Taehoon¹  Lee, Minhyun² 

[1] Yonsei Univ, Dept Architecture & Architectural Engn, Seoul 03722, South Korea

[2] Hong Kong Polytech Univ, Dept Bldg & Real Estate, Hong Kong, Peoples R China

关键词: Optimal trading price of electricity;    Peer-to-Peer electricity trading;    Energy prosumer;    Levelized cost of electricity;    Business feasibility evaluation;    Genetic algorithm;   

DOI  :  10.1016/j.jclepro.2021.126138

来源: Elsevier

【 摘 要 】

For the market participants (i.e., energy consumers and prosumers) in a microgrid to acquire profits via trading surplus electricity, it is essential to determine an appropriate trading price of electricity. Therefore, this study developed a business feasibility evaluation model to predict the optimal trading price of electricity that maximizes the profits of both the market participants participating in the Peer-to Peer (P2P) electricity trading, by reflecting the structure of electricity market in South Korea. The residential areas located in the seven metropolitan cities in South Korea (Seoul, Incheon, Daejeon, Daegu, Ulsan, Busan, and Gwangju) were selected for the model application. The main findings from the model application are as follows. First, the annual electricity generation of the solar photovoltaic (PV) panel was highest in Daegu (5,541 kWh) and lowest in Seoul (3,569 kWh). In addition, the electricity generation was generally shown to be higher in spring (MarcheMay) and relatively lower in summer and winter. Second, the estimated annual maximum profit of the energy prosumer was highest in Daegu (US$995.5) and lowest in Seoul (US$638.1). Furthermore, it was determined to be beneficial to the energy prosumers to reduce their self-use rate to the extent possible. By using the developed business feasibility evaluation model, decision makers, including specialists and non-specialists, can determine the optimal trading price of electricity and whether to participate in the market of P2P electricity trading. (c) 2021 Elsevier Ltd. All rights reserved.

【 授权许可】

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