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| A Rolling P2P Energy Trading Strategy Based on Distributed Information Interaction for Multi-Intelligent Buildings in Microgrids |
| Zhang Hong1, Zhang Zexi1, Li Yazhou2, Zhang Lianshuai1, Lu Chunxiao3 |
1. Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin 132012 China;
2. Shandong Weifang Pumped Storage Co. Ltd Weifang 262600 China;
3. State Grid Liaoning Electric Power Co., Ltd Shenyang Power Supply Company Shenyang 110002 China |
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Abstract In recent years, with the in-depth reform of the electricity market and the continuous improvement of the penetration rate of distributed resources in the distribution network, the energy trading between intelligent buildings with dual attributes of production and consumption has brought new opportunities and challenges to the nearby consumption of distributed energy. However, for the microgrid system with multi-intelligent buildings, there are defects such as large amount of communication information, low robustness and user privacy in the process of power trading. At the same time, it will also be affected by various uncertain factors such as the access of new energy and the lack of timeliness of transactions. In order to solve the above problems, this paper proposes a rolling P2P energy trading optimization strategy based on distributed information interaction for multi-intelligent buildings in microgrid.
Firstly, considering the aggregation characteristics of various flexible resources in intelligent buildings, the prediction interval results of distributed photovoltaic power generation and the feasible range of flexible resources are characterized in the form of aggregation power interval by Minkowski summation theory, and the aggregation interval model of P2P transaction is established. Among them, the distributed photovoltaic prediction interval is modeled by transforming the benchmark output at different confidence levels into the prediction quantile for the feasible region. At the same time, an interval rolling P2P energy trading framework is constructed. During the energy management period, each building participates in the rolling P2P energy trading by combining the aggregated power interval with its own electricity purchase and sale strategy. Secondly, the risk cost brought by the uncertainty of photovoltaic output to P2P transactions is quantified by CVaR, and an economic dispatch model with the minimum total operating cost of microgrid multi-intelligent buildings is established. On this basis, the P2P transaction power between buildings is used as a consistency variable, and the P2P transaction power and transaction price are obtained based on the distributed solution of the information interaction between adjacent buildings, and the energy transaction period is continuously pushed backward until it meets the requirements of all intelligent buildings in the microgrid.
In the case analysis, the scheduling results of different buildings in the microgrid and the optimization results of different algorithms are compared respectively, which verifies the effectiveness of the interval rolling P2P energy trading model proposed in this paper. At the same time, the practicability and solution efficiency of the distributed information interaction algorithm in this paper have also been reflected. Through the example analysis, the following conclusions can be drawn: (1) Participating in the energy transaction between buildings in the form of aggregation interval fully taps the scheduling potential of flexible resources in buildings and improves the flexibility of coordinated scheduling of multi-intelligent buildings in microgrid. (2) Compared with the ordinary P2P trading, the rolling P2P energy trading improves the enthusiasm of intelligent buildings to participate in energy trading and the self-consumption level of distributed energy while taking into account the economy of system operation. (3) The distributed information interaction strategy proposed in this paper makes the multi-intelligent buildings in the microgrid only need to interact with the expected transaction volume information, and at the same time solve their own optimization problems in parallel, which has a good fit with the rolling P2P transaction mode. It avoids the problems of high computational pressure and privacy leakage, and improves the convergence speed of distributed information interaction. It has good scalability and can effectively solve the optimization iteration problem of large-scale intelligent buildings.
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Received: 17 June 2024
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2025, Vol. 40 
