消费者
可再生能源
点对点
环境经济学
投标
电
电力市场
需求响应
虚拟发电厂
业务
分布式发电
计算机科学
微观经济学
经济
分布式计算
工程类
电气工程
作者
Kaile Zhou,Yibo Chu,Hui Yin
标识
DOI:10.1016/j.scs.2024.105465
摘要
Peer-to-peer electricity trading has emerged as a critical way to meet the varied demands of prosumers within urban virtual power plants. To better support supply-demand balance and ensure the stable, low-carbon and efficient peer-to-peer electricity trading, both prosumer trading preferences and power demand heterogeneity need to be considered. This study proposes a peer-to-peer electricity trading model for urban virtual power plants that considers both preference of prosumers and power demand heterogeneity. First, to effectively meet the trading demands of diverse prosumers and enhance the penetration of renewable energy, prosumers are classified based on variations in financial returns, green electricity preferences and risk avoidance. Power demand is further classified based on the trading preferences of prosumers. Then, a peer-to-peer electricity trading model incorporating a game model and a market bidding mechanism is proposed to enable efficient and dynamic matching between supply and demand. Finally, to mitigate the impact of renewable energy uncertainty on peer-to-peer electricity trading, real-time auctions are implemented across multiple virtual power plants. The results show that the proposed model is capable of more effectively accommodating the diverse demands of prosumers, and facilitates a more stable, low-carbon and efficient peer-to-peer electricity trading.
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