日前连续双拍卖为基础的点对点能源交易平台,包括交易损失和网络使用费

IF 2.4 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC IET Smart Grid Pub Date : 2023-02-20 DOI:10.1049/stg2.12103
Sheroze Liaquat, Tanveer Hussain, Berk Celik, Robert Fourney, Timothy M. Hansen
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引用次数: 1

摘要

分布式能源的整合,例如光伏太阳能(PV),为建立本地能源市场框架提供了新的机会,以提高住宅部门对可再生能源的利用。这种点对点(P2P)能源交易是指一种本地市场结构,客户(和生产消费者)相互作用,分享多余的光伏发电,以提高个人和社区的社会福利。本文设计了一种考虑网络损失和网络使用费的基于日前连续双拍卖(CDA)的P2P市场结构。日前PV能量使用分数积分多项式建模,并使用每个市场区间的自回归集成移动平均模型预测输出。基于客户负荷和多余的光伏能源,CDA市场使用出价/要价匹配机制进行清算。在分析网络约束效应的同时,通过计算不同的福利指标来评估P2P市场的绩效。研究结果表明,设计的基于cda的P2P市场结构使所有参与者的社会福利比基线平均增加了17.75%。此外,还量化了前一天市场和实时市场之间预测误差的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Day-ahead continuous double auction-based peer-to-peer energy trading platform incorporating trading losses and network utilisation fee

Integration of distributed energy resources, such as photovoltaic solar (PV), introduces new opportunities to establish local energy market frameworks to improve renewable energy utilisation in residential sectors. Such peer-to-peer (P2P) energy trading refers to a local market structure where customers (and prosumers) interact to share excess PV generation to enhance the individual and community social welfare. In this work, a day-ahead continuous double auction (CDA)-based P2P market structure considering network losses and network utilisation fees was designed. Day-ahead PV energy is modelled using fractional integral polynomials and the output is forecasted using an autoregressive integrated moving average model for each market interval. Based on the customer load and excess PV energy, the CDA market is cleared using a bid/ask matching mechanism. The performance of the P2P market was evaluated by computing different welfare metrics while analysing the effect of network constraints. The results show that the designed CDA-based P2P market structure increases the social welfare of all participants by an average of 17.75% compared to the baseline for the presented cases. Moreover, the impact of the forecasting error between the day-ahead and real-time market was also quantified.

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来源期刊
IET Smart Grid
IET Smart Grid Computer Science-Computer Networks and Communications
CiteScore
6.70
自引率
4.30%
发文量
41
审稿时长
29 weeks
期刊最新文献
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