A Multi-Hyperparameter Prediction Framework for Distributed Energy Trading on Photovoltaic Network

IF 6.6 1区 计算机科学 Q1 Multidisciplinary
Chun Chen;Yong Zhang;Boon Han Lim;Li Ning;Shengzhong Feng;Peng Xie
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引用次数: 0

Abstract

The rapid evolution of distributed energy resources, particularly photovoltaic systems, poses a formidable challenge in maintaining a delicate balance between energy supply and demand while minimizing costs. The integrated nature of distributed markets, blending centralized and decentralized elements, holds the promise of maximizing social welfare and significantly reducing overall costs, including computational and communication expenses. However, achieving this balance requires careful consideration of various hyperparameter sets, encompassing factors such as the number of communities, community detection methods, and trading mechanisms employed among nodes. To address this challenge, we introduce a groundbreaking neural network-based framework, the Energy Trading-based Artificial Neural Network (ET-ANN), which excels in performance compared to existing algorithms. Our experiments underscore the superiority of ET-ANN in minimizing total energy transaction costs while maximizing social welfare within the realm of photovoltaic networks.
光伏网络分布式能源交易的多参数预测框架
分布式能源,特别是光伏系统的迅速发展,对维持能源供需之间的微妙平衡,同时尽量降低成本提出了巨大的挑战。分布式市场的综合性质,混合了集中和分散的元素,有望最大限度地提高社会福利,并显著降低总体成本,包括计算和通信费用。然而,实现这种平衡需要仔细考虑各种超参数集,包括社区数量、社区检测方法和节点之间采用的交易机制等因素。为了应对这一挑战,我们引入了一种突破性的基于神经网络的框架,即基于能源交易的人工神经网络(ET-ANN),与现有算法相比,它在性能上更胜一筹。我们的实验强调了ET-ANN在光伏网络领域内最小化总能源交易成本和最大化社会福利方面的优势。
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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来源期刊
Tsinghua Science and Technology
Tsinghua Science and Technology COMPUTER SCIENCE, INFORMATION SYSTEMSCOMPU-COMPUTER SCIENCE, SOFTWARE ENGINEERING
CiteScore
10.20
自引率
10.60%
发文量
2340
期刊介绍: Tsinghua Science and Technology (Tsinghua Sci Technol) started publication in 1996. It is an international academic journal sponsored by Tsinghua University and is published bimonthly. This journal aims at presenting the up-to-date scientific achievements in computer science, electronic engineering, and other IT fields. Contributions all over the world are welcome.
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