论文标题
开放挑战和问题：交易管理的人工智能
Open Challenges and Issues: Artificial Intelligence for Transactive Management
论文作者
论文摘要
人工智能（AI）的进步改善了能源管理的自动化。在智能能源管理或智能电网框架中，所有设备，分布式资源和可再生资源都嵌入了嵌入，从而降低了成本。智能能源管理系统，交易管理（TM）是提高电力系统效率和可靠性的概念。本文的目的是寻找基于AI和机器学习（ML）技术的TM方法的当前开发。在AI范式中，基于多基因系统（MAS）的方法是一个活跃的研究领域，仍处于进化状态。因此，本文介绍了如何在TM中应用的基于MAS的方法。本文还发现，基于MAS的方法面临设计或为各种代理设定目标的主要困难，并描述了ML技术如何为该解决方案做出贡献。还提供了MAS和ML技术之间的简短比较分析。最后，本文总结了基于AI的交易能源管理方法最相关的开放挑战和问题。
The advancement of Artificial Intelligence (AI) has improved the automation of energy managements. In smart energy management or in a smart grid framework, all the devices and the distributed resources and renewable resources are embedded which leads to reduce cost. A smart energy management system, Transactive management (TM) is a concept to improve the efficiency and reliability of the power system. The aim of this article is to look for the current development of TM methods based on AI and Machine Learning (ML) technology. In AI paradigm, MultiAgent System (MAS) based method is an active research area and are still in evolution. Hence this article describes how MAS based method applied in TM. This paper also finds that MAS based method faces major difficulty to design or set up goal to various agents and describes how ML technique can contribute to that solution. A brief comparison analysis between MAS and ML techniques are also presented. At the end, this article summarizes the most relevant open challenges and issues on the AI based methods for transactive energy management.
