智能电网技术作为创新能源发展的概念:对乌克兰发展的初步建议

V. Pliuhin, Vitaliy Teterev, Anatolii Lapko
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引用次数: 3

摘要

智能电网概念的形成涉及许多问题,包括理论和方法。这一理论形成的主要问题之一是其基础的构建,其发展的起点是智能电网的定义,这是一种关于未来电力工程的观点系统概念,其运行原理和技术基础与现代能源相比发生了重大变化。本文旨在回顾和发展智能电网定义的方向和方法,结合机器学习机制,突出其多样性和共性,以发展整体的创新能源发展。本文对乌克兰的能源部门进行了研究。考虑了其效率和创新发展。会议强调了在使用替代能源以及监测和管理系统时出现的实施智能电网技术的问题。采用基于机器学习系统和神经网络的数据科学方法,确定了智能电网优化问题的数学表述方式。分析了大数据处理方法、数据挖掘、统计方法、人工智能方法和机器学习。数据库和应用软件的设计和开发将使用数据科学方法完成。智能技术将接管资产的控制、会计和诊断过程,这将为电力系统的自我恢复以及固定资产的有效运营提供有希望的机会。随着智能电网技术的引入,乌克兰电力行业将发生重大的根本性变化。这是从集中发电和输电方式向分布式网络的过渡,分布式网络能够在任何点(包括消费者层面)控制能源生产设施和网络拓扑结构。以消费者主动影响的方法取代集中的需求预测成为管理体系的一个要素和主题。构建以高性能信息计算基础设施为核心的能源体系。这种方法为广泛引进新设备创造了先决条件,增加了设备的可操作性和可控性。下一代操作应用程序(SCADA/EMS/NMS)的创建允许使用创新的算法和电力系统管理方法,包括其新的有源电源元件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart Grid Technologies as a Concept of Innovative Energy Development: Initial Proposals for the Development of Ukraine
The formation of the concept of Smart Grid is associated with a number of issues, including theoretical and methodological. One of the main problems in forming such theory is to build its basis, the starting point for the development of which is the definition of Smart Grid as a systems of views concept on the future of power engineering, the principles of operation and technological basis of which undergoes significant changes compared to modern energy. The paper is aimed at reviewing and developing directions and approaches to the definition of Smart Grid in combination with machine learning mechanisms, highlighting their diverse and common nature to develop a holistic innovative energy development. In this paper, a study of the energy sector in Ukraine was conducted. Its efficiency and innovative development are considered. Problems with the implementation of Smart Grid technology, which arise when using alternative sources and monitoring and administration systems, were highlighted. The ways of mathematical formulation of the Smart Grid optimization problem are determined using the Data Science approach based on the machine learning system and neural networks. Big Data processing methods, Data Mining, statistical methods, artificial intelligence methods, and Machine Learning are analyzed. The design and development of databases and application software will be done using the Data Science method. Smart-technologies will take over the processes of control, accounting and diagnostics of assets, which will provide promising opportunities for self-recovery of the power system, as well as efficient operation of fixed assets. With the introduction of Smart Grid technologies for the Ukrainian power industry, significant fundamental changes will take place. This is the transition from centralized methods of generation and transmission of electricity to distributed networks with the ability to control energy production facilities and network topology at any point, including at the consumer level. Replacement of centralized demand forecasting according to the methodology of active consumer influence becomes an element and subject of the management system. A high-performance information and computing infrastructure will be built as the core of the energy system. This approach creates the preconditions for the widespread introduction of new devices that increase the maneuverability and controllability of the equipment. The creation of next-generation operational applications (SCADA/EMS/NMS) allows the use of innovative algorithms and methods of power system management, including its new active power elements.
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