Nature-Inspired Algorithms for Energy Management Systems

IF 0.8 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE International Journal of Swarm Intelligence Research Pub Date : 2023-03-10 DOI:10.4018/ijsir.319310
Meera P. S., Lavanya V.
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引用次数: 1

Abstract

The electric grid is being increasingly integrated with renewable energy sources whose output is mostly fluctuating in nature. The load demand is also increasing day by day, mainly due to the increased interest in electric vehicles and other automated devices. An energy management system helps in maintaining the balance between the available generation and the load demand and thus optimizes the energy usage. It also helps in reducing the peak load, green-house gas emissions, and the operational cost. Energy management can be performed at different levels and is essential for realizing smart homes, smart buildings, and even smart grid. The different objectives considered for designing energy management systems are reduction of emissions, energy cost, operational cost, peak demand, etc. Many traditional and hybrid nature-inspired algorithms are used for optimizing these various objectives. This paper intends to give an overview about the various nature-inspired algorithms used for optimizing energy management systems in homes, buildings, and micro grid.
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能源管理系统的自然启发算法
电网正越来越多地与可再生能源相结合,而可再生能源的输出大多是波动的。负载需求也日益增加,主要是由于对电动汽车和其他自动化设备的兴趣增加。能源管理系统有助于维持可用发电量和负荷需求之间的平衡,从而优化能源使用。它还有助于减少峰值负荷、温室气体排放和运营成本。能源管理可以在不同的层次上进行,是实现智能家居、智能建筑甚至智能电网的必要条件。设计能源管理系统时考虑的不同目标是减少排放、能源成本、运营成本、峰值需求等。许多传统的和混合的自然启发算法被用于优化这些不同的目标。本文旨在概述用于优化家庭,建筑物和微电网中能源管理系统的各种自然启发算法。
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来源期刊
International Journal of Swarm Intelligence Research
International Journal of Swarm Intelligence Research COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
2.50
自引率
0.00%
发文量
76
期刊介绍: The mission of the International Journal of Swarm Intelligence Research (IJSIR) is to become a leading international and well-referred journal in swarm intelligence, nature-inspired optimization algorithms, and their applications. This journal publishes original and previously unpublished articles including research papers, survey papers, and application papers, to serve as a platform for facilitating and enhancing the information shared among researchers in swarm intelligence research areas ranging from algorithm developments to real-world applications.
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