Algorithm based on particle swarm applied to electrical load scheduling in an industrial setting

被引：9

作者：

Lopes, Rafael F. ^{[1
,3
]}

Costa, Fabiano F. ^{[1
]}

Oliveira, Aurenice ^{[2
]}

Lima, Antonio Cezar de C. ^{[1
]}

机构：

[1] Univ Fed Bahia, Dept Elect Engn, Salvador, BA, Brazil

[2] Michigan Technol Univ, Dept Elect & Comp Engn, Houghton, MI 49931 USA

[3] Fed Inst Educ Sci & Technol Baiano, Campus Urucuca, Urucuca, BA, Brazil

来源：

ENERGY | 2018年 / 147卷

关键词：

Metaheuristics; Combinatorial optimization; Particle swarm binary; Demand response management; DEMAND; CUSTOMER;

D O I：

10.1016/j.energy.2018.01.090

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

In this work we propose the development of a novel particle swarm-based heuristic to solve a discrete mathematical problem. Such a problem is present in allocating electrical loads throughout the day in an industrial setting. Data on the total installed load and energy demand throughout the day at 15-min intervals were collected in five industrial facilities. The loads were randomly distributed and the developed algorithm was applied to balance and optimize the energy demand throughout the day. The performance of the proposed algorithm was compared to a standard binary Particle Swarm Optimization and a mathematical model, which was also implemented to solve the problem. Our results demonstrate that the proposed algorithm is more efficient for all the considered scenarios, regardless of the amount of loads and constraints applied. (C) 2018 Elsevier Ltd. All rights reserved.

引用

页码：1007 / 1015

页数：9

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