Demand-Side Management Optimization Using Genetic Algorithms: A Case Study

被引：5

作者：

dos Santos Junior, Lauro Correa ^{[1
]}

Tabora, Jonathan Munoz ^{[1
,2
]}

Reis, Josivan ^{[1
]}

Andrade, Vinicius ^{[1
]}

Carvalho, Carminda ^{[1
]}

Manito, Allan ^{[1
]}

Tostes, Maria ^{[1
]}

Matos, Edson ^{[1
]}

Bezerra, Ubiratan ^{[1
]}

机构：

[1] Fed Univ Para, Inst Technol, Elect Engn Fac, BR-66075110 Belem, PA, Brazil

[2] Natl Autonomous Univ Honduras UNAH, Elect Engn Dept, Tegucigalpa 04001, Honduras

来源：

ENERGIES | 2024年 / 17卷 / 06期

关键词：

genetic algorithms; demand-side management; energy efficiency; optimization; active power demand; ENERGY;

D O I：

10.3390/en17061463

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

This paper addresses the optimization of contracted electricity demand (CD) for commercial and industrial entities, focusing on cost reduction within the Brazilian time-of-use electricity tariff scheme. Leveraging genetic algorithms (GAs), this study proposes a practical approach to determining the optimal CD profile, considering the complex dynamics of energy demand on a city-like load. The methodology is applied to a case study at the Federal University of Para, Brazil, where energy efficiency and demand response initiatives as well as renewable energy projects are underway. The findings highlight the significance of tailored demand management strategies in achieving energy-related cost reduction for large-scale consumers, with implications for economic efficiency in energy consumption.

引用

页数：14

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