A cost-benefit multiobjective approach for placement of meters in electrical distribution systems
| Autor: | Leonardo W. de Oliveira, Felipe G. Duque, Julio Cesar Stacchini de Souza, Edimar J. de Oliveira |
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| Rok vydání: | 2021 |
| Předmět: |
Mathematical optimization
Computer science 020209 energy 020208 electrical & electronic engineering Pareto principle Phasor Energy Engineering and Power Technology 02 engineering and technology Investment (macroeconomics) Units of measurement 0202 electrical engineering electronic engineering information engineering Benchmark (computing) Metre Metering mode Electrical and Electronic Engineering Metaheuristic |
| Zdroj: | Electric Power Systems Research. 191:106897 |
| ISSN: | 0378-7796 |
| DOI: | 10.1016/j.epsr.2020.106897 |
| Popis: | The present work proposes a multiobjective approach for optimal allocation of metering devices in Electrical Distribution Systems. The proposed approach seeks to obtain solutions that represent attractive investment options for utilities, while providing good performance for State Estimation (SE) when processing measurements from the allocated meters. The requirements of low investment costs and good SE performance are conflicting ones. In this paper, the Pareto multiobjective method, associated with the Modified Monkey Search (MMS) metaheuristic, is employed to obtain concurrent candidate solutions for optimal allocation of smart meters and phasor measurement units. The proposed method, called MMS-Pareto, is employed along with an efficient tool for SE in distribution networks, known as Enhanced Optimal Power Flow. The proposed method is assessed using benchmark systems of the literature, as well as a real Brazilian utility network, being adopted practical and updated costs for the meter devices. Comparisons with a weighted mono-objective approach are presented and the obtained results show that the MMS-Pareto can lead to good trade-off solutions, useful for system planners. Moreover, comparisons with the results obtained when employing other metaheuristics are presented. |
| Databáze: | OpenAIRE |
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