Optimal strategy to reduce energy waste in an electricity distribution network through direct/indirect bulk load control
In recent decades, the ever-increasing demand for electricity in large cities is leading the electricity distribution network (EDN) to an operational state of fatigue, especially at peak load times. In this context, load congestion, technical losses, and voltage deviations across the EDN can contrib...
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| Veröffentlicht in: | Energy (Oxford) Jg. 294; S. 130835 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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01.05.2024
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| ISSN: | 0360-5442 |
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| Abstract | In recent decades, the ever-increasing demand for electricity in large cities is leading the electricity distribution network (EDN) to an operational state of fatigue, especially at peak load times. In this context, load congestion, technical losses, and voltage deviations across the EDN can contribute to the high waste of electricity as well as to the worsening of the supply service. To face this problem, this paper proposes a mixed integer linear programming (MILP) model that aims to reshape the demand profile (i.e., load reduction in peak periods without load rebound in the remaining periods of the day) of total consumers while the voltage deviations and technical losses are minimized. In the proposed model, the demand profile reshaping is carried out through direct (DC) and indirect (IC) bulk control of residential, commercial, and industrial loads, while the load factor (LF), i.e., indicator related to the efficient use of electricity, is improved. Due to the scheduling of these loads at certain times of the day, the occurrence of voltage deviations and technical losses can be mitigated by the efficient control of capacitor banks (CBs). To corroborate the applicability of the proposed MILP model, the 33-node IEEE test system was used. The results show the technical and economic gains for the distribution company (DISCO) and the total number of consumers.
•A MILP model is proposed to reduce electricity waste in EDN.•DC and IC of bulk loads to reduce peak demand without occurrence of load rebound.•Control of CBs to mitigate EDN under and over voltages due to load variation.•Improvement of LF related to the EDN demand profile to alleviate operational stress. |
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| AbstractList | In recent decades, the ever-increasing demand for electricity in large cities is leading the electricity distribution network (EDN) to an operational state of fatigue, especially at peak load times. In this context, load congestion, technical losses, and voltage deviations across the EDN can contribute to the high waste of electricity as well as to the worsening of the supply service. To face this problem, this paper proposes a mixed integer linear programming (MILP) model that aims to reshape the demand profile (i.e., load reduction in peak periods without load rebound in the remaining periods of the day) of total consumers while the voltage deviations and technical losses are minimized. In the proposed model, the demand profile reshaping is carried out through direct (DC) and indirect (IC) bulk control of residential, commercial, and industrial loads, while the load factor (LF), i.e., indicator related to the efficient use of electricity, is improved. Due to the scheduling of these loads at certain times of the day, the occurrence of voltage deviations and technical losses can be mitigated by the efficient control of capacitor banks (CBs). To corroborate the applicability of the proposed MILP model, the 33-node IEEE test system was used. The results show the technical and economic gains for the distribution company (DISCO) and the total number of consumers. In recent decades, the ever-increasing demand for electricity in large cities is leading the electricity distribution network (EDN) to an operational state of fatigue, especially at peak load times. In this context, load congestion, technical losses, and voltage deviations across the EDN can contribute to the high waste of electricity as well as to the worsening of the supply service. To face this problem, this paper proposes a mixed integer linear programming (MILP) model that aims to reshape the demand profile (i.e., load reduction in peak periods without load rebound in the remaining periods of the day) of total consumers while the voltage deviations and technical losses are minimized. In the proposed model, the demand profile reshaping is carried out through direct (DC) and indirect (IC) bulk control of residential, commercial, and industrial loads, while the load factor (LF), i.e., indicator related to the efficient use of electricity, is improved. Due to the scheduling of these loads at certain times of the day, the occurrence of voltage deviations and technical losses can be mitigated by the efficient control of capacitor banks (CBs). To corroborate the applicability of the proposed MILP model, the 33-node IEEE test system was used. The results show the technical and economic gains for the distribution company (DISCO) and the total number of consumers. •A MILP model is proposed to reduce electricity waste in EDN.•DC and IC of bulk loads to reduce peak demand without occurrence of load rebound.•Control of CBs to mitigate EDN under and over voltages due to load variation.•Improvement of LF related to the EDN demand profile to alleviate operational stress. |
| ArticleNumber | 130835 |
| Author | Contreras, Javier Cerna, Fernando V. Naderi, Ehsan Dantas, Jamile T. |
| Author_xml | – sequence: 1 givenname: Fernando V. orcidid: 0000-0002-1880-626X surname: Cerna fullname: Cerna, Fernando V. email: fernando.cerna@ufrr.br organization: Department of Electrical Engineering, Federal University of Roraima, Boa Vista 69310-000, Brazil – sequence: 2 givenname: Jamile T. orcidid: 0000-0002-3435-2202 surname: Dantas fullname: Dantas, Jamile T. email: jamile.alves@ufrr.br organization: Department of Electrical Engineering, Federal University of Roraima, Boa Vista 69310-000, Brazil – sequence: 3 givenname: Ehsan surname: Naderi fullname: Naderi, Ehsan email: enaderi@astate.edu organization: Department of Electrical Engineering, College of Engineering and Computer Science, Arkansas State University, Jonesboro, AR, 72401, United States – sequence: 4 givenname: Javier orcidid: 0000-0002-9395-3964 surname: Contreras fullname: Contreras, Javier email: javier.contreras@uclm.es organization: School of Industrial Engineering, University of Castilla-La Mancha, 13071, Ciudad Real, Spain |
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| Keywords | Capacitor banks Distribution company Direct control Mixed-integer linear programming model Electricity distribution network Indirect control |
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