Probabilistic Multi Objective Optimal Reactive Power Dispatch Considering Load Uncertainties Using Monte Carlo Simulations
Optimal Reactive Power Dispatch (ORPD) is a multi-variable problem with nonlinear constraints and continuous/discrete decision variables. Due to the stochastic behavior of loads, the ORPD requires a probabilistic mathematical model. In this paper, Monte Carlo Simulation (MCS) is used for modeling of...
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Gespeichert in:
| Autor*in: |
S.M. Mohseni-Bonab [verfasserIn] A. Rabiee [verfasserIn] S. Jalilzadeh [verfasserIn] B. Mohammadi-Ivatloo [verfasserIn] S. Nojavan [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015 |
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In: Journal of Operation and Automation in Power Engineering - University of Mohaghegh Ardabili, 2015, 3(2015), 1, Seite 83-93 |
|---|---|
| Übergeordnetes Werk: |
volume:3 ; year:2015 ; number:1 ; pages:83-93 |
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| 520 | |a Optimal Reactive Power Dispatch (ORPD) is a multi-variable problem with nonlinear constraints and continuous/discrete decision variables. Due to the stochastic behavior of loads, the ORPD requires a probabilistic mathematical model. In this paper, Monte Carlo Simulation (MCS) is used for modeling of load uncertainties in the ORPD problem. The problem is formulated as a nonlinear constrained multi objective (MO) optimization problem considering two objectives, i.e., minimization of active power losses and voltage deviations from the corresponding desired values, subject to full AC load flow constraints and operational limits. The control variables utilized in the proposed MO-ORPD problem are generator bus voltages, transformers’ tap ratios and shunt reactive power compensation at the weak buses. The proposed probabilistic MO-ORPD problem is implemented on the IEEE 30-bus and IEEE 118-bus tests systems. The obtained numerical results substantiate the effectiveness and applicability of the proposed probabilistic MO-ORPD problem. | ||
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(DE-627)DOAJ044678398 (DE-599)DOAJ7c71b36b338e4c71ab8f41c172dcba80 DE-627 ger DE-627 rakwb eng TK1-9971 TK1001-1841 S.M. Mohseni-Bonab verfasserin aut Probabilistic Multi Objective Optimal Reactive Power Dispatch Considering Load Uncertainties Using Monte Carlo Simulations 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Optimal Reactive Power Dispatch (ORPD) is a multi-variable problem with nonlinear constraints and continuous/discrete decision variables. Due to the stochastic behavior of loads, the ORPD requires a probabilistic mathematical model. In this paper, Monte Carlo Simulation (MCS) is used for modeling of load uncertainties in the ORPD problem. The problem is formulated as a nonlinear constrained multi objective (MO) optimization problem considering two objectives, i.e., minimization of active power losses and voltage deviations from the corresponding desired values, subject to full AC load flow constraints and operational limits. The control variables utilized in the proposed MO-ORPD problem are generator bus voltages, transformers’ tap ratios and shunt reactive power compensation at the weak buses. The proposed probabilistic MO-ORPD problem is implemented on the IEEE 30-bus and IEEE 118-bus tests systems. The obtained numerical results substantiate the effectiveness and applicability of the proposed probabilistic MO-ORPD problem. Monte Carlo simulation Multi objective optimal reactive power dispatch Real power loss Voltage deviation Electrical engineering. Electronics. Nuclear engineering Production of electric energy or power. Powerplants. Central stations A. Rabiee verfasserin aut S. Jalilzadeh verfasserin aut B. Mohammadi-Ivatloo verfasserin aut S. Nojavan verfasserin aut In Journal of Operation and Automation in Power Engineering University of Mohaghegh Ardabili, 2015 3(2015), 1, Seite 83-93 (DE-627)176059119X 23224576 nnns volume:3 year:2015 number:1 pages:83-93 https://doaj.org/article/7c71b36b338e4c71ab8f41c172dcba80 kostenfrei http://joape.uma.ac.ir/article_297_24132e6e4adb189bffd1678113c9d456.pdf kostenfrei https://doaj.org/toc/2322-4576 Journal toc kostenfrei https://doaj.org/toc/2423-4567 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ AR 3 2015 1 83-93 |
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(DE-627)DOAJ044678398 (DE-599)DOAJ7c71b36b338e4c71ab8f41c172dcba80 DE-627 ger DE-627 rakwb eng TK1-9971 TK1001-1841 S.M. Mohseni-Bonab verfasserin aut Probabilistic Multi Objective Optimal Reactive Power Dispatch Considering Load Uncertainties Using Monte Carlo Simulations 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Optimal Reactive Power Dispatch (ORPD) is a multi-variable problem with nonlinear constraints and continuous/discrete decision variables. Due to the stochastic behavior of loads, the ORPD requires a probabilistic mathematical model. In this paper, Monte Carlo Simulation (MCS) is used for modeling of load uncertainties in the ORPD problem. The problem is formulated as a nonlinear constrained multi objective (MO) optimization problem considering two objectives, i.e., minimization of active power losses and voltage deviations from the corresponding desired values, subject to full AC load flow constraints and operational limits. The control variables utilized in the proposed MO-ORPD problem are generator bus voltages, transformers’ tap ratios and shunt reactive power compensation at the weak buses. The proposed probabilistic MO-ORPD problem is implemented on the IEEE 30-bus and IEEE 118-bus tests systems. The obtained numerical results substantiate the effectiveness and applicability of the proposed probabilistic MO-ORPD problem. Monte Carlo simulation Multi objective optimal reactive power dispatch Real power loss Voltage deviation Electrical engineering. Electronics. Nuclear engineering Production of electric energy or power. Powerplants. Central stations A. Rabiee verfasserin aut S. Jalilzadeh verfasserin aut B. Mohammadi-Ivatloo verfasserin aut S. Nojavan verfasserin aut In Journal of Operation and Automation in Power Engineering University of Mohaghegh Ardabili, 2015 3(2015), 1, Seite 83-93 (DE-627)176059119X 23224576 nnns volume:3 year:2015 number:1 pages:83-93 https://doaj.org/article/7c71b36b338e4c71ab8f41c172dcba80 kostenfrei http://joape.uma.ac.ir/article_297_24132e6e4adb189bffd1678113c9d456.pdf kostenfrei https://doaj.org/toc/2322-4576 Journal toc kostenfrei https://doaj.org/toc/2423-4567 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ AR 3 2015 1 83-93 |
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probabilistic multi objective optimal reactive power dispatch considering load uncertainties using monte carlo simulations |
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TK1-9971 |
| title_auth |
Probabilistic Multi Objective Optimal Reactive Power Dispatch Considering Load Uncertainties Using Monte Carlo Simulations |
| abstract |
Optimal Reactive Power Dispatch (ORPD) is a multi-variable problem with nonlinear constraints and continuous/discrete decision variables. Due to the stochastic behavior of loads, the ORPD requires a probabilistic mathematical model. In this paper, Monte Carlo Simulation (MCS) is used for modeling of load uncertainties in the ORPD problem. The problem is formulated as a nonlinear constrained multi objective (MO) optimization problem considering two objectives, i.e., minimization of active power losses and voltage deviations from the corresponding desired values, subject to full AC load flow constraints and operational limits. The control variables utilized in the proposed MO-ORPD problem are generator bus voltages, transformers’ tap ratios and shunt reactive power compensation at the weak buses. The proposed probabilistic MO-ORPD problem is implemented on the IEEE 30-bus and IEEE 118-bus tests systems. The obtained numerical results substantiate the effectiveness and applicability of the proposed probabilistic MO-ORPD problem. |
| abstractGer |
Optimal Reactive Power Dispatch (ORPD) is a multi-variable problem with nonlinear constraints and continuous/discrete decision variables. Due to the stochastic behavior of loads, the ORPD requires a probabilistic mathematical model. In this paper, Monte Carlo Simulation (MCS) is used for modeling of load uncertainties in the ORPD problem. The problem is formulated as a nonlinear constrained multi objective (MO) optimization problem considering two objectives, i.e., minimization of active power losses and voltage deviations from the corresponding desired values, subject to full AC load flow constraints and operational limits. The control variables utilized in the proposed MO-ORPD problem are generator bus voltages, transformers’ tap ratios and shunt reactive power compensation at the weak buses. The proposed probabilistic MO-ORPD problem is implemented on the IEEE 30-bus and IEEE 118-bus tests systems. The obtained numerical results substantiate the effectiveness and applicability of the proposed probabilistic MO-ORPD problem. |
| abstract_unstemmed |
Optimal Reactive Power Dispatch (ORPD) is a multi-variable problem with nonlinear constraints and continuous/discrete decision variables. Due to the stochastic behavior of loads, the ORPD requires a probabilistic mathematical model. In this paper, Monte Carlo Simulation (MCS) is used for modeling of load uncertainties in the ORPD problem. The problem is formulated as a nonlinear constrained multi objective (MO) optimization problem considering two objectives, i.e., minimization of active power losses and voltage deviations from the corresponding desired values, subject to full AC load flow constraints and operational limits. The control variables utilized in the proposed MO-ORPD problem are generator bus voltages, transformers’ tap ratios and shunt reactive power compensation at the weak buses. The proposed probabilistic MO-ORPD problem is implemented on the IEEE 30-bus and IEEE 118-bus tests systems. The obtained numerical results substantiate the effectiveness and applicability of the proposed probabilistic MO-ORPD problem. |
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Probabilistic Multi Objective Optimal Reactive Power Dispatch Considering Load Uncertainties Using Monte Carlo Simulations |
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https://doaj.org/article/7c71b36b338e4c71ab8f41c172dcba80 http://joape.uma.ac.ir/article_297_24132e6e4adb189bffd1678113c9d456.pdf https://doaj.org/toc/2322-4576 https://doaj.org/toc/2423-4567 |
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| author2 |
A. Rabiee S. Jalilzadeh B. Mohammadi-Ivatloo S. Nojavan |
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A. Rabiee S. Jalilzadeh B. Mohammadi-Ivatloo S. Nojavan |
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176059119X |
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TK - Electrical and Nuclear Engineering |
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2024-07-04T00:03:39.246Z |
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