Reactive power price clearing using multi-objective optimization
This paper presents a new multi-objective optimization based reactive power price clearing (RPPC) mechanism, considering voltage stability. Use of realistic voltage dependent load models is important in power system analysis and optimization. The influence of the same on RPPC is investigated in this...
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| Published in | Energy (Oxford) Vol. 36; no. 5; pp. 3579 - 3589 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Kidlington
Elsevier Ltd
01.05.2011
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0360-5442 |
| DOI | 10.1016/j.energy.2011.03.070 |
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| Abstract | This paper presents a new multi-objective optimization based reactive power price clearing (RPPC) mechanism, considering voltage stability. Use of realistic voltage dependent load models is important in power system analysis and optimization. The influence of the same on RPPC is investigated in this paper. Investigations have also been carried out to ascertain the effectiveness of objectives such as, Total Payment Function (TPF), Loss Minimization (LM), Load Served (LS) and Voltage Stability Enhancement Index (VSEI). The unsuitability of LM/TPF minimization as independent or joint objective(s) for this problem, due to load served reduction is emphasized. The effect of loading condition on judicious combination of these objectives is further probed. The multi-objective RPPC problem is solved using Strength Pareto Evolutionary Algorithm (SPEA). Some of the results are also compared with the Multi-Objective Particle Swarm Optimization (MOPSO). The utility of the proposed approach is demonstrated through detailed investigation on IEEE 30 bus system considering base and stressed cases with constant and voltage dependent load modeling.
► The present work uses realistic
‘voltage dependent load models’ which is extremely important in Reactive Power Price Clearing (RPPC). ► The suitability of various objectives for RPPC is highlighted. ► This paper establishes the necessity of multi-objective optimization for RPPC, in view of voltage dependent load models. ► The paper emphasizes the need for selecting judiciously a combination of objectives best suited for a given operating condition. |
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| AbstractList | This paper presents a new multi-objective optimization based reactive power price clearing (RPPC) mechanism, considering voltage stability. Use of realistic voltage dependent load models is important in power system analysis and optimization. The influence of the same on RPPC is investigated in this paper. Investigations have also been carried out to ascertain the effectiveness of objectives such as, Total Payment Function (TPF), Loss Minimization (LM), Load Served (LS) and Voltage Stability Enhancement Index (VSEI). The unsuitability of LM/TPF minimization as independent or joint objective(s) for this problem, due to load served reduction is emphasized. The effect of loading condition on judicious combination of these objectives is further probed. The multi-objective RPPC problem is solved using Strength Pareto Evolutionary Algorithm (SPEA). Some of the results are also compared with the Multi-Objective Particle Swarm Optimization (MOPSO). The utility of the proposed approach is demonstrated through detailed investigation on IEEE 30 bus system considering base and stressed cases with constant and voltage dependent load modeling. This paper presents a new multi-objective optimization based reactive power price clearing (RPPC) mechanism, considering voltage stability. Use of realistic voltage dependent load models is important in power system analysis and optimization. The influence of the same on RPPC is investigated in this paper. Investigations have also been carried out to ascertain the effectiveness of objectives such as, Total Payment Function (TPF), Loss Minimization (LM), Load Served (LS) and Voltage Stability Enhancement Index (VSEI). The unsuitability of LM/TPF minimization as independent or joint objective(s) for this problem, due to load served reduction is emphasized. The effect of loading condition on judicious combination of these objectives is further probed. The multi-objective RPPC problem is solved using Strength Pareto Evolutionary Algorithm (SPEA). Some of the results are also compared with the Multi-Objective Particle Swarm Optimization (MOPSO). The utility of the proposed approach is demonstrated through detailed investigation on I II 30 bus system considering base and stressed cases with constant and voltage dependent load modeling. This paper presents a new multi-objective optimization based reactive power price clearing (RPPC) mechanism, considering voltage stability. Use of realistic voltage dependent load models is important in power system analysis and optimization. The influence of the same on RPPC is investigated in this paper. Investigations have also been carried out to ascertain the effectiveness of objectives such as, Total Payment Function (TPF), Loss Minimization (LM), Load Served (LS) and Voltage Stability Enhancement Index (VSEI). The unsuitability of LM/TPF minimization as independent or joint objective(s) for this problem, due to load served reduction is emphasized. The effect of loading condition on judicious combination of these objectives is further probed. The multi-objective RPPC problem is solved using Strength Pareto Evolutionary Algorithm (SPEA). Some of the results are also compared with the Multi-Objective Particle Swarm Optimization (MOPSO). The utility of the proposed approach is demonstrated through detailed investigation on IEEE 30 bus system considering base and stressed cases with constant and voltage dependent load modeling. ► The present work uses realistic ‘voltage dependent load models’ which is extremely important in Reactive Power Price Clearing (RPPC). ► The suitability of various objectives for RPPC is highlighted. ► This paper establishes the necessity of multi-objective optimization for RPPC, in view of voltage dependent load models. ► The paper emphasizes the need for selecting judiciously a combination of objectives best suited for a given operating condition. |
| Author | Abhyankar, A.R. Bijwe, P.R. Reddy, S. Surender |
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| Keywords | Multi-objective optimization Electricity markets Ancillary services Reactive power management Load modeling Genetic algorithms |
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| SubjectTerms | algorithms Ancillary services Applied sciences Clearing Economic data Electric energy Electric potential Electricity markets Energy Energy economics Exact sciences and technology General, economic and professional studies Genetic algorithms Load modeling Methodology. Modelling Minimization Multi-objective optimization Optimization prices Reactive power Reactive power management Utilities Voltage Voltage stability |
| Title | Reactive power price clearing using multi-objective optimization |
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