Artificial Intelligent Systems and Machine Learning

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Application of Differential Evolution in the Assessment of Capacity Benefit Margin


Affiliations
1 Department of Electrical and Electronics Engineering, Pondicherry Engineering College, Puducherry, India
2 Department of Physics, Pondicherry Engineering College, Puducherry, India
     

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In a competitive electric power market, the knowledge of available transfer capability (ATC) can help power marketers,sellers and buyers in planning, operation and reserving transmission services. Capacity Benefit Margin is an important factor in the calculation of ATC. In this paper, a new algorithm using Differential Evolution is proposed to calculate CBM. Monte Carlo method is used to calculate necessary loss of load indices. The proposed algorithm is tested on Practical Indian utility 62 bus test system. The results of proposed algorithm are compared with those obtained using Particle Swarm Optimization (PSO). It is found that DE yields better results than PSO.

Keywords

Total Transfer Capability (TTC), Differential Evolution (DE), Capacity Benefit Margin (CBM), Loss-of-Load Expectation (LOLE), Particle Swarm Optimization (PSO).
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  • Application of Differential Evolution in the Assessment of Capacity Benefit Margin

Abstract Views: 329  |  PDF Views: 4

Authors

R. Rajathy
Department of Electrical and Electronics Engineering, Pondicherry Engineering College, Puducherry, India
R. Gnanadass
Department of Electrical and Electronics Engineering, Pondicherry Engineering College, Puducherry, India
K. Manivannan
Department of Electrical and Electronics Engineering, Pondicherry Engineering College, Puducherry, India
Harish Kumar
Department of Physics, Pondicherry Engineering College, Puducherry, India

Abstract


In a competitive electric power market, the knowledge of available transfer capability (ATC) can help power marketers,sellers and buyers in planning, operation and reserving transmission services. Capacity Benefit Margin is an important factor in the calculation of ATC. In this paper, a new algorithm using Differential Evolution is proposed to calculate CBM. Monte Carlo method is used to calculate necessary loss of load indices. The proposed algorithm is tested on Practical Indian utility 62 bus test system. The results of proposed algorithm are compared with those obtained using Particle Swarm Optimization (PSO). It is found that DE yields better results than PSO.

Keywords


Total Transfer Capability (TTC), Differential Evolution (DE), Capacity Benefit Margin (CBM), Loss-of-Load Expectation (LOLE), Particle Swarm Optimization (PSO).