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A novel approach towards uncertainty modeling in multiobjective optimal power flow with renewable integration
被引:24
作者:
Saha, Anulekha
[1
]
Bhattacharya, Aniruddha
[2
]
Das, Priyanath
[1
]
Chakraborty, Ajoy Kumar
[1
]
机构:
[1] Natl Inst Technol Agartala, Dept Elect Engn, Agartala, Tripura, India
[2] Natl Inst Technol Durgapur, Dept Elect Engn, Durgapur, W Bengal, India
关键词:
differential evolution (DE);
metaheuristics;
OPF;
symbiotic organisms search (SOS);
two-point estimate method (2PEM);
OPTIMIZATION;
ALGORITHM;
SEARCH;
DISPATCH;
NEWTON;
OPF;
D O I:
10.1002/2050-7038.12136
中图分类号:
TM [电工技术];
TN [电子技术、通信技术];
学科分类号:
0808 ;
0809 ;
摘要:
This paper presents a novel methodology for solving multiobjective optimal power flow (MOPF) considering uncertain renewable generation. Two-point estimate method (2PEM) is employed to take care of the uncertainty in renewable generation. Optimal power flow (OPF) is a very challenging optimization problem to solve due to its nonlinear nature. To overcome the constraints faced by classical optimization techniques, a novel hybrid metaheuristic algorithm is designed and applied to solve the MOPF problem. Since uncertainty in generation is considered, a probabilistic approach is required. Five different algorithms have been applied to the MOPF problem using 2PEM for the sake of comparison, and results show superiority of the proposed metaheuristic in achieving optimal results.
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页数:29
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