Congestion management is one of the most important task in the modern power system. Considering the solar electric vehicle (SEV), generator rescheduling based congestion management approach is proposed here to mitigat...
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ISBN:
(纸本)9781538640210
Congestion management is one of the most important task in the modern power system. Considering the solar electric vehicle (SEV), generator rescheduling based congestion management approach is proposed here to mitigate the transmission congestion. Generator sensitivity factor (GSF) with whale optimization algorithm (WOA) is applied here to find the rescheduling amount and congestion cost of the system. The optimal location of the electric vehicle (EV) charging station is found by using bus sensitivity factor (BSF). To analyze the proposed congestion management approach, WOA algorithm is tested with modified IEEE 30 bus system. To validate the obtained results with WOA algorithm, particle swarm optimization (PSO) and ant lion optimizer (ALO) algorithms are also used in this paper. The obtained results prove the effectiveness of utilization of SEV for minimizing the active power rescheduling amount, active power loss and congestion cost of the system.
This paper presents, grey wolf optimizer (GWO) algorithm to solve a constrained nonlinear optimization problem of optimal placement and sizing of multiple active power filters (OPSMAPFs) for radial distribution system...
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ISBN:
(纸本)9781538617892
This paper presents, grey wolf optimizer (GWO) algorithm to solve a constrained nonlinear optimization problem of optimal placement and sizing of multiple active power filters (OPSMAPFs) for radial distribution system (RDS). It is a nature inspired stochastic algorithm. It has balanced exploration and exploitation characteristics. Minimization of the current of APF is taken as an object with three inequality constraints. To evaluate the performance of GWO algorithm, the simulation is performed on 33-bus RDS for twenty independent runs and compared with recently developed dragonfly algorithm (DA) and whale optimization algorithm (WOA). Simulation results demonstrate the effectiveness and stability of GWO algorithm.
The aim of economic dispatch is to allocate the generated power to minimize the total fuel costs while satisfying the overall constraints. In this paper, we propose a hybrid whale-wolf optimization method to accuratel...
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ISBN:
(纸本)9781538609903
The aim of economic dispatch is to allocate the generated power to minimize the total fuel costs while satisfying the overall constraints. In this paper, we propose a hybrid whale-wolf optimization method to accurately solve the economic dispatch problem. The proposed method efficiently integrates the mechanisms of whale optimization algorithm and gray wolf optimization with crossover and mutation operators. To demonstrate the effectiveness of the proposed method, it is compared with six optimization methods: gray wolf optimization, whaleoptimization, particle swarm optimization, artificial bee colony algorithm, ant lion algorithm, and dragonfly algorithm. Two different test systems (6 and 10 generating units) are used to evaluate the performance of the proposed method. The experimental results show that the hybrid whale-wolf optimization method shows better performance to find the optimal solution of the economic dispatch problem compared to the other methods.
This paper presents a new power system planning strategy by combining whale optimization algorithm (WOA) with pattern search algorithm (PS). The proposed approach has been carried out on the IEEE 30-bus test system co...
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ISBN:
(纸本)9780956715777
This paper presents a new power system planning strategy by combining whale optimization algorithm (WOA) with pattern search algorithm (PS). The proposed approach has been carried out on the IEEE 30-bus test system considering several objective functions, such as generating fuel cost, voltage profile improvement, minimization of total power losses and emission reduction are also considered. The obtained results are compared with recently published metaheuristic algorithms. Simulation results clearly reveal the effectiveness and the rapidity of the proposed algorithm for solving the OPF problem.
This paper presents a new power system planning strategy by combining whale optimization algorithm (WOA) with pattern search algorithm (PS). The proposed approach has been carried out on the IEEE 30-bus test system co...
详细信息
ISBN:
(纸本)9781509015948
This paper presents a new power system planning strategy by combining whale optimization algorithm (WOA) with pattern search algorithm (PS). The proposed approach has been carried out on the IEEE 30-bus test system considering several objective functions, such as generating fuel cost, voltage profile improvement, minimization of total power losses and emission reduction are also considered. The obtained results are compared with recently published metaheuristic algorithms. Simulation results clearly reveal the effectiveness and the rapidity of the proposed algorithm for solving the OPF problem.
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