Fuzzy Multiobjective Optimal Power Flow Based on Modified Artificial Bee Colony Algorithm

He, Xuanhu; Wang, Wei

doi:10.1155/2014/961069

Cited by 5 publications

(5 citation statements)

References 28 publications

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“…Compared to subjective setting or several tests for weighting methods to get proper weight coefficients, the fuzzy mathematics method uses a membership function to perform objective function fuzzification to form the fuzzy multi-objective function. There is no need to use weighting coefficients to tackle multi-objective problems in the fuzzy mathematics method, and the solution is obtained objectively [14].…”

Section: Fuzzy Mathematical Methods For Multi-objective Problemsmentioning

confidence: 99%

Coordinated Charging Strategy for Electric Taxis in Temporal and Spatial Scale

et al. 2015

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Currently, electric taxis have been deployed in many cities of China. However, the charging unbalance in both temporal and spatial scale has become a rising problem, which leads to low charging efficiency or charging congestion in different stations or time periods. This paper presents a multi-objective coordinated charging strategy for electric taxis in the temporal and spatial scale. That is, the objectives are maximizing the utilization efficiency of charging facilities, minimizing the load unbalance of the regional power system and minimizing the customers' cost. Besides, the basic configuration of a charging station and operation rules of electric taxis would be the constraints. To tackle this multi-objective optimizing problems, a fuzzy mathematical method has been utilized to transfer the multi-objective optimization to a single optimization issue, and furthermore, the Improved Particle Swarm Optimization (IPSO) Algorithm has been used to solve the optimization problem. Moreover, simulation cases are carried out, Case 1 is the original charging procedure, and Cases 2 and 3 are the temporal and spatial scale optimized separately, followed with Case 4, the combined coordinated charging. The simulation shows the significant improvement in charging facilities efficiency and users' benefits, as well as the better dispatching of electric taxis' charging loads. OPEN ACCESSEnergies 2015, 8 1257

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Section: Fuzzy Mathematical Methods For Multi-objective Problemsmentioning

confidence: 99%

Coordinated Charging Strategy for Electric Taxis in Temporal and Spatial Scale

et al. 2015

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“…Consumer incentive will be paid with consumers. Based on model is planned at aspect [59]. In their manuscript, they established a method to congestion via combining DR as well as FACTS.…”

Section: Demand Response Managementmentioning

confidence: 99%

A Comprehensive Review of Congestion Management in Power System

Manohar¹,

Rajesh²,

Shajin³

2022

IJIE

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In recent decades, restructuring has cut across all probable domains, involving the power supply industry. The restructuring has brought about considerable changes whereby electricity is now a commodity and has become a deregulated one. These competitive markets have paved the way for countless entrants. This has caused overload and congestion on transmission lines. In addition, the open access transmission network has created a more intensified congestion issue. Therefore, congestion management on power systems is relevant and central significance to the power industry. This manuscript reviews few congestion management techniques, consists of Reprogramming Generation (GR), Load Shedding, Optimal Distributed Generation (DG) Location, Nodal Pricing, Free Methods, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Fuzzy Logic System Method, as well as Additional Renewable Energy Sources. In this manuscript a review work is performed to unite the entire publications on congestion management.

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“…The fuzzy mathematics method, with the membership function, has been utilized to perform the objective function fuzzification to transfer the multi-objective optimization to a single-objective issue [15,16].…”

Section: Fuzzy Multi-objective Optimizationmentioning

confidence: 99%

Optimal Scheduling of a Battery Energy Storage System with Electric Vehicles’ Auxiliary for a Distribution Network with Renewable Energy Integration

et al. 2015

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Abstract:With global conventional energy depletion, as well as environmental pollution, utilizing renewable energy for power supply is the only way for human beings to survive. Currently, distributed generation incorporated into a distribution network has become the new trend, with the advantages of controllability, flexibility and tremendous potential. However, the fluctuation of distributed energy resources (DERs) is still the main concern for accurate deployment. Thus, a battery energy storage system (BESS) has to be involved to mitigate the bad effects of DERs' integration. In this paper, optimal scheduling strategies for BESS operation have been proposed, to assist with consuming the renewable energy, reduce the active power loss, alleviate the voltage fluctuation and minimize the electricity cost. Besides, the electric vehicles (EVs) considered as the auxiliary technique are also introduced to attenuate the DERs' influence. Moreover, both day-ahead and real-time operation scheduling strategies were presented under the consideration with the constraints of BESS and the EVs' operation, and the optimization was tackled by a fuzzy mathematical method and an improved particle swarm optimization (IPSO) algorithm. Furthermore, the test system for the proposed strategies is a real distribution network with renewable energy integration.

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Fuzzy Multiobjective Optimal Power Flow Based on Modified Artificial Bee Colony Algorithm

Cited by 5 publications

References 28 publications

Coordinated Charging Strategy for Electric Taxis in Temporal and Spatial Scale

Coordinated Charging Strategy for Electric Taxis in Temporal and Spatial Scale

A Comprehensive Review of Congestion Management in Power System

Optimal Scheduling of a Battery Energy Storage System with Electric Vehicles’ Auxiliary for a Distribution Network with Renewable Energy Integration

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