Fuzzy Embedded Genetic Algorithm Method for Distributed Generation Planning

Vinothkumar, K; Selvan, M. P.

doi:10.1080/15325008.2010.528533

Cited by 70 publications

(36 citation statements)

References 25 publications

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“…The ε-constrained method [21,22]; MCS [23]; goal programming [26,32]; fuzzy, WSM [29]; MCS, AHP [30]; PSO [31] and multi-criteria stochastic programming model (MSPM) [34]; VPQ (B): GA based fuzzy multi-objective method [54,60].…”

Section: Hybrid Methodsmentioning

confidence: 99%

Section: Planning Techniques Based On Evaluation Methods In Multi-objmentioning

confidence: 99%

“…GA is also used for comparison of results and advocated for large DNW systems even with suboptimal solutions. [29] 2010 5 2 ✓ --✓ A fuzzy embedded GA is employed to solve fuzzy weighted single objective function employing fuzzy set theory for MODGP. [30] 2011 5 1 ✓ ---MCS-embedded GA is presented to solve chance constrained programming framework considering future uncertainties of loads/DGs.…”

Section: Planning Techniques Based On Evaluation Methods In Multi-objmentioning

confidence: 99%

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Multi-Objective Planning Techniques in Distribution Networks: A Composite Review

2017

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Distribution networks (DNWs) are facing numerous challenges, notably growing load demands, environmental concerns, operational constraints and expansion limitations with the current infrastructure. These challenges serve as a motivation factor for various distribution network planning (DP) strategies, such as timely addressing load growth aiming at prominent objectives such as reliability, power quality, economic viability, system stability and deferring costly reinforcements. The continuous transformation of passive to active distribution networks (ADN) needs to consider choices, primarily distributed generation (DG), network topology change, installation of new protection devices and key enablers as planning options in addition to traditional grid reinforcements. Since modern DP (MDP) in deregulated market environments includes multiple stakeholders, primarily owners, regulators, operators and consumers, one solution fit for all planning scenarios may not satisfy all these stakeholders. Hence, this paper presents a review of several planning techniques (PTs) based on mult-objective optimizations (MOOs) in DNWs, aiming at better trade-off solutions among conflicting objectives and satisfying multiple stakeholders. The PTs in the paper spread across four distinct planning classifications including DG units as an alternative to costly reinforcements, capacitors and power electronic devices for ensuring power quality aspects, grid reinforcements, expansions, and upgrades as a separate category and network topology alteration and reconfiguration as a viable planning option. Several research works associated with multi-objective planning techniques (MOPT) have been reviewed with relevant models, methods and achieved objectives, abiding with system constraints. The paper also provides a composite review of current research accounts and interdependence of associated components in the respective classifications. The potential future planning areas, aiming at the multi-objective-based frameworks, are also presented in this paper.Keywords: active distribution network (ADN); distributed generation (DG); distributed energy resources (DERs); distribution network planning (DP); multi-objective optimization (MOO); multi-criteria decision analysis (MCDA); distributed generation placement (DGP); volt-ampere reactive power (VAR) compensation and power quality (VPQ); component reinforcement and up gradation (CRU); network (distribution) topology change and reconfiguration (NTR); planning techniques (PT); multiple objective planning (MOP); multi-objective planning techniques (MOPTs); future distribution networks (FDNs)

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Section: Hybrid Methodsmentioning

confidence: 99%

Section: Planning Techniques Based On Evaluation Methods In Multi-objmentioning

confidence: 99%

Section: Planning Techniques Based On Evaluation Methods In Multi-objmentioning

confidence: 99%

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Multi-Objective Planning Techniques in Distribution Networks: A Composite Review

2017

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“…The pareto front is obtained for simultaneous optimization of three objectives and final solution is selected from non-dominated solutions by normalized membership functions. Optimal allocation of DG models has been done by minimizing voltage deviation index, real and reactive power loss index, line loading index and short-circuit index using fuzzy embedded GA [22]. The multi-objective problem is simplified by assigning fuzzy membership function to each index.…”

Section: Introductionmentioning

confidence: 99%

“…The multi-objective problem is simplified by assigning fuzzy membership function to each index. Goal optimization algorithm [23] has been used for optimal allocation of DG in distribution system by achieving the set goal for the indices used in [22]. In [24] combination of GA and PSO has been utilized by where optimal site is obtained by GA and size of DG is obtained by PSO.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization Approach for Placement of Multiple DGs for Voltage Sensitive Loads

Kaur

Jain

2017

Energies

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This paper presents the optimal placement of multiple Dispersed Generators using multi-objective optimization. The optimization is carried out with objectives namely active power loss, reactive power loss, voltage deviation and overall economy. The multi-objective optimization and accounting conflicting objectives are realized through Particle Swarm Optimization with fuzzy decision approach to find the optimal sizes and sites of Dispersed Generators for voltage dependent residential, commercial and industrial loads. The clusters of buses are formulated from base case load flow to limit the search space for finding the placement of the Dispersed Generators. The effectiveness of the proposed approach is tested on a 69-bus radial distribution. It is found that the optimal placement of the Dispersed Generators improves the overall performance of the system and the optimal allocation is affected by the type of load.

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Power loss minimization in distribution systems using multiple distributed generations

Mahmoud

Yorino

Ahmed

2015

IEEJ Transactions Elec Engng

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In this work, an efficient analytical method is proposed for optimally allocating distributed generations (DGs) in electrical distribution systems to minimize power losses. The proposed analytical method can be employed for obtaining the optimal combination of different DG types in a distribution system for loss minimization. The validity of the proposed method is demonstrated using two test systems with different configurations by comparing with the exact optimal solution obtained from the exhaustive optimal power flow (OPF) algorithm. The calculated results and the comprehensive comparisons with existing methods prove the superiority of the proposed method in terms of accuracy and calculation speed. The proposed loss minimization method can be a useful tool for any general DG allocation problem since it provides effective and fast loss evaluation taking into account other benefits.

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Fuzzy Embedded Genetic Algorithm Method for Distributed Generation Planning

Cited by 70 publications

References 25 publications

Multi-Objective Planning Techniques in Distribution Networks: A Composite Review

Multi-Objective Planning Techniques in Distribution Networks: A Composite Review

Multi-Objective Optimization Approach for Placement of Multiple DGs for Voltage Sensitive Loads

Power loss minimization in distribution systems using multiple distributed generations

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