A review of optimum DG placement based on minimization of power losses and voltage stability enhancement of distribution system

Sultana, Umbrin; Khairuddin, Azhar; Aman, M.M.; Mokhtar, Ahmad Safawi; Zareen, Naila

doi:10.1016/j.rser.2016.05.056

Cited by 193 publications

(101 citation statements)

References 104 publications

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“…The most extensive literature belongs to the studies that aim to plan the size and location of the DG, and a recent review of these studies is given in [17]. In addition, the studies that involve planning of DG sizing [18] or planning of DG siting [19,20] are examples of studies that have been carried out by different DG planning scopes.…”

Section: Motivation and Backgroundmentioning

confidence: 99%

“…In the optimum value approach, the most appropriate sizing and/or siting is determined according to the criteria considered in the study. The most important optimization studies can be given as grouped according to their objectives on which they are based; minimization of power losses [20,[23][24][25][26], minimization of energy losses [27], increasing system reliability based on various reliability indices [28,29] and minimization of costs [29,30]. There are also approaches to define the maximum permissible capacity value based on a single system criterion other than the hosting capacity and optimum values approaches [31][32][33][34][35][36][37].…”

Section: Motivation and Backgroundmentioning

confidence: 99%

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Maximum Permissible Integration Capacity of Renewable DG Units Based on System Loads

et al. 2018

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Abstract:Increasing demand for electricity, as well as rising environmental and economic concerns have resulted in renewable energy sources being a center of attraction. Integration of these renewable energy resources into power systems is usually achieved through distributed generation (DG) techniques, and the number of such applications increases daily. As conventional power systems do not have an infrastructure that is compatible with these energy sources and generation systems, such integration applications may cause various problems in power systems. Therefore, planning is an essential part of DG integration, especially for power systems with intermittent renewable energy sources with the objective of minimizing problems and maximizing benefits. In this study, a mathematical model is proposed to calculate the maximum permissible DG integration capacity without causing overvoltage problems in the power systems. In the proposed mathematical model, both the minimum loading condition and maximum generation condition are taken into consideration. In order to prove the effectiveness and the consistency of the proposed mathematical model, it is applied to a test system with different case studies, and the results are compared with the results obtained from other models in the literature.

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Section: Motivation and Backgroundmentioning

confidence: 99%

Section: Motivation and Backgroundmentioning

confidence: 99%

Maximum Permissible Integration Capacity of Renewable DG Units Based on System Loads

et al. 2018

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“…Probabilistic approach with DG penetration was discussed in Kolenc et al (2015). In distribution network voltage profile improvement and voltage stability issues have been taken as objectives in Aman et al (2012), Sultana et al (2016) and Singh and Parida (2016). Das et al (2016) proposed symbiotic organisms search algorithm for DG placement.…”

Section: Open Accessmentioning

confidence: 99%

Whale optimization algorithm for optimal sizing of renewable resources for loss reduction in distribution systems

2017

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Distributed generator (DG) resources are small scale electric power generating plants that can provide power to homes, businesses or industrial facilities in distribution systems. Power loss reductions, voltage profile improvement and increasing reliability are some advantages of DG units. The above benefits can be achieved by optimal placement of DGs. Whale optimization algorithm (WOA), a novel metaheuristic algorithm, is used to determine the optimal DG size. WOA is modeled based on the unique hunting behavior of humpback whales. The WOA is evaluated on IEEE 15, 33, 69 and 85-bus test systems. WOA was compared with different types of DGs and other evolutionary algorithms. When compared with voltage sensitivity index method, WOA and index vector methods gives better results. From the analysis best results have been achieved from type III DG operating at 0.9 pf.

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“…Numerous distribution planning techniques proposed in the literature since the last decade address the complex nature of DP problems from MDP perspectives. Major research accounts are nowadays more focused on DG planning options, conventional solution techniques and modified grid reinforcement strategies [6][7][8][9][10][11][12][13][14][15][16][17].…”

Section: Potential Planning Techniques In Modern Distribution Planningmentioning

confidence: 99%

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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A review of optimum DG placement based on minimization of power losses and voltage stability enhancement of distribution system

Cited by 193 publications

References 104 publications

Maximum Permissible Integration Capacity of Renewable DG Units Based on System Loads

Maximum Permissible Integration Capacity of Renewable DG Units Based on System Loads

Whale optimization algorithm for optimal sizing of renewable resources for loss reduction in distribution systems

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

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