Multiobjective distributed generation placement using fuzzy goal programming with genetic algorithm

Kim, Kyu Ho; Song, Kyung Bin; Joo, Sung Kwan; Lee, Yu Jeong; Kim, Jin O.

doi:10.1002/etep.226

Cited by 74 publications

(37 citation statements)

References 13 publications

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“…[23] 2007 2 1 ✓ ---MCS embedded in GA planning methodology is proposed to improve the accuracy for stochastic DG integration with tradeoff solution. [24] 2008 3 1 ✓ ---NSGA-II along with max-min approach solves MODGP problem considering future load uncertainties and risk management [25] 2008 6 1 ✓ ---EA is employed to solve IMO considering both time-varying generation and demand behavior aiming at various technical impacts of DGP [26] 2008 2 1 ✓ ---GA with goal programming methodology finds a solution with associated uncertainties among MO and constraints. [27] 2008 3 1 ✓ ---The proposed NSGA algorithm finds arrangements for wind-based DGs regarding compromise solution among contrasting objectives.…”

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

confidence: 99%

“…EA is employed to solve IMO considering both time-varying generation and demand behavior aiming at various technical impacts of DGP [26] 2008 2 1 ✓ ---GA with goal programming methodology finds a solution with associated uncertainties among MO and constraints. [27] 2008…”

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

confidence: 99%

“…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%

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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: 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 DG units change the flow over the feeders of the distribution network by injecting active and reactive power to their interconnection node. They may cause different benefits for Distribution Network Operators (DNOs) as reported in the literature, such as: network investment deferral [1], [2], active loss reduction [3]- [6], environmental emission reduction [7] and reliability improvement [8]. These benefits are obtained just if they are connected in the appropriate sizes and locations.…”

Section: Introductionmentioning

confidence: 99%

“…This makes a chance for DNO to identify the technical characteristics of the network and provide economic signals for investors to know how much and where they should invest. Most of the reported models and methods of the literature deal with the DG sizing and placement problem in a DG-owned DNO environment, like [3], [9], [12], [15], [16]. In [3], a fuzzy goal programming is proposed to solve a multi-objective model which minimizes the active losses and improves voltage profile.…”

Section: Introductionmentioning

confidence: 99%

Efficient immune‐GA method for DNOs in sizing and placement of distributed generation units

Soroudi

Ehsan

2010

Int Trans Elec Energy Syst

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This paper proposes a hybrid heuristic optimization method based on genetic algorithm and immune systems to maximize the benefits of distribution network operators (DNOs) accrued due to sizing and placement of distributed generation (DG) units in distribution networks. The effects of DG units in reducing the reinforcement costs and active power losses of distribution network have been investigated. In the presented method, the integration of DG units in distribution network is done considering both technical and economical aspects. The strength of the proposed method is evaluated by applying it on a small and a realistic large scale distribution network and the results are compared with analytical classic and other heuristic methods and discussed.

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Evaluating the effects of renewable and non-renewable DGs on DNEP from the reliability, uncertainty, and operational points of view by employing hybrid GA and OPF

Bagheri

Monsef

Lesani

2014

Int. Trans. Electr. Energ. Syst.

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SUMMARYThis paper proposes an approach to evaluate the effects of renewable and non-renewable distributed generations (DGs) on distribution network expansion planning from the reliability, uncertainty, and operational viewpoints. This methodology aims to determine the optimal capacity reinforcement of distribution network to meet the load growth in the planning horizon subject to the technical and operational constraints in the presence of utility-owned DG units. The capacity reinforcement includes determining 'the expanded capacity of existing medium voltage (MV) lines as well as high voltage/medium voltage (HV/MV) substations', 'the capacity of new MV lines (feeders) and HV/MV substations', and 'the site, capacity and generation schedule of DGs'. To precisely calculate the operational and interruption costs, the variation of load is regarded using the annual load duration curve. Also, the uncertainty of the load, energy price, and the power generated by renewable DGs have been considered. The possibility of islanding and also the load transferring through the reserve feeders have been regarded in the problem to improve the reliability of network. The proposed approach has been formulated as an optimization problem where a hybrid genetic algorithm and optimal power flow is employed to solve it. Finally, the proposed method is applied to the 54-bus test system in different scenarios and the results are discussed. The simulation results show the effectiveness of the presented method.

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Multiobjective distributed generation placement using fuzzy goal programming with genetic algorithm

Cited by 74 publications

References 13 publications

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

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

Efficient immune‐GA method for DNOs in sizing and placement of distributed generation units

Evaluating the effects of renewable and non-renewable DGs on DNEP from the reliability, uncertainty, and operational points of view by employing hybrid GA and OPF

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