A Method for Placement of DG Units in Distribution Networks

Hedayati, H.; Nabavi-Niaki, S.A.; Akbarimajd, Adel

doi:10.1109/tpwrd.2007.916106

Cited by 348 publications

(183 citation statements)

References 20 publications

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“…The latter includes biomass, wind, solar photovoltaic (PV) and ocean-based power plants. From the utilities' perspective, DG units can bring multiple technical benefits to distribution systems such as loss reduction, voltage profile improvement, voltage stability enhancement, network upgrade deferral and reliability while supplying energy sales as a primary purpose [3][4][5][6][7][8][9][10][11][12][13]. In addition, DG units can participate into the competitive market to provide ancillary services such as spinning reserve, voltage regulation, reactive power support and frequency control [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, in recent years, due to shar-ply increased loads and the demand for higher system security, DG allocation for voltage stability at the distribution system level has attracted the interest of some recent research efforts. For instance, DG units are located and sized using different methods: iterative techniques based on Continuous Power Flow (CPF) [8] and a hybrid of model analysis and CPF [28], power stability index-based method [29], numerical approach [30,31], simulated annealing algorithm [32] and PSO [33][34][35]. However, the cost-benefit analyses of DG planning have been ignored in the works presented above.…”

Section: Introductionmentioning

confidence: 99%

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An optimal investment planning framework for multiple distributed generation units in industrial distribution systems

2014

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highlights DG allocation for minimizing energy loss and enhancing voltage stability. Expressions to find the optimal power factor of DG with commercial standard size. A methodology for DG planning to recover investment for DG owners.Impact of technical and environmental benefits on DG investment decisions. Benefit-cost analysis to specify the optimal location, size and number of DG units. Keywords:Distributed generation; Emission reduction; Loss reduction; Network upgrade deferral; Optimal power factor; Voltage stability abstract This paper presents new analytical expressions to efficiently capture the optimal power factor of each Distributed Generation (DG) unit for reducing energy losses and enhancing voltage stability over a given planning horizon. These expressions are based on the derivation of a multi-objective index (IMO), which is formulated as a combination of active and reactive power loss indices. The decision for the optimal location, size and number of DG units is then obtained through a benefit-cost analysis. Here, the total benefit includes energy sales and additional benefits, namely energy loss reduction, network upgrade deferral and emission reduction. The total cost is a sum of capital, operation and maintenance costs. The methodology was applied to a 69-bus industrial distribution system. The results showed that the additional benefits are imperative. Inclusion of these in the analysis would yield faster DG investment recovery.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An optimal investment planning framework for multiple distributed generation units in industrial distribution systems

2014

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“…To do this, different technical, economical and environmental issues have been taken into account such as voltage stability improvement [2], investment deferral in network capacity [3], active loss reduction [4], reliability improvement, network security [5], emission reduction [6], system restoration [7] and load modeling [8]. The reported models for DG planning can be categorized based on four main attributes as follows:…”

Section: Literature Reviewmentioning

confidence: 99%

Hybrid immune-genetic algorithm method for benefit maximisation of distribution network operators and distributed generation owners in a deregulated environment

Soroudi

Ehsan

Caire

et al. 2011

IET Gener. Transm. Distrib.

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In deregulated power systems Distribution Network Operators (DNO) are responsible for maintaining the proper operation and efficiency of distribution networks. This is achieved traditionally through specific investments in network components and by using some optimization methods for reducing the active losses. The event of Distributed Generation (DG) has introduced new challenges to these distribution networks both at the planning and operation stages. The role of Distributed Generation (DG) units must be correctly assessed to optimize the overall operating and investment cost for the whole system. However the Distributed Generation Owners (DGOs) have different objective functions which might be contrary to the objectives of DNO. This paper presents a long-term dynamic multi-objective model for planning of distribution networks regarding the benefits of DNO and DGOs. The proposed model simultaneously optimizes two objectives, namely the benefits of DNO and DGO and determines the optimal schemes of sizing, placement and specially the dynamics (i.e., timing) of investments on distributed generation units and network reinforcements over the planning period. The proposed model also considers the uncertainty of electric load, electricity price and wind turbine power generation using the point estimate method. The effect of benefit sharing is investigated for steering * Corresponding author

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“…A new methodology based on nodal pricing is proposed in [9] for optimally allocating DG units in order to reduce losses and voltage profile improvement. In [10], a method for placement of distributed generation (DG) units in distribution networks has been presented based on the analysis of power flow continuation and determination of most sensitive buses to voltage collapse. The objective function is to improve the voltage profile and reduction of power losses.…”

mentioning

confidence: 99%

“…Applying these methods change the multi objective function into a benefit to cost ratio index [14] or an additive utility function [7][8][9][10][11][12][13], [15][16][17] (using a predefined set of weight factors) and then it is tried to maximize (minimize) the constructed single objective problem. The weighted sum approaches cannot guarantee to find all Pareto optimal solutions in the case of non-convex objective spaces [18,19].…”

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confidence: 99%

Application of a Modified NSGA Method for Multi-Objective Static Distributed Generation Planning

Soroudi

Ehsan

2011

Arab J Sci Eng

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A Method for Placement of DG Units in Distribution Networks

Cited by 348 publications

References 20 publications

An optimal investment planning framework for multiple distributed generation units in industrial distribution systems

An optimal investment planning framework for multiple distributed generation units in industrial distribution systems

Hybrid immune-genetic algorithm method for benefit maximisation of distribution network operators and distributed generation owners in a deregulated environment

Application of a Modified NSGA Method for Multi-Objective Static Distributed Generation Planning

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