Optimal Investment Planning for Distributed Generation in a Competitive Electricity Market

El-Khattam, Walid; Bhattacharya, Kankar; Hegazy, Yasser G.; Salama, M.M.A.

doi:10.1109/tpwrs.2004.831699

Cited by 447 publications

(211 citation statements)

References 10 publications

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“…DG can be defined as small-scale generating units located close to the loads that are being served [1]. It is possible to classify DG technologies into two broad categories: non-renewable and renewable energy re-sources [2].…”

Section: Introductionmentioning

confidence: 99%

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%

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

2014

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“…To solve this problem a pseudo fitness value is assigned to each solution as (15) The first term in (15) guides the population toward the Pareto optimal front since the solutions which are members of lower fronts get higher fitness while the second term insures the diversity among the solutions. It is calculated as follows:…”

Section: )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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“…The presently worth of the hourly DG fixed cost, considering a life-time of 30 years with a yearly payment of 0.05 M$ and 9.15% discount rate, is calculated to be 137 $/MW-day. Assuming a gas price of 0.14 $/liter, the operating cost of the DG unit is calculated to be 42 $/MWh [2].…”

Section: Constant Power Load Model: Frommentioning

confidence: 99%

“…The authors used Monte Carlo approach to model the operating histories of the installed distributed generators. Walid El-Khattam et al [2,3] proposed a method of solving distributed generation planning problem (location and size) in different utility scenarios as an optimization problem. The objective function was based on supply-demand chain which aimed to minimize the investment and operating costs of local candidate DGs, payments towards purchasing the required extra power by the DISCO, payments toward loss compensation services, as well as the investment cost of other chosen new facilities for different market scenarios.…”

Section: Introductionmentioning

confidence: 99%

Distributed Generation Planning Strategy with Load Models in Radial Distribution System

Singh¹,

Singh²,

Verma³

2009

IJCEE

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Abstract-This paper proposes a new approach for distributed generation (DG) planning from the perspective of a distribution company (disco). Optimal sizing and siting decisions for distributed generator is obtained through different approaches: Power loss minimization, System MVA minimization, System cost minimization and System Energy loss minimization. The methodology adopted permits the planner to decide optimal location and size of DG with compromise between Power loss, System MVA, System cost and System energy loss. Normally a constant power (real and reactive) load model is assumed in most of the studies. It is shown that load models can significantly affect the optimal location and sizing of DG resources in distribution systems. A comparative study of optimal location and size of distributed generator provided by installing DG resources with different type of loads models has been performed.

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Optimal Investment Planning for Distributed Generation in a Competitive Electricity Market

Cited by 447 publications

References 10 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

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

Distributed Generation Planning Strategy with Load Models in Radial Distribution System

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