Locating Distributed Generator in the LMP-based Electricity Market for Social Welfare Maximization

Gautam, Durga; Mithulananthan, Nadarajah

doi:10.1080/15325000601078146

Cited by 27 publications

(24 citation statements)

References 5 publications

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“…The objective of the market operator is to maximize the social welfare, subject to load flow equality and operational inequality constraints [4,17]:…”

Section: Problem Formulationmentioning

confidence: 99%

“…Therefore, it is necessary for the independent system operator (ISO) to reduce the waste and sacrifice cost to use some devices such as distributed generator or flexible AC transmission system (FACTS) devices. Gautam and Mithulananthan [4] presented distributed generators locating for social welfare maximization. Different approaches based on sensitivity methods have been proposed for optimal locating of FACTS devices in both vertically integrated and restructured power systems [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

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A Fuzzy-based Genetic Algorithm for Social Welfare Maximization by Placement and Sizing of Static Synchronous Series Compensator

Nabavi

Masoum

Kazemi

2011

Electric Power Components and Systems

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This article presents a fuzzy-based genetic algorithm to maximize total social welfare and alleviate congestion by placement and sizing of one static synchronous series compensator device, considering its investment cost in a double-sided auction market. The generating units cost curves are considered to be quadratic with sine components to show the impacts of valve point loading. By adding the valve point effect, the model presents non-differentiable and convex regions that challenge most gradientbased optimization algorithms. In addition, the impact of distribution companies on the social welfare maximization and congestion management is presented as a quadratic function. The proposed approach makes use of the fuzzy-based genetic algorithm to optimal schedule generating companies and distribution companies and setting the static synchronous series compensator location and its size while the NewtonRaphson algorithm minimizes the mismatch of the power flow equations. Simulation results on the modified IEEE 14-and 30-bus test systems (with/without line flow constraints, before/after compensation) are used to examine the impacts of the static synchronous series compensator on the total system social welfare improvement versus its cost. Several cases are considered to test and validate the consistency of detecting best solutions. Simulation results are compared to solutions obtained by the genetic algorithm and sequential quadratic programming approach, which has been used in MATPOWER (available on-line; see [1]). The aim of this article is the utilization of static synchronous series compensator for the social welfare maximization problem considering the impact of valve point loading effect on the operation point of the generating companies by inclusion of fuzzy rules in the genetic algorithm to guarantee fast convergence for locating/sizing the static synchronous series compensator. The proposed method shows the benefits of the static synchronous series compensator in a deregulated power market and demonstrates how it can be utilized by the independent system operator to improve the total social welfare and prevent congestion.

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“…The objective of the market operator is to maximize the social welfare, subject to load flow equality and operational inequality constraints [4,17]:…”

Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Fuzzy-based Genetic Algorithm for Social Welfare Maximization by Placement and Sizing of Static Synchronous Series Compensator

Nabavi

Masoum

Kazemi

2011

Electric Power Components and Systems

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show abstract

“…Several investigations on optimal placement of DGs were reported in the literature [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. The DG placement problem usually involves two major tasks.…”

Section: Introductionmentioning

confidence: 99%

“…The first task is the selection and use of an appropriate DG model. Generally, either the constant power factor model [4, 7-9, 12, 14-16] or the constant power model [5,6,10,11,[17][18][19][20] of DG was employed. Among various DG technologies, the wind turbine generator system (WTGS) is the most popular and is installed in a large scale in several parts of the world.…”

Section: Introductionmentioning

confidence: 99%

Distributed Generation Planning: A New Approach Based on Goal Programming

Vinothkumar

Selvan

2012

Electric Power Components and Systems

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This article proposes a novel methodology that employs a goal programming technique and genetic algorithm for formulation and evaluation of a multiobjective function, respectively, for optimal planning of distributed generator units in the distribution system. The multi-objective function consists of various performance indices that govern the optimal operation of a distribution system with distributed generator units. The proposed method aims to greatly diminish the dependence in existing methods on the global preference information of the distribution system planner by means of simplicity in problem formulation utilizing a goal programming technique. The capacity of the distribution system to accept distributed generator integration is evaluated such that with the placement of every additional distributed generator unit, the value of multi-objective function reduces without any violation in the system operating constraints. The effectiveness of the proposed method is tested using various distribution systems of different sizes and configurations, and the results are validated with the existing methods, namely the iterative genetic algorithm method and the fuzzy embedded genetic algorithm method. Further, different types of distributed generator models are also employed to demonstrate the adaptability of the proposed method in distributed generator planning studies.

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“…Numerous methods based on market model [1], particle swarm optimization (for generation rescheduling and/or load shedding) [2], genetic algorithm (GA) [3], and sensitivity analysis using transmission line susceptances [4] have been reported for social welfare maximization and congestion management. Distributed generators that locate social welfare maximization are presented in [5]. Maximization of social welfare is represented as a marginal benefit versus demand function in [6].…”

Section: Introductionmentioning

confidence: 99%

Maximizing the Overall Satisfaction Degree of all Participants in the Market Using Real Code-based Genetic Algorithm by Optimally Locating and Sizing the Thyristor-Controlled Series Capacitor

Nabavi¹,

Hajforoosh²,

Hajforoosh³

et al. 2011

Journal of Electrical Engineering and Technology

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-The present paper presents a genetic algorithm (GA) to maximize social welfare and perform congestion management by optimally placing and sizing one Thyristor-Controlled Series Capacitor (TCSC) device in a double-sided auction market. Simulation results, with line flow constraints before and after the compensation, are compared through the Sequential Quadratic Programming SQP method, and are used to analyze the effect of TCSC on the congestion levels of modified IEEE 14-bus and 30-bus test systems. Quadratic, smooth and nonsmooth (with sine components due to valve point loading effect) generator cost curves, and quadratic smooth consumer benefit functions are considered. The main aims of the present study are the inclusion of customer benefit in the social welfare maximization and congestion management objective function, the consideration of nonsmooth generator characteristics, and the optimal locating and sizing of the TCSC using real code-based GA to guarantee fast convergence to the best solution.

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Locating Distributed Generator in the LMP-based Electricity Market for Social Welfare Maximization

Cited by 27 publications

References 5 publications

A Fuzzy-based Genetic Algorithm for Social Welfare Maximization by Placement and Sizing of Static Synchronous Series Compensator

A Fuzzy-based Genetic Algorithm for Social Welfare Maximization by Placement and Sizing of Static Synchronous Series Compensator

Distributed Generation Planning: A New Approach Based on Goal Programming

Maximizing the Overall Satisfaction Degree of all Participants in the Market Using Real Code-based Genetic Algorithm by Optimally Locating and Sizing the Thyristor-Controlled Series Capacitor

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