Power loss minimization using fuzzy multi-objective formulation and genetic algorithm

Bagriyanik, F.G.; Aygen, Z.E.; Bağrıyanık, Mustafa

doi:10.1109/ptc.2003.1304713

Cited by 9 publications

(7 citation statements)

References 10 publications

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“…Bagriyanik et al (2003) used a fuzzy multi-objective optimization and genetic algorithm-based method to find optimum power system operating conditions. In addition to active power losses, series reactive power losses of transmission system are also considered as one of the multiple objectives.…”

Section: Motivation For the Studymentioning

confidence: 99%

Mathematical Model for the Determination of Voltage and Current on Lossy Power Transmission Lines

Oke¹

2012

IOSR-JM

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Section: Motivation For the Studymentioning

confidence: 99%

Mathematical Model for the Determination of Voltage and Current on Lossy Power Transmission Lines

Oke¹

2012

IOSR-JM

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“…In the paper [4] in order to minimise power losses the goal function as well as constraints have been formulated as fuzzy sets and the solution has been determined as taking an optimal decision with the genetic algorithm technique. In the paper [5] the description by means of fuzzy sets has been adopted to solve the problem of optimal reactive power flow and minimisation of power losses in an electrical system taking into considerations their costs.…”

Section: Introductionmentioning

confidence: 99%

Determination of optimal current in the non-ideal one-phase system with unsteady parameters

Dębowski

2014

Bulletin of the Polish Academy of Sciences Technical Sciences

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Abstract. Some of parameters in electrical systems cannot be considered as constants. In particular, some electrical loads should be described as unsteady because of physical reasons, e.g. arc and arc-resistance furnaces. One of the method to describe parameters of such loads is description by fuzzy numbers. Moreover, this description enables to determine optimal current of the system with unsteady parameters by an application of the optimisation technique called as fuzzy mathematical programming. The optimisation problem has been presented for one-phase system with sinusoidal waveforms. The obtained solution (optimal current) can be determined as crisp one (real numbers) in frequency domain in the numerical way. The determined optimal current has minimal RMS value in this case when the power constraints do not have to be fulfilled strictly because of changes of system parameters. It means simultaneously the minimisation of power losses in the system. This solution generalizes the classical optimisation solution obtained for the systems with constant parameters. In order to illustrate the problem the appropriate example has been presented.

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“…In recent years, penetration of DG into distribution systems has been increasing around the world. Major reasons for this trend are liberalization of electricity markets, need to increase the system capacity and constraints on building new transmission and distribution lines, environmental concerns, peak reduction, improving power quality and reducing power losses [4][5][6][7][8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

“…In distribution systems, DG can deliver a portion of real and/or reactive power so that the feeder current is reduced and voltage profile can be improved with reduction in losses. However, studies indicate that poor selection of location and size would lead to higher losses than the losses without DGs [12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Introduction a multi-objective function in unbalanced and unsymmetrical distribution networks for optimal placement and sizing of distributed generation units using NSGA-II

Dehghani-Arani

Maddahi

2013

18th Electric Power Distribution Conference

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Connection of distributed generation units with appropriate allocation and size in network will have different effects such as increasing of reliability in network, decreasing of losses, improving of voltage profile, decreasing of transmission and distribution energy costs and improving of power quality parameters like voltage unbalance. So far, researches about allocation of distributed generation sources would have been done in completely balanced systems. In this paper optimized allocation of these sources in unbalanced distributed system in different consumed loads and unsymmetrical in transmission lines structure has been discussed. Since the voltage unbalance is one of current problems in distribution networks, decreasing of voltage unbalance factor (VUF) in distribution network in order to increase quality of power delivery to customers is one of the aims in optimized allocation of distributed generations in this study. Introducing multi-objective function for allocation of distributed generation sources, in order to minimize voltage unbalance factor and real power loss, improving of voltage profile and increasing of economic profit, the concepts of multi objective optimizing (PARETO) in studied networks is used.With due attention to necessity of power flow studies in studied unbalanced distribution systems, this study using Cyme-Dist software and optimizing process, with connection between the mentioned software and MATLAB software is done. In continuation, allocation of distributed generation in IEEE standard 13 bus network, in three different load levels and using NSGA-II algorithm has been studied. Results show that proper placement of distributed generation sources in unbalanced distribution systems; can decrease both losses and amount of voltage unbalance. Also in this study shown that, appropriate placing of distributed generation sources, provides considerable profit to distribution companies.

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Power loss minimization using fuzzy multi-objective formulation and genetic algorithm

Cited by 9 publications

References 10 publications

Mathematical Model for the Determination of Voltage and Current on Lossy Power Transmission Lines

Mathematical Model for the Determination of Voltage and Current on Lossy Power Transmission Lines

Determination of optimal current in the non-ideal one-phase system with unsteady parameters

Introduction a multi-objective function in unbalanced and unsymmetrical distribution networks for optimal placement and sizing of distributed generation units using NSGA-II

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