Estimation of Power Losses on Radial Feeder Using Minimum Electrical Measurements and Differential Evolution Method

Barukčić, Marinko; Nikolovski, Srete; Hederić, Željko

doi:10.7321/jscse.v2.n4.1

Cited by 6 publications

(3 citation statements)

References 16 publications

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“…With reasonable optimization, the proposed method could lead to produce real time, efficient, commercial solar emulators and enhance the field of innovative software development in relation to photovoltaic technology. Apart from that, it may be possible to improve the proposed application by introducing methods to model the losses associated with hardware solar panel setups by adopting a modeling technique similar to that in [20].…”

Section: Discussionmentioning

confidence: 99%

A Simple Software Application for Simulating Commercially Available Solar Panels

Ulapane¹,

Abeyratne²,

Binduhewa³

et al. 2012

JSCSE

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This article addresses the formulation and validation of a simple PC based software application developed for simulating commercially available solar panels. The important feature of this application is its capability to produce speedy results in the form of solar panel output characteristics at given environmental conditions by using minimal input data. Besides, it is able to deliver critical information about the maximum power point of the panel at a given environmental condition in quick succession. The application is based on a standard equation which governs solar panels and works by means of estimating unknown parameters in the equation to fit a given solar panel. The process of parameter estimation is described in detail with the aid of equations and data of a commercial solar panel. A validation of obtained results for commercial solar panels is also presented by comparing the panel manufacturers' results with the results generated by the application. In addition, implications of the obtained results are discussed along with possible improvements to the developed software application

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Section: Discussionmentioning

confidence: 99%

A Simple Software Application for Simulating Commercially Available Solar Panels

Ulapane¹,

Abeyratne²,

Binduhewa³

et al. 2012

JSCSE

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show abstract

“…As the size of the network grows, the computation time, data and storage requirement increases exponentially. Artificial intelligence techniques, such as fuzzy logic [28] and clustering algorithm [29] are also applied to solve the problem, which requires large datasets to be trained to estimate TL. When the complete set of networks and energy metering data are not available, the prevailing method to estimate TL in the distribution network is to use the "load loss factor" method [30].…”

Section: Existing Methodologies To Determine Distribution Feeder Techmentioning

confidence: 99%

A new methodology for technical losses estimation of radial distribution feeder

Ibrahim

Gan

2019

IJEECS

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<span lang="EN-US">Power distribution feeders is one of the key contributors of technical losses (TL) as it is typically large in numbers and scattered over large geographic areas. Traditional approach using classical formulation or time series load flow simulations to determine TL in each and every feeder and feeder sections in all distribution network require is an expensive exercise as it requires extensive modelling of the feeders and voluminous data. This paper presents a simple analytical approach to estimate monthly TL of a radial distribution feeder using analytical approach. TL for each feeder sections are evaluated on a monthly basis based on estimation of the load profile of the load points, peak power loss characteristics and loss factor. Total feeder TL are then estimated as the sum of all TL contributed by each feeder section. The developed models and procedure have been demonstrated through case studies performed on three (3) typical and representative feeders characterized by the different area served, number of feeder sections, load distribution and feeder length. The results shows close agreement (less than 5% differences) when compared with time series load flow simulations. With this model, the approach could be extended and applied to estimate TL of any radial distribution feeders of different configurations and characteristics</span>

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“…Numerical simulations of load flow over time intervals are commonly utilized to analyze EL precisely in distribution feeders [11], [14], [21]- [23]. Fuzzy logic [24], clustering algorithm [25], and machine learning [26] are examples of artificial intelligence techniques. However, these methods require a thorough understanding and detailed modeling of a load profile (LP) of the distribution system, making EL estimation complicated and impractical when dealing with extensive distribution networks.…”

Section: Introductionmentioning

confidence: 99%

An efficient method for estimating energy losses in distribution's feeder

et al. 2023

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This paper explains a simple and efficient methodology for calculating monthly energy losses (EL) using the load loss factor technique and a representative composite load profile. One of the important benefits of the proposed work is a simpler, more efficient and less rigorous method to estimate the system-wide energy loss of an extensive distribution network with reasonable accuracy. The sum of all EL provided by each feeder section is used to calculate the total feeder EL. A base case feeder with a typical cable type and power factor is used to generate regression equations, a peak power loss function to estimate the EL. A case study is then used to show the models and techniques that have been established. The result indicates a high level of agreement with the time-series load flow simulations (smaller than 10% deviations). With this model, an approach to estimate the EL of all radial feeders of various configurations and characteristics could be extended and implemented. The spreadsheet approach is ideal for completing a quick energy audit of existing distribution feeder EL and determining the sensitivity of distribution network efficiency to changes in feeder sections and load characteristics.

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Estimation of Power Losses on Radial Feeder Using Minimum Electrical Measurements and Differential Evolution Method

Cited by 6 publications

References 16 publications

A Simple Software Application for Simulating Commercially Available Solar Panels

A Simple Software Application for Simulating Commercially Available Solar Panels

A new methodology for technical losses estimation of radial distribution feeder

An efficient method for estimating energy losses in distribution's feeder

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