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Defining of normalized load profile curves for domestic customer groups to estimate feeder power loss

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dc.contributor.advisor Hemapala, KTMU
dc.contributor.advisor De SIlva, PSN
dc.contributor.author Jayawardhana, HACH
dc.date.accessioned 2019-03-20T07:34:47Z
dc.date.available 2019-03-20T07:34:47Z
dc.identifier.uri http://dl.lib.mrt.ac.lk/handle/123/14073
dc.description.abstract ‘Estimation of load profiles for domestic customers’ is a multi-purpose activity and ‘Estimation of daily feeder power loss' is only a one use of customer load profiles. In a country, domestic electricity customer percentage is higher in number wise, but energy usage of one customer is lower compared to other categories. Therefore installation of load profile recording meters for each domestic customer to obtain customer load profile is impractical and not economical. In this research, set of domestic customers are grouped by clustering their daily load profiles with respect to differences of patterns. Representative normalized load profile is obtained for each group. Same customers were interviewed for collecting family member composition and electric equipment usage information. Relationships between load profile pattern and customer information were investigated. Then a methodology was developed to estimate load profile of a new customer by only using customer information and monthly total energy consumption. These load profiles were used to calculate low voltage feeder power loss. As outcome of this research, MATLAB GUI software interface was developed to input customer information and selection of best-matched representative load profile of a new customer. An algorithm is proposed to estimate time dependant LV feeder power loss by using estimated customer load profiles. en_US
dc.language.iso en en_US
dc.title Defining of normalized load profile curves for domestic customer groups to estimate feeder power loss en_US
dc.type Thesis-Abstract en_US
dc.identifier.faculty Engineering en_US
dc.identifier.degree Master of Science in Electrical Engineering en_US
dc.identifier.department Department of Electrical Engineering en_US
dc.date.accept 2018-05
dc.identifier.accno TH3550 en_US


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