Abstract:
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,
installing a load profile recording meter for each domestic
customer is not worthwhile and impractical. In this research, a
methodology is proposed to estimate domestic customer load
profile by using customer information to avoid the use of
advanced costly energy meter. In methodology, the domestic
customers were divided into several groups by clustering their
daily load profiles according to differences of patterns.
Representative normalized load profile is defined for each
group. Same customers were interviewed for collecting family
member information and electric equipment usage information.
Relationships between load profile and customer information
were investigated. Then a methodology was developed to
estimate load profile of another new customer. These load
profiles were used for calculation of low voltage feeder power
loss estimation. As outcome of this research, MATLAB GUI
software interface was developed to input customer information
and selection of relevant load profile of a new customer
depending on customer information. An algorithm is proposed
to estimate hourly LV feeder power loss variation by using preestimated
customer load profiles.
Citation:
H. Jayawardhana, K. Hemapala, A. Bandara and P. De Silva, "Defining of Normalized Load Profile Curves for Domestic Customer Groups to Estimate Feeder Power Loss," 2018 3rd International Conference on Information Technology Research (ICITR), 2018, pp. 1-6, doi: 10.1109/ICITR.2018.8736138.