TY - GEN
T1 - Electrical Energy Needs Projection of Bangka Belitung Province in 2019-2033 using Fuzzy Logic
AU - Najmi, Muhammad
AU - Dalimi, Rinaldy
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - Electrical energy is very important in human life. Electrical energy is widely used in various sectors, including the household, industrial, commercial and general sectors. To achieve compatibility between generation and demand for electrical energy, then must know the amount value of electrical energy needs for some time to come by doing forecasting. This paper discusses projection of electrical energy needs in the Bangka Belitung Province. Forecasting method used for the projection is the fuzzy logic method and is long-term in nature, namely until 2033. Forecasting characteristics are influenced by several factors including household sector customers, industrial sector customers, commercial sector customers, general sector customers, population, Gross Regional Domestic Product (GDP) and inflation. So, this fuzzy logic method uses historical or actual data accumulated in several time periods, from 2007 to 2018. The value of projection using the Fuzzy Logic method is obtained by using those factors. Based on the results of calculations and analysis, the electrical energy needs up to 2033 increased by 1060,0219 Gigawatt hours. The value of errors between the results of forecasting with fuzzy logic and actual data in 2018 was 0,169 percent.
AB - Electrical energy is very important in human life. Electrical energy is widely used in various sectors, including the household, industrial, commercial and general sectors. To achieve compatibility between generation and demand for electrical energy, then must know the amount value of electrical energy needs for some time to come by doing forecasting. This paper discusses projection of electrical energy needs in the Bangka Belitung Province. Forecasting method used for the projection is the fuzzy logic method and is long-term in nature, namely until 2033. Forecasting characteristics are influenced by several factors including household sector customers, industrial sector customers, commercial sector customers, general sector customers, population, Gross Regional Domestic Product (GDP) and inflation. So, this fuzzy logic method uses historical or actual data accumulated in several time periods, from 2007 to 2018. The value of projection using the Fuzzy Logic method is obtained by using those factors. Based on the results of calculations and analysis, the electrical energy needs up to 2033 increased by 1060,0219 Gigawatt hours. The value of errors between the results of forecasting with fuzzy logic and actual data in 2018 was 0,169 percent.
KW - electrical energy needs
KW - forecasting
KW - fuzzy logic
KW - fuzzy rules
KW - projection
UR - http://www.scopus.com/inward/record.url?scp=85086012395&partnerID=8YFLogxK
U2 - 10.1109/ICECOS47637.2019.8984588
DO - 10.1109/ICECOS47637.2019.8984588
M3 - Conference contribution
AN - SCOPUS:85086012395
T3 - ICECOS 2019 - 3rd International Conference on Electrical Engineering and Computer Science, Proceeding
SP - 176
EP - 180
BT - ICECOS 2019 - 3rd International Conference on Electrical Engineering and Computer Science, Proceeding
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd International Conference on Electrical Engineering and Computer Science, ICECOS 2019
Y2 - 2 October 2019 through 3 October 2019
ER -