1 AIT Asian Institute of Technology

Long term peak load forecasting using artificial neural networks : the case of Java-Madura-Bali Interconnection, Indonesia

AuthorTanoto, Yusak
Call NumberAIT Thesis no.ET-10-05
Subject(s)Electric power consumption--Forecasting

NoteA thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Energy
PublisherAsian Institute of Technology
AbstractThis thesis presents the application of artificial neural network for long-term peak load forecasting to forecast annual peak load of Java-Madura-Bali interconnection, Indonesia, for the period of 2009-2018. In this study, 11 actual historical (1995-2008) and projection regional (2009-2018) factors including economic, electricity statistics, and weather are taken into account thought to affect the load demand. The proposed network are based on multi-layered feedforward backpropagation and recurrent network structure. A selected four-layered feedforward network using Levenberg-Marquardt learning algorithm and Elman and Jordan recurrent network are first trained using the set of data over the past 11 years (1995-2005) to forecast annual peak load of 2006-2008. Subsequently, the justified network structure is trained over the past 14 years (1995-2008) to forecast annual peak load of 2009-2018. Several simulations involve changes in historical actual peak load target and variation on projected regional economic growth are carried out to observe the network adaptability. Results obtained by the networks are then compared with that achieved by the multiple regression model and projection made by utility. In this case, forecasting result exhibited by the proposed network is the closest to actual values of 2006-2009 among others taken the average error in the range of 0.16% to 0.25%. In the case of the proposed feedforward network, its forecasting differences for 2010-2018 are less than 7% compared to others. Moreover, outputs generated by the proposed feedforward network are well adjusted to the projected inputs variation over the forecasting period of 2009-2018.
Year2010
TypeThesis
SchoolSchool of Environment, Resources, and Development (SERD)
DepartmentDepartment of Energy and Climate Change (Former title: Department of Energy, Environment, and Climate Change (DEECC))
Academic Program/FoSEnergy Technology (ET)
Chairperson(s)Weerakorn Ongsakul;
Examination Committee(s)Marpaung, Charles O.P.;Singh, Jai Govin;
Scholarship Donor(s)Directorate General of Higher Education (DIKTI);The Ministry of National Education of Republic of Indonesia;
DegreeThesis (M.Eng.) - Asian Institute of Technology, 2010


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