Abstract
This paper reviews unconventional methodsused in short-term loadforecasting. The basic theory of these methods and their suitability to short term load forecasting is discussed. Application and the basic formulation strategy adopted for the purpose are also discussed. These methods are classified into supervised and unsupervised learning and self-organizing with optimization categories. Different models of artificial neural network, fuzzy logic, evolutionary programming, simulatedannealing, learningmachine, andexpert system have been dealt within appropriate classification of each.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
