A Theoretical Approach To Forecasting Of Electric Power Of Distribution Transformers
Journal Title: IOSR Journals (IOSR Journal of Electrical and Electronics Engineering) - Year 2017, Vol 12, Issue 6
Abstract
This paper is targeted at discussing the theory involved in addressing the problem of forecasting electric power at a substation transformer in a distribution network. Accurate power forecast is of great essence in power distribution planning, reactive power support control and intelligent power management. Due to the dynamics of the power system, an intelligent and adaptive forecast algorithm based on the Adaptive Neuro-fuzzy Inference System (ANFIS) is proposed for the power forecast. However the forecast model involves the use of five layer Adaptive neuro-fuzzy inference system (ANFIS) and its learning algorithm for the forecast of active and reactive power. For efficiency of the forecast model, training and validation, historical data for active and reactive power distribution network are utilized. Therefore the input voltage v(t) to the network is time varying series of vector patterns called sequence. Ultimately, this paper presents an algorithm for forecasting electric power of distribution transformers.
Authors and Affiliations
Ugwudike D. U. , Madueme T. C.
Keywords
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- EP ID EP388494
- DOI 10.9790/1676-1206032031.
- Views 144
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