A new short-term load forecasting approach using self-organizing fuzzy ARMAX models
- 1 February 1998
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Power Systems
- Vol. 13 (1), 217-225
- https://doi.org/10.1109/59.651639
Abstract
This paper proposes a new self-organizing model of fuzzy autoregressive moving average with exogenous input variables (FARMAX) for one day ahead hourly load forecasting of power systems. To achieve the purpose of self-organizing the FARMAX model, identification of the fuzzy model is formulated as a combinatorial optimization problem. Then a combined use of heuristics and evolutionary programming (EP) scheme is relied on to solve the problem of determining optimal number of input variables, best partition of fuzzy spaces and associated fuzzy membership functions. The proposed approach is verified by using diverse types of practical load and weather data for Taiwan Power (Taipower) systems. Comparisons are made of forecasting errors with the existing ARMAX model implemented by the commercial SAS package and an artificial neural networks (ANNs) method.Keywords
This publication has 14 references indexed in Scilit:
- Identification of ARMAX model for short term load forecasting: an evolutionary programming approachIEEE Transactions on Power Systems, 1996
- Implementation of hybrid short-term load forecasting system using artificial neural networks and fuzzy expert systemsIEEE Transactions on Power Systems, 1995
- An introduction to simulated evolutionary optimizationIEEE Transactions on Neural Networks, 1994
- Forecasting daily load curves using a hybrid fuzzy-neural approachIEE Proceedings - Generation, Transmission and Distribution, 1994
- A generalized knowledge-based short-term load-forecasting techniqueIEEE Transactions on Power Systems, 1993
- Electric load forecasting using an artificial neural networkIEEE Transactions on Power Systems, 1991
- Structure identification of fuzzy modelFuzzy Sets and Systems, 1988
- The Time Series Approach to Short Term Load ForecastingIEEE Transactions on Power Systems, 1987
- Fuzzy identification of systems and its applications to modeling and controlIEEE Transactions on Systems, Man, and Cybernetics, 1985
- An Application of State Estimation to Short-Term Load Forecasting, Part I: Forecasting ModelingIEEE Transactions on Power Apparatus and Systems, 1970