Short-Term Wind Power Prediction Using Hybrid Auto Regressive Integrated Moving Average Model and Dynamic Particle Swarm Optimization
نویسندگان
چکیده
منابع مشابه
A new hybrid for improvement of auto-regressive integrated moving average models applying particle swarm optimization
A time series forecasting is an active research applied significantly in a variety of economics areas. Over the past three decades an auto-regressive integrated moving average (ARIMA) model, as one of the most important time series models, has been applied in financial markets forecasting. Recent researches in time series forecasting ARIMA models indicate some basic limitations which detract fr...
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متن کاملShort-Term Wind Power Forecasting Using the Enhanced Particle Swarm Optimization Based Hybrid Method
High penetration of wind power in the electricity system provides many challenges to power system operators, mainly due to the unpredictability and variability of wind power generation. Although wind energy may not be dispatched, an accurate forecasting method of wind speed and power generation can help power system operators reduce the risk of an unreliable electricity supply. This paper propo...
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ژورنال
عنوان ژورنال: International Journal of Cognitive Informatics and Natural Intelligence
سال: 2021
ISSN: 1557-3958,1557-3966
DOI: 10.4018/ijcini.20210401.oa9