An Adaptive Hybrid Soft Computing Approach for Wind Energy Prediction
نویسندگان
چکیده
The prediction of wind farm output power is considered as an emphatic way to increase the wind energy capacity and improve the safety and economy of the power system. The wind farm output energy depends upon various factors such as wind speed, temperature, etc. , which is difficult to be described by some mathematical expression. This paper introduces a method of wind energy prediction for a wind farm of Vietnam based on historical data of wind speed and
منابع مشابه
A COMPARATIVE STUDY OF TRADITIONAL AND INTELLIGENCE SOFT COMPUTING METHODS FOR PREDICTING COMPRESSIVE STRENGTH OF SELF – COMPACTING CONCRETES
This study investigates the prediction model of compressive strength of self–compacting concrete (SCC) by utilizing soft computing techniques. The techniques consist of adaptive neuro–based fuzzy inference system (ANFIS), artificial neural network (ANN) and the hybrid of particle swarm optimization with passive congregation (PSOPC) and ANFIS called PSOPC–ANFIS. Their perf...
متن کاملAdaptive Online Traffic Flow Prediction Using Aggregated Neuro Fuzzy Approach
Short term prediction of traffic flow is one of the most essential elements of all proactive traffic control systems. Although various methodologies have been applied to forecast traffic parameters, several researchers have showed that compared with the individual methods, hybrid methods provide more accurate results . These results made the hybrid tools and approaches a more common method for ...
متن کاملAn Intelligent Hybrid Neural Network Model in Renewable Energy Systems
This paper presents a hybrid neural network approach to predict wind speed automatically in renewable energy systems. Wind energy is one of the renewable energy systems with lowest cost of production of electricity with largest resources available. By the reason of the fluctuation and volatility in wind, the wind speed prediction provides the challenges in the stability of renewable energy syst...
متن کاملPrediction of Driver’s Accelerating Behavior in the Stop and Go Maneuvers Using Genetic Algorithm-Artificial Neural Network Hybrid Intelligence
Research on vehicle longitudinal control with a stop and go system is presently one of the most important topics in the field of intelligent transportation systems. The purpose of stop and go systems is to assist drivers for repeatedly accelerate and stop their vehicles in traffic jams. This system can improve the driving comfort, safety and reduce the danger of collisions and fuel consumption....
متن کاملLong Term Wind Speed Prediction Using Wavelet Coefficients and Soft Computing
In the past researches, scholars have carried out short-term prediction for wind speed. The present work deals with long-term wind speed prediction, required for hybrid power generation design and contract planning. As the total database is quite large for long-term prediction, feature extraction of data by application of Lifting wavelet coefficients are exploited, along with soft computing tec...
متن کامل