TY - JOUR
T1 - Deep learning technique for forecasting solar radiation and wind speed for dynamic microgrid analysis
AU - Islam, Md Mainul
AU - Shareef, Hussain
AU - Al Hassan, Eslam Salah Fayez
PY - 2023
Y1 - 2023
N2 - The key variables in the development and operation of wind and solar power systems are wind speed and solar radiation. The prediction of solar and wind energy parameters is important to alleviate the effects of power generation fluctuations. Consequently, it is essential to predict renewable energy sources like solar radiation and wind speed precisely. An artificial intelligence-based random forest method is recommended in this paper to estimate wind speed and solar radiation. The number of decision trees in the random forest model is suggested to be optimised using a novel coot algorithm (CA), and the effectiveness of the CA is evaluated to that of the currently used particle swarm optimisation (PSO) method. The best forecasting data are used in this work to develop a dynamic Microgrid (MG) in MATLAB/SIMULINK. A novel binary CA is proposed to control the MG to minimize the cost. The effect of the energy storage system is also investigated during the simulation of the MG.
AB - The key variables in the development and operation of wind and solar power systems are wind speed and solar radiation. The prediction of solar and wind energy parameters is important to alleviate the effects of power generation fluctuations. Consequently, it is essential to predict renewable energy sources like solar radiation and wind speed precisely. An artificial intelligence-based random forest method is recommended in this paper to estimate wind speed and solar radiation. The number of decision trees in the random forest model is suggested to be optimised using a novel coot algorithm (CA), and the effectiveness of the CA is evaluated to that of the currently used particle swarm optimisation (PSO) method. The best forecasting data are used in this work to develop a dynamic Microgrid (MG) in MATLAB/SIMULINK. A novel binary CA is proposed to control the MG to minimize the cost. The effect of the energy storage system is also investigated during the simulation of the MG.
UR - https://hdl.handle.net/1959.7/uws:72614
U2 - 10.15199/48.2023.04.27
DO - 10.15199/48.2023.04.27
M3 - Article
SN - 0033-2097
VL - 99
SP - 162
EP - 170
JO - Przeglad Elektrotechniczny
JF - Przeglad Elektrotechniczny
IS - 4
ER -