Title :
Supervisory control of standalone wind/solar energy generation systems
Author :
Prakash, M. ; Preetha, R.
Author_Institution :
Dept. of EEE, MES Coll. of Eng., Kuttippuram, India
Abstract :
The use of renewable energy technology to meet the energy demands has been increasing for the past few years. However, the important drawbacks associated with renewable energy systems are their inability to guarantee reliability and their intermittent nature. At present, standalone solar photovoltaic energy system cannot provide reliable power during night time or non-sunny days. The standalone wind system cannot satisfy constant load demands due to fluctuations in the magnitude of wind speeds from hour to hour throughout the year. This work focuses on the development of a supervisory model predictive control method for the optimal management and operation of hybrid standalone wind-solar energy generation systems. The proposed method is to design the supervisory control system via model predictive control which computes the power references for the wind and solar subsystems. The power references are sent to two local controllers which drive the two subsystems to the requested power references. The system is modeled in MATLAB SIMULINK and simulation results show that maximum power generated from hybrid system at varying environmental conditions.
Keywords :
hybrid power systems; power generation control; power generation reliability; power system management; predictive control; solar power stations; wind power plants; MATLAB SIMULINK; energy demands; hybrid system; load demands; power references; renewable energy systems; renewable energy technology; solar subsystems; standalone solar photovoltaic energy system; standalone wind system; standalone wind-solar energy generation systems; supervisory control system; supervisory model predictive control method; wind speeds; wind subsystems; Batteries; Hybrid power systems; Predictive control; Supervisory control; Wind forecasting; Wind turbines; Model predictive control (MPC); solar energy; standalone wind and solar systems; supervisory predictive control; wind energy;
Conference_Titel :
Intelligent Systems and Control (ISCO), 2014 IEEE 8th International Conference on
Print_ISBN :
978-1-4799-3836-0
DOI :
10.1109/ISCO.2014.7103944