Abstract
ABSTRACTAn autonomous power generation system (APGS) contains units such as diesel energy generator, solar photovoltaic units, wind turbine generator and fuel cells along with energy-storing units such as the flywheel energy storage system and battery energy storage system. The components either run at lower/higher power output or may turn on/off at different instants of their operation. Due to this, the conventional controllers will not provide desired performance under varied load conditions. This paper proposes an adaptive fuzzy logic PID (AFPID) controller for load frequency control. In order to achieve an improved performance, a modified whale optimization algorithm (mWOA) was also proposed in this paper for tuning of the AFPID parameters. The proposed algorithm was first evaluated using standard test functions and compared with other recent algorithms to authenticate the competence of algorithm. The proposed mWOA algorithm outperforms PSO, GSA, DE and FEP algorithms in five out of seven unimodal test functions and four out of six multimodal test functions. The effectiveness of the AFPID compared with the conventional PID and the proposed AFPID provides better performance. Reduction of 39.13% in error criteria (objective function) compared with WOA-PID controller. The proposed approach was also compared with some recently proposed frequency control approaches in a widely used two-area test system.
Highlights
The increasing power demand, rising costs of electricity transmission and distribution, deregulation of the energy markets, depletion of fossil fuels are making a significant entrance of renewable energy resources into the energy sector [1,2,3,4]
The objective function value is further reduced (J = 2.1809) with the proposed modified whale optimization algorithm (mWOA) optimized adaptive fuzzy logic PID (AFPID) controller, i.e. there is a reduction of 39.13% in error criteria compared with the whale optimization algorithm (WOA) optimized PID controller
Classical PID controller is commonly used for load frequency control (LFC) problem
Summary
The increasing power demand, rising costs of electricity transmission and distribution, deregulation of the energy markets, depletion of fossil fuels are making a significant entrance of renewable energy resources into the energy sector [1,2,3,4]. Few papers addressed fuzzy logic techniques for optimal tuning of the standard PID controller [13,14,15] and FOPID controller [5] for solving LFC problem. In original WOA algorithm, the present best solution is the target prey and the others attempt to modify their positions towards the best agent. This process of update may result in being stuck in local optima. The mWOA technique is used to tune AFPID (adaptive fuzzy logic PID) controller parameters; results are compared with WOA and mWOA optimized PID controller. Control signal and the output of different controlled sources of APGS system are analysed with standard PID and AFPID controllers and the superiority of the AFPID over PID is demonstrated
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