Maximum power point tracking (MPPT) algorithms have become key elements in improving solar photovoltaic (PV) energy conversion systems. Numerous algorithms have been developed and implemented successfully in recent technology. This paper intended to introduce an improved incremental conductance (IC) algorithm based on the mathematical residue theorem. The major difference introduced in this paper is in considering the residual value of the IC to ensure MPPT achievement. Ensuring the minimal residue in IC improves the operation and eliminates the fluctuation around the operation points. Improved energy conversion efficiency has been achieved and the system has been proved mathematically and by simulations. One of the advantages that the system is free of parameters affect and atmospheric condition data are not required. The controller gain is based on sliding mode compensator to improve the uncertainty handling ability of the developed control approach.
This paper proposes a residue theorem based soft sliding mode control strategy for a permanent magnet synchronous generator (PMSG) based wind power generation system (WPGS), to achieve the maximum energy conversion and improved in the system dynamic performance. The main idea is to set a soft dynamic boundary for the controlled variables around a reference point. Thus the controlled variables would lie on a point inside the boundary. The convergence of the operating point is ensured by following the Forward Euler method. The proposed control has been verified via simulation and experiments, compared with conventional sliding mode control (SMC) and proportional integral (PI) control.
This paper proposes a Maximum Power Point Tracking (MPPT) controller for photovoltaic (PV) system using sliding mode control scheme (SMC) in stand-alone configuration. The aim of this controller is to achieve an optimum MPP operation without the need of atmospheric conditions measurements and to enhance the efficiency of the PV power system. The proposed controller overcomes the power oscillation around the operating point which appears in most implemented MPPT techniques. The proposed MPPT controller using SMC has been developed in such a way that the sliding surface is set to be the MPP condition, so that the operating point converges to the optimum operating point. An adaptive SMC gain has been designed and implemented in the proposed controller to allow the compensation of the uncertainty of ambient conditions. The results show a satisfactory operation of a PV power system and a better achievability of the operating point to the optimal operating point. The validation of the proposed controller is shown by MATLAB/SIMULINK simulation. Moreover, classical MPPT algorithm using incremental condition has been developed for the same PV power system in order to evaluate the proposed SMC controller. A comparison analysis of the proposed controller with incremental condition algorithm has been undertaken and results in noticeably better reachability of the proposed SM controller.Index Terms-Adaptive SMC gain, Maximum power point tracking, PV control, Sliding mode control, Solar power system.
I. INTRODUCTIONRecently, solar energy or photovoltaic energy applications are getting increased especially in stand-alone configuration. It is one of the most promising sources of renewable energy. The limitations of PV energy system such as the low efficiency and the non-linearity of the output characteristics, make it necessary to obtain a MPP operation. Variations on solar irradiance levels, ambient temperatures and dust accumulation on the surface of the PV panel affect the output of the PV system [1].The aim of MPPT technique is to automatically obtain an optimal MPP operation under variable atmospheric conditions. Several MPPT techniques have been developed for PV system. Incremental condition and perturbation and observation (P&O) algorithms were widely used in MPPT controller. The idea of those algorithms is quite similar. In P&O, the perturbation is made in the operating point till maximum power achieved.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.