Power management of a photovoltaic/battery pumping system in agricultural experiment station

• A photovoltaic/battery pumping system has been studied.
• Neuro-fuzzy and fuzzy controllers have been developed.
• Extracting maximum PVP power acting on the reference speed.
• Regulation and optimization of the quantity of water pumped.
• Neuro-fuzzy controller deserves to be implemented in agricultural experiment station.

This paper focuses on dynamic modeling, simulation, control and energy management in an agricultural experiment station located at Sahline–Tunisia consisting of a 1.5 kW photovoltaic panel (PV) and a 25 A h Lead Acid battery storage supplying an induction motor coupled to a centrifugal pump as mechanical load. The cost-optimally design and the new suitable power management approach are the two main objectives. An iterative optimization approach namely, the Deficiency of Power Supply Probability (DPSP), the Relative Excess Power Generated (REPG), the Energy Cost (EC) as well as the Total Net Present Cost (TNPC) have been developed in order to find the optimal configuration of PV/battery. To reach the second object, three new supervisory controllers are designed, a neuro-fuzzy controller, a fuzzy controller and an algorithm controller. In order to show the effectiveness of the first one, a comparison of the three controllers is proposed. The principal objectives of the three supervisory controllers are: (i) the design of an adequate tracking system maximum power point (MPPT) to extract the maximum power which is given by the theory of conservation of energy, (ii) the insurance of the control speed needed for the vectorial control of the induction motor, (iii) the regulation of the water in the tank which is taken as a second storage system and finally (iv) the insurance of the correct operation for all the conversion string in order to optimize the quantity of water pumped.