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A standalone PV system is designed to supply power to a DC water pump using an artificial neural network MPPT with PI controller, achieving high performance and avoiding AC system components.

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What they did

System
MDC

What worked

Voltage64.9Vbest of 12

Abstract

This paper presents a new design of a standalone photovoltaic system which is supplying the required power to a direct current water pump that have difficulty to supply by the utility electricity. The system is controlled by an artificial neural networks (ANN) algorithm with function softening by PI controller that to guarantee the maximum power point tracking (MPPT) working conditions. A parallel connected PV array is designed to supply the required power to the water pump. The proposed design considers Permanent Magnet DC motor (PMDC) of 48 Volts, and 500 Watts as a water pump’s motor, the direct current (DC) pump is adopted to avoid the complexity of the alternating current AC pumping system which includes inverter, power filter, and insulated step up transformer, so the presented design avoids the mentioned AC system components. A feed forward ANN algorithm is adopted in this study to produce the reference voltage for the MPPT functioning of the PV system, Proportional Integral (PI) controller is inserted to soften the MPPT controller performance. System design, MATLAB simulation with results and the results’ analysis all are presented in this paper. The study conclusion confirms the effectiveness of the proposal as a successful system for practical applications.

Key findings

  • The proposed system uses a parallel connected PV array to supply power to the water pump.
  • A feed forward ANN algorithm is used to produce the reference voltage for the MPPT functioning of the PV system.
  • The PI controller is inserted to soften the MPPT controller performance.

Keywords

Maximum power point trackingPhotovoltaic systemControl theory (sociology)InverterPID controllerTransformer

Identifiers

DOI
10.11591/ijpeds.v10.i3.pp1329-1338
Journal
International Journal of Power Electronics and Drive Systems (IJPEDS)
Year
2019