# The Synergy of Renewable Energy and Desalination:
## 5 Energy Efficient Operation of Centrifugal Pumping System in Desalination
The suggested hybrid method is used to operate the DTC-based control system using a programmable logic controller. In [78], the perturb and observe (P&O) control method and the incremental conductance (INC) maximum power point tracking (MPPT) control method with an automatically adjustable variable step size are compared. As an example, a PV-powered centrifugal pumping system with an induction motor in a stand-alone application without energy storage is assessed. Studying these two methods makes it easier to determine which one may provide a system with less oscillation and higher efficiency. This MPPT operates on the boost converter's working duty cycle. The converter then transforms DC electricity into AC power with the help of a voltage source inverter (VSI). The authors also employed indirect field-oriented control (IFOC), which operated the centrifugal pump by sequentially driving the three phases of an induction motor. The application of high-efficiency electrical motors can help to achieve better performance and energy efficiency, as shown in [79]. The author's primary focus was on the productivity of pumping plants driven by two different  
Figure 10: The direct torque control of CPP, where \(p^{\star}\)and \(p\) are reference and feedback pressures respectfully, \(n^{\star}\) and \(U^{\star}\) and reference rotational speed and voltage respectively, \(I\) and \(U\) are feedback current and voltage respectively. Figure 9: Major optimization techniques for CPPs. types of electrical machines called synchronous reluctance motors and induction motors. A centrifugal pumping plant efficiency prediction simulation approach for flow regulation was suggested. The Simulink/Matlab simulation method that has been proposed is quite useful for confirming efficiency when it comes to pumping plants that are equipped with different kinds of electrical machinery. Another hybrid control approach was proposed in [80,81]. A model based on Simulink/DriveSize was suggested for the hybrid throttle and speed operation of a CPP with a variable speed drive. Input power estimation for speed control and mutual throttling was made possible by the model. With the aid of a hybrid speed and throttle control technique, the proposed model enabled the selection of the most optimal valve position and pumping system rotational speed. The model was divided into two primary sections: one for simulating speed control and the other for simulating throttle position. As mentioned before, centrifugal pumps play a vital role in desalination processes, including not only reverse osmosis but also multi-stage flash distillation, where they are responsible for transporting seawater and brine. Accurate performance prediction of these pumps is essential for optimizing system efficiency, reducing operational costs, and ensuring reliability. Various methods exist for predicting pump performance, including empirical models, computational fluid dynamics (CFD), and machine learning approaches. However, the effectiveness and applicability of these methods can vary significantly based on factors such as pump design, operating conditions, and fluid properties. A comparison of different performance prediction methods is shown in Table 3.  
The application of artificial neural networks (ANNs) has started to play an important role in recent periods for the performance prediction of CPPs. ANNs are a subset of machine learning methods that employ the principles of neural organization. They are primarily composed of units or nodes connected by edges that specify the connections between each node. Generally, mathematical functions are used to calculate the various outputs, and all edges and nodes have weights that are modified as learning progresses (Figure 11). In general, the network input, \(\mathrm{x_{i}}\), is sent unchanged to the hidden layer by the input layer neurons so that \(\mathrm{I_{i}}=\mathrm{x_{i}}\)[82].