Solar array fed synchronous reluctance motor driven water pump : an improved performance under partial shading conditions

An improved performance of a photovoltaic (PV) pumping system employing a synchronous reluctance motor (SynRM) under partial shading conditions is proposed. The system does not include the dc-dc converter that is predominantly being utilized for maximizing the output power of the PV array. In addition, storage batteries are also not contained. A conventional inverter connected directly to the PV array is used to drive the SynRM. Further, a control strategy is proposed to drive the inverter so that the maximum output power of the PV array is achieved while the SynRM is working at the maximum torque per Ampere condition. Consequently, this results in an improved system efficiency and cost. Moreover, two maximum power point tracking (MPPT) techniques are compared under uniform and partial shadow irradiation conditions. The first MPPT algorithm is based on the conventional perturbation and observation (P&O) method and the second one uses a differential evolution (DE) optimization technique. It is found that the DE optimization method leads to a higher PV output power than using the P&O method under the partial shadow condition. Hence, the pump flow rate is much higher. However, under a uniform irradiation level, the PV system provides the available maximum power using both MPPT techniques. The experimental measurements are obtained to validate the theoretical work

Low-cost global MPPT scheme for photovoltaic systems under partially shaded conditions

Maximum Power Point Tracking (MPPT) is a technique applied to improve the efficiency of power conversion in Photovoltaic (PV) systems. Under partially shadowed conditions, the Power-Voltage (P-V) characteristic exhibits multiple peaks and the existing MPPT methods such as the Perturb and Observe (P&O) are incapable of searching for the Global Maximum Power Point (GMPP). This paper proposes a low-cost on-line MPPT scheme to overcome this drawback. By using hybrid numerical searching process, the operating point approaches Local Maximum Power Points (LMPPs) gradually and the GMPP is caught by comparing all the LMPPs. Simulation results prove the effectiveness and correctness of the proposed method. © 2013 IEEE.published_or_final_versio

A modified particle swarm optimization based maximum power point tracking for photovoltaic converter system

This thesis presents a modified Particle Swarm Optimization based Maximum Power Point Tracking for Photovoltaic Converter system. All over the world, many governments are striving to exploit the vast potential of renewable energy to meet the growing energy requirements mainly when the price of oil is high. Maximum Power Point Tracking (MPPT) is a method that ensures power generated in Photovoltaic (PV) systems is optimized under various conditions. Due to partial shading or change in irradiance and temperature conditions in PV, the power-voltage characteristics exhibit multiple local peaks; one such phenomenon is the global peak. These conditions make it very challenging for MPPT to locate the global maximum power point. Many MPPT algorithms have been proposed for this purpose. In this thesis, a modified Particle Swarm Optimisation (PSO)-based MPPT method for PV systems is proposed. Unlike the conventional PSO-based MPPT methods, the proposed method accelerates convergence of the PSO algorithm by consistently decreasing weighting factor, cognitive and social parameters thus reducing the steps of iterations and improved the tracking response time. The advantage of the proposed method is that it requires fewer search steps (converges to the desired solution in a reasonable time) compared to other MPPT methods. It requires only the idea of series cells; thus, it is system independent. The control scheme was first created in MATLAB/Simulink and compared with other MPPT methods and then validated using hardware implementation. The TMS320F28335 eZDSP board was used for implementing the developed control algorithm. The results show good performance in terms of speed of convergence and also guaranteed convergence to global MPP with faster time response compared to the other MPPT methods under typical conditions (partial shading, change in irradiance and temperature, load profile). This demonstrates the effectiveness of the proposed method

Development of Maximum Power Extraction Algorithms for PV system With Non-Uniform Solar Irradiances

This thesis addresses the problem of extraction of maximum power from PV arrays subjected to non-uniform solar irradiances e.g partial shading. In the past, a number of maximum power point tracking algorithms (MPPTs) such as Perturb & Observe, Hill climbing, Incremental Conductance, etc. have been proposed. These are extensively used for obtaining maximum power from a PV module to maximize power yield from PV systems under uniform solar irradiance. However, these techniques have not considered partial shading conditions and the stochastic nature of solar insolation. In the event of non-uniform solar insolation, a number multiple maximum power points (MPPs) appear in the power-voltage characteristic of the PV module. In the present thesis, the stochastic nature of the solar insolation is considered to obtain the global MPP of a PV module with a focus on developing global optimization techniques for MPPT that would handle the multiple MPPs. Thus, the thesis will address the above problem by developing a number of global MPPT algorithms. In this thesis, an extensive review on MPPT algorithms for both uniform and non-uniform insolation levels is presented. Subsequently, an analysis with respect to their merits, demerits and applications have been provided in order to design new MPPTs to achieve higher MPPT efficiency under non-uniform solar irradiances. Firstly, PV modules are modelled with and without bypass diodes for handling Partial shading conditions (PSCs). Then, a new Ring pattern (RP) configuration has been proposed which is compared with different existing configurations such as Series parallel (SP), Total cross tied(TCT) and Bridge linked(BL) configurations on the basis of maximum power and fill factor. As described earlier, under non-uniform irradiances the MPPT problem boil down to determining the global MPP. Thus, the MPPT problem can be cast as a global optimization problem. It may be noted that evolutionary computing approaches are extensively used for obtaining global optimum solutions. One of the most recent evolutionary optimization techniques called grey wolf optimization technique has gained enormous popularity as an efficient global optimization approach. In view of this, Grey wolf optimization is employed to design a global MPPT such that maximum power from PV modules can be extracted which will work under partial shading conditions. Its performance has been compared with two existing MPPTs namely P&O and IPSO based MPPT methods. From the obtained simulation and experimental results, it was found that the GWO based MPPT exhibits superior MPPT performance as compared to both P&O and IPSO MPPTs on the basis of dynamic response, faster convergence to GP and higher tracking efficiency. Further, in order to scale down the search space of GWO which helps to speed up for achieving convergence towards the GP, a fusion of GWO-MPPT with P&O MPPT for obtaining maximum power from a PV system with different possible patterns is developed. An experimental setup of 600W solar simulator is used in the laboratory having characteristics of generating partial shading situation. Firstly, the developed algorithms were implemented for a PV system using MATLAB/SIMULINK. Subsequently, the aforesaid experimental setup is used to implement the proposed global MPPT algorithms. From the obtained simulation and experimental results it is observed that the Hybrid-MPPT converges to the GP with least time enabling highest possible maximum power from the solar PV system. In this thesis, analytical modeling of PV modules for handling non-uniform irradiances is pursued as well as a new RP configuration of PV modules is developed to achieve maximum power and fill factor. In order to extract maximum power from PV panels subjected to non-uniform solar irradiances, two new MPPT algorithms are developed namely Grey wolf optimization based MPPT (GWO-MPPT) and GWO assisted PO (GWO-PO)

Design and experimental implementation of a hysteresis algorithm to optimize the maximum power point extracted from a photovoltaic system

In the several last years, numerous Maximum Power Point Tracking (MPPT) methods for photovoltaic (PV) systems have been proposed. An MPPT strategy is necessary to ensure the maximum power efficiency provided to the load from a PV module that is subject to external environmental perturbations such as radiance, temperature and partial shading. In this paper, a new MPPT technique is presented. Our approach has the novelty that it is a MPPT algorithm with a dynamic hysteresis model incorporated. One of the most cited Maximum Power Point Tracking methods is the Perturb and Observer algorithm since it is easily implemented. A comparison between the approach presented in this paper and the known Perturb and Observer method is evaluated. Moreover, a new PV-system platform was properly designed by employing low cost electronics, which may serve as an academical platform for further research and developments. This platform is used to show that the proposed algorithm is more efficient than the standard Perturb and Observer method.Peer ReviewedPostprint (published version

Simulation-based coyote optimization algorithm to determine gains of PI controller for enhancing the performance of solar PV water-pumping system

In this study, a simulation-based coyote optimization algorithm (COA) to identify the gains of PI to ameliorate the water-pumping system performance fed from the photovoltaic system is presented. The aim is to develop a stand-alone water-pumping system powered by solar energy, i.e., without the need of electric power from the utility grid. The voltage of the DC bus was adopted as a good candidate to guarantee the extraction of the maximum power under partial shading conditions. In such a system, two proportional-integral (PI) controllers, at least, are necessary. The adjustment of (Proportional-Integral) controllers are always carried out by classical and tiresome trials and errors techniques which becomes a hard task and time-consuming. In order to overcome this problem, an optimization problem was reformulated and modeled under functional time-domain constraints, aiming at tuning these decision variables. For achieving the desired operational characteristics of the PV water-pumping system for both rotor speed and DC-link voltage, simultaneously, the proposed COA algorithm is adopted. It is carried out through resolving a multiobjective optimization problem employing the weighted-sum technique. Inspired on theCanis latransspecies, the COA algorithm is successfully investigated to resolve such a problem by taking into account some constraints in terms of time-domain performance as well as producing the maximum power from the photovoltaic generation system. To assess the efficiency of the suggested COA method, the classical Ziegler-Nichols and trial-error tuning methods for the DC-link voltage and rotor speed dynamics, were compared. The main outcomes ensured the effectiveness and superiority of the COA algorithm. Compared to the other reported techniques, it is superior in terms of convergence rapidity and solution qualities

Power optimization in partially shaded photovoltaic systems

The Power-Voltage characteristic of a photovoltaic (PV) array exhibits non-linear behaviour when exposed to uniform solar irradiance. Maximum Power Point (MPP) tracking is challenging due to the varying climatic conditions in a solar PV system. Moreover, the tracking algorithm becomes more complicated due to the presence of multiple peaks in the power voltage characteristics under the condition of partial shading. This research is devoted to the Stochastic Beam Search (SBS) based algorithm and Stochastic Hill Climbing (SHC) for a maximum power point tracking (MPPT) at a partial shading condition in the PV system. To give a partial shading effect over the entire array of a PV system, a mast is placed in front of the modules. The modules in the array are connected in such a way that one does not need to rewire the electrical connection during the rearrangement of modules. It is validated that the power generation performance of an array under a moving shading condition is increased. Furthermore, it is observed that the SHC method outperforms the SBS method in the MMP tracking