Photovoltaic Pumping System Research Articles

Design, and dynamic evaluation of a novel photovoltaic pumping system emulation with DS1104 hardware setup: Towards innovative in green energy systems.

Diesel engines (DEs) commonly power pumps used in agricultural and grassland irrigation. However, relying on unpredictable and costly fuel sources for DEs pose's challenges related to availability, reliability, maintenance, and lifespan. Addressing these environmental concerns, this study introduces an emulation approach for photovoltaic (PV) water pumping (WP) systems. Emulation offers a promising alternative due to financial constraints, spatial limitations, and climate dependency in full-scale systems. The proposed setup includes three key elements: a PV system emulator employing back converter control to replicate PV panel characteristics, a boost converter with an MPPT algorithm for efficient power tracking across diverse conditions, and a motor pump (MP) emulator integrating an induction motor connected to a DC generator to simulate water pump behaviors. Precise induction motor control is achieved through a controlled inverter. This work innovatively combines PV and WP emulation while optimizing system dynamics, aiming to develop a comprehensive emulator and evaluate an enhanced control algorithm. An optimized scalar control strategy regulates the water MP, demonstrated through MATLAB/Simulink simulations that highlight superior performance and responsiveness to solar irradiation variations compared to conventional MPPT techniques. Experimental validation using the dSPACE control desk DS1104 confirms the emulator's ability to faithfully reproduce genuine solar panel characteristics.

Multilayer decoupling control of photovoltaic integrated heat pump based on expected value

Abstract In this paper, a multilayer decoupling control method for photovoltaic heat pumps based on expected values is proposed, which aims to achieve the optimal operation of the photovoltaic heat pump system and photovoltaic heat pump system. This method predicts the output energy of photovoltaic photovoltaic system and realizes multilayer decoupling control based on the load demand of the heat pump system. In order to adapt to the change in environment, the adaptive fuzzy PID compound control method is adopted to optimize the control strategy. Experimental results show that this method can effectively improve the system efficiency, reduce energy consumption, and demonstrate good adaptability and stability.

Techno economic analysis of PV pumping system for rural village in East Java

Renewable energy systems offer a sustainable alternative for addressing energy needs, especially in rural settings. This study investigates the optimization of a hybrid photovoltaic (PV) pumping system by minimizing the Cost of Energy (COE), maximizing the Renewable Fraction (RF), and reducing Carbon Dioxide Emissions (ECO₂). The optimization process was carried out using Python to implement the Queen Honeybee Migration (QHBM) algorithm, which evaluated three distinct scenarios to determine the most efficient system configuration. The optimal setup comprised 48 units of 600 Wp PV panels, 17 units of 250 Ah batteries, and 3 units of 8,000 W inverters. This configuration achieved a COE of $0.041 per kWh, an RF of 43.96 %, and an ECO₂ reduction of 118.49 kgCO₂e, with a cumulative objective value of -146.76. A comparative analysis with the Particle Swarm Optimization (PSO) algorithm indicated that QHBM excels in optimizing RF and ECO₂, whereas PSO demonstrates marginally superior performance in reducing COE. The economic evaluation reveals a Net Present Value (NPV) of $40,206.11 over a 35-year period, a Return on Investment (ROI) of 398 %, a Break-Even Point (BEP) of 6.45 years, and a Payback Period (PP) of 13.25 years. The system is projected to yield daily and annual cost savings of $6.33 and $2,310.90, respectively. These results underscore the efficacy of QHBM in achieving superior techno-economic and environmental performance in hybrid PV pumping systems.

Energy, exergy, exergy‐economic, and environmental evaluation of an optimized hybrid photovoltaic heat pump system with solar collector and PCM

AbstractNowadays, the use of hybrid systems has become very common all over the world. In this study, the aim is to minimize the use of grid energy to provide heating and cooling energy with the help of a hybrid heat pump equipped with a flat solar collector, phase change material (PCM), and photovoltaic (PV) panels. To achieve the best results, a numerical dynamic model consisting of different solar PV panels in three models, batteries, inverters, and hybrid heat pump along with collector and PCM has been modeled by solving Engineering Equation Solver (EES) and TRNSYS software. According to the proposed scenarios, multi‐objective optimization has been done to simultaneously improve the study answers in several sections by multi‐objective particle swarm optimization algorithm with MATLAB software. Also, economic and environmental optimization is also presented separately for comparing and reviewing solutions. The results of multi‐objective optimization show that the amount of lifecycle cost (LCC) when using polycrystalline panel is 21.26% lower than monocrystalline panel and 38.71% higher than thin film panel. As a result, according to the specific conditions and attitude, you can choose the desired system. Also, in the economic optimization, it was found that the best system is related to the polycrystalline panel, the volume of PCM used in the system is equal to 1 , the number of panels used is 18, and the minimum amount of LCC is $3929.08.

Economy and energy flexibility optimization of the photovoltaic heat pump system with thermal energy storage

Photovoltaic systems have been widely applied in building energy systems. However, with the sharp increase in demand of electricity in buildings during heating and cooling seasons, the uncertainty of photovoltaic generation further exacerbates the peak-valley difference in electricity use. To improve the economy and energy flexibility of buildings in hot summer and cold winter zones of China, a rule-based operation strategy was proposed for the photovoltaic heat pump with thermal energy storage system to optimize the size of the thermal energy storage system and system operation, with aims of minimizing the total annual cost of the system and maximizing the self-consumption rate of the photovoltaic generation. The effects of grid export power limits, grid import power limits, feed-in tariffs, and PV generation on the system operation optimization results were also investigated. The results indicated that by integrating the thermal energy storage system into the photovoltaic heat pump system, the self-consumption rate of the photovoltaic generation was reduced by 2.39 %, the total annual cost of the system was decreased by 6.61 %, and the payback period of the thermal energy storage system was 1.31 years. The optimum size of the thermal energy storage system and the self-consumption rate of the photovoltaic generation decreased with the increasing grid export power limits and grid import power limits. In contrast, higher grid export power limits, grid import power limits, feed-in tariffs, and PV generation all resulted in a lower total annual cost. This study provided a systematic design and operation optimization method for building energy systems.

DESIGN AND SIMULATION OF PV-POWERED MOTORPUMP RECIRCULATING WATER SYSTEM IN RICE FIELD CRAB FARM USING MPPT-BASED NEUROFUZZY AND BIDIRECTIONAL CONVETER CHARGER CONTROLLERS

Community enterprises engaged in rice field crab farming face significant challenges due to the absence of an electricity grid, resulting in energy shortages that hinder the operation of a 24-hour recirculating water system, essential for maintaining optimal conditions during the crab laviculture phase. Consequently, crab larva survival rates have experienced a significant 60% decline. To address this issue, this paper introduces the design and simulation of an off-grid photovoltaic solar-powered motor-driven water pumping system (PVWPS) using maximum power point tracking (MPPT) and charger controllers, to meet the power demands. The proposed MPPT-based neuro-fuzzy controller (NFC), in conjunction with a proportional-integral-derivative (PID) controller, maximizes the utilization of PV power for the motor pump. Additionally, a bidirectional converter facilitates battery charging and discharging. The motor speed, which directly influences the required pump flow rate, is regulated by controlling the voltage across the DC-linked capacitor, using an additional proportional-integral (PI) controller. The Kp, Ki, and Kd parameters of both the PID and PI controllers are meticulously adjusted through a genetic algorithm (GA) to optimize control performance. Simulation results demonstrate the effectiveness of the implemented MPPT-NFC and charge controller. The energy utilization efficiency can be increased by up to 97% and the overall efficiency of the PVWPS is improved by up to 10.5%, effectively overcoming the power shortage challenge. Consequently, the proposed PVWPS, utilizing MPPT-NFC with PID-controller and a bidirectional converter PI-controller, enables 24-hour operation of the recirculating water system, with the anticipation of an increased crab larva survival rate.

Design of novel IoT-based solar powered PV pumping systems for agricultural applications in diverse climatic zones of India

Irrigation is a crucial component of the agriculture industry. The gross domestic output of India is about 15 % derived from its farmers. Crop failure is common among farmers, primarily because of inadequate irrigation techniques and irregular power and water supplies. To begin with, a survey of farmers from various parts of India was undertaken in this regard, and the results indicated that most of them lacked an effective irrigation system. An inventive solar-powered irrigation system devised and deployed to address this problem includes an automated Internet of Things (IoT) system. This IoT system, which functions based on the moisture content of the soil, plays a crucial role in ensuring that the crops receive the right amount of water at the right time. Furthermore, the PV pumping system addresses irrigation issues in various Indian climate conditions, including composite, warm and humid, cold, moderate, hot, and dry. The locations chosen for these climate conditions are Jaisalmer in Rajasthan, Bangalore in Karnataka, Itanagar in Arunachal Pradesh, Patna in Bihar, and Amaravati in Andhra Pradesh. Performance ratios range from 0.514 to 0.739, system and pump efficiencies from 61 % to 88.80 %, and 57.10 %–58.60 %, respectively.

Research on experiment for operation performance of water pumping and energy storage by photovoltaic pump

In this article, the behaviors of both flow and generated output of photovoltaic pump, the characteristics of both water pumping efficiency and output frequency, and the feature of charge capacity in accumulators have been tested through experiments, based on the integrated application system for water pumping, energy storage and illumination by photovoltaic pump, and in combination with composition and operation performance of photovoltaic water pumping system. According to the experimental results and under a constant delivery head, the photovoltaic pump and accumulator energy storage system with a total measured power of 1.8375 kWp in a photovoltaic array produces a daily water output of 13.1 m3 and an average water output of 1.93 m3/h; the maximum water pumping efficiency of the system is 12.7% and the average water pumping efficiency is 11.1%; meanwhile, the energy storage capacity of accumulators by charging in three time periods throughout a day is 1.01 kWh, which accounts for about 9.72% of the photovoltaic array's all-day generated energy, namely 10.3 kWh. Those conclusions have certain practical implications for the optimal configuration of photovoltaic water pumping system.

The effects of solar insolation and cloud opacity on the optimum array size for a direct-coupled solar pumping system

The widespread adoption of solar photovoltaic pumping technology requires pertinent information on the sizing and design of these systems. This research investigated how the ratio of photovoltaic array peak power to motor power consumption, solar insolation and cloud opacity affects the water yield of a direct-coupled solar PV pumping system. The specific aim was to estimate the optimum photovoltaic power to motor power consumption (OPVM) ratio for a 3 W DC pump under Jamaican weather conditions. The PVM ratio is the ratio of peak array power to nominal motor power consumption. Four experimental direct coupled solar pumping systems were set up and the water yield for each measured daily for thirty days. Each system was identical in every respect except each having a different solar array peak power. The findings show that there is a strong correlation (Pearson coefficient of −0.903) between solar insolation and the optimum photovoltaic power to motor power consumption ratio. Additionally, there was found to be a strong correlation between average cloud opacity and optimum photovoltaic power to motor power consumption ratio (Pearson coefficient of 0.899). Both correlations were shown to be statistically significant, with both yielding p-values <0.001. The findings of the correlation analysis indicate that a relatively large PVM ratio would be economical when used on a site that regularly receives relatively low insolation and heavy cloud cover. Finally, the daily optimum photovoltaic power to motor power consumption ratio ranged from approximately 2.3 to 5.0. Generally, it was observed that the OPVM ratio shifted below 2.4 on clear sunny days and above 4.0 on very cloudy days. While these conclusions may not exactly extrapolate to scales of practical application, performance metrics of larger systems are expected to bear some similarity. Being guided by these results, additional studies at these larger scales are recommended.

Improving and evaluating the performance of a real photovoltaic pumping system for agricultural irrigation purposes in a desert environment at Ghardaia, Algeria

Algeria has one of the highest solar resources in the world. The availability of this significant solar energy can make photovoltaic (PV) water pumping applications a very attractive solution for many uses, including irrigation of agricultural areas, village water supply and domestic uses. The cost of water pumped by a PV pumping system is directly linked to the efficiency and reliability of the different elements constituting the system and also to the solar irradiation available at the installation site. Consequently, it is necessary to improve the reliability and efficiency of the PV generator in order to extract the maximum possible power at all times in order to achieve the most reliable and economic operation. On a real well of 25 m height in desert and semi-arid climate at the Sebseb site, Ghardaïa, Algeria, a typical PV pumping system for irrigation purposes is studied and optimized using two conventionels methods, a P&amp;O method and a incremental method.These methods are essentially based on the assessment of water needs to irrigate 70 palm trees, the data on solar irradiation and the average temperature for the studied site (Sebseb, Ghardaia).

Implementation of fuzzy logic MPPT based on Arduino in small scale PV pumping system

The performance of photovoltaic (PV) affected directly by climatic changes, The controller maintain maximum potential energy conversation to operate the pimping system at nominal conditions, fuzzy logic intelligent controllers are successfully suitable and applicable in engineering and applied science. The aim of this paper is present an experimental approach in Implementation of fuzzy logic maximum power point tracking (MPPT) with boost converter based on Arduino Mega micro-controller to maximize energy production in different weather condition applied to small scale pumping system for water and chemical fluid analyses in isolated area. The system is supplied by 20 (W) solar photovoltaic (PV) panel. This paper present a real-time MATLAB/Simulink fuzzy logic method controlling and monitoring MPPT application using an low cost Arduino Mega micro-controller combined with (LV25, LP55) sensors controlling boost converter interconnected with solar panel and plastic pump.

Electrical charge and discharge characteristics of battery under remote control of water level with PV pumping system

This paper presents introduction and load characteristics of stand-alone PV pumping system, which was especially designed for rice planting irrigation of small form units, under remote control of water level. By application of these systems, it is expected to increase agricultural fresh water reuse, and to save labor for water management. The feature of this system is simplicity with having the control function of matching to weather condition. We confirmed remote control of water level by using batteries under cloudy.

Predictive Control for PV- Water Pumping System based of Interconnected High Gain Observer

This article presents a comprehensive evaluation of an integrated photovoltaic (PV) and water pumping system employing both Finite Set Model Predictive Control (FS-MPC) and Deat Beat Predictive Control (DB-MPC) under varying insolation levels (1000 W/m² to 700 W/m²). The system, initially tested at 1000 W/m², rapidly achieves Maximum Power Point Tracking (MPPT), stabilizing PV parameters at the MPP within 0.2 seconds. Notably, DB-MPC demonstrates superior dynamic response and faster settling times compared to conventional methods. The Interconnected High-Gain Observer accurately estimates motor speed, facilitating the attainment of the rated rotor speed in line with the desired reference speed. Transitioning from 1000 W/m² to 700 W/m² insolation, the system exhibits stability in Vpv and rapid Ipv adjustment at MPP. The InC algorithm extends PV array operation, showcasing a decrease in power output to 2204 W at 60% flow rate. These results affirm the efficacy and adaptability of the proposed control strategies in optimizing the performance of the PV-driven water pumping system, offering promising advancements in sustainable energy applications.

Enhancing Performance of Photovoltaic Pump Systems in Remote Areas Using a Sliding Mode Technique for Maximum Power Point Tracking

Enhancing Performance of Photovoltaic Pump Systems in Remote Areas Using a Sliding Mode Technique for Maximum Power Point Tracking

Recent Advances in Solar-powered Photovoltaic Pumping Systems for Drip Irrigation

Solar-powered photovoltaic pumping systems (SPVPSs) have emerged as a promising solution for sustainable drip irrigation in agriculture. This review article presents recent advances in SPVPSs for drip irrigation, with a focus on their design, performance and integration. The paper provides an overview of the key components and working principles of SPVPSs. Various system configurations and optimization strategies are discussed, emphasizing the importance of system sizing, energy management and water supply efficiency. The review also addresses challenges and future directions in the field. The initial investment costs, technical constraints, and the need for capacity building are identified as key challenges to widespread adoption. However, ongoing research and development efforts are focused on cost reduction, system optimization, and policy support to overcome these challenges. Technological innovations, such as advanced control algorithms and energy storage systems, are paving the way for improved system performance and reliability. The integration of SPVPSs with drip irrigation offers environmental and socio-economic benefits. These systems contribute to reduced greenhouse gas emissions and water conservation. Moreover, they enhance agricultural productivity, income generation, and food security, particularly in off-grid and rural areas. SPVPSs for drip irrigation hold great promise for sustainable agriculture and water resource management. Continued research, collaboration, and policy support are essential to further advance these systems, address challenges, and promote their widespread adoption. This review paper provides insights for researchers, policymakers, and practitioners interested in harnessing the potential of SPVPSs for sustainable drip irrigation.

A Single Stage Photovoltaic Solar Pumping System based on the Three Phase Multilevel Inverter

This paper presents a study of a single-stage DC-AC converter for a solar water pumping application. The topology was based on solar panels connected to a new structure of a three-phase multilevel inverter through DC-bus capacitors. The inverter offers simplicity, requires fewer components compared to conventional ones, and provides optimal voltage and current waveforms with reduced harmonics, eliminating the need for filters. The applied control technique aimed to stabilize the input DC-bus voltage, extract the maximum power using a simple MPPT algorithm, and enhance the efficiency of the water pump through scalar V/f control, regardless of weather changes. A simulation was conducted using the PSIM software, considering a variable daily climate scenario. The results obtained demonstrate the efficiency of the system in extracting energy with optimal torque and current for the pump compared to a classic design based on a three-phase H-bridge inverter.

Design and optimization of automatic solar irrigation-based PLC

&#x0D; &#x0D; &#x0D; Irrigation is the most important step in agriculture. In order to obtain a good agricultural crop, water must be used wisely and appropriately without waste. This article presents an automatic solar irrigation system developed and designed by the authors. The system consists of two parts: a photovoltaic water pumping system and a unit of control based on programmable logic controller. The programmable logic controller (PLC) uses two sensors: one is placed in the field to measure the moisture in the soil, while the second is used to control the amount of water in the storage unit. The photovoltaic pumping system was designed to be able to irrigate one-hectare area of henna Lawsonia inermis L. with daily water need of 33 m3/day and total dynamic head (TDH) of 14 m. The region opted for this study and analysis is 34°41.1’ N latitudes and 6°29.6’ E longitudes in Zribet el Oued-biskra, Algeria.&#x0D; &#x0D; &#x0D;

Sliding mode controller with fuzzy supervisor for MPPT of photovoltaic pumping system

&lt;p&gt;This paper focuses on a photovoltaic system for pumping water. The control strategy for this water pumping system is based on Takagi-Sugeno type fuzzy supervisors and sliding mode controller. The first generates the maximum power point current under varying climatic condition whereas the second allows tracking the reference signal produced by the fuzzy supervisor. The system includes a photovoltaic generator (PVG) followed by a DC-DC Converter, DC bus, an AC/DC inverter which is connected to the induction motor. This latter is coupled with a centrifuge pump. The induction motor is driven based on field-oriented control strategy. The Takagi-Sugeno type fuzzy supervisor predicts, depending on the variations of climatic variables such as irradiation and temperature, the optimum operating point for the photovoltaic source. The simulation results show the effectiveness of the proposed approach in transient and stationary regimes for different values of climatic variables.&lt;/p&gt;

A sustainable and efficient alternative for water pumping in electrically isolated rural areas of Ecuador

The main economic activities in rural areas of Ecuador are agriculture and livestock rearing, with water being the primary resource for these activities. Approximately 3% of the rural population lacks access to the conventional electrical grid, so photovoltaic pumping systems can fulfil the need to capture and distribute water without emitting greenhouse gases. This research aims to study the appropriate technologies to develop a photovoltaic pumping system for future implementation in rural areas of Ecuador, based on a centrifugal pump, induction motor, variable speed drive, and powered by a photovoltaic array. Simulink/MATLAB R2019B is used for system modelling and simulation. Additionally, two maximum power point tracking methods are studied, the perturb and observe algorithm and the artificial neural network algorithm. The simulation results show that when using the artificial neural network maximum power point tracking technique, the system performs better, being faster in transitions and presenting fewer oscillations in the steady state. The EN50530 standard is also employed to test the performance of the maximum power point tracker, and as a result, the artificial neural network-based algorithm achieves the highest efficiency of 99.5%. Finally, it is shown how the automatic regulation of speed allows adjustment of the pumping capacity in response to variations in irradiation and temperature. Even in unfavourable levels of irradiation and temperature, the water supply is not interrupted, and the pump capacity is adjusted to the maximum power supplied by the photovoltaic array.

Optimal control of a grid-connected photovoltaic agricultural water pumping system

Optimization of water pumping systems has been studied using various techniques which include classical, mathematical, and heuristics. Few studies have explored use of optimal controllers in agricultural water pumping applications. Some studies also ignore the interconnection between the water demand and energy used. Introduction of renewable energy sources such as photovoltaic (PV) necessitates different geographical studies as the intensity of the renewable energy varies widely with location. In this paper, an optimal controller for a batteryless grid-connected photovoltaic system to power water supply system for irrigation purposes was developed. The aim was to minimize the operational cost of grid energy by maximizing utilization of photovoltaic power and minimizing the utilization of grid power. A case study was done at a farm in Kajiado (−1.6033257^{circ } latitude and 36.7863352^{circ } longitude). The farm photovoltaic, grid power, water pumps (underground and booster pump), and storage tanks were modelled into a binary linear programming optimization problem and solved using intlinprog solver on MATLAB. Energy demand data was collected using a three-phase power logger, while water demand data was collected using onsite water meter and stopwatch timer. Photovoltaic power produced was estimated using Photovoltaic Geographical Information System (PVGIS). Simulation results obtained show that the use of an optimal controller results in reduced cost of energy by 44.4%. Better utilization of renewable photovoltaic energy by 24% was observed, and 3.6% more water was pumped.