Simulation Of Photovoltaic System Research Articles

Optimization and simulation of a grid-connected PV system using load forecasting methods: A case study of a university building

Distributed generation represents a paradigm shift from the traditional electric grid to localized generation of electric power along with the capability of incorporating renewable energy (RE) sources into the energy mix. Responding to the need for sufficient analysis, simulation, and study of feasibility of distributed generation, this study aims to design a hybrid energy system for a university building and analyze its economic benefits. The viability of existing load forecasting methodologies for energy systems is also presented in this paper. The energy system design was determined through predictive modeling of the load profile of the building using historical data and optimization using machine learning methods, namely auto-regressive integrated moving average (ARIMA) and long short-term memory (LSTM). Simulations were run in HOMER Pro. Results show that a grid-connected solar photovoltaic (PV) system installed on the roof coupled with an energy storage system (ESS) will provide the most economic benefits because it yields a reduced cost of energy (COE) per kilowatt-hour (kWh) for the building. This study shows that in line with efforts to transition towards clean energy, hybrid energy systems using RE not only have economic benefits, but can also ensure energy security and environmental sustainability.

Optimization of fractional order PI controller to regulate grid voltage connected photovoltaic system based on slap swarm algorithm

Problems with voltage and stability have arisen as a result of the dramatic development in renewable energy generating units, notably solar energy systems linked to low and medium voltage networks, and the influence of active loads that vary rapidly from time to time during the day. Because reactive power is directly proportional to voltage, its use to renewable energy producing units can only improve their efficiency. Better performance for these controllers is possible via the usage of several controller types. In this paper, we use a salp swarm optimization algorithm (SSA) to design fractional order proportional-integral (FO-PI) controllers, whose job it is to regulate the active and reactive power of solar inverters by compensating for the overvoltage and undervoltage presented by the inverters' ability to absorb and produce reactive power. After that, we compared the FO-PI controller's results to those of the standard PI controller. Grid-connected photovoltaic (PV) system modeling and simulation were performed using the MATLAB/ Simulink modeling and simulation tools. After that, the full PV system was simulated in the most likely situations across a range of grid and weather conditions. We may infer from the simulation results that this model is credible, reliable, and applicable to the analysis of grid-connected PV systems.

Agricultural Grid Connected Photovoltaic System Design and Simulation in Egypt by using PVSYST Software

Agricultural Photovoltaic Systems are a key technology to achieve sustainable development goals by reducing competition between land for food and electricity. In addition, Agricultural Photovoltaic Systems are at the heart of the link between power generation, crop production and irrigation water conservation. The main ecophysiological constraint on crop production under photovoltaics is the reduction of light. It is difficult to recommend shade tolerance for some plant varieties due to insufficient information on shading conditions for most plants. The use of shading panels (photovoltaic panels) requires more crop-specific research to determine the optimal percentage of panels and their placement that will not reduce agricultural yields. Crop yield variation versus field shading and availability to maximize the system require extensive research. This study aims to develop a standard procedure for designing an agricultural grid-connected photovoltaic power generation system for solar power generation in an agricultural area in Bahteem, Egypt. The technical and annual performance of the grid-connected PV system was simulated using PV Syst software. The paper started with a pre-feasibility study of a grid-connected photovoltaic system using PV Syst. Software with an extensive database of meteorological data, including global daily horizontal solar irradiance, and a database of various renewable energy system components from different manufacturers. In this work, a comprehensive literature review of agricultural solar photovoltaic systems is conducted, with a particular focus on grid-connected systems, followed by a design procedure for grid-connected solar photovoltaic systems. The planned photovoltaic system will generate a total of 400 KWp of electricity. This generated electricity can drive down electricity prices by exporting excess electricity to the national grid. In addition, solar power systems are fuel-efficient and have a low environmental impact.

Switch-Averaged Frequency Domain Simulation of Photovoltaic Systems

This paper pushes forward frequency domain (FD) modeling of switched networks aimed at transient simulation, with particular interest in photovoltaic (PV) systems. The PV system simulation is performed via the numerical Laplace transform (NLT) in a sequential (partitioned-time) fashion by using a set of time-windows. The proposed technique enhances existing FD PV models by a) averaging switching functions and b) using sample overlapping to alleviate numerical oscillations due to rise-time phenomenon at time-window interfaces. The proposed enhancements provide a more efficient dynamic simulation compared to both classical single-window full-sample NLT implementation and non-averaged FD PV models. Verification is performed via prevalent electromagnetic transient (EMT) software tools.

Hybrid multi-group stochastic cooperative particle swarm optimization algorithm and its application to the photovoltaic parameter identification problem

The accurate estimation of model parameters is significant for the simulation, evaluation, control, and optimization of photovoltaic systems. Recently, meta-heuristic algorithms(MHAs) have been proposed to solve the photovoltaic parameter identification problem. However, extracting the accurate and reliable parameters of PV models is still a great challenge, and many HMAs may present unsatisfactory performance due to their premature or slow convergence. Therefore, how to develop algorithms efficiently balancing the exploration and exploitation to improve the accuracy and reliability of the algorithm is extremely important. This paper proposes a Hybrid multi-group stochastic cooperative optimization algorithm (HMSCPSO). In the proposed algorithm, we designed a multi-group cooperation search mechanism to enhance the global search capability: Each group utilized different strategies. The first group used classic velocity and position updates, the second group employed the chaos strategy, and the third group utilized the lévy flight strategy. Through cooperation search between groups to increase the diversity of the population and reduce the possibility of falling into local optimum, but also concentrate some individuals to explore the current global optimum to improve the accuracy of the solution. HMSCPSO and its variants were tested on 27 benchmark functions to verify the proposed algorithm’s effectiveness. Then, the HMSCPSO is applied to solve four PV parameter identification problems of different photovoltaic models. Statistical experiment results demonstrate that the proposed algorithm has excellent advantages compared with other meta-heuristic algorithms in terms of accuracy, reliability, and convergence speed. Therefore, HMSCPSO is expected to be an effective parameter identification method for solar cells and photovoltaic modules.

Heuristic Approach for Net-Zero Energy Residential Buildings in Arid Region Using Dual Renewable Energy Sources

Optimizing a net-zero energy (NZE) residential building using what renewable energy resources are available in desert environments and budgeted within the limits of a governmental construction project is proving to be increasingly challenging for many countries, including the Kingdom of Saudi Arabia (KSA). Buildings in such regions encounter significantly high annual energy consumption rates, especially in the cooling capacity across a project’s life cycle, which in turn impacts the investment value. Therefore, this study presents a heuristic approach that aimed to examine the feasibility of NZE residential buildings in the KSA using an arid campus case study within the period of 2021–2022 based on the dual renewable energy sources of a geothermal heat pump (GHP), which served as a cooling system, and photovoltaic thermal collectors (PVT) serving as a power generation system. This study adopted a numerical technical assessment in the case study, using HAP software to analyze heating/cooling systems, and PVsyst V7.1.0 software for the variable simulation of solar photovoltaic power systems. This heuristic approach, through two assessment stages, achieved significant outcomes for a sustainable bottom-line, and provide a practical approach for achieving an NZE residential building in the King Faisal University (KFU) case study, as well as a reduction in energy consumption as well as the maintenance cost, which has a positive consequence on the payback period. Our study’s results have implications for both sustainable and green buildings with similar characteristics to those we investigated, and our results could be used to develop installation guidelines for renewable energy systems. Furthermore, our results can provide decision makers with a basis for retrofitting existing buildings to enhance their energy efficiency, increase investment value, as well as prevent the indiscriminate installation of renewable energy sources to merely increase the renewable energy installation rate.

Automated Solar PV Simulation System Supported by DC–DC Power Converters

Solar photovoltaic simulators are valuable tools for the design and evaluation of several components of photovoltaic systems. They can also be used for several purposes, such as educational objectives regarding operation principles, control strategies, efficiency, maintenance, and other aspects. This paper presents an automated solar photovoltaic simulation system with the capability to generate automated tests considering different parameters of solar photovoltaic panels and different operation conditions. The proposed simulator is composed of three buck-boost DC–DC power converters controlled in such a way that will behave similarly to solar photovoltaic panels. It allows to introduce additional variable loads and maximum power point tracker algorithms similar to real systems. Some converters are controlled by a DSP microcontroller connected to a single programmable logic controller which generates the automated tests. Thus, using the presented solution, it is possible to implement the I-V and P-V characteristic curves of solar photovoltaic panels and evaluate different maximum power point tracker algorithms considering different meteorological conditions and load variations, being a useful tool to teach subjects related to renewable energy sources and related applications. Several simulation results using Matlab/Simulink and experimental results are presented to validate the operation of the proposed solution. Experimental results achieve a ripple between 2% and 5% of the desired average current in MPP conditions.

Design and simulation of a novel solar photovoltaic system assisted single‐slope solar still distillation unit

AbstractWater is an essential component of our lives. Conventional seawater desalination, based on fossil fuel energy, is primary in meeting freshwater demands. Thus, solar desalination still emerged as an alternative technology that employs environmentally friendly renewable energy. Here, we aim to design and simulate a novel hybrid solar photovoltaic (PV) system coupled with a single‐slope solar still unit for freshwater production. Various design techniques were utilized to fine‐tune the model towards producing 3–4.6 kg/m2 · day of distillate water, thereby calculating the design aspects such as tank size, energy, and cost. The results revealed that a conventional solar desalination system had 22% lower efficiency than the proposed novel still distillation unit assisted with a solar PV system (connected to a heating element). The maximum efficiency of 45% has been recorded at the peak solar insolation due to the combination of the solar PV system. According to our design constraints, only a 3 m2 basin area was required to achieve a productivity of = 1–5 kg/day. Design analysis showed that the total capital cost of a conventional still can be significantly reduced from 2600 to 1500 $/unit with PV system integration at the specified productivity and optimal solar radiation of ~17 MJ/m2 · day at peak time (02.00 PM). This work paves the way towards maximizing solar energy utilization from PV integration with solar desalination to achieve high freshwater productivity in single‐basin solar still systems.

Simulacija proizvodnje električne energije iz fotonaponskih panela korišćenjem solarnih sistema za praćenje

Roofs and walls of buildings represent an important location for the installation of photovoltaic systems in urban areas. High-rise buildings, with a specific spatial shape, provide the possibility of installing these systems both on the roof and on the exterior walls. Possible way to increase the efficiency of solar systems is to use solar tracking systems which maximize electricity production. In this paper, a simulation of photovoltaic systems installed on the roof and walls of a high-rise building in the city of Kragujevac, Serbia was performed, using fixed installation and installations with single and dual axis systems for solar tracking. The simulation was performed in the EnergyPlus software. The results show that usage of solar tracking systems increases electricity production, especially dual axis system for solar systems with an unfavourable orientation.

Agricultural Grid Connected Photovoltaic System Design and Simulation in Egypt by using PVSYST Software

Agricultural Photovoltaic Systems are a key technology to achieve sustainable development goals by reducing competition between land for food and electricity. In addition, Agricultural Photovoltaic Systems are at the heart of the link between power generation, crop production and irrigation water conservation. The main ecophysiological constraint on crop production under photovoltaics is the reduction of light. It is difficult to recommend shade tolerance for some plant varieties due to insufficient information on shading conditions for most plants. The use of shading panels (photovoltaic panels) requires more crop-specific research to determine the optimal percentage of panels and their placement that will not reduce agricultural yields. Crop yield variation versus field shading and availability to maximize the system require extensive research. This study aims to develop a standard procedure for designing an agricultural grid-connected photovoltaic power generation system for solar power generation in an agricultural area in Bahteem, Egypt. The technical and annual performance of the grid-connected PV system was simulated using PV Syst software. The paper started with a pre-feasibility study of a grid-connected photovoltaic system using PV Syst. Software with an extensive database of meteorological data, including global daily horizontal solar irradiance, and a database of various renewable energy system components from different manufacturers. In this work, a comprehensive literature review of agricultural solar photovoltaic systems is conducted, with a particular focus on grid-connected systems, followed by a design procedure for grid-connected solar photovoltaic systems. The planned photovoltaic system will generate a total of 400 KWp of electricity. This generated electricity can drive down electricity prices by exporting excess electricity to the national grid. In addition, solar power systems are fuel-efficient and have a low environmental impact.

Design and Implementation of Three-Phase Smart Inverter of the Photovoltaic Power Generation Systems

The main purpose of this paper is to conduct design and implementation on three-phase smart inverters of the grid-connected photovoltaic system, which contains maximum power point tracking (MPPT) and smart inverter with real power and reactive power regulation for the photovoltaic module arrays (PVMA). Firstly, the piecewise linear electrical circuit simulation (PLECS) power electronic real-time control system was applied to construct the simulation and actual test environment for the three-phase mains parallel photovoltaic system, where the KC200GT photovoltaic module was used to form a 1600 W system for conducting the simulation. For enabling the PVMA to output the maximum power in terms of both insolation and ambient temperature, where the perturbation and observation (P&O) method was used for MPPT. Then, the voltage-power control technology was added to the grid-connected photovoltaic inverter. When the grid voltage p.u. value is between 1.0 and 1.03, the smart inverter starts voltage-power regulation, reducing the real power output to 1440 W, and absorbing the system’s reactive power to 774 VAr. The power factor of the grid system end is controlled to 0.9 (lagging), and the grid voltage is reduced to norminal value 220 V. If the grid voltage p.u. value is between 0.97 and 1.0, the smart inverter starts voltage-power regulation, controlling the output real power to 1440 W and the reactive power to the system to 774 VAr, so that the power factor of the system end is controlled to 0.9 (leading), and the grid voltage is increased to norminal value 220 V. Finally, the results from the simulation and actual test were used to demostrate the effectiveness of the regulation performance of the smart inverter.

Optimized selection of component models for photovoltaic and energy storage system simulations

Photovoltaic (PV) systems have become an integral and widespread part of renewable energy generation. In combination with energy storage, they offer a variety of advantages such as increased self-sufficiency or improved grid stability. However, geographic location, subsidies, energy tariffs, size of PV panels and battery, and other factors significantly influence the overall performance and profitability of the system. Solving this complex task of system design and component dimensioning is not easy. The diversity and multitude of parameters therefore usually requires the help of, more or less complex, computer simulations. This led and still leads to a high publication activity on techno-economic and other optimizations for such systems. However, the operating strategies and component models are often oversimplified, leading to results with significant errors. The goal of this paper is to provide in-depth insight into component modeling and parametrization for PV module, battery energy storage, and inverter, as well as giving suggestions on appropriate control strategies. The focus lies on the description of suitable simple-but-accurate models and their parametrization. In order to avoid the effort of having to conduct measurements for component characterization, an approach relying on values presented in product data sheets is considered. Furthermore, the effects of model simplifications, as they are found in many publications, are shown. Finally, the importance of an uncertainty analysis for the entire simulation is discussed in order to gain insight into the accuracy of the calculated simulation results and their dependency on model- and input-parameters.

Photovoltaic Models’ Parameter Extraction Using New Artificial Parameterless Optimization Algorithm

Identifying parameters in photovoltaic (PV) cell and module models is one of the primary challenges of the simulation and design of photovoltaic systems. Metaheuristic algorithms can find near-optimal solutions within a reasonable time for such challenging real-world optimization problems. Control parameters must be adjusted with many existing algorithms, making them difficult to use. In real-world problems, many of these algorithms must be combined or hybridized, which results in more complex and time-consuming algorithms. This paper presents a new artificial parameter-less optimization algorithm (APLO) for parameter estimation of PV models. New mutation operators are designed in the proposed algorithm. APLO’s exploitation phase is enhanced by each individual searching for the best solution in this updating operator. Moreover, the current best, the old best, and the individual’s current position are utilized in the differential term of the mutation operator to assist the exploration phase and control the convergence speed. The algorithm uses a random step length based on a normal distribution to ensure population diversity. We present the results of a comparative study using APLO and well-known existing parameter-less meta-heuristic algorithms such as grey wolf optimization, the salp swarm algorithm, JAYA, teaching-learning based optimization, colliding body optimization, as well as three major parameter-based algorithms such as differential evolution, genetic algorithm, and particle swarm optimization to estimate the parameters of PV the modules. The results revealed that the proposed algorithm could provide excellent exploration–exploitation balance and consistency during the iterations. Furthermore, the APLO algorithm shows high reliability and accuracy in identifying the parameters of PV cell models.

Benefits of MPP tracking PV system using perturb and observe technique with boost converter

In recent decades, researchers have become interested in the photovoltaic (PV) system as one of the renewable energies. There are nonlinear I-V and P-V features in the PV generators. The greatest power generated varies with temperature and irradiation. To increase PV power, it is necessary to watch MPP carefully. In order to avoid some of shortcomings of conventional perturb & observe (P&O) MPP tracking approach and increase the transient responsiveness and decrease oscillations of steady-state terminal voltage, this study introduces a modified (P&O) MPPT algorithm employing fuzzy logic-based variable step size. An indoor simulated PV source built from a typical solar panel, DC power supplying, a DC-DC converter, in addition to P&O-based MPPT controlling unit was used to create and test the suggested MPPT algorithm. To demonstrate the P&O strategy's performance benefits under both constant and fluctuating irradiations and temperatures, their simulation under unsteady state circumstances is already performed with MATLAB/Simulink. Results of the simulations demonstrate that the photovoltaic simulation system can precisely monitor the highest power point. According to the simulation findings, efficiency is attained at 95% under typical test settings and at 96% when the weather is unpredictable and there are changes in temperature and irradiance.

Design, simulation and performance analysis of photovoltaic solar water pumping system

Abstract The solar photovoltaic system is one of the technologies which is used to pump water in rural, isolated and desert areas where electric connection to the main grid is a problem. The study area is selected because of its higher natural resources of solar radiation over the year. Thus, that encourages us to adopt this study in order to understand the effects of various operating parameters on performance behaviour, which leads to enhancing the system design. This paper aims to assess the solar water pump system’s design and estimated performance in real environmental conditions. The PVsyst has been used to design and simulate a system which allows us to analyse the operating behaviour of a photovoltaic solar water pumping system. The solar PV pumping system design is considered; the photovoltaic module has characteristics and the pumping system characteristics. The photovoltaic array losses due to temperature were estimated about −14.3% and the soiling losses represented approximately −5%. The results showed that performance losses were significant variance in the months of the summer season from May to July. Therefore, their implication on the water flow rates significantly decreases throughout the months of the summer season from May to July, respectively.

Modeling and Implementation of Photovoltaic Modules for a DC-DC Boost Converter

A photovoltaic (PV) system is a renewable energy system intended to convert sunlight into the usable electricity. Due to the rapid world infrastructure development, the demand for electricity is increasing drastically. One of the promising energy resources is the PV. The required energy demand can be provided by the increase of PV system deployment. Thus, as part of the design, development and implementation of a new PV system, a system design simulation is essential. This is to ensure that the designed system works properly according to design specifications. For this reason, a PV mathematical model is necessary in the development process of the PV system especially in the MATLAB/Simulink software environment. With the developed PV model, the PV system design and simulation is made handy, thus escalates the future energy demand. This work describes the development of the PV mathematical model in the MATLAB/Simulink software environment based on the PV related equations. The equations are formed by the consideration of the equivalent circuit of PV cell. The developed PV model characteristics such as the Power-Voltage (P-V) and Current-Voltage (I-V) curves are obtained as the simulation output in MATLAB/Simulink. The obtained characteristics are compared to the actual PV model A 100W RNG-50D Renogy, as to verify the effectiveness and closeness of the developed PV model to the real PV module. In addition, in the simulation, a dc-dc boost converter is also designed and integrated with the PV model as to verify the PV module and capability as a PV power source. The simulation results with the dc-dc boost converter DC-DC integration have shown that the developed PV model is very effective to be used for the PV system simulation.

Floating photovoltaics performance simulation approach

Floating photovoltaics (FPVs) provide various benefits especially where land is scarce (e.g., reducing land occupancy, water evaporation and environment control…), or when they are combined with hydropower plants (enhanced capacity factor and green energy generation). Software such as PV∗SOL, SAM and PVSyst® are commonly used for the design and simulation of land-based photovoltaic (PV) systems. However, when it comes to the simulation of photovoltaics installed on water surface, such software does not offer the option to directly simulate FPV systems.In this work, a new approach combining MATLAB and Rhino/Grasshopper environments is proposed for the assessment of FPV systems performance. The approach is divided into various steps considering major influencing parameters such as temperature, irradiance, albedo, PV modelling, panel rows spacing, tilt angle, as well as the benefits of including a tracking mechanism. The proposed approach was validated against PV∗SOL simulations for land-based PV systems with a small deviation of less than 2.4%. FPVs simulations considering climatic conditions of Štěchovice, Czechia, showed an increase of the performance in the range of 3% compared to terrestrial PVs. This result is in accordance with some published studies based on real FPVs installations. Finally, the developed approach was applied in the simulations of two large-scale FPV systems with different designs (fixed and with a tracking mechanism) including economical aspects.

Modelling and simulation of photovoltaic system using hybrid improved shuffled frog leaping algorithm -Fuzzy controller under partial shaded condition

Due to its technical characteristics and economic benefits, the use of the photovoltaic (PV) system has become very common in the world. Nevertheless, the intermittent behavior of solar systems has created challenges for power grids due to their strong dependence on radiation and temperature. Moreover, PV systems must be operated at their maximum power so that they can return the investment costs in less time and also have higher efficiency. As a result, it is crucial to propose new maximum power point tracking (MPPT) methods to track the maximum power in conditions of uncertainty. To cope with this challenge, the fuzzy logic controller (FLC) is very effective approach. This study suggests the FCL for the MPPT algorithm for an isolated PV system using a push-pull converter. The suggested technique is optimized using the improved shuffled frog leaping algorithm (ISFLA) to improve the current MPPT controllers. To deal with the intermittent behavior of solar systems during peak load conditions, Grid is used to respond to the essential load. Fast convergence and low power fluctuations are the advantages of the recommended algorithm in tracing the MPP. The MATLAB/SIMULINK software is used to confirm the effectiveness of the recommended scheme. According to the simulation results, the PV system efficiency is increased to 99.7%.

Design and Simulation of Grid-Connected Photovoltaic System’s Performance Analysis with Optimal Control of Maximum Power Point Tracking Based on Artificial Intelligence

The research presented in this paper is part of a more significant effort to improve the dynamic and static performance of power generation systems using solar panels under specific climatic conditions. The solar panel can produce the greatest power only at the specified voltage and electric current levels. Environmental variables, such as random atmospheric oscillations, have a significant effect on the performance of a solar system connected to the network. Irradiation and ambient temperature are the two inputs to a PV (photovoltaic) system. Because solar radiation varies in nature, the PV system efficiency is low. To improve the efficiency of a solar PV system, several maximum power point tracking (MPPT) approaches are used. The purpose of this paper is to improve the performance of DC/DC chopper controllers and PV inverters in the face of abrupt climate change. To that end, the primary goal of this paper is to compare the following maximum power point search (MPPT) algorithms: the incremental conductance (IC) algorithm, the fuzzy logic (FL) algorithm, VSI controller, and the particle swarm optimization (PSO) strategy. These algorithms were evaluated in terms of efficiency, stability, and speed. A 100 kW PV system is design using MATLAB software 2021a version.

Comparative Study of Different MPPT Methods of a Boost Chopper of PV Generator

Abstract In this article, we focus on improving the performance and efficiency of photovoltaic systems. The main objective is to study and compare the performance of different MPPT methods, and to find the most efficient method (in terms of convergence speed, the MPP point where the oscillation is reduced), so that the generator of maximum power supplied by the photovoltaic can be extracted.. The main points involved in this research are: Modeling of the photovoltaic system Simulation of four MPPT algorithms. The simulation results are obtained using simulink in matlab.