Optimization of Solar PV System Efficiency in Bangladesh

In recent years, the integration of Distributed Energy Resources (DERs) and communication networks has presented significant challenges to power system control and protection, primarily as a result of the emergence of smart grids and cyber threats. As the use of grid-connected solar Photovoltaic (PV) systems continues to increase with the use of intelligent PV inverters, the susceptibility of these systems to cyber attacks and their potential impact on grid stability emerges as a critical concern based on the inverter control models. This study explores the cyber-threat consequences of selectively targeting the components of PV systems, with a special focus on the inverter and Overcurrent Protection Relay (OCR). This research also evaluates the interconnectedness between these two components under different cyber-attack scenarios. A three-phase radial Electromagnetic Transients Program (EMTP) is employed for grid modeling and transient analysis under different cyber attacks. The findings of our analysis highlight the complex relationship between vulnerabilities in inverters and relays, emphasizing the consequential consequences of affecting one of the components on the other. In addition, this work aims to evaluate the impact of cyber attacks on the overall performance and stability of grid-connected PV systems. For example, in the attack on the PV inverters, the OCR failed to identify and eliminate the fault during a pulse signal attack with a short duration of 0.1 s. This resulted in considerable harmonic distortion and substantial power losses as a result of the protection system’s failure to recognize and respond to the irregular attack signal. Our study provides significant contributions to the understanding of cybersecurity in grid-connected solar PV systems. It highlights the importance of implementing improved protective measures and resilience techniques in response to the changing energy environment towards smart grids.

Hot and humid climates with high solar radiation have the potential to offset residential building energy consumption with the application of solar hot water and photovoltaic electricity generation. However, costs, lack of incentives for the systems, and the need for proof-of-concepts continue to limit market penetration. The surplus of natural gas in certain areas of the United States, particularly Texas, continues to keep gas and electricity production economical compared to solar alternatives. However, trends that demand lower energy homes, a desire for local energy independence, and the lowering of carbon dioxide emissions continue to fuel solar energy systems penetration. To support solar use, this research was performed to evaluate and analyze the real-world life cycle energy and costs of a solar photovoltaic and solar hot water system (SHWS) installed on a high-end residential home in Houston, TX (IECC Zone 2). The house was a well-insulated, large urban home with two renewable energy systems installed: a 3.5 kW solar photovoltaic system (SPVS) and a 1.71 kW solar hot water system. Analyses were part of a larger study performed to investigate the contributions of the solar energy offsets on the operational energy of the building over a life cycle period of 30-years. Field measurements of energy production were compared to solar energy simulations based on the typical meteorological year and the National Solar Radiation Database (NSRDB) data. NSRDB provided the basis for a probabilistic interpretation of annual energy production in terms of probability measures, P50/P90. It was found that field estimates were within simulation uncertainties and P90 predictions were within 2.5% of TMY3 (typical meteorological year data 3) results for both the solar photovoltaic system (SPVS) and solar hot water system (SHWS). Additionally, optimizations in the system design and life cycle costs were investigated to determine the annual optimal performance for the solar energy systems. The SHWS was installed at a less than optimum azimuth of 270° instead of 180° (corresponding to a 16% reduction in annual output). The SPVS was installed at optimal design conditions of 180° azimuth and 42° tilt. Payback and levelized cost of energy (LCOE) could have been minimized with the addition of another solar hot water collector with a minimal impact to overall cost. Cost sensitivity analysis on the LCOE and net-present value (NPV) were also performed and over a 30-year life cycle period, TMY3 based simulations predicted a NPV of $796 (21.8-year non-discounted payback) and -$1246 (29.2-year non-discounted payback) for the SHWS and SPVS, respectively. The SHWS achieved a LCOE of 8.1 ¢/kWh, while the value for the SPVS was 12.29 ¢/kWh. For the SPVS, the photovoltaic module and collector costs were the largest life cycle costs, and of special note, a reduction in the module cost by 67% reduces the LCOE to the market average-high electricity price of 10 ¢/kWh. Finally, the combined renewable energy systems generated an estimated 30-year life-cycle energy production of 184 814 kWh, with auxiliary gas provided for supplemental hot-water heating. On average, a Texas residential home utilizes 420 000 kWh of electrical energy, 19% of which is domestic hot water demand.

German Malaysian Institute (GMi) has a great potential for utilising solar photovoltaic (PV) electricity. In this study, the performance of a 3kW grid-connected solar PV (GCSPV) system is monitored using Sunny Portal web in conjunction with Sunny SensorBox. The daily solar energy that strikes a PV array cannot be totally transformed into grid-compatible electricity. As a result of power losses, the production of solar PV systems falls short of expectations. The primary objective of this study is to examine the influence of solar insolation and PV module temperature on the actual output of the GCSPV system compared to the predicted output system by considering elements that affect the conversion of solar power to electrical power in GCSPV systems. The study prediction method based on calculations was carried out. Prediction of output system considered all losses, including efficiency of PV module, solar insolation, temperature of PV module, dirt, manufacturer’s tolerance and module mismatch, the voltage drop in DC cables to inverter, and inverter efficiency. The data indicate that the average power generation is 7.26% lower than predicted by the system. The GCSPV system’s performance efficiency is diminished by the temperature increase and somewhat enhanced by an increase in solar insolation. Temperature has a crucial impact in the energy conversion process of PV module. The effectiveness of the PV module in generating energy and power is dependent on its operating temperature.

With over 8,000 inhabited islands, the distribution of fuels and electricity is extremely challenging in Indonesia. Photovoltaic (PV) energy systems could offer new opportunities and could become increasingly important for the future electricity mix of Indonesia. To stimulate this transition, it is necessary that existing barriers to a successful implementation of PV systems are indicated in order to be tackled. This thesis adds to this goal by enhancing the technical knowledge about PV systems in Indonesia. This has been achieved by modelling and simulation of PV systems. The main research question in this thesis is: What can be learned from experiences with and modelling of PV systems for the stimulation of PV in the future electricity mix in Indonesia? Since the successful implementation of PV systems depends on several factors, PV systems have been evaluated at three different levels: the national, system and product level. At the national level, the potential and costs of PV systems are modelled and assessed. For this purpose, a distinction has been made for grid-connected and off-grid PV systems. For both PV system configurations the potential nominal installed capacity and levelized cost of electricity (LCOE) of PV systems has been determined for each of the provinces of Indonesia. To assess the cost-effectiveness the LCOE has been compared with the generation cost of electricity. At the system level, a pilot grid-tied PV system - which has been installed in Jayapura in the province of Papua during this project - has been analysed. Jayapura regularly suffers from power outages due to aged diesel generators and a weak electricity grid. The performance of the grid-tied PV system in such a weak electricity grid has been evaluated. Subsequently, at the product level, monitoring data from this PV system are used to simulate the power output of the PV system, evaluating the appropriateness of existing models for the determination of the power output under tropical weather conditions. Finally, to increase the accuracy of short-term PV power output simulations, a new PV module temperature model has been proposed.

In this article, we deal with the development of a fractional-order notch filter (FONF) for a grid-connected solar photovoltaic (PV) system. The developed FONF control approach is used to estimate fundamental active constituents from the distorted load currents, and hence, gating pulses for operating voltage source converter (VSC) are used in the PV system. This control approach for the grid-connected solar PV system is designed to achieve several purposes, such as feeding active power demand of the load/grid and countercurrent-related power quality issues at the common connecting point. The power quality issues taken into consideration are harmonics distortion, reactive power burden on the system, and unbalancing of connected loads. The FONF-based control proposes a modified structure of an integer-order notch filter. The integer-order filters have a limitation due to the fixed integrator and differentiator terms. In FONF, the power of integrator used in a notch filter can be modified according to the application required for obtaining the accurate response of the system. A prototype of the grid-connected solar PV system is developed in the laboratory using IGBTs based VSC and dSPACE MicroLabBox (DS-1202) to demonstrate the behavior of the FONF-based control. Simulation and experimental results are obtained for steady-state and unbalanced loads with variation in the solar irradiance. The harmonic distortions in the system are observed as per the IEEE-519 standard.

In the present trend, the grid-connected solar photovoltaic systems are playing a major role in supporting the utility peak power and providing the quality of power supply. The installation of solar photovoltaic system is reasonable cost for producing the power. But the solar power may not meet the utility peak demand continuously due to the intermittent nature of solar power. To make continuous supply, the battery storage system is proposed with the bidirectional convert using PI controller. In this work, the grid integration of solar photovoltaic with battery storage system is proposed using the hysteresis current controller for conditioning the electrical power. The solar power is extracted using fuzzy-based maximum power point tracking methods under dynamic variations in the irradiance and temperature. The extracted power is integrate with DC link, and the voltage at DC link is stabilized with the help of battery storage system. The DC link is integrated with the grid through the inverter using a hysteresis current control technique with the PI controller. The inverter and battery storage controllers are used for providing quality of power supply and can meet the necessary peak demand. The performance of the grid-connected solar photovoltaic and battery storage systems is simulated in MATLAB–Simulink software under the dynamic irradiance and the temperature variations.

The growing global need for energy has spurred the widespread adoption of grid-connected Solar Photovoltaic (SPV) systems. These systems harness the advantages of photovoltaic power generation, such as environmental sustainability, low maintenance requirements and noise-free operation, positioning them as a prominent Renewable Energy Source (RES). This conceptual framework emphases on demonstrating and control design of a PV grid-tied system, integrating a Modified Single-Ended Primary Inductance (SEPIC) - Luo Converter. The central objectives of this work are to investigate the behavior of solar PV systems and to develop an efficient grid-connected solar power solution. To achieve these objectives, a Maximum Power Point Tracking (MPPT) circuit is designed, leveraging Red deer algorithm optimized Adaptive Neuro-Fuzzy Inference System (ANFIS). This innovative approach ensures the continuous optimization of power extraction from solar PV modules. The DC voltage generated by the PV system is subsequently directed to a Single-Phase Voltage Source Inverter (1ΦVSI) for conversion into AC voltage. The resulting AC voltage is then made available for various applications within the grid. Based on the simulation results, the algorithm efficiency is of 98.8% and the converter efficiency is found to be 98.92%. The MPPT efficiency is of 98.61%, which gives better optimization when compared to that of other algorithms. This framework encapsulates the advancements in SPV systems, offering a sustainable energy solution that aligns with the growing demand for clean and efficient power generation.

The purpose of this research is to develop an efficient single-phase grid-connected PV system using a better performing asymmetrical multilevel inverter (AMI). Circuit component reduction, harmonic reduction, and grid integration are critical criteria for better inverter efficiency. The proposed inverter’s optimized topology requires seven unidirectional switches, three symmetric dc sources, and three diodes to produce an asymmetric fifteen level output; whereas, the same configuration will generate 7, 11, and 15-level output with an appropriate choice of dc source magnitudes. It is possible to reduce inverter losses and boost efficiency by decreasing the number of switches used. The integration of an asymmetric 15-level inverter with a grid-connected solar photovoltaic system is discussed in this article. A grid-connected solar photovoltaic (GCSPV) system is modelled and simulated using an asymmetric 15-level inverter. The dc sources of the 15-level inverter are replaced with PV sources. The results were analyzed with different operating temperatures and solar irradiance conditions. The GCSPV system is controlled by a closed-loop control system using Particle Swarm Optimization (PSO), Harris Hawk Optimization (HHO), and Hybrid Particle Swarm Optimization-Genetic Algorithm (PSOGA) based Proportional plus Integral (PI) controllers. Grid voltage, grid current, grid power, and total harmonic distortion (THD) of grid currents were analyzed. The performance of the 15-level asymmetric inverter was evaluated by comparing the THD of the grid current and the efficiency of the grid-connected photovoltaic system.

<a name="_Hlk98601430"></a><span lang="EN-US">In this research, a sensor free DC-link voltage controller based multifunctional inverter is proposed for a two-stage three-phase grid-connected solar photovoltaic (PV) system. First, the proposed scheme consists of an outer voltage controller requiring DC-link voltage knowledge, has the ability to manage power-sharing between the PV system and the utility grid, and second, has the ability of the VSI to act as a compensator for harmonics in the grid current polluted by non-linear loads. The suggested active power controlling grid reference current signal scheme replaces the standard controller, requiring the high voltage sensor to sense DC-link voltage, which is pricey, increasing the hardware complexity and reducing reliability. The performance of the proposed active power management approach is comparable to that of a conventional voltage sensor-based voltage controller. The effectiveness of the proposed method for two stage three-phase grid-connected solar PV system under fixed and variable irradiance feeding nonlinear loads is rigorously verified using MATLAB/Simulink software</span><span lang="EN-US">.</span>

The goal of this research is to improve the efficiency and dependability of grid-connected solar photovoltaic (PV) systems by utilizing Artificial Neural Networks (ANN) and Space Vector Pulse Width Modulation (SVPWM). The main issues with power quality were reducing total harmonic distortion (THD) and enhancing voltage control. In the field of solar photovoltaic (PV) systems, these issues are crucial as power electronics converters and the amount of incoming solar radiation are both subject to fluctuation. An artificial neural network (ANN) technique uses the high-quality voltage waveform and real-time power regulation of the SVPWM inverter to dynamically adjust the inverter's switching patterns. We were able to conclude that the suggested method worked better than the conventional SVPWM processes after conducting simulations in a number of work situations. One noteworthy discovery was the average overall harmonic distortion, which is now being lowered to less than 5% in order to comply with IEEE 519 standards. The efficiency of the ANN-SVPWM system was 96% higher than that of the conventional one, and it maintained a steady voltage even when the sun's irradiation levels changed. Furthermore, this function demonstrated that grid-connected PV systems may respond more quickly to changes in the sun's conditions in real time, perhaps making them a more effective option. In the biological sciences, researchers discovered that combining artificial neural networks (ANN) with systematic vector pulse width modulation (SVPWM) enhanced the dependability, efficiency, and power quality of solar photovoltaic (PV) systems.

The aim of this research is to perform an in-depth performance comparison of ground-mounted and rooftop photovoltaic (PV) systems. The PV modules are tilted to receive maximum solar irradiance. The efficiency of the PV system decreases due to the mutual shading impact of parallel tilted PV modules. The mutual shading decreases with the increasing interrow distance of parallel PV modules, but a distance that is too large causes an increase in land cost in the case of ground-mounted configuration and a decrease in roof surface shading in the case of rooftop configuration, because larger sections of roof are exposed to sun radiation. Therefore, an optimized interrow distance for the two PV configurations is determined with the aim being to minimize the levelized cost of energy (LCoE) and maximize the energy yield. The model of the building is simulated in EnergyPlus software to determine the cooling load requirement and roof surface temperatures under different shading scenarios. The layout of the rooftop PV system is designed in Helioscope software. A detailed comparison of the two systems is carried out based on energy output, performance ratio, capacity utilization factor (CUF), energy yield, and LCoE. Compared to ground-mounted configuration, the rooftop PV configuration results in a 2.9% increase in CUF, and up to a 23.7% decrease in LCoE. The results of this research show that installing a PV system on a roof has many distinct advantages over ground-mounted PV systems such as the shading of the roof, which leads to the curtailment of the cooling energy requirements of the buildings in hot regions and land cost savings, especially for urban environments.

In this paper, a detailed documentation revealing the design, development, and implementation aspects of grid-connected solar photovoltaic (SPV) power conversion system is presented. Since the inverter is considered as a key constituent of an SPV system, a laboratory developed three-phase four-legged (3P4L) inverter is employed to diminish the overall cost of the SPV system considerably. The multifunctional inverter controlled SPV system proposed in this work not only injects active power into the electric grid, but it also serves as an active power filter (APF) to provide various power quality (PQ) solutions. This typically includes source current harmonic attenuation, load reactive current mitigation, neutral current elimination, source current balancing, in addition to ensure unity power factor operation. A various hardware circuits including signal sensing circuit, signal conditioning circuit, pulse amplification and isolation circuit, and blanking circuit are fabricated and assembled to develop a complete laboratory prototype model. In addition, the voltage and current controllers, the synchronize reference frame theory (SRFT)-based approach, and the phase-locked loop (PLL) control algorithms are embedded in dSPACE 1104 control platform. Furthermore, an STM32F407VGT microcontroller is employed to implement the incremental conductance based maximum power point (MPP) tracking algorithm. The effectiveness of the developed SPV system is first simulated in MATLAB/Simulink software. In the second step, the efficacy of the proposed configuration is investigated under balanced and unbalanced nonlinear loads on a laboratory developed prototype.

Performance measurement of 5 kWp rooftop grid-connected SPV system in moderate climatic region of Imphal, Manipur, India

Performance evaluation of two grid-connected solar photovoltaic systems under temperate climatic conditions in South Korea

The performance of a commercial-scale (86.4 kWp) rooftop grid-connected photovoltaic (PV) system was investigated from the measured daily power generation and weather. The PV system was installed in Atlanta, GA, USA, where global solar irradiation varies from 3.3 to 9.0 kWh/m2 day (average: 4.7 kWh/m2 day). Annual power generation measured from this PV system was 110 MWh with a capacity factor of 14.5%. This is also equivalent to a carbon reduction of 25.2 tons/yr. Furthermore, for an accurate assessment of the total system derate losses and the levelized cost of electricity (LCOE), System Advisory Model modelings were performed. From the modelling, the total PV system derate losses were calculated to be 27% (including inverter loss) and the LCOE value was 14¢/kWh. Note that the installed system cost was 4.18$/W when it was installed in 2011, assuming 30 years of lifetime and a weighted average cost of capital of 5.6%. However, in 2016, one can install PV systems only at 2.2$/W instead of 4.18$/W, so the LCOE can be down to 7¢/kWh. As the price of commercial electricity in GA is about 9.6¢/kWh, a LCOE of 7¢/kWh can match the grid parity.