Large-scale Grid-connected Photovoltaic Research Articles

Reliability and Criticality Analysis of a Large-Scale Solar Photovoltaic System Using Fault Tree Analysis Approach

Solar Photovoltaic (PV) systems typically convert solar irradiance into electricity, thereby helping to reduce the need for fossil fuels and the amount of greenhouse gases released. They provide a reliable and continuous renewable source of energy. However, PV systems are continuously exposed to diverse and changing environmental conditions, such as temperature, humidity, dust, and rain. Exposure to such conditions creates electrical and visible faults in the PV systems. These faults may reduce the PV system’s performance, reliability, and lifetime. In this regard, this paper aims to propose a framework/methodology for reliability modeling and assessment of large-scale grid-connected PV systems using a Fault Tree Analysis (FTA) approach. Specifically, an exhaustive literature survey is carried out to acquire the failure rates of different components/faults existing on the DC side of the PV system. Then, the Fussel-Vesely (F-V) importance measure is employed to identify critical faults and their criticality ranking. Results showed that solder bond failure, broken cell, broken interconnect (finger interruption), rack structure, grounding/lightning protection system, delamination, discoloration, and partial shading are the most critical faults which severely degrade the performance of the PV systems. The recommendations and scope for further study are provided to optimize operations and maintenance costs.

75MW AC PV Module Field Anomaly Detection Using Drone-Based IR Orthogonal Images With Res-CNN3 Detector

In recent years, the use of solar photovoltaic (PV) technologies for generating electricity has gained much popularity due to their efficiency, cost-effectiveness, reliability and the need to reduce carbon emissions and air pollution levels around the world in order to control and limit global climate change. Drone-based inspection of Solar Plants is an efficient method to perform preventative and corrective maintenance on the Solar PV arrays installed in large-scale grid-connected Solar PV Plants. Quite a few studies have been made in detecting PV module anomalies from these drone-captured thermal images. The main challenge that most of the applied techniques and models in these studies experience is the capability to detect and localize various PV module defects with high and consistent confidence scores and accuracy. The efficiency and robustness of anomaly detection of these models are also reduced when the testing image scales vary. In this article, we propose the Res-CNN3 framework for defective PV modules region object detection. Res-CNN3 follows a bipartite process for defect regions detection to process the thermal delta of a thermal PV module image using a combination of concatenated CNNs and residual networks to identify whether the thermal image is characteristic of defect regions or not. Logistic regression is employed as the loss function whist the Selective Search (SS) algorithm is utilized to predict the regions of interest (RoI) of the input thermal images for PV module defect regions object detection. Several categories of experiments are performed on the consolidated dataset. The results of these experiments demonstrate that the proposed model surpasses the advanced benchmarked methods in accuracy and computing resource efficiency.

Why Can Simple Operation and Maintenance (O&M) Practices in Large-Scale Grid-Connected PV Power Plants Play a Key Role in Improving Its Energy Output?

Existing megawatt-scale photovoltaic (PV) power plant producers must understand that simple and low-cost Operation and Maintenance (O&M) practices, even executed by their own personal and supported by a comparison of field data with simulated ones, play a key role in improving the energy outputs of the plant. Based on a currently operating 18 MW PV plant located in an under-developing South-Asia country, we show in this paper that comparing real field data collected with simulated results allows a central vision concerning plant underperformance and valuable indications about the most important predictive maintenances actions for the plant in analysis. Simulations using the globally recognized software PVSyst were first performed to attest to the overall power plant performance. Then, its energy output was predicted using existing ground weather data located at the power plant. Compared with the actual plant’s annual energy output, it was found that it was underperforming by −4.13%, leading to a potential monetary loss of almost 175,000 (EUR)/year. Besides, an analysis of the O&M power plant reports was performed and compared to the best global practices. It was assessed that the tracker systems’ major issues are the forerunner of the most significant PV power plant underperformance. In addition, issues in inverters and combiner boxes were also reported, leading to internal shutdowns. In this case, predictive maintenance and automated plant diagnosis with a bottom-up approach using low-cost data acquisition and processing systems, starting from the strings level, were recommended.

Research on Optimal Strategy of Peak-shaving of Photovoltaic Grid-connected System Based on Simulated Annealing-Q Learning Algorithm

In order to alleviate the problem of large-scale grid-connected photovoltaics and increase the pressure of grid peak regulation, this paper proposes a dynamic economic dispatch method considering the system peak regulation margin. The system peak shaving margin is proposed to deal with the flexibility problem in economic dispatch and improve the enthusiasm of thermal power unit peak shaving. The economic dispatch model is transformed into a dynamic programming model and solved by the simulated annealing-Q learning algorithm. The analysis of the results shows that the proposed dynamic programming strategy can effectively improve the operating economy of the system and increase the flexibility of peak shaving of thermal power units.

Reliability Analysis and Repair Activity for the Components of 350 kW Inverters in a Large Scale Grid-Connected Photovoltaic System

The reliability of photovoltaic (PV) generators is strongly affected by the performance of Direct Current/Alternating Current (DC/AC) converters, being the major source of PV underperformance. However, generally, their reliability is not investigated at component level: thus, the present work presents a reliability analysis and the repair activity for the components of full bridge DC/AC converters. In the first part of the paper, a reliability analysis using failure rates from literature is carried out for 132 inverters (AC rated power of 350 kW each) with global AC power of 46 MW in a large scale grid-connected PV plant. Then, in the second part of the work, results from literature are compared with data obtained by analyzing industrial maintenance reports in the years 2015–2017. In conclusion, the yearly energy losses involved in the downtime are quantified, as well as their availability.

Investigating policies on improving household rooftop photovoltaics adoption in Indonesia

Indonesia has an enormous solar energy potential equivalent to 207.8 Gigawatt (GW) of power generation because of its equatorial location. Nevertheless, solar energy development in Indonesia is still considerably low, with no more than 3% of household consumers using solar energy (estimated 2018). Building a large-scale grid-connected photovoltaics (PV) system offers an excellent opportunity to boost solar energy development. However, it requires a considerable investment that the government cannot currently provide. One feasible solution is through the distributed PV system adoption, such as the household rooftop PV. Net metering and net billing have been implemented as policy instruments to increase the household rooftop PV adoption, but their effectiveness was never assessed. Therefore, this study aims to examine the effectiveness of the two policy instruments by analyzing and understanding the dynamic complexity of the household rooftop PV adoption using system dynamics approach incorporated with policy analysis framework. The findings suggest that the net metering is more effective than the net billing in boosting the household rooftop PV adoption. The study also emphasizes the importance of taking a systems perspective to acquire a sufficient understanding of the dynamic complexity of solar energy development for a better evaluation of energy policy.

Sizing Optimization of Large-Scale Grid-Connected Photovoltaic System Using Cuckoo Search

<p>This study presents the development of Cuckoo Search (CS)-based sizing algorithm for sizing optimization of 5MW large-scale Grid-Connected Photovoltaic (GCPV) systems. CS was used to select the optimal combination of the system components which are PV module and inverter such that the Performance Ratio (PR) is correspondingly optimized. The oversized and undersized of this large-scale GCPV system can give huge impact towards the performanceof this system. Before incorporating the optimization methods, a sizing algorithm for large-scale GCPV systems was developed. Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods.The results showed that the CS-based sizing algorithm was unable to found the optimal PR for the system if compared with ISA. However, CS was outperformed ISA in producing the lowest computation time in finding the optimal sizing solution.</p>

Development of Probabilistic Reliability Models of Photovoltaic System Topologies for System Adequacy Evaluation

The contribution of solar power in electric power systems has been increasing rapidly due to its environmentally friendly nature. Photovoltaic (PV) systems contain solar cell panels, power electronic converters, high power switching and often transformers. These components collectively play an important role in shaping the reliability of PV systems. Moreover, the power output of PV systems is variable, so it cannot be controlled as easily as conventional generation due to the unpredictable nature of weather conditions. Therefore, solar power has a different influence on generating system reliability compared to conventional power sources. Recently, different PV system designs have been constructed to maximize the output power of PV systems. These different designs are commonly adopted based on the scale of a PV system. Large-scale grid-connected PV systems are generally connected in a centralized or a string structure. Central and string PV schemes are different in terms of connecting the inverter to PV arrays. Micro-inverter systems are recognized as a third PV system topology. It is therefore important to evaluate the reliability contribution of PV systems under these topologies. This work utilizes a probabilistic technique to develop a power output model for a PV generation system. A reliability model is then developed for a PV integrated power system in order to assess the reliability and energy contribution of the solar system to meet overall system demand. The developed model is applied to a small isolated power unit to evaluate system adequacy and capacity level of a PV system considering the three topologies.

Spatial matching of large-scale grid-connected photovoltaic power generation with utility demand in Peninsular Malaysia

Deployment of large-scale grid-connected photovoltaics (PV) power plants requires very reliable technical evaluation to reduce electricity demand and achieve efficient utilization of electricity generated from PV. At lower PV penetration levels, it is likely that the energy mix could under-supply utility demand, thus requiring extra units of generators, while at higher penetration levels it may oversupply demands, thus wasting generator capacity. Thus, determining the optimum installed capacity, technical limits, and economic benefits of large-scale PV systems are the main issues for both power utilities and decision makers. This study describes the development and validation of an alternative method (called the generation-demand matching model, GDMM) for evaluating the large-scale implementation of grid-connected PV power plants in Peninsular Malaysia relative to its interface with the traditional power grid system. The method explicitly provides a detailed assessment of the temporal and spatial factors that facilitate the match between PV generated electricity and electricity demand. These evaluation factors are analyzed using simulations of PV performance located at optimal sites. Optimal sites along with physical constraints were mapped using geographic information systems (GIS) for visualization and representation by location. PV electricity generation at different levels of penetration was predicted hourly for a year using time series analysis. This allowed comparison of electricity generation with electricity demand to evaluate the impacts of increasing levels of PV penetration. A novel feature of the proposed method is its combination of topographical and topological map data with metric data. The ability of the new method to accurately predict the performance of PV compared to PVWatts demonstrates the robustness of the method in evaluating the technical limits of PV systems in conventional power systems.

Research on harmonic and overvoltage of photovoltaic power plant electricity energy collection system based on passive network model

In large-scale photovoltaic (PV) power plant, the output power of each grid-connected inverter is collected by electricity energy collection system and then is put into the grid. Previous studies have demonstrated that the harmonic problem may occur when PV inverters run in parallel even if all the PV inverters output power do individually satisfy the standards. Considering the electricity energy collection system, this study builds the model of harmonic transfer passive network for the typical topological structure of large-scale grid-connected PV power plant, and study the generating mechanism of harmonic and overvoltage. The harmonic power flow of a given calculation example is calculated by using node matrix method and the harmonic voltage magnification of each node is got. The point of common coupling is chosen as the study object. In this study, the impacts of cable parameters, the equivalent impedance of power grid and operation mode of PV power plant on the voltage magnification properties of the transfer network are analysed.

Stable reactive power balancing strategies of grid-connected photovoltaic inverter network

Summary In this paper, a distributed reactive power control based on balancing strategies is proposed for a grid-connected photovoltaic (PV) inverter network. Grid-connected PV inverters can transfer active power at the maximum power point and generate a certain amount reactive power as well. Because of the limited apparent power transfer capability of a single PV inverter, multiple PV inverters usually work together. The communication modules of PV inverters formulate a PV inverter network that allows reactive power to be cooperatively supplied by all the PV inverters. Hence, reactive power distributions emerge in the grid-connected PV inverter network. Uniform reactive power distributions and optimal reactive power distributions are considered here. Reactive power balancing strategies are presented for both desired distributions. Invariant sets are defined to denote the desired reactive power distributions. Then, stability analysis is conducted for the invariant sets by using Lyapunov stability theory. In order to validate the proposed reactive power balancing strategies, a case study is performed on a large-scale grid-connected PV system considering different conditions. Copyright © 2015 John Wiley & Sons, Ltd.

Power Tracking Control Strategy Based on Feedback Frequency of Large-Scale Grid-Connected PV Generation

PV (Photovoltaic) generation output with MPPT (Maximum power point tracking) is unadjustable. In this paper, PV generation is expected to regulate grid frequency. Thus a power tracking control strategy based on feedback frequency instead of MPPT is put forward. The feedback frequency is transferred to controlling unit of DC-DC inverter. The DC bus voltage is adjusted by controlling the duty cycle of DC-DC invertor. A grid-connected PV system with a power tracking control strategy based on feedback frequency and a DC-AC inverter control module are built in MATLAB-Simulink platform. Experiment result indicates that PV generation could regulate grid frequency by the control strategy based on feedback frequency.

Dynamic Stability of Three-Phase Grid-Connected Photovoltaic System Using Zero Dynamic Design Approach

This paper presents a new approach to control the grid current and dc-link voltage for maximum power point tracking and improvement of the dynamic response of a three-phase grid-connected photovoltaic (PV) system. To control the grid current and dc-link voltage, the zero dynamic design approach of feedback linearization is used, which linearizes the system partially and enables controller design for reduced-order PV system. This paper also describes the zero dynamic stability of the three-phase grid-connected PV system, which is a key requirement for the implementation of such controllers. Simulation results on a large-scale grid-connected PV system show the effectiveness of the proposed control scheme in terms of delivering maximum power into the grid.