Corrected Performance Ratio Research Articles

Performance and reliability analysis of an off-grid PV mini-grid system in rural tropical Africa: A case study in southern Ethiopia

Although some progress has been made in recent years, ensuring universal access to electricity remains a major challenge in many countries in sub-Saharan Africa, particularly in rural areas. In light of this challenge, solar photovoltaic (PV) mini-grid systems have emerged as a promising solution for off-grid electrification. However, little is known about their actual performance and reliability when used in real-world applications. Using real-time monitored data and IEC's evaluation standard, this paper examines the performance and reliability of a 375 kWp off-grid PV mini-grid system installed in a remote small town in Ethiopia. The findings showed that the mini-grid produced 1182 kWh/day of electricity compared to the estimated generation of 2214 kWh/day, a difference of 1032 kWh/day (46.6% less). In contrast, 87% of the average daily electricity generated was delivered to the load. The discrepancies can be attributed to average PV capture losses of 2.75 kWh/kWp/day and system losses of 0.40 kWh/kWp/day. The performance evaluation results revealed that the mini-grid system is performing poorly, with average on-site module efficiency (ηpc), temperature corrected performance ratio (PRcorr), capacity factor (CF) and overall system efficiency (ηsys) of 9.85%, 42%, 13%, and 8.76%, respectively. It was found that the daily PV energy output could not meet the daily demand. As a result, the load is shed off from the power supply for 13 h a day; between 17:00 and 19:00 and again between 21:00 and 08:00. The study demonstrated that accurate demand assessment and robust system sizing, taking into account the impact of local weather conditions and prospective electricity demand growth is critical to ensure high performance and reliability of off-grid PV mini-grid systems.

Performance Loss Rates of a 1 MWp PV Plant with Various Tilt Angle, Orientation and Installed Environment in the Capital of Cyprus

Evolution from fossil fuel sources to environmentally friendly and sustainable energy sources is one of the key aspects of the energy transition goal. On the other hand, Solar Photovoltaic systems are the most promising and improving technologies in the energy market However, it is well known that the performance of PV panels decreases in the process of time. This paper focuses on analyzing the performance loss rates (PLR) of mid-scale crystalline silicon (c-Si) PV systems of the same manufacturer with different orientations and tilt angles in the same region for the duration of four years of outdoor exposure. Three commonly used statistical methods are deployed to calculate PLRs; seasonal and trend decomposition using locally weighted scatterplot smoothing (STL), classical seasonal decomposition (CSD) and year on year (YoY) methods coupled with various performance metrics, namely Performance ratio (PR), temperature corrected performance ratio TCPR) and weather corrected performance ratio suggested by National Renewable Energy Laboratory (NRELPR). It is found that PLRs of analyzed venues, Arazi, Arena and Stonite, with the YOY approach are −1.2%/year, −0.73%/year and −2.65%/year, respectivelty., respectively. Furthermore, STL method demonstrated PLRs of −0.69%/year, −0.65%/year and −2.91%/year, respectively. On the other hand, the CSD method generated positive PLRs for some inverters while aforementioned statistical approaches proposed PLRs close to −2%/year, making the CSD method inappropriate for use under a heavy soiling environment. Within two km distance, variations up-to four-fold in PLRs are recorded between the venues during analyzed period. Furthermore, variations in PLRs are more dependent on the statistical approach rather than the performance metric.

Long-term performance and degradation analysis of different PV modules under temperate climate

The share of solar photovoltaic in the energy mix is achieving significant growth worldwide. Accurate forecasts of return on investment and a good choice of optimal PV technology for different regions require proper PV studies. Long-term performance and degradation analysis, as well as an economic investigation of three based-silicon PV technologies including amorphous silicon (a-Si), polycrystalline silicon (p-Si), and monocrystalline silicon (m-Si) have been performed in this work. This study has been done based on different performance indicators such as AC energy production (EAC), reference yield (Yr), final yield (Yf), performance ratio (PR), temperature corrected performance ratio (PRSTC), degradation rate (Dr), and levelized cost of energy (LCOE). The results of the performance ratio analysis revealed that crystalline silicon technologies are better than amorphous PV system with values of 84.25% for m-Si, 84.32% for p-Si, and 79.14% for a-Si. The degradation analysis was performed using linear regression (LR) and classical seasonal decomposition (CSD) statistical techniques. The results of these latter indicate that a-Si degrades faster than its counterparts with a ratio of 0.9 ± 0.009%/year and 0.75 ± 0.003%/year, followed by m-Si (0.53 ± 0.01%/year and 0.41 ± 0.003%/year), and p-Si (0.36 ± 0.01%/year and 0.28 ± 0.004%/year) using LR and CSD, respectively. However, these degradation rates are comparable to other degradation rates obtained in studies performed in different climates in Morocco. Finally, the LOCE results demonstrate that p-Si technology is the most cost-effective system with a value of 0.09 USD/kWh compared to 0.1 USD/kWh for m-Si, and 0.13 USD/kWh for a-Si. According to the obtained findings, p-Si is the most optimal and suitable technology to be installed in the mountain temperate climate.

Comparison of normal and weather corrected performance ratio of photovoltaic solar plants in hot and cold climates

Performance Ratio (PR) is one of the best performance metrics used to assess solar power plant performance. PR is also used for commercial acceptance of an installed PV power plants. If the PR is tested in different climatic conditions or seasons, there are bias errors, affecting the contractual acceptance testing. PR is often corrected to the Standard Test Conditions (STC), resulting in higher PR since modules usually operate at higher temperatures. This research work utilizes NREL's advanced methodology to determine weather corrected PR of PV power plants in six different geographical locations and climatic regions. The Solar PV plant performance is simulated to get the normal PR as per IEC 61724-1:2017. Percentage variation of Weather corrected PR with Normal PR is determined for all these six geographical regions and compared. The weather corrected PR of Montana (with the lowest annual average temperature of 1.58 °C.) PV power plant has a maximum variation of 7.64% from the normal PR during the summer and −8.61% variation in December during the winter. The weather corrected PR of Kuzhalmannam (with the highest annual average temperature of 27.28 °C) PV power plant has a maximum variation of only 1.16% from the normal PR during summer and a variation of −0.91% in July during the rainy season. It is concluded that the metric of weather-corrected PR gains paramount importance for colder areas, whereas it has minimal influence for tropical regions.

Prognostic and Diagnostic Coupling Framework Based on OSA-CBM strategy for Photovoltaic Generators

This article proposes a prognostic and diagnostic coupling framework based on the OSA-CBM (Open System Architecture for Condition Based Maintenance) for photovoltaic generators (PVG). At First, this work presents some PVGs performance degradation studies and the main degradation indicators. We select the Corrected performance ratio (CPR) as degradation indicator associated with the Loess data analysis method to avoid aberrations and errors from acquisition system. Then, the main methods of coupling diagnostic and prognostic processes are explained: Watch Dog, Prognostic Enhancements to Diagnosis Systems (PEDS), Integrated Predictive Maintenance Systems (SIMP) and OSA-CBM. This last strategy with its seven specialized layers permits the interoperability of both processes. The monitoring system provides health indicators of PVGs and results are returned to human operator. The annual reduction rate of the CPR and reduction rate (Rd), allows us controlling the proposed coupling framework. This approach is validated with experimental data collected on four photovoltaic installations from the IEA PVPS Task13 database.

Photovoltaic system monitoring for high latitude locations

Reliable monitoring of PV systems is essential to establish efficient maintenance routines that minimize the levelized cost of electricity. The existing solutions for affordable monitoring of commercial PV systems are however inadequate for climates where snow and highly varying weather result in unstable performance metrics. The aim of this work is to decrease this instability to enable more reliable monitoring solutions for PV systems installed in these climates.Different performance metrics have been tested on Norwegian installations with a total installed capacity of 3.3 MW: (i) comparison of specific yield, (ii) temperature corrected performance ratio, and (iii) power performance index based on both physical modelling and machine learning. The most influential effects leading to instability are identified as snow, low light, curtailment, and systematic irradiance differences over the system. The standard deviation of all the performance metrics is reduced when filters targeting these four effects are applied. Compared to general low irradiance or clear sky filtering, a greater reduction in the variation of the metrics is achieved, and more data remains in the useful dataset. The most suitable performance metrics are comparison of specific yield and performance index based on machine learning modelling.The analysis highlights two paths to accomplish increased reliability of PV monitoring systems without increased hardware costs. First, better reliability can be achieved by selecting a suitable performance metric. Second, the variability of the performance metric can be reduced by utilizing filters that specifically target the origin of the variability instead of using standard literature thresholds.

Performance evaluation and degradation assessment of crystalline silicon based photovoltaic rooftop technologies under outdoor conditions

Keeping track of field performance and degradation rate of photovoltaic panels in regions with diverse environmental exposures is critical. The objective of this paper is to determine two and half year performance characteristics and degradation rate of poly-crystalline and heterojunction with intrinsic thin layer roof-top photovoltaic units under prevailing weather conditions in the Central Anatolia region. Degradation rates of the photovoltaic units were determined through analysing the effective peak power, and the temperature corrected performance ratio of each technology. Processing of the measured data covering the test period reveals that the thin film technology offers lower degradation rate with nearly −0.1% than the poly-crystalline based technology within the range of −0.67% to −0.83%, respectively. The study allows a better understanding of variations in performance and behaviour of the output power of poly-crystalline and heterojunction with intrinsic thin layer roof-top photovoltaic units after 2.5 years of outdoor exposure.

Field Analysis of three different silicon-based Technologies in Composite Climate Condition – Part II – Seasonal assessment and performance degradation rates using statistical tools

This paper is an extension study to the ‘Field Analysis of three different Silicon-based Technologies in Composite Climate Condition’ wherein, monthly average performance ratio, temperature corrected performance ratio, series resistance and effective peak power of multi-crystalline (mc-si), heterojunction with intrinsic thin layer (HIT) and amorphous silicon (a-si) based photovoltaic modules for three years were presented. The present study attempts to investigate seasonal performance and determine the degradation rates using three statistical tools, i.e. linear regression, classical seasonal decomposition (CSD), and locally weighted scatterplot smoothing (LOESS) on normalized performance ratio and normalized efficiency for three years. Further, comparative analysis of nine PV modules, i.e. three modules of each technology, and sensitivity analysis of solar irradiance and module temperature on performance ratio have been evaluated. The degradation rates are found to be 1.24%/year, 1.16%/year and 1.16%/year for a-si modules, 0.14%/year, 0.56%/year and 0.11%/year for HIT modules and 1.50%/year, 0.82%/year and 1.46%/year for mc-si modules using linear regression, CSD and LOESS analysis respectively. The average efficiency is found to be 5.17% for a-si, 15.40% for HIT and 10.78% of mc-si modules. Furthermore, the performance of these module technologies during particular season after three years of outdoor operation has also been assessed.

Endogenous Soiling Rate Determination and Detection of Cleaning Events in Utility-Scale PV Plants

As the deployment rate of PV power plants continues to soar, the need for robust, scalable methods for performance analytics increases. In this paper, we demonstrate the usefulness of one approach for quantifying soiling rates in utility-scale PV power plants endogenously, i.e., directly from the production data. The temperature corrected performance ratio, normalized to a clean state, is used to derive the soiling ratio (SR). Cleaning events, caused by either rain or manual cleaning, are automatically detected by positive shifts in the running median of the SR time series. Soiling rates are then estimated by the rate of change of the SR between the cleaning events, which is determined by linear regression. The method is validated on data from three utility-scale PV power plants in the Middle East, yielding soiling rates that are in the range 0%-0.18%/day at least 50% of the time, with a median of 0.1%/day.

Grid connected mega-watt range solar power plant in India: experimental measurement & performance analysis

<p>in India to meet its future energy demand. This paper emphasis on the performance assessment of grid connected mega-watt solar power plant which is of 23MW and 5MW are located in different geographical location in India. Performance assessment is the finest way to determine the potential of energy generation in solar power plant and it also helps in evaluating the design, operation and maintenance of existing and future solar power plant. The parameters namely calculation of annual energy generated, reference yield, final yield, system losses, cell temperature losses, performance ratio and capacity utilization factor are considered in examining solar power plant performance. In this study experimental measurement of two solar power plant one is located in Gujarat (23MW) and another in Andhra Pradesh (5MW) are compared with the results of estimated model from METEONORM 7.1 and PVSYST V6.67 software tools. Experimental measurement at solar power plant location covers the following measurement for analysis like actual weather condition, daily/hourly irradiance, actual energy yield and compares with capacity utilization factor, performance ratio and temperature corrected performance ratio parameters. The results demonstrated in this paper show the gap between the actual performance of solar power plant and the estimated model from software tool. Performance of solar power plant is satisfactory in comparison with other literature reviews. The actual annual energy generated for 23MW solar power plant was 37991MWh, 18.83% capacity utilization factor, 73.87% performance ratio and 75.33% temperature corrected performance ratio. Similarly, the actual annual energy generated for 5MW solar power plant was 9047.7MWh, 18.41% capacity utilization factor, 80.31% performance ratio and 79.90% temperature corrected performance ratio.</p>

Field Analysis of three different Silicon-based Technologies in Composite Climatic Condition

This paper investigates the performance of the photovoltaics based on the filtering techniques, performance monitoring metrics, and numerical methodologies at real outdoor conditions. The experimental study is carried out on a set of nine photovoltaics modules consisting three modules of each technology i.e. Multi-crystalline (mc-si), Heterojunction with Intrinsic Thin layer (HIT) and Amorphous Silicon (a-si). Various electrical performance data has been collected and characterized for a period of three years in the composite climate of India. The research methodology includes mapping of series resistance, estimation of monthly average effective peak Power (Peff), Performance Ratio (PR) and temperature corrected Performance Ratio (PRT_CORR) has been carried out. The average percentage reduction in the effective peak power (ΔPeff) for the mc-si, a-si and HIT modules were 15.8%, 17.2%, and 7.1% respectively over a period of three years. The monthly average PR for mc-si, a-si and HIT modules were 0.70, 0.82 and 0.83 respectively for the same period. The PR T_CORR over three-year duration for mc-si is 0.77, for a-si is 0.89, and 0.90 for a HIT modules respectively. The annual degradation is 1.5%, 1.6% and 0.39% for mc-si, a-si and HIT modules respectively. The increment in the series resistance has been calculated estimated using the procedure I of the IEC 60,891 Edi 2.0 and the mapping of the series resistance has been done with the matrix of in-plane irradiance and module temperature. Further, the uncertainty calculations of series resistance have been estimated for three different irradiation ranges i.e. 1000 W/m2, 900 W/m2 and 800 W/m2 which is around 4% to ensure the sanctity of measurements and calculations. It has been observed that module degrades faster in hot climatic zones. The interpretation of measured and calculated results, correlation of bus-bar corrosion, and module degradation have been delineated for the composite climate. Finally, it also discusses the usage of the above-proposed methods/tools for optimization of solar cell design parameters at different climatic conditions.

Evaluation of the performance and degradation of crystalline silicon-based photovoltaic modules in the Saharan environment

The aim of this paper is to present three years of an evaluation of the performance and degradation rate of three different crystalline silicon-based photovoltaic (PV) modules in the Saharan environment. The PV modules are: mc-Si (multi-crystalline), c_Si (mono-crystalline, back contacted) and HiT (heterojunction with intrinsic thin-layer); they are installed in Saida which is located at the proximity of Algeria’s Sahara. Two methods were used to calculate the degradation rate; the effective peak power of the PV modules and the temperature corrected performance ratio. It was found that the HIT technology performs worse than the other technologies with the highest degradation rate, ranging from −1.53%/year to −1.92%/year. The mc_Si PV and c_Si PV module technologies present a lower degradation rate than the HIT technology in the range of −0.74%/year to −0.83%/year and −0.58%/year to −0.79%/year respectively.

Comparative Assessment of PV Plant Performance Models Considering Climate Effects

The climate conditions can affect the accuracy of photovoltaic (PV) system performance models that can be used for monitoring and diagnostic purposes. In this paper, an improved energetic physical model has been considered to estimate the power production of PV systems. Specifically, in this model, special attention has been devoted to the modeling of optical losses (IAM losses) and to the inverter efficiency under low-power conditions.A comparative analysis of the proposed model applied to two PV plants installed respectively in the north of Denmark (Aalborg) and in the south of Italy (Agrigento) has been performed. The different ambient, operating and installation conditions allow to understand how these factors impact the precision and effectiveness of such model. The experimental results show that the proposed model allows us to have a good estimation of AC power in terms of Relative Mean Bias Error, normalized Root-Mean-Square Error, and the Correlation Coefficient. Further in order to have the possibility to analyze and compare the performance of the studied PV plants with others, the efficiency of the systems has been estimated by both Performance Ratio and Corrected Performance Ratio.

Utility scale photovoltaic plant indices and models for on-line monitoring and fault detection purposes

Improving reliability and reducing maintenance and operating costs have become important factors in increasing the competitiveness of photovoltaic (PV) systems. For grid connected PV power plants every kilowatt-hour is crucial, because only kilowatt-hours that are fed into the grid are remunerated.A plant's operator can only adopt prompt measures to eliminate operational faults when these are immediately signaled. In fact, just reading the feed-in meter periodically is not sufficient to promptly recognize faults and to avoid the loss of yields. For this reason, continuous, absolute and comparative measurements are necessary to ensure the highest efficiency and availability of photovoltaic plants. Specifically, comparing the estimated, by means of suitable models of the PV plant, and the measured power allows to provide information on the operating status of the photovoltaic systems and so to perform preventive and/or reparative maintenance.In this context, a physical model has been developed and compared with other models to estimate the DC and AC power. Further, a novel figure of merit, named Non-Uniformity Index is proposed. It permits to individuate those cases the whole system, which is composed of many sections, e.g. PV fields, is working with a sufficient efficiency, but one or more photovoltaic fields are working at lower efficiencies compared to the others.The quality of the measured data has a significant influence on the estimation accuracy of the performance model and thus on the monitoring system, for this reason, models for irradiance and PV module temperature are used to check the measured data for inconsistency and other anomalies.Based on such models, a straightforward methodology for PV plants monitoring and fault detection purposes, which allows to minimize the number of required sensors and that can be applied to PV plants of any dimension, has been developed.The proposed methodology has been applied to a utility scale PV power plant (rated 1MW), where a Supervisory Control and Data Acquisition system has been installed; operational data are saved on a remote server and available on a dedicated website. The experimental results show the effectiveness of the proposed approach. In order to have the possibility to analyze and compare the performance of the studied PV plant with others, the efficiency of the system has been estimated by both conventional Performance Ratio and Corrected Performance Ratio.

Development of Models for On-line Diagnostic and Energy Assessment Analysis of PV Power Plants: The Study Case of 1 MW Sicilian PV Plant

For photovoltaic (PV) power plants, every kilowatt-hour is important, because only kilowatt-hours that are fed into the grid are remunerated. A plant's operator can only adopt prompt measures to eliminate operational faults when these are immediately signaled. In fact, just reading the feed-in meter each month is not sufficient to promptly recognize faults and to avoid the loss of yields. Many inverters record the most important operational data, automatically evaluate the data and, in case of a fault, send the operator notifications via email or text message. However, it only allows obvious faults to be recorded. On the other hand, continuous, absolute and comparative measurements are necessary to ensure the maximum efficiency and availability. Based on real time and historical data, a technical plant manager should inform the operators of any fault which occurs or even take independent measures to rectify it. In this context, suitable models are developed and applied to a 1 MW power plant where a SCADA, Supervisory Control And Data Acquisition, has been installed and operational data are available on a Web page. In order to evaluate the performance of the PV system, firstly the daily corrected Performance ratio has been evaluated. Then, different approaches to estimate the AC and the DC power of the PV plant have been developed. Basing on the difference between the measured and the estimated power, a statistical approach is proposed; it allows to define suitable thresholds on the AC and DC power in order to individuate a fault when occurs. The experimental results show the effectiveness of the proposed approach.