Impact of Component Reliability on Large Scale Photovoltaic Systems' Performance

In this work, the impact of component reliability on large scale photovoltaic (PV) systems’ performance is demonstrated. The analysis is largely based on an extensive field-derived dataset of failure rates of operation ranging from three to five years, derived from different large-scale PV systems. Major system components, such as transformers, are also included, which are shown to have a significant impact on the overall energy lost due to failures. A Fault Tree Analysis (FTA) is used to estimate the impact on reliability and availability for two inverter configurations. A Failure Mode and Effects Analysis (FMEA) is employed to rank failures in different subsystems with regards to occurrence and severity. Estimation of energy losses (EL) is realised based on actual failure probabilities. It is found that the key contributions to reduced energy yield are the extended repair periods of the transformer and the inverter. The very small number of transformer issues (less than 1%) causes disproportionate EL due to the long lead times for a replacement device. Transformer and inverter issues account for about 2/3 of total EL in large scale PV systems (LSPVSs). An optimised monitoring strategy is proposed in order to reduce repair times for the transformer and its contribution to EL

The UK Solar Farm Fleet: A Challenge for the National Grid? †

This is an Open Access Article. It is published by MDPI under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/Currently, in the UK, it is widely believed that supply from renewable energy sources is capable of reaching proportions too great for the transmission system. This research investigates this topic objectively by offering an understanding of year-to-year and area-to-area variability of PV (photovoltaic) performance, measured in terms of specific yield (kWh/kWp). The dataset is created using publicly available data that gives an indication of impact on the grid. The daily and seasonal variance is determined, demonstrating a surprisingly good energy yield in April (second only to August). The geographic divergence of generation from large scale solar systems is studied for various sized regions. Generation is compared to demand. Timing of output is analyzed and probability of achieving peak output ascertained. Output and demand are not well matched, as regards location. Nevertheless, the existing grid infrastructure is shown to have sufficient capacity to handle electricity flow from large scale PV. Full nameplate capacity is never reached by the examples studied. Although little information is available about oversizing of array-to-inverter ratios, this is considered unlikely to be a major contributor to grid instability. It is determined that output from UK solar farms currently presents scant danger to grid stability

The UK Solar Farm Fleet: A Challenge for the National Grid? †

Currently, in the UK, it is widely believed that supply from renewable energy sources is capable of reaching proportions too great for the transmission system. This research investigates this topic objectively by offering an understanding of year-to-year and area-to-area variability of PV (photovoltaic) performance, measured in terms of specific yield (kWh/kWp). The dataset is created using publicly available data that gives an indication of impact on the grid. The daily and seasonal variance is determined, demonstrating a surprisingly good energy yield in April (second only to August). The geographic divergence of generation from large scale solar systems is studied for various sized regions. Generation is compared to demand. Timing of output is analyzed and probability of achieving peak output ascertained. Output and demand are not well matched, as regards location. Nevertheless, the existing grid infrastructure is shown to have sufficient capacity to handle electricity flow from large scale PV. Full nameplate capacity is never reached by the examples studied. Although little information is available about oversizing of array-to-inverter ratios, this is considered unlikely to be a major contributor to grid instability. It is determined that output from UK solar farms currently presents scant danger to grid stability

Inference of missing data in photovoltaic monitoring datasets

This is an Open Access Article. It is published by IET publishing under the Creative Commons Attribution 3.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/3.0/Photovoltaic (PV) systems are frequently covered by performance guarantees, which are often based on attaining a certain performance ratio (PR). Climatic and electrical data are collected on site to verify that these guarantees are met or that the systems are working well. However, in-field data acquisition commonly suffers from data loss, sometimes for prolonged periods of time, making this assessment impossible or at the very best introducing significant uncertainties. This study presents a method to mitigate this issue based on back-filling missing data. Typical cases of data loss are considered and a method to infer this is presented and validated. Synthetic performance data is generated based on interpolated environmental data and a trained empirical electrical model. A case study is subsequently used to validate the method. Accuracy of the approach is examined by creating artificial data loss in two closely monitored PV modules. A missing month of energy readings has been replenished, reproducing PR with an average daily and monthly mean bias error of about −1 and −0.02%, respectively, for a crystalline silicon module. The PR is a key property which is required for the warranty verification, and the proposed method yields reliable results in order to achieve this