Papers by Ralph Gottschalg
Outdoor performance of anti-soiling coatings in various climates of Saudi Arabia
Solar Energy Materials and Solar Cells, 2022
光起電力素子の圧縮センシング電流マッピング空間特性化【Powered by NICT】
IEEE Journal of Photovoltaics, 2017
Renewable Energy, Apr 1, 2019
This paper uses site suitability analysis to identify locations for solar farms in the UK to help... more This paper uses site suitability analysis to identify locations for solar farms in the UK to help meet climate change targets. A set of maps, each representing a given suitability criterion, is created with geographical information systems (GIS) software. These are combined to give a Boolean map of areas which are appropriate for large-scale solar farm installation. Several scenarios are investigated by varying the criteria, which include geographical (land use) factors, solar energy resource and electrical distribution network constraints. Some are dictated by the physical and technical requirements of large-scale solar construction, and some by government or distribution network operator (DNO) policy. It is found that any suitability map which does not heed planning permission and grid constraints will overstate potential solar farm area by up to 97%. This research finds sufficient suitable land to meet Future Energy Scenarios (UK National Grid outlines for the coming energy landscape).
Evaluation of uncertainty sources and propagation from irradiance sensors to PV yield
This work quantifies the uncertainties of a pyranometer. Sensitivity to errors is analysed regard... more This work quantifies the uncertainties of a pyranometer. Sensitivity to errors is analysed regarding the effects generated by adopting different time resolutions. Estimation of irradiance measurand and error is extended throughout an annual data set. This study represents an attempt to provide a more exhaustive overview of both systematic (i.e. physical) and random uncertainties in the evaluation of pyranometer measurements. Starting from expanded uncertainty in a monitored pyranometer, the study concludes with an evaluation of its impact on the estimation uncertainty in the performance of a photovoltaics (PV) solar farm.
Training the Next Generation of PV Reliability Experts – New Marie-Sklodowska Curie (MSCA) Project SOLAR-TRAIN
33rd European Photovoltaic Solar Energy Conference and Exhibition, Nov 8, 2017
The service life estimation in the photovoltaic (PV) industry is yet in its infancy, requiring bo... more The service life estimation in the photovoltaic (PV) industry is yet in its infancy, requiring both underpinning science and trained personnel to reduce costs of energy. An unmet industrial requirement is an accelerated and operating environment specific, service life time and energy yield assessment. SOLAR-TRAIN qualifies early stage researchers (ESRs) in the field of PV durability as part of a highly innovative, multi-disciplinary project meeting industry requirements. The research objective is to develop novel and validated models for the service life time and energy prediction of PV modules and systems. The elements to this puzzle are researched in the frame of 14 PhD projects with individual areas of focus, ranging from investigations on climatic degradation factors, through to research on material level, simulations and modelling of energy yield and life time. The research projects are enhanced by an innovative training scheme in close cooperation with industry. This inter-sectoral approach provides excellent theoretical and technical background as well as immersion in different business sectors and career mentoring.
Evaluation of uncertainty sources and propagation from irradiance sensors to PV energy production
This work quantifies the uncertainties of a pyranometer. Sensitivity to errors is analysed regard... more This work quantifies the uncertainties of a pyranometer. Sensitivity to errors is analysed regarding the effects generated by adopting different time resolutions. Estimation of irradiance measurand and error is extended throughout an annual data set. This study represents an attempt to provide a more exhaustive overview of both systematic (i.e. physical) and random uncertainties in the evaluation of pyranometer measurements. Starting from expanded uncertainty in a monitored pyranometer, the study concludes with an evaluation of its impact on the estimation uncertainty in the performance of a photovoltaics (PV) solar farm.
PVデバイスのエレクトロルミネセンスイメージング:カメラキャリブレーションと画像補正【Powered by NICT】
IEEE Conference Proceedings, 2016
Space and time analysis of irradiation variation across the UK: A 10 year study of solar farm yield
This research offers an understanding of year-to-year and area-to-area variability of PV performa... more This research offers an understanding of year-to-year and area-to-area variability of PV performance, measured in terms of specific yield (kWh/KWp). This information will assist in grid management.
32nd European Photovoltaic Solar Energy Conference and Exhibition, 2016
The development of adhesive and cohesive failures at the EVA-backsheet interface under different ... more The development of adhesive and cohesive failures at the EVA-backsheet interface under different damp-heat (DH) testing condition is investigated in this paper. The adhesive and cohesive failures are classified by the surface roughness of the peeled off backsheet strips. Different DH testing condition leads to different dominating failure modes. The adhesive failure is the main failure mode at lower testing temperature, which has been masked by the mixed failure mode at the higher testing temperatures due to the different temperature acceleration factor of the two processes. Development of accelerated environmental testing protocol requires the failure mode analysis to ensure the target failure mode or degradation mechanism is accelerated and not masked by any other processes.
Propagation of measurement uncertainties in mismatch factor correction for photovoltaic device calibration
World Conference on Photovoltaic Energy Conversion, 2014
The mismatch factor uncertainty is one of the major uncertainty contributors in calibration measu... more The mismatch factor uncertainty is one of the major uncertainty contributors in calibration measurements, especially for thin film devices, and the most complex to calculate analytically due to underlying correlations in uncertainty. Typically, empirical estimates or Monte Carlo simulations based on wavelength dependent uncertainty analysis are used and sampling is conducted by random walks. A different sampling approach is proposed based on fitting a sum of Gaussian distributions to measurement data and generating spectral response curves within the uncertainty envelope by altering the fitting parameters. The generated curves are smooth and approximate real measurement data. Presently, the sampling method is limited to SRs.
A fast and effective model for the computation of solar energy potential in complex shading envir... more A fast and effective model for the computation of solar energy potential in complex shading environments is presented. Accurate calculation and identification of solar energy potential profiles is demonstrated over large areas. Calculation time is exceptionally fast, even on an average specification PC (typically under 1 min per 1 km 2). Problems with commonly used low-resolution sky domes that can lead to irradiance calculation errors of ~5% are identified. Ideal placements are easily visually identified from resultant irradiance/irradiation profile images. Image processing techniques for spatially distributed optimization problems are described and an example of energy value optimization is presented by means of individual dwelling demand separation & comparison.
Assessment of PV system performance with incomplete monitoring data
An analysis of PV system performance requires both meteorological and electrical data for the ass... more An analysis of PV system performance requires both meteorological and electrical data for the assessment period. However, actual in-field data acquisition is rarely 100%, often resulting in a significant amount of incomplete data sets for performance assessment. These gaps, if not taken into account, may add noticeable bias in yield assessment and thus estimations of the lacking data need to be made. An approach of back-filling the required data is given and validated here. Three different categories of data loss are identified and case-specific methods of synthesising missing data are developed. The integrity of the performance assessment process is assessed. The three cases of data loss are defined as: missing meteorological data only, missing electrical monitoring data only and missing both electrical and meteorological data. Case-specific methods are proposed and their performance against measured data is evaluated statistically by means of: root mean square error (RMSE), mean absolute error (MAE) and mean bias error (MBE). The inferred monthly performance ratio on two of the selected cases showed accurate agreement against measured data presenting significantly low MBE values, equal or less than -0.01.
Detection of Roof Shading for PV Based on Lidar Data Using a Multi-Modal Approach
31st European Photovoltaic Solar Energy Conference and Exhibition, 2015
There is a current drive to increase rooftop deployment of PV. Suitable roofs need to be located,... more There is a current drive to increase rooftop deployment of PV. Suitable roofs need to be located, especially as regards shading. A shadow cast on one small section of a solar panel can disproportionately undermine output of the entire system. Nevertheless, few shading figures are available to researchers and developers. This paper reviews and categorizes a number of methods of determining shade losses on photovoltaic systems. Two existing methods are tested on case study areas: shadow simulation from buildings and ambient occlusion. The first is conceptually simple and was found to be useful where data is limited. The second is slightly more demanding in terms of data input and mathematical models. It produces attractive shadow maps but is intended for speed and represents an approximation to ray-tracing. Accordingly, a new model was developed which is fast, flexible and accurately models solar radiation.
ASPIRE - a tool to investigate spectral effects on PV device performance
World Conference on Photovoltaic Energy Conversion, May 18, 2003
ABSTRACT
Revista Brasileira de Energia Solar, Apr 3, 2023
Smart PV Module Batch Testing: Reduction of Performance Measurment Uncertainty by Up to 50%
33rd European Photovoltaic Solar Energy Conference and Exhibition, Nov 8, 2017
Measurement uncertainty may bias verification measurements for PV systems, e.g. delivered DC capa... more Measurement uncertainty may bias verification measurements for PV systems, e.g. delivered DC capacity for a PV power plant or establishing warranty claims. The problem is present when evaluating modules both on site in a PV plant and in a laboratory. This becomes quite critical if the module's STC performance is borderline in terms of compliance with stated/expected power levels as minimum acceptable power levels are minimum power minus measurement uncertainty. The measurement uncertainty equates directly to a financial risk in the due diligence of larger plants. This is even more obvious as PV module prices have fallen by 30% in 2016 alone. The cost of capital plays an increasingly important role in the overall systems' cost and is strongly affected by the perceived risk. To reduce this risk of false DC rating, for large enough projects – typically in the range of several MW, a batch of modules is tested to confirm DC baseline performance. Typical measurement uncertainties are from 2.5% to 3% with 95% confidence for crystalline PV modules. This contribution presents an approach to nearly halve the uncertainty in the measurement of batches of modules compared to the uncertainty of a single laboratory. This is achieved via measuring a sub-sample of these modules by two additional laboratories with different traceability chains. A GUM-compliant uncertainty analysis is presented for this approach and an example is given for the three measurement laboratories involved in this work. These laboratories have measurement uncertainties (k=2) in the range of 2.5-3% and the resulting uncertainty is less than 1.5%. The presented approach is a cost-effective method to verify large numbers of modules in field tests with very low uncertainty, which is comparable to expensive high precision individual PV module measurements.
PV Camper: Colaboração Internacional Para Avanços Na Pesquisa Multiclimática Em Energia Solar Fotovoltaica
The impact of acetic acid corrosion on the front-side contacts and the finger electrodes of c-Si PV cells
Damp-heat stresses typically lead to corrosion related degradation for Ethylene-vinyl acetate (EV... more Damp-heat stresses typically lead to corrosion related degradation for Ethylene-vinyl acetate (EVA) encapsulated PV modules. The degraded module appears as bright areas along the busbars in electroluminescence (EL) images. The most likely mechanism that causes these bright areas is corrosion at the silver contacts and the finger electrodes at the front surface of the cell, due to acetic acid accumulation. In this work, these mechanisms are investigated by immersion of half encapsulated cells into acetic acid solutions with different concentrations. Dark and light I-V curve measurements and electroluminescence images were conducted during the course of ageing to investigate the power degradation. The chemical changes in materials are identified by optical microscopy images and SEM-EDX analysis.
Remote monitoring and failure detection for distributed small-scale PV systems
An automatic failure detection procedure for distributed small scale photovoltaic (PV) systems is... more An automatic failure detection procedure for distributed small scale photovoltaic (PV) systems is presented. The procedure is based on a few input parameters where only energy output is available and irradiance and temperature are derived from a network of ground based meteorological stations. The employed PV system model is described and the fault detection is demonstrated for three cases in Nottingham. Shading is identified as the most common factor of underperformance, and wrongly declared systems are also detected and corrected, whereby the strengths and limitations of remote monitoring are discussed.
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Papers by Ralph Gottschalg