Measuring and modelling the influence of weather factors on CSP reflector soiling

[摘要] ENGLISH ABSTRACT: South Africa is among the countries with a plan to reduce GHG emissions of up to34% by 2020 through investment in renewable energy in order to reduce its base loadcoal generation. High solar resource and the potential of concentrated solar power(CSP) to address the challenges facing other solar technologies have attracted CSPinvestment in the country. CSP uses reflector surfaces or mirrors to focus low solarenergy radiation from a large field into a small area of high energy concentration.In their working conditions, CSP reflector surfaces are subjected to harsh outdoorenvironments which drastically degrade their performance. The main objective ofthe study was to develop and test reflector optical degradation measurement deviceand use these optical degradation measurements from the device to relate opticallosses caused by soiling to weather.A reflector optical degradation assessment device termed as real-time cleanlinessmonitoring sensor (RCMS) was designed, developed and tested for its ability tomeasure soiling optical degradation. The device was then utilised to relate weatherconditions with optical losses caused by soiling on CSP reflectors. Furthermore, aneural network model was developed to simultaneously relate various weather factorsto the optical loss caused by soiling on CSP reflectors. Error analysis and calibrationwere undertaken for RCMS measurement in order to improve confidence in thedata, which was further used in experimental analysis. Two experimental analyseswere carried out. The results from the first experimental analysis showed only thevariation of cleanliness with weather factors that directly influence the rate of soiling.Wind speed and humidity were observed to degrade cleanliness, while rain leadto reflector cleaning. In the second experimental analysis, factors that directly orindirectly influence cleanliness were statistically analysed using clustering method.The results showed that temperature and direct normal irradiation (DNI) correlaterelatively well with cleanliness although they do not directly influence it. The neural network model demonstrated that a combination of weather factors could be used toestimate the optical degradation caused by soiling on CSP reflectors. High coefficientof determination was observed from the neural network model results, as comparedto the correlations that considered the relationship between cleanliness and a singleweather factor, done in the experimental analysis.

[发布机构] Stellenbosch University