Simulation of Daily Diffuse Solar Radiation Based on Three Machine Learning Models

Solar radiation is an important parameter in the fields of computer modeling,engineering technology and energy development.This paper evaluated the ability of three machine learning models,i.e.,Extreme Gradient Boosting(XGBoost),Support Vector Machine(SVM)and Multivariate Adaptive Regression Splines(MARS),to estimate the daily diffuse solar radiation(Rd).The regular meteorological data of 1966-2015 at five stations in China were taken as the input parameters(including mean average temperature(Ta),theoretical sunshine duration(N),actual sunshine duration(n),daily average air relative humidity(RH),and extra-terrestrial solar radiation(Ra)).And their estimation accuracies were subjected to comparative analysis.The three models were first trained using meteorological data from 1966 to 2000.Then,the 2001-2015 data was used to test the trained machine learning model.The results show that the XGBoost had better accuracy than the other two models in coefficient of determination(R2),root mean square error(RMSE),mean bias error(MBE)and normalized root mean square error(NRMSE).The MARS performed better in the training phase than the testing phase,but became less accurate in the testing phase,with the R2 value falling by 2.7-16.9%on average.By contrast,the R2 values of SVM and XGBoost increased by 2.9-12.2%and 1.9-14.3%,respectively.Despite trailing slightly behind the SVM at the Beijing station,the XGBoost showed good performance at the rest of the stations in the two phases.In the training phase,the accuracy growth is small but observable.In addition,the XGBoost had a slightly lower RMSE than the SVM,a signal of its edge in stability.Therefore,the three machine learning models can estimate the daily Rd based on local inputs and the XGBoost stands out for its excellent performance and stability.

Prediction of the Diffuse Solar Energy on Horizontal at Different Selected Locations

The main objective of this paper is to predict the diffuse solar energy on a horizontal surface by using data of global solar energy (H) and diffuse solar energy (Hd) at different selected geographical locations in Saudi Arabia during the period time from 1980 to 2019. The low values of the root mean square error RMSE for all correlations indicated a good agreement between the measured and calculated values of Hd. The negative values of mean percentage error MPE % for all models show that for all locations, the proposed correlations slightly overestimate Hd, and the absolute values of MPE never reach 1.35%. The first, second and third order correlations between the diffuse solar fraction Hd/H and the clearness index Kt and between the diffuse transmittance Hd/H0 and the sunshine hours have been proposed for the selected locations using the method of regression analysis. The differences between the measured and calculated values of Hd show that a first order correlation between Hd/H and Kt can be used for estimating Hd at the present locations with good accuracy. However, second order correlations between Hd/H or Hd/H0 and S/So are recommended for estimating Hd at these locations. The average annual differences between measured and calculated values of diffuse solar energy Hd on horizontal at selected sites in the present research are discussed.

Study on the evaluation method of diffuse radiation models——taking 5 typical cities in China as examples

Diffuse solar radiation models play an extremely important role in solar photothermal utilization,resource assess-ment and energy consumption simulation,etc.The accuracy of these diffuse solar radiation models usually need to be evaluated by various statistical parameters.Among these statistical parameters,the Global Performance In-dex(GPI)has been extensively employed in recent years because of its comprehensiveness and wide applicability.This paper takes five cities in China as representatives of 5 typical climate regions,and 12 solar scattered radia-tion models are fitted with the meteorological data of 5 cities.Based on the comparative analysis of the existing GPI calculation methods,this paper points out that there are some defects in the existing GPI,and modifies the existing GPI based on the comprehensive consideration of statistical parameters,normalization preprocessing of statistical parameters,unified evaluation direction of parameters,weight redistribution of statistical parameters,and adjustment of extreme coefficient.12 types of new GPI are established in this paper,and the performance of diffuse solar radiation models are compared based on these GPI.The rationality of GPI corrective measures is analyzed by means of the method reasonable index(MRI).The results show that the GPI calculation method(N10)which takes five corrective measures has the best performance,and the accuracy of the existing GPI can be improved by 13.33 to 65%.

Research exploring greenhouse environment control over the last 50 years

Environments do not exist in isolation.Their main components in greenhouse systems are plants.Without consideration of plants,analysis of greenhouse environments and environmental control of greenhouses can be accomplished,although it is not simple to achieve.Initial attempts were undertaken to analyze greenhouse environments and then reproduce them.Ventilation rate effects on plant photosynthesis in a growth chamber were reported in 1966.Computer simulations then became a main subject of research.The first dynamic computer simulation of a greenhouse environment including plants was published in 1971.According to innovations of computer technology,the use of minicomputers and microcomputers spread in many areas.By measuring the net photosynthesis of lettuce plants grown under artificial lighting,air temperature was optimized using a minicomputer with the hill-climbing method.The method was designated as the Speaking Plant Approach to environment control(SPA).After the author developed the first reported environmental control system in Japan,systems using microcomputers spread widely for greenhouse environmental control.Knowledge-based expert systems were tested for plant management.Also,a machine vision system was developed to detect critical moments for watering of muskmelon plants.The first feed-forward control method for greenhouses with a large heat mass was reported.Then space farming was tested in 1996 to assess gravity effects on plants.Energy-saving aspects such as solar sterilization,ground heat storage system,and storage using phase change material(PCM)have been reported.Defects of ordinary solarimeters were reported in 2008 along with an approach to estimate evapotranspiration in a greenhouse without the effect of so-called cosine law.Later,this technique was expanded to estimate photosynthesis of the plant canopy in a greenhouse using newly developed sensor units.