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Research on the Prediction of Solar Energy Generation based on Measured Environmental Data
Guojing Zhang,Xiaoying Wang,Zhihui Du 보안공학연구지원센터 2015 International Journal of u- and e- Service, Scienc Vol.8 No.5
As a kind of renewable energy, solar power becomes more and more widely used as the power supply for large-scale datacenters to save the brown energy consumption and to reduce the overall cost. The prediction accuracy of solar energy generation becomes a fundamental issue in the research of how to efficiently manage the renewable energy resources. This paper explores the possible ways to predict the solar radiation intensity based on the assumption that it impacts the solar power generation proportionally. Through the analysis and research of photovoltaic power generation system, we explore the influence factors for solar radiation intensity, establish a relationship of solar radiation intensity and ambient temperature, time, humidity, wind speed in the forecasting model, and finally established the multivariate linear regression model and artificial neural network model. According to the two models, the environmental monitoring data measured at the Qinghai University are employed as the basis of the prediction of solar radiation intensity, and compared with the actual measurement data monitoring system. Experimental results show that, by using the BP neural network prediction model, the achieved accuracy is higher than other empirical model. The prediction method and good results provide a necessary foundation for future related research based on solar radiation values forecasts.
Shui Wang,Guojing Zhao,Yizhen Du,Yixin Qu 한국화학공학회 2015 Korean Journal of Chemical Engineering Vol.32 No.6
A new multistage countercurrent melt crystallizer with sieve plates is proposed that combines the advantages of the TNO column crystallizer and the inclined column crystallizer. With the naphthalene-indene solid solution system, the purification process of organic materials in the new multistage countercurrent melt crystallizer with sieve plates under total reflux was investigated. Two of the influencing factors on the separation and purification performance in the new multistage countercurrent melt crystallizer with sieve plates were crystal settling velocity and crystal breakage, which were controlled by stirring speed, the sieve plates, the angle of the sieve plates, the diameter of the pores, particle sedimentation area, and the number of plates. The results of this study show that the optimum stirring speed was determined to be 20 rpm, sieve plates can obviously increase the separation and purification effect, the optimum angle of the sieve plates was determined to be 45o, the optimum diameter of the pores was determined to be 8 mm, the optimum particle sedimentation area was determined to be 0.5 r, and two plates in the crystallizer were shown to be the best.
Jianjing Ma,Guojing Wang,Yongsheng Xing 대한수학회 2019 대한수학회보 Vol.56 No.6
This paper analyzes a robust optimal reinsurance and investment strategy for an Ambiguity-Averse Insurer (AAI), who worries about model misspecification and insists on seeking robust optimal strategies. The AAI's surplus process is assumed to follow a jump-diffusion model, and he is allowed to purchase proportional reinsurance or acquire new business, meanwhile invest his surplus in a risk-free asset and a risky-asset, whose price is described by an Ornstein-Uhlenbeck process. Under the criterion for maximizing the expected exponential utility of terminal wealth, robust optimal strategy and value function are derived by applying the stochastic dynamic programming approach. Serval numerical examples are given to illustrate the impact of model parameters on the robust optimal strategies and the loss utility function from ignoring the model uncertainty.
Ma, Jianjing,Wang, Guojing,Xing, Yongsheng Korean Mathematical Society 2019 대한수학회보 Vol.56 No.6
This paper analyzes a robust optimal reinsurance and investment strategy for an Ambiguity-Averse Insurer (AAI), who worries about model misspecification and insists on seeking robust optimal strategies. The AAI's surplus process is assumed to follow a jump-diffusion model, and he is allowed to purchase proportional reinsurance or acquire new business, meanwhile invest his surplus in a risk-free asset and a risky-asset, whose price is described by an Ornstein-Uhlenbeck process. Under the criterion for maximizing the expected exponential utility of terminal wealth, robust optimal strategy and value function are derived by applying the stochastic dynamic programming approach. Serval numerical examples are given to illustrate the impact of model parameters on the robust optimal strategies and the loss utility function from ignoring the model uncertainty.