The Design And Application Analysis Of Reward-penalty Functions For Zero Energy Buildings

Meeting the rising energy demand and limiting its environmental impact are the two intertwined issues faced in the 21 st century.Governments in different countries have been engaged in developing regulations and related policies to encourage environment friendly renewable energy generation along with energy,conservation strategies and technological innovations.This paper reviews the development of sustainable energy policies at home and abroad,provides an overview of sustainable energy policies promoting renewable energy,and surveys articles aimed at promoting the development of renewable energy policies and their models.On the basis of literature survey and building energy consumption as the basic data,a reward-penalty mechanism of annual,monthly and daily assessment methods is established,different forms of reward-penalty function models are constructed,and the influence of different factors on the total building cost is analyzed.In addition,this paper also considers the development prospects of zero energy buildings under incentive policies,and analyzes the results through investigation and research on the choice behavior of building users to further promote the development of zero energy buildings.The result shows:(1)Research on reward-penalty function based on annual energy consumption data.When the reward-penalty function is introduced,the three schemes of S1,S2 and S3 in the models can all enable building users to obtain rewards when the zero energy consumption level is 1.0.The minimum value of the total building cost obtained under the three schemes in Model 1 is $453.8,$333.6,and $93.1,in Model 2 is$399.0,$528.9,$432.9,and in the model 3,which are $248.5,$262.3,and $0.0respectively.Through comparison,it can be seen that the economic benefits of the building under Model 3 are the best.(2)Research on reward-penalty function based on monthly energy consumption data.When the zero energy level of the building is 1.0,under the S1 in January,the total building costs before and after model optimization are $70.9 and $83.3.Under the S2,the corresponding total building costs are $70.9 and $83.3.In April under the S1,the total building costs before and after model optimization are $48.7 and $38.8.Under the S2,the corresponding total building costs are $48.7 and $38.8.In July,under the S1,the total building costs before and after model optimization are $61.7and $64.8.Under the S1,the corresponding total building costs were $52.6 and $46.7before and after model optimization.Under the S2,the corresponding total building costs were $52.6 and $46.7.By analyzing the building cost before and after model optimization,it can be seen that after model optimization,the construction received the most significant effect in April and October.(3)Research on reward-penalty function based on daily energy consumption data.High load freedom can reduce the annual energy consumption of buildings,reduce fines,and achieve better stability,and the average daily zero energy consumption level is around 1.0.In addition,four quadratic fit curves are obtained to describe the relationship between building performance and loading degrees of freedom.Through uncertainty analysis,in case 1,the average annual energy consumption of the building,the daily zero energy consumption level,the stability and the annual penalty are 4643 k Wh/a,1.0,0.35 and 96 $/a,respectively.In case 2,the building’s average annual energy consumption,daily zero energy consumption level,stability and annual penalty are 4629 k Wh/a,1.01,0.12 and 4 $/a,respectively.(4)Analysis of the development prospects of zero energy buildings under incentive policies.Design the content of the questionnaire,collects data,and then conducts online SPSS analysis on the questionnaire data,derives the design formula of the regression analysis model,and the results of the prediction accuracy through the model,indicating that the incentive policy affects the development of zero energy buildings.