Research on the efficiency ofCleanEnergyuseinfourStatesoftheUnitedStates

:In this paper, we use regression analysis, comprehensiveevaluation and regression prediction to build up several models,which have showed historical energy structures and futureenergy consumption in each state. And then we use make aoptimal programming model to get the energy consumptionstructures of each state under the best target. Finally, we give ourfeasible policy measures in order to meet their new four-stateenergy compact.

Energy is a serious problem in today's world, which isclosely related to the sustainable development of all mankindand to the fundamental interests of each country. Today, theworld still operates on the basis of three traditional fossilfuels, coal, oil and natural gas, but faced with the scarcity,non-renewable, strong political color and the devastatingblow caused by the depletion of fossil fuels, human beingshave begun to realize the necessity and urgency of developingalternative energysources since lastcentury.

The United States is one of the most advanced countriesin the world for clean energy development and utilizationof renewable energy. As the largest oil consumption and oilimporting country, After the impact of the two oil crisisin 1970s, the U.S . government has begun to attach greatimportance to the development of renewable energy, introduceda number of laws, regulations and policy measures to supportand encourage the development of clean energy.In the United States, many aspects of energy policy aredecentralized to the State level. Additionally, the varyinggeographies and industries of different States affect energyusage and production. In 1970, 12 western States in the U.S.formed the Western InterState Energy Compact, whose missionfocused on fostering cooperation between these States for thedevelopment and management of nuclear energy technologies.An interState compact is a contractual arrangement madebetween two or more States in which these States agree ona specific policy issue and either adopt a set of standards orcooperate with one another on a particular regional or nationalmatter.

II Research Purpose

Along the U.S. border with Mexico, there are four States –California (CA), Arizona(AZ), New Mexico (NM), and Texas (TX)– that wish to form a realistic new energy compact focusedon increased usage of cleaner, renewable energy sources. Thisarticle has finished this problem bythe four governors of these States toperform data analysis and modeling togive the way to develop clean energy.III Basic AssumptionsIgnore the influence of the abnormaland missing values in the original dataon the analysis results.Each State has the same price forthe same energy at the same time.In question B of the first part, weonly consider the impact of populationand economy on the similarities anddifferences in energy developmentbetween States.

IV Make Energy Profiles

(1) AnalysisApproach

This problem requires us to use thedata provided, create an energy profilefor each of the four States, and themain problem is the energy allocationof the States. In order to solve the firstproblem, we first sift and summarizethe data, then classify the selected data,and get the energy ratio of four Statesby classifying and summarizing.

(2) EnergyProfile

First of all, after analyzing thevariables in the dataset, we find thatthe end letters of each variable nameare different, and the unit of variablesis different, that is, the last letterrepresents the unit of measurementof each variable. At the same time,the difference in the third letter ofeach var i ab le de te r mi ne s the useand other energy. Clean energy includeswind energy, natural gas and nuclearfuel. Solid energy includes coal coke,petrochemical feedstock, and petroleumcoke, wood and waste. Liquid energyincludes aviation gasoline, asphaltand road oil, distillate fuel oil, fuelethanol, kerosene, LPG, motor gasolineand lubricant. Other energy includeselectricity and residual fuel oil. Then weuse the time series data of the variablesto get the energy trends from 1970 to2009, and find out the total energyexpenditure data for 2009.According tothe previous classification, and sumup the total expenditure of each kind ofenergy, get the total expenditure dataof each kind of classification, and thenget the energy ratio. According to thismethod, we can analogize the energyratio of different years.The State's energy configuration isshown in the table below:Table1 State's energy configurationStateEnergy

regression model：

Independent variables must have asignificant effect on dependent variablesand havea closelinearcorrelation.Independent variables shouldhave complete statistical data andtheir predicted values can be easilydetermined.Data processing: Because of thelack of data during the decade 1960-1970, we preprocessed the data andscreened out the data for the period1970-2009 from six variables: GDP,population, solid energy, liquid, cleanenergy and other sources of energy.Considering the selection criteria ofindependent variables, we regard GDPas dependent variables and the rest asindependent variables.(2) The construction of the modelThe multivariate linear regressionmodel is:y=a1x1+a2x2+a3x3+……+anxnw he r ea 1、a 2、a 3…… a n a r e a llunknown parameter independent ofx1 、x2 、x3……xn . a1 、a2 、a3……an areregression coefficients.According to the classification ofquestion 1, we analyze the data furtherand study the evolution of State energyin time series.We establish multiple regressionmodels, take GDP as dependent variable; pop ulation, solid energy , liquidenergy, clean energy, other sources ofenergy as independent variablesx 、x 、and consumption of each variable.1 2x3……xnTherefore, we can draw the conclusionthat the same energy source may The time series data of the energy,po p u l a t i o n and GDP of AZ Sta tecomposed of many different variables, 4000 Liquid 50000 Liquid from 1970 to 2009 are fitted by using2000 Energy Energyeach of which describes the use ofenergy from different sectors and0 SoildEnergy0 SoildEnergyEviews software. On the basis,we setup the coefficient table of the energyunits of measurement. For subsequentstatistical analysis, we select variablesthat represent the consumption of thetotal energy sector. And then we unifythe unit of measurement of energy, andwe choose million dollars as the unitof measurement. In this way, we havecompleted the selection of variables,that is, the variables representing thetotal sector expenditure of 17 kinds ofenergy.Secondly, we classify the selected17 energy sources according to cleanenergy, solid energy, liquid energyState energy trends from1970 to 2009and energy allocation by State in 2009are shown below：State EnergyV Problem 2 Multiple LinearRegression Model(1) The preparation for the modelSelection of independent variables:In order to ensure that the regressionmodel has good interpretation abilityand prediction effect, the selectionof independent variables should payattent ion to the follow ing pointswhen establishing multivariate lineardevelopment of each State accordingto the coefficients of the independentvariables of each regression equation,a nd c om p a r e t he si m i l a r it y a nddifference of each State by the coefficienttable.