A Study On The Relationship Between Industrial Structure Evolution And Changes In Electricity Consumption In Zhejiang Province

As the most important secondary energy, electricity is the driving force of economicdevelopment. To maintain a steady supply of electricity and the legitimate needs are ofhigh significance, whether it is for local governments or whole country. Since thereforming and opening up, industrial output value of Zhejiang accounted for an averageof43.96%of GDP, industrial electricity consumption accounted for more than75%oftotal social consumption.Zhejiang province has always been the big user of electricity,the whole provincial electricity consumption up to311.691billion kwh in2011. Large-scale electricity shortage occurred many times in recent years, the province’s economicproduction and people’s lives are seriously affected, Apart from imperfections on theelectric power system and power construction is lagging behind other issues, the energyefficiency of Zhejiang is not high and the unreasonable industrial structure is also themain reasons. This paper analyzes the relationship between the evolution of industrialstructure and the electricity consumption changes in Zhejiang, the main researchcontents contain several points:First of all, analyze the process of industrialization of Zhejiang, measure outindustrialized composite index of Zhejiang from1995to2011and then use the chart toshow the economic aggregate and electricity consumption in different stages. Indifferent stages, the total electricity consumption and the industrial electricityconsumption are of different characteristics. After that, we focus on Zhejiang industrialeconomic and its electricity consumption, compare relationship between the twovariables in1987-2011period time.In order to explain the relationshiop I take themethod of the Granger causality test, and found that there existed a long-termcointegration relationship between the two variables, and the industrial economydevelopment is the Granger cause of industrial electricity consumption, not vice versa.Then I selected annual output value of100billion in the year of2011over18industries,concluded that which one is of lower output and lower power efficiency, and it shouldbe the key industry to save electricity energy.Then, analyze the grey correlation between terminal power consumption inZhejiang Province with total electricity consumption. As we know, according to theChina Energy Statistical Yearbook, the terminal composed by industry, construction, residential, transportation and other seven terminals. After calculating, sort the sevengrey relational coefficient between1995and2011, and it means that the total electricityconsumption trend change relatively close to the corresponding power saving and itprovide a theoretical basis to restructure the industry. To Concluded, the order is,Industry， Construction， Transportation and warehousing postal industry，Household consumption，Other consumer terminals， Wholesale and retail trade andaccommodation and catering industry， Agriculture, forestry and Fishery and WaterConservancy.After calculating the grey correlation between total electricity consumption inZhejiang Province and related industry relationship, I found another important variablewhich affecting electricity consumption is electricity intensity.First of all, I measuredthe intensity of each year during the period from1995to2011and calculate the changebetween the adjacent two year. And then use the method of Logarithmic Mean DivisiaIndex to divide the change part into structural variables and power efficiency within theindustry. Eventually I found that the main factor which causes intensity to rise or fall isthe industrial electricity efficiency. In order to reduce the electricity intensity we shouldimprove the efficiency of electricity to energy-saving and optimized within theindustrial structure, improve high-tech content in each industry, and then improve theefficiency of electricity use.Last, I selected the factors which affect electricity consumption of Zhejiang province,including the total economic aggregate, electricity price, industrial structure, electricityefficiency and changes in population. Then establish the model of electricity needs ofZhejiang to predict the total consumption during "the12thFive-Year Plan" and "the13thFive-Year Plan "period. In this chapter I mainly use cointegration theory and short-termerror correction model. Finally found that the growth rate of electricity consumptiondecreased year by year, and lower than the growth rate of the total economy. Increasedenergy efficiency and electricity price can explain this.