Study On Load Characteristics Of Typical Family Shenzhen

With the economic development rapidly, China’s total energy consumption is alsogrowing rapidly. Now China’s total energy consumption second only to the UnitedStates, the form is not optimistic. In energy consumption, construction and consumptionincreased year by year, residential building energy consumption60%of the totalbuilding energy consumption. Many factors that affect building energy consumption isclosely related with people’s habits.This paper has conducted an investigation to Shenzhen households. We recovered580valid questionnaires. Research content more comprehensive, including basicinformation on family、lifestyle、expectations to the indoor environmental assessmentand detailed energy consumption information. And we carried out a detailed descriptionof the information. We carried out with SPSS software partial correlation analysis,regression analysis and ridge regression based on the information of the questionnaire.Partial correlation analysis revealed: family income、family size、the number ofbuilding area、and the number of air conditioning have significant impact on annualelectricity consumption. Per unit area of electricity consumption was significantlynegatively correlated with the housing area. Family size and annual household incomehave significant impact on per unit area electricity consumption. Per capita of electricityconsumption was significantly negatively correlated with family size. Family incomeand the housing area have significant impact on per capita of electricity consumption.Other factors,for example building ’s completion、the number of types of housing andair conditioning had no significant effect.Regression analysis showed that: For household electricity consumption, sorting isfamily size>housing area>revenue>Air Conditioning number>completed years> Typeof Housing; For power consumption per unit area, sorting is housing area> familysize>revenue>Air Conditioning number>completed years>type of housing; Annual percapita electricity consumption sorting is family size>revenue>housing area>AirConditioning number>completed years> type houses.Ridge regression analysis showed: when K=10, sorting is housing area> familysize> Air Conditioning number> average annual per capita income. But K values islarge, it reflected been a linear relationship between the factors, but not a serious linearrelationship. This paper selected four typical households for analysis. We analysis annual powerconsumption、 per unit area of power consumption and per capita electricityconsumption about the four typical families, and we analysis everyone in the family ’sliving habits. We test the rules of operating equipment, understand the variation of theload in a day. We found that each time the power is not the same in different family. Thepeak load occurs there is a common feature is that during the cooking andair-conditioning turned on at night time, the duration of the evening peak airconditioning long open time. Factors affecting electricity consumption by householdstests found that the main factors affecting the air conditioning energy consumption forair conditioning turned on the number, several families where large differences in powerconsumption is not air-conditioned, but the home consumption of other commonly usedequipment, other consumption electric power consumption equipment have a greatrelationship with people’s living habits.This paper also predicted Shenzhen household energy loads from a few questionsin the questionnaire and the measured angle, then proposed energy consumption trends.