Study On The User Load Period Division Of Typical Industries In Suzhou Area

Depend on the development of economy,upgrading and adjustment of industrial structure,in the summer high temperature period,peak load period is relatively intensive,power supply and demand situation is very tense,all regions have adopted various load management measures to guarantee the normal supply of electricity.In 2003,various provinces and cities in China began to implement the TOU(time-of-use)price policy in the user side,TOU price policy as an important means of power demand side management(Demand Side Management,DSM),therefore,it is necessary to respond to the situation according to the system load characteristics and user demand response for electricity under the new situation,and analysing deeply the load of power system,the investigation of TOU price policy which has been implemented whether can effectively play a guiding role in power consumption,and it is of great significance to improve the efficiency of the power allocation of resources,and also promote energy-saving emission reduction work.Firstly,the basic knowledge of power load characteristic analysis is studied.Based on the measured hourly load data of typical industry in Suzhou area,the characteristics and variation law of typical industry load in Suzhou area are obtained.The results show that the load characteristics of different industries vary greatly,for the typical day,the load peaks and valleys of the time period reflects the industry differences and seasonal differences.Taking five textile enterprises as an example,then study the demand response model,based on the re-division of the time period by using the fuzzy semi-gradient membership function and the response degree,the results show that there are 7 time points in textile enterprise A which are inconsistent with the current time plan,the coincidence degree is 71%,textile enterprise B,textile enterprise D and textile enterprise E have 12 time points which are inconsistent with the current time plan,and the coincidence degree with the current time plan is 50%,textile enterprise C has 17 time points and the current time program is inconsistent with the current program fit time is only 29.1%.Using electricity price elasticity of demand matrix model,with fuzzy clustering method and then divided on rush hour based on the original peak period,get the peak period of enterprise A is14:00 ~ 19:00;the peak period of enterprise B is 19:00 ~ 20:00;the peak period of enterprise C is 10:00~14:00;the peak period of enterprise D is 10:00~15:00;the peak period of enterprise E is 7:00~10:00,15:00~16:00.On the basis of the new time division,the typical daily load curve is optimized,the results show that the effect of adjusting load is different for five enterprises in the same period;for textile enterprises,B,in reducing the peak and valley of the enterprise,improve the load rate of enterprises in the new period of time the effect is better;for the other 4 companies,in accordance with the new period of time before and after the adjustment of the effect is far better than the current period of time to adjust the effect.