SOUTHEAST UNIVERSITY, NANJING, CHINA, MAY 15-16,2014. US-CHINA WORKSHOP:SMART GRID RESEARCH OPPORTUNITY IDENTIFICATION

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1 SOUTHEAST UNIVERSITY, NANJING, CHINA, MAY 15-16,2014. US-CHINA WORKSHOP:SMART GRID RESEARCH OPPORTUNITY IDENTIFICATION Prof. Ciwei Gao School of Electrical Engineering, Southeast University, Nanjing, P.R.China Tel ,

2 OUTLINE 1. Background 2. Framework 3. Progress 4. Conclusions Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 2

3 OUTLINE 1. Background 2. Framework 3. Progress 4. Conclusions Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 3

4 BACKGROUND WE SEE THEM EVERY WHERE~ Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 4

5 Background Air conditioning load accounts for load peak Air conditioning load becomes the major reason of peak load; Usually it accounts for 30% of the peak load; This number approaches 50% in Shanghai, Beijing and Guangzhou in summer. Building is able to store thermal energy Air conditioning load can be regulated within a certain temperature band; Huge potential for load regulation. Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 5

6 Background Smart Grid technology support AC regulation AC load regulation is applied around the world Telecommunication Automated demand response Distributed control, Remote control ; U.S. Australia Japan Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 6

7 Background U.S. Texas and California Automatic thermostat Remote control of thermostat South California Edison Optional choices of AC load duty cycle of 0,50% and 70%.with different incentives. 1.Customer comfort? Real time tariff display Optional duty cycle program 2. Purpose? A special measure for power shortage? CN Survey of commercial and residential AC load by NDRC and SGCC SGCC planned AC load optimal control for 12 five year plan. Investigation and planning Pilot operation of AC optimal control in Nanjing, Shanghai, Guangxi and Fujian Province. Pilot operation Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 7

8 OUTLINE 1. Background 2. Framework 3. Progress 4. Conclusions Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 8

9 FRAMEWORK thermal dynamics model Energy storage modelin g Fundamental theory Methodology 1 Application Methodology 2 AC load dispatch control AC load aggregatio n Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 9

10 THERMAL DYNAMICS MODEL P T out C a T in R 1 ΔtRC / a T T T T e s 1 = -( - ) =1 t+1 t+1 t+1 t in out out in Cm R 2 T m ΔtRC / a T T PR T PR T e s 1 = -η -( -η - ) =0 t+1 t+1 t+1 t in out x 1 out x 1 in Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 10

11 THERMAL DYNAMICS MODEL Temperatures setting d e c i s i o n m a d e b y consumers, can be very different Energy storage Performances of the buildings are various Parameters identification Experiment data+ identification model Different refrigirating capacity Different energy efficiency ratio Different temperatures setting Different outdoor temp. Different wall material Different window-wall ratio Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 11

12 ENERGY STORAGE MODELING Model AC loads as conventional electric energy storage units participating the power system operation. Step 1 Step 2 Step 3 Analyze the energy storage function of AC load modeling the associated discharge and charge process. Transform the AC parameters like environmental medium heat capacity comfort temp. constraints into the parameters of elec. energy storage unit. energy storage modeling of AC load parameters identification. Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 12

13 AC LOAD AGGREGATION AC loads (energy storage units) Comprehensive energy storage modelling Widely distributed Load aggregating the AC load in a small area share the same ambient environment, namely temperature, solar radiation etc. therefore zonal AC loads aggregating can be proposed. Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 13

14 ` AC LOAD DISPATCH CONTROL ice storage airconditioning Energy Efficient project central air-conditioning DR based on price TOU PTP CPP Annual system planning Alternative/ energy saving load Monthly operation planning Load can transfer between days Day-ahead scheduling Economic Dispatch in a day Minutely response load (response time<30min) AGC Instant response load (response time<2min) Capacity deficiency of accident Interruptible load (reserve) AGC units arrangeme Instant response load (response time<2min) 10 min spinning reserve arrangement Interruptible load (Respinse immediately, full output within 10min, last at least 2h) Generation scheduling Load dispatch Load can transfer within a day hourly response load (response time<1h) 10 min non-spinning reserve arrangement Interruptible load (full output within 10min, last at least 2h) 30 min non-spinning reserve arrangement Interruptible load (repsonse in 30-60min, last at least 2h) Emergency DR IL DSB arrangement DLC scheduling Capacity Ancillary Service Program DR based on incentive the cluster of small business and residential users Air conditioning AC load with direct control is able to respond to the instruction instantly, namely in seconds level. It is suitable for participating in AGC dispatch. Its application to other levels of dispatch needs to be investigated. Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 14

15 OUTLINE 1. Background 2. Framework 3. Progress 4. Conclusions Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 15

16 DAY AHEAD BI-LEVEL DISPATCH MODEL Day ahead market trade, competition between the aggregators defining the power scheduling of next day. Load aggregater 1 area 1 Air- conditioning 1 Air- conditioning 2 Air- conditioning n dispatching department Load aggregater 2 area 2 Air- conditioning 1 Air- conditioning 2 Air- conditioning n Power system Load aggregater m area m Air- conditioning 1 Air- conditioning 2 Air- conditioning n macro layer micro layer 1. Controllable load prediction; 2. Maximize profit by proper load control algorithm. Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 16

17 DAY AHEAD BI-LEVEL DISPATCH MODEL Controllable Capacity evaluation T/ T max T min τoff τc 时间 /min Cx τ off off,basic =( ) τ c τ np τ c,basic Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 17

18 DAY AHEAD BI-LEVEL DISPATCH MODEL Upper level model objective minimize dispatch cost constraints total AC load shedding > power shortage 调度计划 /MW 总需求功率 A B C 负荷聚合商 D E F 0 12:00 12:10 12:20 12:30 12:40 12:50 13:00 时间 Lower level model objective minimize actual AC load shedding deviation constraints off time limit for keeping a comfort temperature 功率 /MW 调度计划实际削减量 :47 12:51 12:55 12:20 12:25 12:30 12:35 12:40 12:45 12:50 12:55 13:00 时间 Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 18

19 ENERGY STORAGE MODELING Solar radiation 太阳辐射 AC 空调制冷 refrigeration S AC refrigirating 外墙 Air 空气对流 convection External wall window 外窗 heat conducting by internal inside temp. 内墙 wall 内部温差传热 difference E store R L (u 2 /R L =P d (t )) P c heat 外部温差传热 conducting by outside temp. difference Representing the heat conducting by Indoor outdoor temp. difference k+ 1 E ( t ) E ( t ) PS( t ) t P ( t) dt store k 1 store k c k d t P c = P + = + Δ rated ( Tout ( tk ) Tin( tk )) Pd( tk) = ηr t k 2 Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 19

20 SECONDARY FREQUENCY REGULATION Begin 12:00-15:00 load regulation (outdoor temp. 38 ) k=1,input parameters including R i C i P rated,i T max,i and T out Test which air-conditionings is on,read their T set,i and T in,i (t k ),calulate E store,i (t 1 ) and C apacity,i Receive power compensation signal from the energy management system P track (t k ) Aggregators remove information of the new quit unit, read T set,i and T in,i (t k ) of new join unit, and calulate E store,i (t k ) and C apacity,i Y Algorithm gives the air conditioning unit control instruction S i (t k ) T out has renewal? N Y Calulate E store,i (t k+1 ) and SOC,i (t k+1 ) Update T out 12:00-13:00 SOC of all the AC load battery N have unit quit or new join in k=k+1 N simulation time end? Y End Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 20

21 OUTLINE 1. Background 2. Framework 3. Progress 4. Conclusions Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 21

22 CONCLUSIONS 1)AC load is a good example of the loads without instant power demand, which allows us to make the load regulation in some extent. It can be ventilation load, heating load, or refrigirating load. 2)Since there are a huge number of AC loads and they are widely scattered, they should be aggregated to be centrally dispatched. The aggregation methodology needs to be further discussed. 3)AC load regulation can be utilized in various levels of power dispatch with different control strategies, but it needs more effort to identify the associated methods. 4)the demand response program and the associated cost effective analysis is a crucial problem for the real application of AC load regulation. Framework of air conditioning load modeling research, Gao Ciwei, Southeast University 22