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1 The Danish W ind Pow er Case Wind power covers the entire demand - PDF document

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Pow er System Balancing by Distributed Energy Resources ( DER) and Flexible Dem and Prof. Jacob stergaard, Centre for Electric Technology, DTU 18-20 May 2011 LCCC, Lund University The Danish Energy Strategy and Goals Danish

  1. Pow er System Balancing by Distributed Energy Resources ( DER) and Flexible Dem and Prof. Jacob Østergaard, Centre for Electric Technology, DTU 18-20 May 2011 LCCC, Lund University The Danish Energy Strategy and Goals • Danish 2020-objectives – At least 30% renewable energy in the energy system – ~ 50% wind power penetration 50% wind power penetration • In 2050 (The governments strategy) – Fossil free energy system – 100% renewable based energy system 2 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 1

  2. The Danish W ind Pow er Case Wind power covers the entire demand for electricity In the future wind power will exceed demand in 200 hours (West DK) in more than 1,000 hours 3 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 Balancing in the Nordic Pow er System • Day-ahead m arket: – Hourly price-volume bids and offers – P i Price is set by intersection point between the supply and demand curves i t b i t ti i t b t th l d d d – The price is settled 12–36 h before the hour of delivery • I ntra-day m arket: – Adjustments to trades done in the day-ahead market are made until one hour prior to delivery • Balancing m arket: – Real-time market operated during the hour of delivery – Up- and down regulation bids until one hour prior to hour of operation – Activated during hour of operation by TSO’s • Frequency control: – Governors with proportional controller – Speed droop 4 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 2

  3. Hom eostatic Utility Control • In 1980 Prof. Schweppe publish a vision for a future power system – Fred Schweppe et al., “Homeostatic Utility Control”, IEEE Transactions on Power Appartus and Systems Vol PAS-99 No 3 Transactions on Power Appartus and Systems , Vol. PAS 99, No. 3, May-June 1980, pp. 1151-1163 • Homeostasis – Property of a system that regulates its internal environment and tends to maintain a stable, constant condition, typically used to refer to a living organism. Multiple dynamic equilibrium adjustment and regulation mechanisms make homeostasis possible. • Idea of a electric energy system based on flow of: – Power – Money – Information 5 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 Outline 1. Two control concept for usage of distributed energy resources (DER) and demand response (DR) for power system balancing a. a Frequency responsive demand Frequency responsive demand b. 5 minute real-time market / control-by-prices 2. Feasibility is illustrated by simulation of the Nordic power system with realistic, verified and tested models 3. Future outlook – Two large-scale demonstrations in the Danish power system 6 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 3

  4. Dem and as Frequency Controlled Reserve ( DFR) • A large share of demand can be disconnected in a short period without reduction in delivered energy service – Air conditioning Air conditioning – Water heating – Refrigeration – Pumping – Ovens – Melting • Potential benefits DFR controller – Fast reaction – Not affected by tear and wear Not affected by tear and wear – Smooth collective response with numerous units – Low costs and utilization of intrinsic energy storage in appliances 7 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 Refrigerator in Pow erLabDK Laboratory at DTU Vestfrost M2 0 0 Bottle Cooler w . Dixell XR3 0 CX therm ostat 8 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 4

  5. Refrigerator Therm al Model Model Verified by Measurem ents Heat transfer between mass j and k is calculated:          Q U T T t  , 1 , , jk i jk j i k i Temperature of mass j is calculated:  Q    1 i T T  , 1 , j i j i C TABLE II j R EFRIGERATOR M ODEL P ARAMETERS Thermal mass, 1* 251 kJ/K ± 50% C 1 Thermal mass, 2 13 kJ/K C 2 Thermal mass, 3 1 kJ/K C 3 Heat transfer coefficient, 1 ↔ 2 30 W/K U 1 ↔ 2 Heat transfer coefficient, 2 ↔ 3 12 W/K U 2 ↔ 3 Heat transfer coefficient, a ↔ 2 5 W/K U a ↔ 2 Heat pump capacity (when ON) 421 W * Randomly, represent a loading between 25 and 75% of capacity. 9 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 Refrigiator Control Thermostat logic, u (1=on; 0=off), is calculated:    min max u T T T i i set set set set     1  min u T T  1 i set   0 max  T T set where:    ( ) T T k f f , 0 0 set set       min / 2 max / 2 T T T T T T set set hys set set hys Parameters: Δ T hys = 2 ° C k = 20 ° C/Hz Limitation: Minimum 3 minutes off-time between on-cycles. Frequency f is low pass filtered with time constant of 1 second. 10 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 5

  6. Refrigerator Operation Measurem ents in Laboratory Without DFR: With DFR: 11 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 Statistical Representation of Frequency Response Measurem ents in Laboratory 12 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 6

  7. Response to 5 0 m Hz Frequency Step and 3 0 0 MW Loss of Load, respectively Sim ulation of 1 ,0 0 0 I nstances/ 2 ,0 0 0 MW ( rated pow er) 13 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 Business Case for DFR • Cost of frequency controlled reserves (Nordic power system) – 25.000-100.000 €/ MW/ year • Assumptions: – DFR production cost is 20 €/ unit (not mass production) – Unit average power demand 100 W • Simple payback time of DFR: – 2-8 years 14 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 7

  8. Control-by-price Extention of Market to Shorter Tim e Scale and Sm aller Users ( DER and Flexible Dem and) Current regulating power market New control-by-price concept • 10+ MW bids • One-way price signal every 5 minutes • Online monitoring • Fit small units • Transactions 15 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 Control-by-price ( 5 m in real-tim e m arket) 16 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 8

  9. Micro-CHP Unit in Pow erLabDK Laboratory at DTU Gas-engine based Senertec DACHS TABLE V M ICRO -CHP C HARACTERISTICS El Electric power t i 5.5 kW 5 5 kW Heating power 12.5 kW Start-up delay 90 seconds Shut-down time Immediately Minimum on-time 30 minutes 17 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 Overview of Micro-CHP System TABLE V M ICRO -CHP T HERMAL P ARAMETERS Building heat demand 6 kW ± 50% Storage tank capacity 750 liter Min. heat storage av. temperature 50 ºC Max. heat storage av. temperature 80 ºC 18 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 9

  10. Relative Price Exam ple from the Nordic System 2 5 Septem ber 2 0 0 9 Relative price:  P P   avg P P rel P dev    t     P P P P   , , 1 , 1 avg i avg i    avg i t      t 2      P P P P P var, var,  1 , var,  1 i i avg i i    t ,  P P var, dev i i Very simple implementation 19 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 Micro-CHP Control Decision diagram: T hs T hs : Heat storage average temperature (state- H t t t t ( t t T of-charge) Stop t on : Minimum operating time per start T hs,max k p : The relative price at which the controller Stop will fully charge the heat storage if t on > t on,min Start T hs,min TABLE V M ICRO -CHP C ONTROLLER Price constant, k p 1 P rel -k p k p Relative price time constant,  12 h 20 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 10

  11. Operation w ith Prices of 2 5 Septem ber 2 0 0 9 Measurem ent in Laboratory 8 c power (kW) 6 4 Electri 2 0 5 10 15 20 Time (h) 150 Price (EUR/MWh) 100 50 0 5 10 15 20 Time (h) 90 90 Temperature (  C) 80 70 60 50 5 10 15 20 Time (h) Increased income is 7 .3 % without loss of comfort. 21 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 Response @ 1 EUR/ MW h Price Step Sim ulation of 1 ,0 0 0 units W h + 1 EUR/ MW / MW h -1 EUR/ Minimum operating time 30 min. 22 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 11

  12. Pow er System Control Schem e Overview Base Base generation load Disturbance + - Price- responsive loads Power system - + + +- + + (Inertia) Δ P Price- responsive generation generation f f Frequency- Price responsive calculation loads 23 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 Pow er System Balancing by Distributed Energy Resources and Flexible Dem and TABLE III P RICE C ONTROLLER Type PID P coefficient 12 EUR / Hz I coefficient S = 7 0 ,0 0 0 MVA 0.02 EUR / (Hz·s) 1 ,0 0 0 MW installed D coefficient 2,400 EUR / ( Hz/s) H = 4 s Price update interval 5 minutes 1 ,0 0 0 MW installed 2 ,0 0 0 MW installed ± 3 0 0 MW 24 DTU Electrical Engineering, Technical University of Denm ark 18 May 2011 12

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