iMinds the conference 2012: Koen Vanthourhout
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The document summarizes the LINEAR project which uses residential demand response to address issues from increased renewable energy. It has a budget of €40 million running from 2009-2014. The project focuses on automating demand shifts using smart devices like washing machines to provide grid benefits like reducing transformer aging or helping balance intermittent renewables. It tests demand response through business cases like dynamic pricing, helping the distribution system operator control voltages, or decreasing a renewable energy provider's balancing costs.
iMinds the conference 2012: Koen Vanthourhout
- 1. Koen Vanthournout, VITO (Flemish Institute for Technological Research) Jan Van Ooteghem, Ghent University / iMinds
- 2. LINEAR “Local Intelligent Networks and Energy Active Regions” 1. Flemish Government decision „dd. 8 mei 2009 VR 2009 0805 DOC.0671‟ 2. Official start: May 2009. Project runs until December 2014. 3. Total budget of 40M€: – Flemish government: 10M€ – Industry: 30M€ (personnel, hardware, ...) www.linear-smartgrid.be 08/11/12 2
- 3. Linear situated • Increased share of intermittent renewables • Electrification of transport and heating • Stabilization/decrease classical production portfolio ⇒ Energy excesses and shortages ⇒ Grid capacity issues Classical control paradigm “production follows consumption” no longer holds ⇒ storage ⇒ “consumption follows production” (i.e., demand response) Linear focuses on Residential Demand Response 08/11/12 3
- 4. Partners Research Partners Flemish Government Industrial Partners Additional Members Steering Committee 08/11/12 4
- 5. Core: large scale residential DR pilot Residential demand response with as little impact on the user comfort as possible 1. Focus on automated ‘smart’ devices. 2. Keep technical targets and BCs hidden for the user. 3. Keep interaction simple and stimulate good behavior financially. 08/11/12 5
- 6. Linear Smart Devices • Washing machines • Dishwashers • Tumble dryers • Electric hot water buffers • (Electrical vehicles) • (Heat pumps) 08/11/12 6
- 7. Linear Control architecture Transformer Linear Historic measurements Server BC data • One business case at the time • # aggregators with # control technology • Generic interfaces for smart devices Server … • P1 smart meter interface definition Fifthplay • Interface definition between aggregator and user flexibility INTERNET GW GW GW GW GW Integration tests in lab ongoing, HOME tests started at friendly users Smart Touch Energy Plugs Miele VITO DHW VITO Smart Meter Display meas. Network GW buffer controller plug Miele Miele Miele BSH BSH wash. tumble dish wash dish EV machine dryer washer mach washer 08/11/12 7
- 8. 250 participating families 3 groups Friendly users Geographically Geographically dispersed concentrated Focus Technical testing BRP cases DSO cases, link with smart meter projects Target 30 100 120 Contract signed 33 81 13 Smart devices 25 203 25 installed Status Integration tests • Installed Recruitment and started • Reference installation ongoing in measurements ongoing Hombeek& Leest (Eandis) • 15 HP owners in and Genk (Infrax) recruitment pipeline 08/11/12 8
- 9. Linear Business Cases Use DEMAND RESPONSE for: 1. Portfolio Management BRP/Retailer Shift consumption in function of the day ahead market (corrected for 2020 production mix) 2. (Wind) Intraday balancing BRP/Retailer Shift consumption in function of the quarter hour unbalance of a BRP portfolio 3. Transformer aging DSO Shift consumption to avoid accelerated aging due to high transformer temperatures 4. Voltage control for LV distribution feeders DSO Shift consumption based on local voltage measurements to ameliorate voltage line deviation 08/11/12 9
- 10. Linear - business cases LV transformer load Peakload Future distribution grid: • More residential consumption => higher offtake peaks on LV transformers P • 1 More intermittent (renewable) generation Peakloadre duction due => injection peaks on LV transformers to DR P Aging of transformer will be accelerated during 2 these peak periods (increase of temperature) t1 Deferrel of t2 Investment If DSOs succeed in controlling temperature of LV transformer, Lifetime they are able to allow a higher share of local generation and extra demand without the need for new network investments Objective: control the temperature on a transformer by the application of automated active demand to defer/decrease network (transformer) investments 08/11/12 10
- 11. Linear - business cases LV feeder voltage profile Future distribution grid: • More residential consumption => voltage drops in feeders • More intermittent (renewable) generation => voltage increases in feeders Predictability of the voltage profile of a feeder decreases Situations can occur where the voltage levels Voltage profile with and without DG either become too high or too low (Source: EELAB) Objective: keep the voltage profile of the different LV lines within permitted limits by the application of automated AD (no coordinated local control at household level) to defer/decrease network (new lines / transformers) investments 08/11/12 11
- 12. Linear - business cases Dynamic Energy component Portfolio management Distribution fee Fixed Transmission fee Dynamic tariffs can be used to Charges incentivize consumers to reschedule their consumption Tariffs used: • 6 time blocks a day • Based on Belpex DAM + prediction sun/wind (scenario 2020) • Communicated DA for the next day Objective: coincide as much as possible periods with low generation costs (based on high availability of renewable generation by wind and/or sun) with consumption by applying dynamic tariffs to residential consumers 08/11/12 12
- 13. Linear - business cases Wind balancing • BRP = responsible for the balance of injection + offtake in their perimeter on a quarter-hourly basis • TSO manages the instantaneous imbalances (that the BRPs are not able to control), by making use of power reserves Costs involved for making use of power reserves are transferred to the BRPs Balancing mechanism (Source: Elia) BRP with wind production in its portfolio: higher imbalance risk + higher imbalance cost Objective: decrease the imbalance cost of the BRP by decreasing the unpredicted imbalance caused by wind production (intraday) in its portfolio by aggregating flexibility available at residential consumers’ premises (flexible cluster) 08/11/12 13
- 14. Linear - business cases Control mechanism DSO BRP/retailer LV Dynamic tariffs Portfolio Automated transformer management active demand load LV feeder Wind voltage balancing profile 08/11/12 14
- 15. Questions? Koen Vanthournout, VITO (Flemish Institute for Technological Research) Jan Van Ooteghem, Ghent University / iMinds