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INTEGRIDS and FLEXYNETS projects DHC networks, heat pump pools, and DSM

INTEGRIDS and FLEXYNETS projects DHC networks, heat pump pools, and DSM Marco Cozzini Eurac Research Institute for Renewable Energy Workshop on Energy sector coupling: electric-thermal interaction through
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INTEGRIDS and FLEXYNETS projects DHC networks, heat pump pools, and DSM Marco Cozzini Eurac Research Institute for Renewable Energy Workshop on Energy sector coupling: electric-thermal interaction through heat pumps Bozen October 23 rd, 2018 District Heating and Cooling with Heat Pumps Traditional FLEXYNETS C C T = C T = K 2 Laboratory Energy Exchange lab 3 The FLEXYNETS approach From the water-loop concept to a decentralised low-temperature DHC network Disadvantages: Electricity costs (HPs and pumping) Heat pump investment costs Advantages: Reduction of thermal losses or pipe costs Reversibility (heating AND cooling) Direct integration of low temperature waste heat Coupling with electric grid 4 Electricity CO2 emissions Natural gas: 250 gco2/kwh 357 5 Potential study on DSM in DHC networks with decentralized HPs Buffa S., Cozzini M., Henze G. P., Dipasquale C., Baratieri M., Fedrizzi R. EURAC University of Boulder Free University of Bolzano ISEC 2018, Graz 6 DSM in DHC networks with HPs Time-of-use pricing (as opposed to real-time pricing) Possible DSM strategy: - Exploit DHW tank for thermal flexibility - Control HP for DHW production according to pricing DHW demand always present (no seasonality) DHW tank always present (with HPs) 7 Building model TRNSYS model Building type: multi-family house (s-mfh) of 10 apartment Space heating (SH) net demand: ~ 45 kwh/(m 2 year) Domestic Hot Water (DHW) demand: ~ 25 kwh/(m 2 year) Heated surface: 50 m 2 per apartment Occupancy level: 2 people/apartment Water-source heat pump (WSHP) capacity: ~ 25 kwth DHW TES capacity: 450 litres DHC energy source: ideal thermal source suppling heat at the desired temperature set-point 8 Temperature [ C] Price vs efficiency Overall cost = amount of electricity electricity price Competing effects: - Exploit lower pricing, thanks to thermal storage - Suffer higher electricity consumption, due to higher temperature and lower efficiency (+ minor effects ) DR Peak hours c el,off peak (E th +E th,add. losses ) COP DR c el,peak E th COP max 9 Results: energy assessment Reference vs scenarios based on time-of-use pricing DSM (yearly simulations): - TOU1: constant network temperature (10 C) - TOU2: optimized network temperature (10-20 C) 10 Results: economic assessment Scenario TOU1A Tdhc const. (10 C) Scenario TOU1B Scenario TOU2A Scenario TOU2B Tdhc const. Tdhc var. Unit (10 C) (10 20 C) Cel off-peak /Cel peak [-] Eel prices off-peak hours [EUR/kWh] Eel prices peak hours [EUR/kWh] Tdhc var. (10 20 C) Tot costs [EUR] -0.4(-0.02%) -7.9(-0.4%) -14.6(-0.7%) -20.8(-1%) 11 Conclusions and future work - Little but non-negligible margin of load shifting with TOU pricing - Higher impact expected with real-time-pricing - Flexibility comes at the price of slightly higher consumptions - Tank temperature variation limits to be investigated - Optimization to be performed - Analysis for a single substation: pool effect to be investigated - DSM based on electricity real-time emission factors rather than pricing and much more 12 Thank you for the attention! Marco Cozzini Senior Researcher SHCS group Institute for Renewable Energy T Via A. Volta 13/A Bolzano/Bozen 13 Electricity CO2 emissions Natural gas: gco2/kwh 14 Electricity CO2 emissions Natural gas: gco2/kwh 15
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