Lakea ja Aalto-yliopisto pilottipalaveri 13.9.2016 Arkkitehtuurin laitos
Aamun agenda Aamun tavoite prof. Hannu Huttunen Lyhyt esittäytyminen Lakea Oy / Kuusiniemi, Koskela Tutkimusavaukset Aalto-yliopisto Keskustelu Jatkotoimenpiteet / jatkokeskustelut Tilaisuuden päättäminen, viimeistään klo 11
Asukastutkimus townhouse asumisessa Eija Hasu Department of Architecture
Townhouse työpajat toteutettu Helsingissä ja Lohjalla avaa Townhouse-asumisen mahdollisuuksia: innostaa ja poistaa epäilyksiä eri mittakaavoissa Mahdollisuudet: kiinnostuneiden asiakkaiden sitouttaminen asukkaiden yhteisten toimintatapojen haarukointi testaus: kustannukset ja maksuhalukkuus testaus: suunnitteluvaihtoehdot toteutusmallit ja vaihtoehdot: aurinkopaneelit ja sähköauto
Asiakas/asukaskyselyt ja -haastattelut Yleensä rakennuttajan/rakentajan toimesta: myynti sisäänmuutto vuoden asuminen Tutkimuksen tavat ja mahdollisuudet, laajentaminen nykyisestä (esim. päiväkirja) http://www.helsinginuutiset.fi/artikkeli/225161-monikayttoisyys-viehattaa-kaupunkipientalossa Ajankohtaista: käyttäjäkokemus, kokemuksellisuus vielä kahden vuoden asumisen jälkeen: asunnon käyttö ja käytettävyys hyödyntäminen muissa kohteissa, muissa talotyypeissä
Achieving sustainable townhouse by inves3ga3ng life cycle energy and cost op3mal design solu3ons Sudip Pal, Kari Alanne Department of Mechanical Engineering Energy efficiency and Systems research group Aalto University
Methodology to achieve life cycle cost op3mal designs Building specifica9ons from Aalto Dept. of Architecture and Lakea Studied townhouse Simulation software Life cycle energy consump9on, kwh/m 2 y Life cycle cost ( /m 2 ) calcula9ons Op9miza9on algorithm Cost informa9on from Lakea Pal & Alanne
Op3miza3on as a part of design process nzeb 2020 1. Cost efficiency 2. Energy efficiency Objec3ves: MIN Life cycle costs (LCC) in /m2 and MIN life cycle energy (LCE) in kwh/ m2y Decision (design) variables: Structure types, envelope insula3on thickness, window types, types of hea3ng system (electrical hea3ng, district hea3ng, ground source heat pump), ven3la3on heat recovery, PV panel area. Constraints: Overhea3ng Degree Hours < 150, Roof area < 80 m 2 Size of solar thermal collector can be considered as a design variable with addi3onal computa3onal and modeling effort. Pal & Alanne
Sample results: set of op3mal solu3ons 1550 Life cycle cost /m 2 1500 1450 1400 Concrete frame Cost op3mal Massive timber frame Cost op3mal Steel frame Cost op3mal 1350 100 105 110 115 120 125 130 Life cycle energy kwh/m 2 y Any solu3on point on these curve are op3mal with a view of LCC and LCE. The right most point is the cost op3mal solu3on and the le^ most point is the energy op3mal solu3on. Pal & Alanne
Sample results: Comparison of cost and energy op3mal solu3ons (concrete frame case) Design variable description Cost optimal design solution Energy optimal design solution U-value of external wall 0.13 W/m2K 0.09 W/m2K U-value of roof 0.065 W/m2K 0.06 W/m2K U-value of floor 0.18 W/m2K 0.12 W/m2K Window type A window with U-value of 0.8 W/m2K A window with U-value of 0.6 W/m2K Pal & Alanne
Intelligent energy management Elahe Doroudchi Prof. Jorma Kyyrä Department of Electrical Engineering and Automation
Grid-connected PV/battery system
Energy cost comparison of proposed scenarios for storage capacity of 10 kwh System modeling 200 150 Scenario 1 100 Scenario 2 50 80 m 2 of PV on roof 80 m 2 of PV on roof + 40 m 2 of PV on south façade 0 80 m Scenario 3 2 of PV on roof + 40 m 2 of PV on south façade + 40 m 2 of PV on north Jan -50 façade Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Cost ( ) -100 Scenario 4-150 -200-250 -300 80 m 2 of PV on roof + 40 m 2 of PV on south façade + 40 m 2 of PV on north façade + 15 m 2 of PV as solar roadways Scenario 1 Scenario 2 Scenario 3 Scenario 4
Re-defining Proposed system the ZEB configuration system boundaries
0,7 0,6 Net Export [W] 0,5 0,4 0,3 0,2 0,1 Net Monthly export analysis (June) 6000 OEF OEM LPSP 4000 2000 0-2000 -4000 OEF: On-site energy fraction OEM: On-site energy matching LPSP: Loss of power supply probability 0,0-6000 Case 1 Case 2 Case 3 Case 4 0 1000 2000 3000 Number 4000 of hours 5000 6000 7000 8000 Case 1 (REF) Case 2 Case 3 Case 4
DC system vs. AC system DC system has: Higher efficiency Less number of converters Two voltage levels are required (380 VDC & 48 VDC) Easier to implement when renewables and storages are applied
Sensors and Automation Sensors; temperature, CO 2, illumination, pressure difference, occupancy, cameras, wearable sensors Energy monitoring; lighting, plugs, radiators/floor heating, water Smart devices; thermostat, lighting control, door locks Integrated interface for control Cloud storage/big data analysis
Heating system When townhouse is built with high energy efficiency, it would be appropriate to make an analysis between several heating system e.g. District heating + PV Electrical heating + heat recovery of domestic hot water + solar heat + PV Ground heating + PV Hypothesis is, that when the need of the space heating is low, then electrical heating, which has low investment costs would be competitive with systems which have high investment costs but lower operating costs
Lighting system Lighting design would be part of the town house design With good design it would be possible to make lighting solutions which energy consumption is low. Typical situation in residential housing is, that some luminaires are fixed but most luminaires can be selected by the resident In that case the energy efficiency and lighting control is not always optimal
Wood Life: Energy-efficient living spaces through the use of wooden interior elements AEF Program 2012-2017 Project leader: Mark Hughes
Material proper9es and energy-efficiency Hygroscopic proper9es of wood can be used to passively lower energy demand through: Moisture buffering effect Heat of sorp9on Hygrothermal mass Buffering found to be about 4 x greater axially than transversely Dis9nct species effects: greater buffering capacity in soswood species Heartwood less effec9ve than sapwood (in pine)
COST Action FP1105 All-in-one wood coa3ng: super-hydrophobic, UV protec3ve, and moisture buffering Layer-by-layer approach Layers are built due to oppositely charged par9cles Build-up of layers + ZnO particles - Wax particles WOOD -
Coated spruce
Percep3on of temperature: wood and flooring Untreated surface (U) Varnish treatment (V) Oil treatment (O) Heat treatment (H) Surface densified (D) Radial surface (R) Pine Pine Pine Pine Pine Pine Oak Oak Oak Birch Birch Birch Larch Colder >>>>>> To >>>>>>>> Warmer Floorings: 1. Vinyl-1 2. Laminate 3. Linoleum 4. Plas9c carpet 5. Vinyl-2 6. Wet plas9c carpet 7. Parquet 8. Regular carpet Wood species: Oak > Birch > Larch > Pine Wood surfaces across treatments 1. Pine: Surface densified >> Varnished >> untreated >> Oiled >> Heat treated 2. Pine: radial-cut surface >> transverse-cut surface 3. Oak: Varnished = Oiled = Untreated 4. Birch: Surface densified >> untreated = Heat treated Difference in perceived temperature up to about 3 o C
Yhteystiedot / e-mail addresses matti.kuittinen@aalto.fi hannu.huttunen@aalto.fi pekka.heikkinen@aalto.fi eija.hasu@aalto.fi jorma.kyyra@aalto.fi kari.alanne@aalto.fi mark.hughes@aalto.fi juha.kuusiniemi@lakea.fi juuso.koskela@lakea.fi