http://orcid.org/0000-0002-3753-858X
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Abstract
Living in multifamily buildings is very common in Italy, and it is important to optimize the design strategies to minimize the energy demand of these buildings and their related operational costs. This is particularly important for low-income tenants and is pursued by many social housing developments where a good energy performance design is reached. In this work, a simulation-based optimization methodology that combines the use of TRNSYS with GenOpt is applied to minimize two objective functions—the annual primary energy demand and the operational energy cost—in different system technology scenarios, and to verify the differences between energy-optimized design and cost-optimized design in a Northern Italy climate. The study is performed on a typical floor of a real multifamily building for social housing. The envelope optimization demonstrates a potential reduction of the energy demand and cost for heating and cooling of more than 35%. The relationship between optimal solutions, system technology scenarios, and optimization objectives is deeply analyzed. It is possible to find a set of design solutions that is optimal for all analyzed scenarios. This provides a set of design alternatives that is close to the environmental optimum and is able to reduce low-income tenants' vulnerability.
| Nomenclature |
| Acronyms | ||
| DH | = | district heating |
| EC | = | electric chiller |
| EHP | = | electric heat pump |
| GAC | = | gas-absorption chiller |
| GCB | = | gas-condensing boiler |
| GHP | = | gas heat pump |
| INI | = | initial building configuration |
| OPT | = | optimal building configuration |
| PSO | = | particle swarm optimization algorithm |
| Latin letters | ||
| abN | = | solar absorption coefficient of external wall, north facade |
| abS | = | solar absorption coefficient of external wall, south facade |
| abWE | = | solar absorption coefficient of external wall, west, east facade |
| Blr | = | width of the window at the ground floor on the south facade (m) |
| Bm | = | width of the window at the first floor on the south facade (m) |
| C | = | operational cost (€) |
| c | = | specific energy cost (€/kWh) |
| fpe | = | primary energy conversion factor |
| inWN | = | thermal resistance of wall insulation, north facade (m²K/W) |
| inWS | = | thermal resistance of wall insulation, south facade (m²K/W) |
| inWE | = | thermal resistance of wall insulation, west, east facade (m²K/W) |
| Loggia N | = | depth of north loggia (m) |
| Loggia S | = | depth of south loggia (m) |
| Lagg S | = | depth of fixed shadings on the south facade windows (m) |
| OF | = | objective function |
| PE | = | primary energy (kWh) |
| p | = | parameter |
| s | = | parameter variation step |
| Q | = | energy need (kWh) |
| w | = | weight |
| WTE | = | window type of east, west facades (-) |
| WTN | = | window type of north facade (-) |
| WTNL | = | window type of north loggia facade (-) |
| WTS | = | window type of south facade (-) |
| WTSL | = | window type of south loggia facade (-) |
| WW | = | window width (m) |
| Subscripts | ||
| c | = | cooling |
| h | = | heating |