Assessing Heat Pump Deployment for PNIEC Targets in Italy Through a Climate-Based Seasonal Performance Analysis

2.1 Meteorological data acquisition

To determine the seasonal performance (sCOP) of heat pump (HP) systems all over the Italian territory at provincial level, the Typical Meteorological Year (TMY) for each provincial capital has been analyzed. Given the coordinates of each province capital, the corresponding TMY file has been downloaded from the PVGIS SARAH-3 database, for a total of 109 locations in the 21 Italian regions. Among the different data provided in TMY files, the hourly air temperature values have been considered.

The present investigation is related to the heating period. The Italian D.P.R. August 26, 1993, n. 412 [11] established the division of the national territory into six climate zones (A–F), based on the heating degree days (HDD) of each municipality. Moreover, the D.P.R. April 16, 2013, n. 74 [12] regulates the periods during which the operation of heating systems is permitted, as shown in Table 1. In each considered location, the analysis has been restricted to the corresponding heating period.

Table 1. Climatic zones in Italy

For each location, the design temperature to be used for the simulation was determined. For each consecutive 12-hour interval, the maximum temperature is calculated. The design temperature is the minimum value, over the course of a year, among all these maximum temperatures over 12 consecutive hours. Therefore, the design temperature T_des has been set as the temperature value below which the external air temperature does not remain for more than 12 consecutive hours during the year.

2.2 Performance estimation of heat pumps

2.2.1 Analyzed model

The present analysis refers to an air-to-air HP, sized for an average 1 family residential unit. Since the coefficient of performance (COP) of an HP is more dependent on the specific model rather than its size, only one model has been considered within the present investigation. The performances of the selected model satisfy the D.M. August 6, 2020, Annex F [13], which establishes the minimum performances for heat pumps to have access to tax incentives. In particular, for air-to-air HP, the minimum COP is 3.9, evaluated at external and internal air temperatures of T_ext = 7℃, T_int = 20℃.

Tables 2 and 3 report the declared performances of the selected air-to-air inverter-type HP. The performance data are expressed in accordance with the Italian Standard UNI/TS 11300-4 [14]. The capacity ratio CR is here the ratio between the actual heating demand and the maximum heating capacity at the same operating conditions, while fCOP is the ratio between the COP at partial load and the COP at full load at the same operating conditions.

Table 2. Selected heat pump performance at full load

Table 3. Selected heat pump performance at partial load

2.2.2 Climatic load curve

For each location, the heating demand has been set to 100% at the design temperature T_des (evaluated as described in paragraph 2.1) and 0% at T_ext = 16℃, following the linear law for the building climate load factor as in Eq. (1).

$PLR=\frac{{{T}_{\text{ext }}}-16}{{{T}_{\text{des }}}-16}$                 (1)

Setting the heating demand at T_des equal to the maximum heating capacity of the selected HP at T_des, the heating demand as a function of external air temperature T_ext can be determined.

The Capacity Ratio (CR) is calculated for each T_ext as the ratio between the heating demand and the maximum heating capacity under the same operating conditions.

2.2.3 Heat pump performance at full and partial load

For T_ext different from the 4 conditions reported in Table 2, the maximum heating capacity has been calculated with linear interpolation, and extrapolated for temperatures below -7℃. However, to calculate COP values at full load, the Italian Standard UNI/TS 11300-4 [14] suggests not to directly interpolate the COP.

First, the Carnot efficiency COP_max is calculated for each of the external air temperatures T_ext of Table 2, considering the internal air temperature T_int = 20℃, as in Eq. (2):

$CO{{P}_{\max }}=\frac{{{T}_{int}}+273.15}{{{T}_{int}}-{{T}_{ext}}}$                   (2)

Then, the second law efficiency η_II for each declared point in Table 2 is calculated as the ratio between COP and COP_max. Therefore, for any different T_ext, the η_II is calculated by interpolating between the 4 calculated points. For T_ext < -7 ℃, the second law efficiency is considered to be constant. The COP at full load at each T_ext can be calculated by multiplying COP_max by the corresponding second law efficiency η_II.

Finally, as suggested by UNI/TS 11300-4 Standard [14], it is assumed that fCOP depends solely on CR and the relationship between fCOP and CR is assumed to be linear between any point pair (CR, fCOP) of Table 3; thus, the fCOP values can be estimated for all the required T_ext, allowing finally to calculate the partial load performance.

2.2.4 Heat pump seasonal performance

For each location and within the heating period relative to the corresponding climatic zone, the HP hourly performance has been evaluated as explained in the previous sections, in terms of COP, heating demand, and CR. In addition, the partial load factor (PLF) is calculated as in Eq. (3):

$PLF=\frac{\text{ Heating demand }}{HP\text{ rated power }}$                 (3)

where the HP rated power is the maximum heating capacity at T_ext = 7℃, T_int = 20℃. The seasonal PLF (sPLF) has been calculated as the average hourly PLF.

The seasonal energy to power ratio (sEPR) has been calculated by multiplying the sPLF by the number of hours of the heating period for each location.

Since the energy demand is not constant throughout the heating period, the seasonal coefficient of performance (sCOP) is calculated as the average hourly COP weighted on the hourly PLF, as in Eq. (4):

$sCOP=\frac{\sum\limits_{i=1}^{N}{C}O{{P}_{i}}\cdot PL{{F}_{i}}}{\sum\limits_{i=1}^{N}{P}L{{F}_{i}}}$                (4)

where, N is the number of hours of the heating period.

As defined in the European Directive RED II [15], the seasonal energy share from renewable energy sources (sERES) has been calculated as in Eq. (5):

$sERES=1-\frac{1}{sCOP}$                    (5)

Finally, the Regional sCOP, sERES, sPLF, sEPR have been calculated as the average of the provincial values weighted on the provincial population.

2.3 Estimation of the new HP fleet in Italy

The Italian PNIEC plan foresees that by 2030, heat pumps will contribute to the renewable energy fraction ERES globally equal to 5225 ktoe [4]. Based on the analysis of data provided by the GSE for each region [16], in 2022 the 8.7% of the demand for heating in the residential and services sector was covered by ERES from heat pumps (2746 ktoe over a demand of 31467 ktoe). Assuming that the heating demand remains almost unchanged, by 2030, the ERES fraction from HP is expected to cover 16.6% of the heating demand in the residential and services sector. Thus, in this preliminary analysis, it has been assumed that all regions will reach the same 16.6% target.

Taking into account the GSE 2022 data, for each Italian region, the additional ERES quote to be achieved by 2030 has been calculated and called ERES_add.

The regional heating demand Q_h covered by new HPs in 2030 has been estimated as in Eq. (6):

${{Q}_{h,\text{add }}}=\frac{\text{ ERE}{{\text{S}}_{\text{add }}}}{sERES}$                    (6)

The regional electric energy demand (E_el) associated with additional HPs operation has been estimated as in Eq. (7):

${{E}_{el,add}}=\frac{{{Q}_{h,add}}}{sCOP}$                     (7)

The regional additional HP installed power P_{inst, add} has been estimated through the calculated seasonal energy to power ratio as in Eq. (8):

${{P}_{\text{inst, add }}}=\frac{{{Q}_{h,\text{ add }}}}{sEPR}$                   (8)

Finally, the impact of the installation of new HPs has been evaluated through the comparison of the additional electrical energy demand E_{el, add} respect to the electrical energy demand of each region in the residential and tertiary sectors and the total electrical energy demand. The electrical energy demand data have been retrieved from the 2023 statistics of Terna [17].

This study presents a comprehensive simulation-based analysis of air-to-air heat pump performance across all Italian provinces, accounting for local hourly climatic conditions (TMY) and heating periods.

The results show significant regional differences in seasonal performance (sCOP), ranging from 2.8 to 4.44, and renewable energy share (sERES) from 0.64 to 0.77.

Northern regions, with higher heating demands, are expected to play the largest role in expanding Italy’s heat pump fleet to meet PNIEC targets. However, colder climates and existing reliance on gas infrastructure may hinder the deployment. Conversely, southern regions and islands, particularly Sicily, have already achieved substantial ERES contributions due to milder winters and dual-use (cooling/heating) applications, remembering that the current European regulations have defined the estimation of the amount of renewable energy used also for HPs in cooling mode.

Achieving the 2030 national goals will require significant new installations in underperforming regions. This will lead to a measurable increase in electricity demand (up to +8.05% of the total regional demand, with an average of +4.03% in Italy), which may challenge local grids, especially in low-demand regions. The integration of distributed renewable sources, such as PV systems, is essential to ensure grid stability. Overall, heat pumps remain a viable solution for decarbonizing residential and tertiary heating in Italy.