• Non ci sono risultati.

Stage II. Assessment of primary energy consumption and

CHAPTER 4. Simulation-based Large-scale uncertainty/ sensitivity

4.2. Methodology

4.2.2. Stage II. Assessment of primary energy consumption and

point, the UA allows the estimation of the effects induced by the EEMsd on energy demand and thermal comfort in the heating and cooling seasons. In addition, the values of the SRRCs are assessed for the boolean parameters representing the EEMsd, in correspondence of EDh, EDc, DHh, DHc, ED, DH. Thus, the SA allows to detect the most influential EEMsd on the seasonal and annual values of energy demand and discomfort hours.

4.2.2. Stage II. Assessment of primary energy

provides the hourly values of the energy demand for heating, cooling, DHW and electricity (which gathers the remaining components of building energy use). These values are handled in MATLAB. First, heating, cooling and DHW demands are turned into hourly demand of electricity or fuel (depending on the type of HVAC system) through the hourly performance curves of the HVAC system. Then, the overall values of electricity and fuel demand are converted in primary energy, by means of primary energy factors. The PEC is so calculated. In presence of RESs, EnergyPlus also yields the hourly values of produced energy. If produced energy is consumed according to a hourly balance, it represents a subtractive term in PEC evaluation.

The GC over the lifecycle of the buildings is calculated in MATLAB, according to the guidelines of EPBD Recast. The real interest rate and the energy price escalation rate are respectively set equal to 3% and 2%.

The annual energy demand is assumed constant during the calculation period.

The exploration of the achievable savings in PEC and GC is carried out in three steps, in order to consider the effects produced by three distinct groups of energy retrofit measures: replacement of the primary heating/cooling system (step 3), installation of RESs (step 4), implementation of EEMsd (step 5).

Step 3. Replacement of the primary heating/cooling system

The replacement of the primary heating/cooling (HVAC) system is initially considered as the only possible measure, in order to detect the impact of new efficient systems on PEC and GC. In fact, this generally represents the most influential retrofit action on energy and economic savings [72].

The PEC-GC analysis is performed (see figure 4.1). Specifically, the values of PEC and GC are calculated for each sample of S (existing

building stock) in correspondence of the reference HVAC system and of different new efficient options. The potential savings are then evaluated.

Hence, the best configurations of the HVAC system are identified, as regards respectively energy and cost perspectives. In the first case, the best solution is the one that ensures the highest PEC saving in the building stock. In the second case, it is the one that leads to the highest number of buildings (samples) with positive GC savings; this represents the cost-optimal configuration. The best compromise between these two perspectives is investigated, by means of the concurrent representation of PEC and GC savings:

 mean values are considered for PEC savings, because they are proportional to the energy saving in the whole stock;

 the box plot is chosen for the representation of GC savings, because it allows to estimate, qualitatively, the percentage of buildings characterized by cost savings.

The described analysis is carried out in absence and in presence of state incentives in order to examine the effect of the current policy of grants addressed to energy retrofit actions. The cost-optimal solution refers to the presence of current incentives.

Eventually, a new incentive strategy is devised to obtain a better congruence between the two investigated perspectives (PEC and GC savings). The aim is to harmonize them, in such a way that the best solution for the single building corresponds to the best solution for the collectivity. The best configurations of the HVAC system are identified also in this in case.

In order to compare the two strategies of current and proposed incentives, some reasonable hypothesis are assumed. First, only the HVAC system which ensures the highest values of GC savings for the whole category can be implemented. Secondly, each building implements such HVAC

system only if the latter provides an economic benefit (positive value of GC saving); otherwise it keeps its reference system. In particuar, the percentage of samples with positive GC savings is denoted with p. In these assumptions, the actual values of PEC savings and of state disbursement for incentives can be calculated by multiplying by p the values obtained for the whole sampling set. In order to point out the advantages induced by proposed incentives, the two incentive strategies are analyzed through the following indicators:

 actual value of the average saving in primary energy consumption per building, dPECb [kWh/a];

 actual value of the average state disbursement per building, Db [€];

 ratio between dPECb and Db, π [kWh/€a]; it’s a sort of state profit, representing the potential energy saving in correspodence of an unitary disbursement.

Therefore, this step allows to:

 detect the cost-optimal HVAC system, when the replacement of such system is the unique implemented EEM;

 evaluate the effectiveness of current incentives directed to HVAC systems and to provide a more efficacious strategy.

Step 4. Installation of RESs

The potential savings in PEC and GC induced by the installation of RESs are investigated for S1.

First, the PEC-GC analysis is performed in presence of the reference HVAC system, in order to assess how the mere implementation of a RES influence PEC and GC. The best configurations of the RES (e.g., area of PV panels), as for PEC and GC savings, are detected in absence and in presence of current state incentives Furthermore, A new incentive

strategy is conceived for the considered RES, and the best configurations are detected also in this case. This procedure allows to:

 determine the cost-optimal configuration of the RES;

 evaluate the effectiveness of incentives directed to the considered RES and to provide a more efficacious strategy.

If more RESs are examined, the same procedure is repeated for each of them.

Then, well-selected combinations of HVAC system and RESs are investigated by assessing PEC and GC savings in presence of current incentives. These combinations are identified on the basis of:

 previous results achieved in correspondence of the mere implementation respectively of new HVAC systems (step 3) and RESs (first part of step 4);

 pecularieties of the explored building category in terms of energy performance.

Eventually, this step identifies:

 the cost-optimal combination between the replacement of the HVAC system and the installation of RESs, when merely these energy measures are implemented.

Step 5. Implementation of EEMsd

The effects of EEMsd on PEC and GC are explored. In this regard, the SA performed in stage I (step 2) identifies the EEMsd which have a significant influence on the annual value of energy demand. This step considers only these EEMsd, since the remaining ones are not convenient from both analyzed perspectives. Thus, a new set S3 is generated through exhaustive sampling, in order to represent all the np possible packages (combinations) of the contemplated EEMsd. S3 has a framework similar to S2. More in detail, it collects np·N’ samples, which are composed of np

groups of N’ samples. N’ denotes the minimum number of samples required to significantly describe the building stock. It can be identified only after the UA performed in stage I (step 1); that’s why it generally doesn’t coincide with N. Each of the np groups of S3 gathers the same buildings, represented by the first N’ samples of the set S1, in presence of one of the np possible EEMsd packages, so that all packages are covered.

Hence, the potential savings in PEC and GC induced by the EEMsd are investigated, by referring to S3. The analysis follows the logical order used in step 4.

First, the reference HVAC system is considered. The best packages of EEMsd, as for PEC and GC savings, are detected in absence and in presence of state current incentives. Furthermore, new incentives are devised for the considered EEMsd and the best packages are found out also in this case. This procedure allows to:

 identify the cost-optimal package of EEMsd, when only these energy measures are applied;

 evaluate the effectiveness of incentives directed to the considered EEMsd and to provide a more efficacious strategy.

Then, PEC and GC savings are evaluated in correspondence of well-selected combinations of HVAC system, RESs and EEMsd, in order to find the cost-optimal package of retrofit actions. Likewise step 4, the examined combinations are chosen on the basis of previous results and energetic characteristics of the building category. Eventually, this step identifies:

 the cost-optimal package of ERMs, including replacement of the HVAC system, installation of RESs and implementation of EEMsd; if different packages ensure similar values of GC savings, the thermal

comfort can be used as discriminating criterion, on the basis of the results achieved in stage I (step 2).