First scenario

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multiple datasets coming from it, and also data referring to longer time horizons. An improvement of our ANN models could be useful to obtain similar or higher quality results than grey-box models. Our models can understand the wide variability between minimum and maximum, but with worse average detail. Nevertheless, our average accuracy is lower. It is also true that for only 24 out of 50 buildings under analysis we know the error metrics of the models developed by Z. Wang et al. [24]. All of these have an RMSE of less than 1 °C. In our case, on the other hand, 28 buildings compared to the total investigated have an RMSE lower than the target value.

However, given the better performance of the models proposed by the other authors, this will be used for simulation of the different scenarios.

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load, the withdrawal from the power grid is provided (blue band of Figure 5.5). For the remaining time frame, the micro-cogeneration plant is able to meet the electrical load of the EC (red band of Figure 5.5) and, in the case of surplus production, the transfer to the power grid is envisaged (grey band of Figure 5.5).

Figure 5.5: Electrical load duration curve (blue) and electrical generation curve (red) for the cluster of buildings belonging to the three different ECs.

Therefore, this analysis allowed defining the size of the micro-cogeneration plant subsequently expressed through a percentage of the electrical load rated sum of air-to-air HPs. This, as a matter of fact, is regarded as a benchmark for the whole community since represent the highest consumption contribution for each building in the basic configuration. Specifically, the size of the MGT was set at 6% of the peak electrical load of HPs for Texas, 8% for California and finally for New York the optimal size is 31%. The micro-cogeneration plant sized in this way allows an average of

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12.2% of the heat load of all building to be met for Texas, 15.7% for California and 15.8% for New York. The supplementary heat load is thus offset by the air-to-air HPs arranged at the individual building level. A properly sized μ-CHP system can realize potential energy savings and a subsequent decrease in energy withdrawal from the power grid. These results are shown in Figure 5.6, through the distribution of the change in net electrical load referred to the three different communities. The net electrical load, defined as the difference between electricity consumption and local generation, ranges from -58 kWh to 240 kWh in the basic configuration for the ECs analysed.

Figure 5.6: Density distribution of net electric load difference for the cluster of building belonging to the three different ECs.

Based on these data obtained from the simulations, we can infer a percentage reduction in the net electrical load of entire communities – resulting from the introduction of the MGT – equal to 23.6% for Texas, 22.2% for California and 27.4%

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for New York. This strategy makes it possible to reduce electricity withdrawal from the power grid by an average of 24%, since the net electrical load is lowered.

Therefore, together with the energy savings achieved, there is a reduction in the purchase cost of electricity, as well as a benefit related to economic enhancement for the use of locally arranged technologies and an economic compensation for electricity fed into the power grid. Although it is not evident from Figure 5.6, operation under nominal conditions of the μ-CHP system during the established time intervals results in a peak in the net electrical load distribution that is lower than in the base case, as on-site generation increases for the same amount of electric consumption by community members. In addition to this, an analysis of the electrical load distribution, when the μ-CHP system is operating, shows no peaks at high electric load values. This is related to the fact that during the night-time period, when no local generation system is serving the buildings and the net load matches with the members electrical load, consumption is low. The cost of taking electricity from the power grid for the entire EC is reduced in average by 27.5%. However, it is critically important to observe the cost increase incurred at the community level to procure the natural gas feedstock for the micro-cogeneration plant.

A lower share of electricity withdrawn corresponds to a lower emission of climate-altering substances produced for its generation. Although the MGT is fossil fuel consuming, an overall reduction in CO2 emission to the atmosphere is observed.

Analyses have shown a net reduction ranging from 0.1% to 7.3% depending on the EC observed. Regarding the individual units belonging to the ECs, Figure 5.7 shows the reduction in electricity purchase costs compared to the CO2 savings resulting from the adoption of this plant system.

Figure 5.7: Percentage reduction in electricity costs compared with the reduction of CO² emitted for the cluster of building belonging to the three different ECs.

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A linear relationship is observed between the reduction in electricity cost and the corresponding CO2 emission for each building. As to this matter, more detailed data are given in Table 5.3, depending on the location.

Parameter Texas California New York

Cost percentage reduction 8.6% 6.6% 11.7%

CO2 percentage reduction 5.7% 6.0% 11.5%

Table 5.3: Average percentage cost reduction and CO2 emissions for each building belonging to the three ECs.

Indeed, assuming a virtual sharing scheme, it is as if the individual building is not attributed the share of CO2 emitted for energy production from the MGT serving the entire EC. In truth, the additional share of climate-altering emissions linked to the use of this plant system is actually considered as attributed to the entire community.