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Sustainability 2022, 14, 10125 23 of 39 • Electricity sold curve (orange one) → total electricity sold by the DS. By comparing Figures 8 and 9, the effect of the presented sharing electricity methodol- ogy is evident. The total electricity sold in Figure 8 (without sharing electricity) is more prominent if compared with the equivalent curve in Figure 9 (with sharing electricity). Moreover, as observed also in Figure 8, the curves of total electricity bought and sold overlap throughout almost the entire year. This happens because, as the users in the ECS scenario are individually connected to the electric grid, at a given moment, a certain user might have an electricity surplus (and sell electricity to the grid) while another user does not cover its electricity demand with self-production (and buy electricity from the grid). On the contrary, this cannot happen to the EC based on the SES scenario. As explained in Section 2.5, the DS cannot buy and sell electricity at the same time. If there is an electricity surplus in the DS, the priority must be given to fulfil the electricity demand of the users within the EC. Only when every single user is fulfilled and there is still an electricity surplus is the DS allowed to sell it. This is the reason why Figure 9 does not present an overlap of the curves. Therefore, it is possible to infer that the EC based on sharing electricity (SES scenario) provides a higher amount of self-produced electricity available to its users. Thus, the optimizer can install more electricity-based components (CCs and HPs) to the detriment of the cogeneration ones. Such a fact can be observed in Table 6, where the EC based on the SES scenario supplied 43% and 45% more electricity to CCs and HPs, respectively. The heat section in Table 6 shows the figures for produced, consumed, and demanded heat. The first thing that should be kept in mind is the fact that each heat-producing component has its efficiency, and, for that reason, they should produce more heat concern- ing the heat demand (as clearly observed in the column regarding the CS scenario). The second thing is the higher amount of heat produced by BOIs (+36%), HPs (+86%), and STp (+15%) when comparing ECS and SES scenarios. A higher amount of heat derived from HPs is consistent with the fact that more self-produced electricity is used within the EC. Although the optimizer devoted fewer STp to the EC users, the central unit received 16% more STp in the SES scenario. This increase in STp in the central unit together with a higher amount of heat produced by BOIs can assist in the compensation of fewer installed cogeneration components. Consequently, with higher amounts of produced heat and transported heat through the DHN (Figure 7), the heat wasted resulted in a 21.5% higher rate in the SES scenario. The cooling section in Table 6 gives the values for produced, wasted, and demanded cooling energy. The cooling produced by CCs and ABSs is 43% and 8% higher for the SES scenario. The higher amount of cooling produced by CCs demonstrates the higher consumption of self-produced electricity within the EC, while the higher amount of cooling produced by the ABSs is a consequence of the higher amount of heat required by them. However, the cooling produced by the HPs was 21% lower for the SES scenario, which shows that the emphasis given to HPs had heat production as the focus. The cooling waste was considerably reduced (−66%) in the SES scenario, which is explained by the reduction in DCN pipelines from six to four. Table 7 displays the optimal economic and environmental results obtained from simu- lations performed under the three considered scenarios. From the CS scenario outcomes, the only values that are lower than the respective ones from the other two scenarios are total maintenance cost, total recovered capital, total annual investment cost, and emissions from NG combustion. The first three figures are explained by the substantially lower number of components considered in the CS superstructure (Figure 5). The fourth figure (emissions from NG combustion) is explained by the same reason; however, in this scenario, a higher amount of electricity must be bought from the electric grid. Such a fact contributes to the total annual emissions that are, at least, 44% (or 3430 t/y) higher than the total ones from the other two scenarios. By comparing the ECS and SES scenarios, Table 7 reveals the effect of the sharing electricity methodology, introduced in this paper, on the costs and emissions of the studied EC. Starting from the objective function (total annual cost), the optimization results showedPDF Image | Optimal Sharing Electricity and Thermal Energy
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