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Sustainability 2022, 14, 10125 5 of 39 to evaluate the environmental effect of the different solutions. Within such a context, the SE between EC users is implemented in order to assess the economic and environmental impacts of this option. The optimal results obtained for a test case are compared with and without SE. Then, an investigation is performed to analyse the behaviour of the optimal solution by varying the prices of the energy vectors through six sensitive scenarios. This approach made it possible to highlight the extent to which the EC option effectively allows one to obtain fewer emissions and reduced exchanges with the external electricity grid, even without the need to introduce objectives other than simple economic convenience. Section 2 is dedicated to the description of the model, presenting the equations of the components, energy balances, objective functions, and the sharing electricity methodology. Section 3 describes the energy community case study, whereas Section 4 presents the results and discussions about the simulations and comparisons mentioned in the previous paragraph. 2. Model Description As mentioned in the last section, the definition of the optimal synthesis, design, and operation of the DHCN was performed through the Mixed Integer Linear Programming (MILP) optimization method. In summary, the synthesis refers to the selection of the equipment that is going to be included in the final optimal structure; the design process concerns the sizing of each selected equipment, and the operation definition has the objective of setting the on/off status of each piece of selected equipment. The MILP method can be divided into three main parts: decision variables, constraints, and objective functions. Decision variables can be of two types: binary or continuous. Binary variables express the selection and on/off status of equipment, whereas continuous variables express the sizing of each selected equipment and auxiliary components, as well as energy quantities and streams. Constraints are mathematical expressions with the aim of determining the model and what its limitations are in terms of equipment size, performance, and energy balance. The objective functions represent the main target of the analysis, which is, for this work, the minimization of the total costs regarding the DHCN and the nine users. As depicted in Figure 1, the superstructure is divided in three main elements. The first one is related to the maximum set of equipment (Polygeneration Unit k) that can be dedicated to a given user building (denoted as “User k”). The second part is associated to the central unit, which is a user-independent structure and can comprise a set of equipment to benefit the energy community with heating and electricity. The third element is “User i”, which represents the other users within the energy community. These three elements are connected through a DHCN, for thermal related energy exchange, and a distribution substation (DS), as an electricity concentrator. The pipeline connections between users, the central unit, and the DHCN are one of the optimized characteristics performed by the model. The users and central unit are not connected directly to the electricity grid. Instead, they are all connected to the DS, the purpose of which is to manage the electricity flow for the three elements. In other words, based on an electricity balance, the DS sends electricity to a given user (if its polygeneration unit did not fulfil its demand), receives electricity from a given user (if its polygeneration unit has fulfilled its demand and now it has an electricity surplus), buys electricity from the grid (if the electricity surplus from the users is not enough to cover the electricity deficit of the other users), and sells electricity to the grid (if there is a surplus and all electricity users demands are covered). Heating, electricity, and cooling have specific origins, destinations, and paths within the polygeneration unit superstructure. Starting from heating connections, the heat is produced from two types of primary energy: natural gas and solar energy. Natural gas drives micro gas turbines (MGT), internal combustion engines (ICE), and boilers (BOI), whereas solar thermal panels (STp) are obviously driven by solar energy. As can be observed in Figure 1, absorption chillers (ABS) can only be powered by the heat coming from MGT and ICE. The heat thermal storage (TStor) is allowed to store the heat coming only from MGT, ICE, and STp, and, on the other hand, it can supply heat only to UserPDF Image | Optimal Sharing Electricity and Thermal Energy
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