This paper presents a study on the optimal district integration of a distributed generation (DG) system for an energy community (EC) and the implementation of sharing electricity (SE) between users. In recent years, the scientific community has frequently discussed potential pathways to achieve a 100% renewable energy source (RES) scenario, mainly through increasing electrification in all sectors. However, cooling-, heat-, and power-related technologies are expected to play a crucial role in the transition to a 100% RES scenario. For this reason, a research gap has been identified when it comes to an optimal SE solution and its effects on the optimal district heating and cooling network (DHCN) allowing both electrical and thermal integration among users. The considered system includes several components for each EC user, with a central unit and a DHCN connecting them all. Moreover, the users inside the EC can exchange electricity with each other through the existing electric grid. Furthermore, the EC considers cooling storage as well as heat storage systems. This paper applies the Mixed Integer Linear Programming (MILP) methodology for the single-objective optimization of an EC, in Northeast Italy, considering the total annual cost for owning, operating, and maintaining the entire system as the economic objective function. After the optimization, the total annual CO2 emissions were calculated to evaluate the environmental effects of the different solutions. The energy system is optimized in different scenarios, considering the usage of renewable resources and different prices for the purchase of electricity and natural gas, as well as different prices for selling electricity. Results showed that, without changing utility prices, the implementation of SE allowed for a reduction of 85% in the total electricity bought from the grid by the EC. Moreover, the total annual EC costs and CO2 emissions were reduced by 80 keuro and 280 t, respectively.

Optimal Sharing Electricity and Thermal Energy Integration for an Energy Community in the Perspective of 100% RES Scenario

De Souza, R;Casisi, M
;
Reini, M
2022

Abstract

This paper presents a study on the optimal district integration of a distributed generation (DG) system for an energy community (EC) and the implementation of sharing electricity (SE) between users. In recent years, the scientific community has frequently discussed potential pathways to achieve a 100% renewable energy source (RES) scenario, mainly through increasing electrification in all sectors. However, cooling-, heat-, and power-related technologies are expected to play a crucial role in the transition to a 100% RES scenario. For this reason, a research gap has been identified when it comes to an optimal SE solution and its effects on the optimal district heating and cooling network (DHCN) allowing both electrical and thermal integration among users. The considered system includes several components for each EC user, with a central unit and a DHCN connecting them all. Moreover, the users inside the EC can exchange electricity with each other through the existing electric grid. Furthermore, the EC considers cooling storage as well as heat storage systems. This paper applies the Mixed Integer Linear Programming (MILP) methodology for the single-objective optimization of an EC, in Northeast Italy, considering the total annual cost for owning, operating, and maintaining the entire system as the economic objective function. After the optimization, the total annual CO2 emissions were calculated to evaluate the environmental effects of the different solutions. The energy system is optimized in different scenarios, considering the usage of renewable resources and different prices for the purchase of electricity and natural gas, as well as different prices for selling electricity. Results showed that, without changing utility prices, the implementation of SE allowed for a reduction of 85% in the total electricity bought from the grid by the EC. Moreover, the total annual EC costs and CO2 emissions were reduced by 80 keuro and 280 t, respectively.
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https://www.mdpi.com/2071-1050/14/16/10125
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3030440
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