Marginal cost analysis applied to complex polygeneration systems: Case study of an Italian energy community

This paper proposes a thermoeconomic assessment of the optimal operation of a complex polygeneration system through the marginal costs analysis and interpretation. Such assessment provides a deep understanding about the effect of energy demand changes in the objective function under analysis. Literature has demonstrated the importance of integrating efficiency-improved processes and renewable energy sources within energy supply systems to minimize overall costs and environmental impacts. However, when it comes to complex polygeneration systems, there is a lack of a deep understanding regarding (i) the cost formation process of each energy service product at any considered time step, and (ii) the influence of energy demand changes on the objective function under scrutiny. The proposed thermoeconomic analysis aims to determine the optimal operation of the system when the energy demand of a specific energy service of a polygeneration system is increased (at any time step), without modifying the operation mode of the system. The case study used to perform the study involves an energy community (EC) model, implemented through a mixed integer linear programming (MILP) algorithm, where nine tertiary sector buildings and a central unit are fed by natural gas, solar energy, and electricity as local energy resources. The buildings share electricity through a local electric grid as well as heating and cooling through a district heating and cooling network (DHCN) of pipelines. The paper focuses on the marginal cost analysis of the heat demand regarding one of the EC buildings by evaluating representative time steps of a typical winter day. Moreover, a detailed examination of the cost formation process concerning the polygeneration heat production is carried out, where the influence of thermal energy storage (TES) on the marginal cost of heat production is also elucidated. Based on the optimal operation of the polygeneration system (obtained through the MILP algorithm), the results regarding the marginal cost analysis and interpretation have shown how to operate the system in the case of a heat demand increase by specifying marginal paths representing the operation with the lowest effect on the MILP objective function. For instance, from the cases analyzed within this paper, it was identified an operation cost reduction ranging from 14.6% to 38.2% when the optimal marginal path (heat production from heat pump, with TES support) is compared to a non-optimal marginal path (heat production from boiler). Such results offer a comprehensive understanding of optimally operating a complex polygeneration system in the eventuality of heat demand increases, considering that typical MILP optimizations are based on fixed energy demand input data. This research contributes valuable insights into enhancing the sustainability and efficiency of energy supply systems, paving the way for informed decision-making in the pursuit of environmentally friendly and economically viable solutions.