Abstract
This work examines a combined-component, fifth-generation district heating system (DHS) with an emphasis on CO2 emission reduction and greater adaptability to diverse heat sources. There are two primary contributions resulting from this analysis. First, a mathematical framework is created to simulate a combined photovoltaic (PV)-assisted CO2 heat pump (HP) with thermal energy storage (TES) to provide domestic hot water (DHW) for a district of 13 houses. Subsequently, this paper applies a mixed-integer nonlinear optimization approach to operating the system, employing a non-dominated sorting genetic algorithm (NSGA-II). The multi-objective optimization is performed to find the optimal trade-off between maximizing the coefficient of performance (COP) of the system and maximizing system self-sufficiency from a locally installed solar-PV system. Optimization is performed over 72 hours in the Fall, using Miami as a case study. The optimal time-resolved charging profiles and HP output water temperature as decision variables are extracted from the Pareto frontier. The results of the Pareto front show that when the system’s self-sufficiency goes up from 71% to 81%, the COP decreases slightly from 4.55 to 4.36. This means a 14% increase in self-sufficiency leads to a small 4.3% decrease in COP.
