A numerical pinch analysis methodology for optimal sizing of a centralized trigeneration system with variable energy demands

The energy and power sectors are critical sectors, especially as energy demands rise every year. Increasing energy demand will lead to an increase in fuel consumption and CO2 emissions. Improving the thermal efficiency of conventional power systems is one way to reduce fuel consumption and carbon emissions. The previous study has developed a new methodology called Trigeneration System Cascade Analysis (TriGenSCA) to optimise the sizing of power, heating, and cooling in a trigeneration system for a Total Site system. However, the method only considered a single period on heating and cooling demands. In industrial applications, there are also batches, apart from continuous plants. The multi-period is added in the analysis to meet the time constraints in batch plants. This paper proposes the development of an optimal trigeneration system based on the Pinch Analysis (PA) methodology by minimizing cooling, heating, and power requirements, taking into account energy variations in the total site energy system. The procedure involves seven steps, which include data extraction, identification of time slices, Problem Table Algorithm, Multiple Utility Problem Table Algorithm, Total Site Problem Table Algorithm, TriGenSCA, and Trigeneration Storage Cascade Table (TriGenSCT). An illustrative case study is constructed by considering the trigeneration Pressurized Water Reactor Nuclear Power Plant (PWR NPP) and four industrial plants in a Total Site system. Based on the case study, the base fuel of the trigeneration PWR NPP requires 14 t of Uranium-235 to an average demand load of 93 GWh/d. The results of trigeneration PWR NPP with and without the integration of the Total Site system is compared and proven that trigeneration PWR NPP with integration is a suitable technology that can save up to 0.2% of the equivalent annual cost and 1.4% of energy compared to trigeneration PWR NPP without integration