Techno-economic-environmental decision-making approach for the adoption of solar and natural gas-based trigeneration systems

Trigeneration systems have the ability to mitigate greenhouse gas emissions as well as result in cost savings, especially in high utility-cost markets. However, sometimes decision-making to adopt a trigeneration system can be complicated due to variations in load demand profiles and locations. The present paper is aimed at developing a generalized decision-making framework to estimate the optimal sizing as per diverse hourly building loads as well as the economic and environmental viability of natural gas and solar-based trigeneration systems. Unlike the existing literature, the decision-making approach has been demonstrated on eight different building types in five North American locations with high utility cost and rebates. EnergyPlus is used to determine the yearlong hourly energy demand of different buildings and then incorporate demand profiles to develop various sizing scenarios. To assist decision-making, economic criteria are proposed based on utility-rate structures to estimate payback periods and use the levelized cost of energy (LCOE) analysis. Incorporating environmental analysis in the decision-making process, location-specific utility scale emissions and emissions from trigeneration systems are considered. For solar-based trigeneration systems, the max area sizing scenario is found to be advantageous for buildings with higher ground-to-floor area ratios (i.e., supermarkets and secondary schools). However, for natural gas-powered trigeneration systems, two sizing scenarios are proposed (i.e., electricity sizing and heat sizing), and multiple micro-combined heat and power units are found to be preferable for various building ap-plications. Solar trigeneration systems offered the fastest payback in vertical farms, and hospitals (the average varies from 5.4 to 9.0 years), while natural gas-based trigeneration systems had the best payback in hospitals, vertical farms, and secondary schools (the average varies from 5.7 to 8.1 years). The environmental performance of the trigeneration system varied based on the building and location combinations, thus decision-making is strongly influenced by grid greenhouse gas emissions. The proposed decision-making method can be generalized and applied to other locations to determine the most viable building applications for solar and natural gas-based trigeneration systems.