Synthesis of Trigeneration Systems: Sensitivity Analyses and Resilience

Abstract

This paper presents sensitivity and resilience analyses for a trigeneration system designed for a hospital. The following information is utilized to formulate an integer linear programming model: (1) energy service demands of the hospital, (2) technical and economical characteristics of the potential technologies for installation, (3) prices of the available utilities interchanged, and (4) financial parameters of the project. The solution of the model, minimizing the annual total cost, provides the optimal configuration of the system (technologies installed and number of pieces of equipment) and the optimal operation mode (operational load of equipment, interchange of utilities with the environment, convenience of wasting cogenerated heat, etc.) at each temporal interval defining the demand. The broad range of technical, economic, and institutional uncertainties throughout the life cycle of energy supply systems for buildings makes it necessary to delve more deeply into the fundamental properties of resilient systems: feasibility, flexibility and robustness. The resilience of the obtained solution is tested by varying, within reasonable limits, selected parameters: energy demand, amortization and maintenance factor, natural gas price, self-consumption of electricity, and time-of-delivery feed-in tariffs.

A simple methodology for capacity sizing of cogeneration and trigeneration plants in hospitals: A case study for a university hospital

“…E c is the cogenerated electricity, F c is the consumption of natural gas measured by its LHV, and Q cc is the cogenerated useful heat. 40 In the case study of the University Hospital, primary energy savings were calculated as 41.14% for the cogeneration plant. All studies and calculations indicate that a trigeneration plant with double-effect absorption chiller, cooling tower, and electrically synchronized from high voltage level can seem a very sensible investment for University Hospital according to the calculations due to the above cooling, heat, and electrical energy consumptions, but the hospital infrastructure is not conformable to implement a trigeneration centre.…”

Performance comparison of energy supply systems under uncertain energy demands based on a mixed-integer linear model

“…(2) is sufficient. Therefore, the following optimization problem is investigated here: (5) This optimization problem cannot be solved easily because of hierarchical operations of minimization and maximization as well as not only continuous but also integer variables.…”

“…Wang et al conducted a sensitivity analysis of the optimal design of a building energy system with respect to the changes in energy demands and others, and they used the genetic algorithm to solve the optimization problem [4]. Carvalho et al conducted a sensitivity analysis to investigate the resilience of the optimal design of an energy system for a hospital with respect to the changes in energy demands and others, and they used a MILP approach for optimization [5]. To conduct such a sensitivity analysis, scenarios for the change in energy demands are inevitable.…”

State-Of-The-Art Review of Mathematical Optimisation Approaches for Synthesis of Energy Systems

“…In this work (Carvalho et al 2012), optimal solutions are obtained and analysed via a Pareto Front. This work was then extended by incorporating a sensitivity analysis on electricity prices toward the optimal configuration (Carvalho et al 2013). Similarly, Buoro et al (2013) developed a MOO approach to obtain the optimal structure, capacity and operational strategy of an industrial co-generation system.…”