Simulation of Tri-generation Systems with application of optimization

Abstract: Despite the fact that cogeneration (CHP) and tri-generation (CHCP) are among the most efficient ways to produce electricity and thermal energy, there is still some unexploited potential for these techniques. One could say that the circumstances for using these techniques are better now than ever. Some of the reasons for applying CHP and CHCP are: the techniques are well understood, their application could generate some profit, and the required technology is available. Moreover, there is increasing concern in regards to energy security, the need to increase the energy efficiency in power generation and distribution as well as to lower the emissions from fossil fuel combustion. CHP/CHCP promoters and developers face difficulties when analyzing the conditions and proposing a plan of application. On one hand, there are some external barriers which have to be torn down by means of energy regulation schemes. These may include economic incentives, easy and safe interconnection to the grid to export electricity and have backup if necessary, and access to the market to sell the surplus of electricity at a fair price. On the other hand, there are some internal barriers such as the difficulty evaluating potential energy savings, emission reduction, and economic performance of a project based on the circumstances of a specific site; lack of awareness; unwillingness to invest in CHP/CHCP projects; and difficulty in selecting and sizing the equipment which would give the maximum benefits in terms of life cycle cost, energy savings and emission reduction. Nowadays, it is possible to develop software tools which use simulations and optimization algorithms to evaluate several options, compare them and chose the ones that give the optimum performance with respect to an objective function defined by the user. In this project, the general context for the application of cogeneration and tri-generation projects was studied including factors which have an impact on its feasibility and performance. Moreover, a survey of the exiting feasibility analysis tools was done, and a case study was chosen and analyzed. Next, a model was developed using the software Trnsys for the simulation and Matlab for the optimization. The model was tested by evaluating the study case. The result of the simulation and optimization gives several possible equipment size combinations. The tradeoff between two different objective functions such as net present value and primary energy savings or emission reduction is presented in Pareto front diagrams. The main conclusion of this project is that by using Trnsys and Matlab, it is possible to develop more complex models which, when applying optimization algorisms, could become a very useful and helpful tool that CHP/CHCP developers could use to speed up the analysis of projects while contributing to the goal of deploying these techniques.