Multi-objective design and optimization of district energy systems including polygeneration energy conversion technologies

In the present context of finding ways to decrease CO2 emissions linked with human activity, district energy systems including polygeneration energy conversion technologies are likely to play a major role. District energy systems meet the heating, hot water, cooling and electricity requirements of a district. Because they meet several types of energy requirements, and for more than one single building, district energy systems represent good opportunities to implement polygeneration energy conversion technologies. Polygeneration energy conversion technologies indeed provide different energy services simultaneously, helping to decrease the CO2 intensity compared to energy conversion technologies that meet only one energy service. Moreover, when providing energy to a whole district, polygeneration energy conversion technologies can take advantage of the various load profiles of the buildings by compensating the fluctuations and having therefore a smoother operation. A district energy system comprises essentially two parts: the plant with the polygeneration energy conversion technologies, and the distribution networks (heating and cooling). When designing the energy system for a district, one has therefore to define which type of polygeneration energy conversion technologies are best suited for the district, as well as which building are worse connecting to the system and which buildings shouldn't be connected (for instance if they are located too far away from the other buildings or if they have too small requirements to justify a connection from the plant). Moreover the operation strategy needs to be defined. In the present thesis, a method is developed that helps designing and optimizing district energy systems, from the structuring of the information available for the district (energy consumption profiles, location of the buildings, available energy sources, possible layouts for the pipes,...), over the thermo-economic modelling of the energy conversion technologies, the design of the network and the simulation of its operation strategy, and finally the evaluation of the results in terms of CO2 emissions and costs. The design and optimization of the district energy system is a multi-objective Mixed Integer Non Linear Programming problem. To solve this problem, a decomposition strategy including a master and a slave problem was developed. The master optimization problem takes care of the energy conversion technologies, whereas the slave optimization problem optimizes the network part. The two sub-problems are solved iteratively and result in the definition of a Pareto optimal curve that gives the trade-offs between the emissions and the costs for various configurations satisfying the requirements of the district. A configuration is characterized by given types and sizes of energy conversion technologies, their location in the district, the network layout, as well as the operation strategy of the technologies. Due to the time dependent energy consu