Multi-Objective Optimisation of District Energy Systems

In the context of finding efficient and environmentally friendly solutions to energy pro- duction and consumption, this work presents a method for the systematic resolution of district energy problems using Multi-Objective Optimisation (MOO) methods. A district energy problem consists in matching the demand in energy of a district with a supply from adapted technologies while minimising environmental and economic objectives. In minimisation, these terms often oppose each other, which means that there is no single correct solution, but rather a multitude of possibilities. Multi-Objective Optimisation (MOO) is therefore necessary in order to find these sets of good solutions in the form of a Pareto frontier. The novelty of this work lies in three major aspects. Firstly, as this work deals with a multi-time approach, a tool is developed allowing for the systematic creation of typical days which reduce the complexity of the MOO. Secondly, post-analysis tools allowing for detailed study of solutions are developed in the form of a global sensitivity analysis. Thirdly a hybrid yearly hour-by-hour simulation tool is developed using MILP optimisa- tion methods. The first part of this work concerns a review of the methods for resolving such a district heating system. Secondly, the development of tools and methods for the implementa- tion of this MOO is undertaken in the form of Evolutionary Multi-Objective Algorithms (EMOO). Tools allowing for a more detailed analysis of specific solutions are also de- veloped. These include tools for the study of specific scenarios, sensitivity analyses and hour-by-hour simulations of the system. This is followed by the development of a database of technologies to be simulated within the context of an EMOO. Conventional energy pro- ducing technologies (boilers, engines, turbines) as well as more environmentally friendly ones (heat pumps, storage systems, solar power) are considered here. Finally, a case study using accurate economical and environmental data obtained from Veolia Environ- ment Research & Innovation (VERI) validates the developed methodology, and provides useful information to engineers working on the project. The data obtained from VERI serves for the Case Study and elaboration of a database it is however confidential.