OMEGAlpes: Decision support tool for an optimal multi-carriers energy planning at the district scale

Mostly responsible for climate change, the energy sector is particularly targeted and energy transition policies are emerging, based on the principles of sobriety, efficiency and low-carbon energy production. Energy systems need to adapt quickly to these changes and be designed to consider a multi-energy approach and demand-side management strategies. In this context, this thesis proposes to develop a methodology and an associated decision support tool OMEGAlpes, offering the different energy actors an aid to design, size, and manage energy systems at the district level. First, an optimal energy planning approach will be developed. A methodology, based on power balances will then be presented, to treat generically study cases about energy planning at the district scale, and then illustrated on a case of wasted heat recycling. Consumption models based on statistical approaches will then be used to represent temporal flexibility scenarios (load shifting). An alternative to this data approach, based on the physical modeling of buildings, will then be presented through the use of reduced thermal models. Finally, all of these models will be capitalized within an automatic generation tool for optimization models, based on a methodology for building energy models from generic elements. The development of this open source tool, in Python language, and the principle of automatic generation of models will finally be detailed. (author)