On the modelling and optimisation of urban energy fluxes

Around 3/4 of global resources are currently consumed in urban settlements, with corresponding adverse environmental consequences. According to population forecasts this situation will worsen in the coming years. It is therefore imperative that we understand how to design less resource intensive urban settlements. Software for the modelling and optimisation of resource flows are of interest to support urban designers in achieving this objective. To this end we have, in the first instance, tackled the problem of optimising the layout and form of buildings for the utilisation of solar radiation by using a multi-objective evolutionary algorithm. This new methodology facilitates a considerably more exhaustive search of the parameter space than manual trial and error which has been favoured in past studies. However, multi-objective optimisers involve many redundant evaluations when only one objective (the energy consumption) and analytical constraints (the volume of the urban form has to remain within bounds) are taken into account. To resolve this, we developed a new evolutionary algorithm that avoids evaluations of potential solutions that violate constraints. This is a hybrid based of the CMA-ES and HDE evolutionary algorithms. This hybrid algorithm achieves 100% convergence to the global minimum relating to two highly multi-modal benchmark functions and good results compared to the multi-objective evolutionary algorithm previously used and to a hybrid of heuristic and direct search methods (PSO/HJ) for real-world problems. Key contributions have also been made to the development of a new urban energy modelling tool: CitySim. These contributions include a mono and multi-zone thermal model, which is linked to an HVAC model that takes into account the increased energy demands due to the use of air as medium for heating, cooling and fresh air supply. In order to complete the provision of heating/cooling as well as electricity, the most commonly used energy conversion systems are modelled. Outputs from these systems may also be coupled with a model of sensible/latent heat storage. Finally the new hybrid evolutionary algorithm was used to optimise the energy performance of a case study of 26 buildings in the Matthäus district (Basel) using CitySim as the energy modelling tool. The results indicated that air conditioning plant should not be necessary in Switzerland if occupants behave appropriately. Concrete strategies for minimising the primary energy demand for the case study were also identified subject to constrained investment capital. This demonstrated that optimally (environmentally) sustainable solutions can be found at the urban scale, to help guide urban designers' decisions.