Integrated modelling framework for the analysis of demand side management strategies in urban energy systems

Influenced by environmental concerns and rapid urbanisation, cities are changing the way they historically have produced, distributed and consumed energy. In the next decades, cities will have to increasingly adapt their energy infrastructure if new low carbon and smart technologies are to be effectively integrated. In this context, advanced planning tools can become crucial to successfully design these future urban energy systems. However, it is not only important to analyse how urban energy infrastructure will look like in the future, but also how they will be operated. Advanced energy management strategies can increase the operational efficiency, therefore reducing energy consumption, CO2 emissions, operational costs and network investments. However, the design and analysis of these energy management strategies are difficult to perform at an urban scale considering the spatial and temporal resolution and the diversity in users energy requirements. This thesis proposes a novel integrated modelling framework to analyse flexible transport and heating energy demand and assess different demand-side management strategies in urban energy systems. With a combination of agent-based simulation and multi-objective optimisation models, this framework is tested using two case studies. The first one focuses on transport electrification and the integration of electric vehicles through smart charging strategies in an urban area in London, UK. The results of this analysis show that final consumer costs and carbon emissions reductions (compared to a base case) are in the range of 4.3-45.0% and 2.8-3.9% respectively in a daily basis, depending on the type of tariff and electricity generation mix considered. These reductions consider a control strategy where the peak demand is constrained so the capacity of the system is not affected. In the second case study, focused on heat electrification, the coordination of a group of heat pumps is analysed, using different scheduling strategies. In this case, final consumer costs and carbon emissions can be reduced in the range of 4-41% and 0.02-0.7% respectively on a daily basis. In this case, peak demand can be reduced in the range of 51-62% with respect to the baseline. These case studies highlight the importance of the spatial and temporal characterisation of the energy demand, and the level of flexibility users can provide to the system when considering a heterogeneous set of users with different technologies, energy requirements and behaviours. In both studies, trade-offs between the environmental and economic performance of demand-side management strategies are assessed using a multi-objective optimisation approach. Finally, further applications of the integrated modelling framework are described to highlight its potential as a decision-making support tool in sustainable and smart urban energy systems.Open Acces

Steps Towards Simulating Smart Cities and Smart Islands with a Shared Generic Framework - A Case Study of London and Reunion Island

International audienceSimulation models can be used as decision support tools for smart city design and planning. They allow to evaluate the possible consequences of projects, before their implementation in the real world. Decision makers could benefit from replicable ones that can be relevant and easily transferable from one territory to another so solutions can be compared and re-use of model components can save time. In this paper we consider the case of citizen’s mobility flow simulation. However, most of such simulation models are designed to be suitable for a specific kind of territory. Some of them are reusable, but in a context that does not differ much from the original one for which they were designed, or require lots of changes to be relevant in another context. We classify those contexts into urban and insular and we show that despite their difference, they could be complementary. We demonstrate that testing a simulation model designed for an urban context, in a context with strong constraints can help in its consolidation. Thereby, after testing an Agent Based Simulation Model originally applied to a case study in London, in Reunion Island, we present a more generic simulation model that works for both systems

Hierarchical price coordination of heat pumps in a building network controlled using model predictive control

status: publishe