Building resilience for social-ecological sustainability in Atlantic Europe

This thesis argues that complex adaptive social–ecological systems (SES) theory has important implications for the design of integrated ocean and coastal governance in the EU. Traditional systems of governance have struggled to deal with the global changes, complexity and uncertainties that challenge a transition towards sustainability in Europe’s maritime macro-regions. There is an apparent disconnect between governance strategies for sustainability in Europe’s maritime macro-regions and a sound theoretical basis for them. My premise is that the design of governance architecture for maritime regional sustainability should be informed by SES theory. Therefore, the aim of this research was to gain insight into a multilevel adaptive governance architecture that combines notions of sustainability and development in the context of the Atlantic Europe maritime macro-region. The central research question asked whether it is possible to achieve this insight by using a SES as a framework and analytical tool. This research adopted social ecology and sustainability science as a foundation for understanding society–nature relations. Concepts from complex adaptive systems, SES and resilience theories were integrated into a conceptual framework that guided the investigation and analysis. A study was conducted to conceptualise the European Atlantic social–ecological system (EASES). This was used to represent and understand the Atlantic Europe macro-region as a SES. The study examined the proposition that governance can be focused on building SES resilience to help achieve maritime regional sustainability. A workbook method was developed and used to elicit expert opinion regarding EASES. The study identified sources of resilience and resilience dynamics that require management in the context of multilevel adaptive governance. This research found that the Atlantic Europe macro-region is a key focal level for multilevel adaptive governance architecture. The majority of the findings are specific to Atlantic Europe and not generalisable to other maritime macro-regions in Europe.

Modelling and predictive control techniques for building heating systems

Model predictive control (MPC) has often been referred to in literature as a potential method for more efficient control of building heating systems. Though a significant performance improvement can be achieved with an MPC strategy, the complexity introduced to the commissioning of the system is often prohibitive. Models are required which can capture the thermodynamic properties of the building with sufficient accuracy for meaningful predictions to be made. Furthermore, a large number of tuning weights may need to be determined to achieve a desired performance. For MPC to become a practicable alternative, these issues must be addressed. Acknowledging the impact of the external environment as well as the interaction of occupants on the thermal behaviour of the building, in this work, techniques have been developed for deriving building models from data in which large, unmeasured disturbances are present. A spatio-temporal filtering process was introduced to determine estimates of the disturbances from measured data, which were then incorporated with metaheuristic search techniques to derive high-order simulation models, capable of replicating the thermal dynamics of a building. While a high-order simulation model allowed for control strategies to be analysed and compared, low-order models were required for use within the MPC strategy itself. The disturbance estimation techniques were adapted for use with system-identification methods to derive such models. MPC formulations were then derived to enable a more straightforward commissioning process and implemented in a validated simulation platform. A prioritised-objective strategy was developed which allowed for the tuning parameters typically associated with an MPC cost function to be omitted from the formulation by separation of the conflicting requirements of comfort satisfaction and energy reduction within a lexicographic framework. The improved ability of the formulation to be set-up and reconfigured in faulted conditions was shown.