Renewable energy integration into diesel generation systems for remote island communities is a rapidly growing energy engineering field. Fuel supply issues are becoming more common and the disruption, instability and panic caused by fuel shortages results in inefficient and unreliable power supplies for remote island communities. This thesis develops an energy engineering approach for meeting renewable energy development, supply security, cost and sustainability objectives. The approach involves adapting proven energy engineering techniques including energy auditing, energy system modelling with basic cost analysis and demand side management. The novel aspect of this research is the development of critical load engineering in the system design, and informing this with an assessment of essentiality of energy services during the audit phase. This approach was prompted by experiences with previous fuel shortages and long term sustainability policy drivers. The methodology uses the most essential electric loads as the requirement for sizing the renewable energy capacity in the hybrid system. This approach is revolutionary because communication with the customers about availability and the need to shed non-essential loads helps to both meet cost and security requirements and to reduce levels of panic and uncertainty when fuel supply issues arise. A sustainable power generation system is a system that provides continuity of supply for electrical appliances that are considered by the residents to be essential and for which adaptability and resilience of behaviour were key design priorities over growth. The sustainable electrical energy supply should match the critical (essential) load and should have the ability to continue without major disruptions to the daily lives of the people in these communities. Essential energy end uses were identified through energy audits and surveys. The electric power system is designed so that renewable energy sources alone can meet that “essential” demand with a plant that is both economically and technically feasible. Diesel generators were supplemented to meet the short fall in meeting the unconstrained electric demand. This is to design a system that is generally competitive with the present conventional power generation. This method should be particularly suitable for handling the complexities of a modern-day energy system in terms of planning a sizable sustainable energy and electricity system, either based on wholly sustainable sources or integrating sustainable sources of energy into a conventional generation system. The final hybrid system chosen after numerous simulations for the case study (Fenfushi island in the Maldives) community has the minimum renewable energy sources to meet the essential load but uses diesel to supplement the present load. A variety of design parameters such as PV size, wind turbine sizes and numbers and battery capacity have been considered. The minimum renewable energy sources to supply the essential loads of the community were simulated with diesel generators to find the optimal supply mix for the present load (typical unconstrained demand). The final outcome has the following characteristics: NPC and COE were $1,532,340 and $0.37/kWh respectively, lower than any diesel-only systems that could supply the demand. The total annual electricity production is 386,444 units (kWh), of which 9.61% is excess electricity and the annual operating cost is $68,688. Compared to the diesel-only systems there is a fuel savings of 77,021 litres of diesel per year, which is a 66.5 % reduction. An annual carbon dioxide emission reduction of 202,824 kg was achieved, which is a reduction of 66.5%. An annual renewable energy contribution of 70% would be achieved, 34% of which would be from PV arrays and 36% from wind turbines. The selected system shows that even with 30 percent power supply from diesel generators, still the highest NPC is on diesel generation for a life of over 25 years.

La conception de systèmes temps-réel embarqués se développe de plus en plus avec l’intégration croissante de fonctionnalités critiques pour les applications de surveillance, notamment dans le domaine biomédical, environnemental, domotique, etc. Le développement de ces systèmes doit relever divers défis en termes de minimisation de la consommation énergétique. Gérer de tels dispositifs embarqués, entièrement autonomes, nécessite cependant de résoudre différents problèmes liés à la quantité d’énergie disponible dans la batterie, à l’ordonnancement temps-réel des tâches qui doivent être exécutées avant leurs échéances, aux scénarios de reconfiguration, particulièrement dans le cas d’ajout de tâches, et à la contrainte de communication pour pouvoir assurer l’échange des messages entre les processeurs, de façon à assurer une autonomie durable jusqu’à la prochaine recharge et ce, tout en maintenant un niveau de qualité de service acceptable du système de traitement. Pour traiter cette problématique, nous proposons dans ces travaux une stratégie de placement et d’ordonnancement de tâches permettant d’exécuter des applications temps-réel sur une architecture contenant des cœurs hétérogènes. Dans cette thèse, nous avons choisi d’aborder cette problématique de façon incrémentale pour traiter progressivement les problèmes liés aux contraintes temps-réel, énergétique et de communications. Tout d’abord, nous nous intéressons particulièrement à l’ordonnancement des tâches sur une architecture mono-cœur. Nous proposons une stratégie d’ordonnancement basée sur le regroupement des tâches dans des packs pour pouvoir calculer facilement les nouveaux paramètres des tâches afin de réobtenir la faisabilité du système. Puis, nous l’avons étendu pour traiter le cas de l’ordonnancement sur une architecture multi-cœurs homogènes. Finalement, une extension de ce dernier sera réalisée afin d’arriver à l’objectif principal qui est l’ordonnancement des tâches pour les architectures hétérogènes. L’idée est de prendre progressivement en compte des contraintes d’exécution de plus en plus complexes. Nous formalisons tous les problèmes en utilisant la formulation ILP afin de pouvoir produire des résultats optimaux. L’idée est de pouvoir situer nos solutions proposées par rapport aux solutions optimales produites par un solveur et par rapport aux autres algorithmes de l’état de l’art. Par ailleurs, la validation par simulation des stratégies proposées montre qu’elles engendrent un gain appréciable vis-à-vis des critères considérés importants dans les systèmes embarqués, notamment le coût de la communication entre cœurs et le taux de rejet des tâches. / The design of embedded real-time systems is developing more and more with the increasing integration of critical functionalities for monitoring applications, particularly in the biomedical, environmental, home automation, etc. The developement of these systems faces various challenges particularly in terms of minimizing energy consumption. Managing such autonomous embedded devices, requires solving various problems related to the amount of energy available in the battery and the real-time scheduling of tasks that must be executed before their deadlines, to the reconfiguration scenarios, especially in the case of adding tasks, and to the communication constraint to be able to ensure messages exchange between cores, so as to ensure a lasting autonomy until the next recharge, while maintaining an acceptable level of quality of services for the processing system. To address this problem, we propose in this work a new strategy of placement and scheduling of tasks to execute real-time applications on an architecture containing heterogeneous cores. In this thesis, we have chosen to tackle this problem in an incremental manner in order to deal progressively with problems related to real-time, energy and communication constraints. First of all, we are particularly interested in the scheduling of tasks for single-core architecture. We propose a new scheduling strategy based on grouping tasks in packs to calculate the new task parameters in order to re-obtain the system feasibility. Then we have extended it to address the scheduling tasks on an homogeneous multi-core architecture. Finally, an extension of the latter will be achieved in order to realize the main objective, which is the scheduling of tasks for the heterogeneous architectures. The idea is to gradually take into account the constraints that are more and more complex. We formalize the proposed strategy as an optimization problem by using integer linear programming (ILP) and we compare the proposed solutions with the optimal results provided by the CPLEX solver. Inaddition, the validation by simulation of the proposed strategies shows that they generate a respectable gain compared with the criteria considered important in embedded systems, in particular the cost of communication between cores and the rate of new tasks rejection.