Development of a Decision Support System to Facilitate Multi-criteria Decision Making during Humanitarian Operation within a Project Life Cycle

Part III: Sustainable ServicesInternational audienceThe use of decision support systems is an important part of supply chain management. Quick and adequate decision making is sometimes difficult to achieve. Three issues arise: how to gather relevant data and use past experiences, how to make the decision when many criteria have to be taken into account and how can we ensure that the decision making process is quick. Those three issues are currently faced by many companies and some solutions have already been proposed in the literature. Yet, in some cases, it is difficult, if not possible to apply those solutions. Humanitarian organizations, for example, have difficulties to build on past experiences. Quick decision making in this sector is vital. The purpose of this paper is to design and develop decision-making tool to support the performance of humanitarian logistics. A case study at the French Red Cross will validate this proposal

Smart households and home energy management systems with innovative sizing of distributed generation and storage for customers

As a recently increasing trend among different applications of smart grid vision, smart households as a new implementation area of demand response (DR) strategies have drawn more attention both in research and in engineering practice. On the other hand, optimum sizing of renewable energy based small scale hybrid systems is also a topic that is widely covered by the existing literature. In this study, the sizing of additional distributed generation and energy storage systems to be applied in smart households, which due to DR activities have a different daily demand profile compared with normal household profiles, is investigated. To the best knowledge of the authors, this is the first attempt in the literature to consider the impact of DR on sizing. The study is conducted using a mixed-integer linear programming framework for home energy management system modeling and techno-economical sizing. Also, different sensitivity analyses considering the impacts of variation of economic inputs on the provided model are realized