A decision support system for fostering smart energy efficient districts

The role of ICT is becoming prominent in tackling some of the urban societal challenges such as energy wastage and increasing carbon emissions. In this context, the concept of DAREED aims to deliver an integrated decision support system (DSS) to drive energy efficiency and low carbon activities at both a building and district level. The main aim of this paper is to present the technical concept of the Best Practices recommendation component of the DAREED system. This component seeks to compare and identify existing best practices to recommend practical actions to various stakeholders (e.g. building managers, citizens) in order to improve energy performance considering the global needs of a building. This paper also discusses the context of the three field trial sites (based in UK, Spain and Italy) in which the DAREED platform along with the best practices tool is to be tested and validated.This work evolved in the context of the project DAREED (Decision support Advisor for innovative business models and useR engagement for smart Energy Efficient Districts), www.dareed.eu, a project cofunded by the EC within FP7, Grant agreement no: 609082

Exploiting multi-agent system technology within an autonomous regional active network management system

This paper describes the proposed application of multi-agent system (MAS) technology within AuRA-NMS, an autonomous regional network management system currently being developed in the UK through a partnership between several UK universities, distribution network operators (DNO) and a major equipment manufacturer. The paper begins by describing the challenges facing utilities and why those challenges have led the utilities, a major manufacturer and the UK government to invest in the development of a flexible and extensible active network management system. The requirements the utilities have for a network automation system they wish to deploy on their distribution networks are discussed in detail. With those requirements in mind the rationale behind the use of multi-agent systems (MAS) within AuRA-NMS is presented and the inherent research and design challenges highlighted including: the issues associated with robustness of distributed MAS platforms; the arbitration of different control functions; and the relationship between the ontological requirements of Foundation for Intelligent Physical Agent (FIPA) compliant multi-agent systems, legacy protocols and standards such as IEC 61850 and the common information model (CIM)

The role of intelligent systems in delivering the smart grid

The development of "smart" or "intelligent" energy networks has been proposed by both EPRI's IntelliGrid initiative and the European SmartGrids Technology Platform as a key step in meeting our future energy needs. A central challenge in delivering the energy networks of the future is the judicious selection and development of an appropriate set of technologies and techniques which will form "a toolbox of proven technical solutions". This paper considers functionality required to deliver key parts of the Smart Grid vision of future energy networks. The role of intelligent systems in providing these networks with the requisite decision-making functionality is discussed. In addition to that functionality, the paper considers the role of intelligent systems, in particular multi-agent systems, in providing flexible and extensible architectures for deploying intelligence within the Smart Grid. Beyond exploiting intelligent systems as architectural elements of the Smart Grid, with the purpose of meeting a set of engineering requirements, the role of intelligent systems as a tool for understanding what those requirements are in the first instance, is also briefly discussed

Integration of Legacy Appliances into Home Energy Management Systems

The progressive installation of renewable energy sources requires the coordination of energy consuming devices. At consumer level, this coordination can be done by a home energy management system (HEMS). Interoperability issues need to be solved among smart appliances as well as between smart and non-smart, i.e., legacy devices. We expect current standardization efforts to soon provide technologies to design smart appliances in order to cope with the current interoperability issues. Nevertheless, common electrical devices affect energy consumption significantly and therefore deserve consideration within energy management applications. This paper discusses the integration of smart and legacy devices into a generic system architecture and, subsequently, elaborates the requirements and components which are necessary to realize such an architecture including an application of load detection for the identification of running loads and their integration into existing HEM systems. We assess the feasibility of such an approach with a case study based on a measurement campaign on real households. We show how the information of detected appliances can be extracted in order to create device profiles allowing for their integration and management within a HEMS

User centered neuro-fuzzy energy management through semantic-based optimization

This paper presents a cloud-based building energy management system, underpinned by semantic middleware, that integrates an enhanced sensor network with advanced analytics, accessible through an intuitive Web-based user interface. The proposed solution is described in terms of its three key layers: 1) user interface; 2) intelligence; and 3) interoperability. The system’s intelligence is derived from simulation-based optimized rules, historical sensor data mining, and a fuzzy reasoner. The solution enables interoperability through a semantic knowledge base, which also contributes intelligence through reasoning and inference abilities, and which are enhanced through intelligent rules. Finally, building energy performance monitoring is delivered alongside optimized rule suggestions and a negotiation process in a 3-D Web-based interface using WebGL. The solution has been validated in a real pilot building to illustrate the strength of the approach, where it has shown over 25% energy savings. The relevance of this paper in the field is discussed, and it is argued that the proposed solution is mature enough for testing across further buildings