Showing papers by "Euan Davidson published in 2010"

AuRA-NMS: An autonomous regional active network management system for EDF energy and SP energy networks

Abstract: This paper discusses the authors' experience of developing an active network management system for use by two different distribution network operators (DNOs) in the UK with differing network management requirements. The paper describes the fundamental building blocks of AuRA-NMS (autonomous regional active network management system) and how their development was driven by the requirements of the partner DNOs. Practical experience of use of AI techniques to provide AuRA-NMS with its required intelligence and how that intelligence was distributed within the network is discussed. The paper also discusses the different deployment approaches taken by the two DNOs.

Distributed voltage control in AuRA-NMS

Abstract: This paper presents real time test results arising from the application of a case based reasoning technique for voltage control of a section of existing UK 11kV network. The test network includes two distributed generation schemes. The objective of the case based reasoning technique is to maintain voltages within statutory limits while also maximizing the DG access to the network. The control algorithm is embedded on a commercially available hardware platform designed for installation in power system substations. The case based reasoning technique employs the following control actions to achieve its objectives: DG real power control, DG reactive power control and transformer tap change control. The voltage control technique is tested during over-voltage conditions and for situations where only partial sensor data is available.

The role of intelligent systems in delivering the Smart Grid

Abstract: 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.

Agents for active network management and condition monitoring in the smart grid

Abstract: Recent interest in the smart grid or intelligent grid concept focuses on the desired capabilities of future energy networks, without much consideration of how to transition from current networks to the smart grid of tomorrow This paper explores the required functionality and capability of an intelligent network management system, and shows how agent technology can address these needs Agents can provide the platform for staged deployment of smart grid functionality, allowing the integration of current equipment and systems while remaining extensible for future developments This paper describes how agent technology can be used to achieve this goal

Minimisation of distribution network real power losses using a smart grid Active Network Management System

Abstract: Network losses in electrical power delivery systems contribute, in-directly, to carbon emissions. Global and national carbon reduction programmes are crucial to meeting obligatory targets. In the UK, the Office of Gas and Electricity Markets (Ofgem) recognise the impact of distribution network power losses and offer incentives to operators to reduce emissions through the published Distribution Price Control Reviews (DPCR). With this increasing pressure upon distribution network operators (DNOs), the development of loss minimisation tools for the purpose of real time evaluation and control strategies for loss reduction could add value over the traditional methods used. This paper will build upon the research carried out within the Autonomous Regional Active Network Management System (AuRA-NMS) project with the scope of implementing a distribution network real power loss management algorithm. Results from development and integration, within a closed loop simulation environment on commercially available substation computing hardware, are presented.

Distributed Generation access and power flow management

Abstract: Connection of Distributed Generation brings about a need to manage operation of distribution networks in a way that is more active. In order to allow for this change, DNOs need to devise strategies of how to manage generator outputs so to facilitate connection of renewable resources and maximize use of network assets. The paper will look into different techniques that allow for this type of operation and analyze possible directions of transitions form current operation strategies used in active power flow management, towards possible new approaches.

Progress in the development of adaptive control for shipboard power systems through modeling and simulations

Abstract: This paper reports on work being conducted on the development of an adaptive control scheme for the proposed zonal Medium Voltage AC and Medium Voltage DC shipboard power systems. These systems are modeled in high fidelity on a Real Time Digital Simulator. Extending the authors' previous work on locating faults using machine learning algorithms, different zonal loadings are simulated on the Medium Voltage AC system to determine how well those algorithms can generalize to previously unseen data. In addition to these system level faults, this paper considers the simulation of faults within power converter modules. The paper also outlines future work, which includes the simulation of the Medium Voltage DC shipboard power system, diagnostic platform integration with the Real Time Digital Simulator to allow real time verification of control schemes and the generation of hardware fault data to validate simulation results.