Picture map of Europe with pins indicating European capital cities

Open Access research with a European policy impact...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by Strathclyde researchers, including by researchers from the European Policies Research Centre (EPRC).

EPRC is a leading institute in Europe for comparative research on public policy, with a particular focus on regional development policies. Spanning 30 European countries, EPRC research programmes have a strong emphasis on applied research and knowledge exchange, including the provision of policy advice to EU institutions and national and sub-national government authorities throughout Europe.

Explore research outputs by the European Policies Research Centre...

Evaluating the robustness of an active network management function in an operational environment

Venturi, Alberto and Dolan, Michael James and Clarkson, Paul and Wright, Paul and Forbes, Alistair and Yang, Xin-She and Roscoe, Andrew and Ault, Graham and Burt, Graeme (2013) Evaluating the robustness of an active network management function in an operational environment. In: CIRED 2013, 22nd International Conference on Electricity Distribution, 2013-06-10 - 2013-06-13.

[img]
Preview
Text (Venturi-etal-CIRED-2013-Evaluating-the-robustness-of-an-active-network-management)
Venturi_etal_CIRED_2013_Evaluating_the_robustness_of_an_active_network_management.pdf - Accepted Author Manuscript

Download (703kB) | Preview

Abstract

This paper presents the integration process of a distribution network Active Network Management (ANM) function within an operational environment in the form of a Micro-Grid Laboratory. This enables emulation of a real power network and enables investigation into the effects of data uncertainty on an online and automatic ANM algorithm's control decisions. The algorithm implemented within the operational environment is a Power Flow Management (PFM) approach based around the Constraint Satisfaction Problem (CSP). This paper show the impact of increasing uncertainty, in the input data available for an ANM scheme in terms of the variation in control actions. The inclusion of a State Estimator (SE), with known tolerances is shown to improve the ANM performance.