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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.

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Optimal flexible alternative current transmission system device allocation under system fluctuations due to demand and renewable generation

Galloway, S. and Sookananta, B. and Elders, I.M. and Burt, G.M. (2010) Optimal flexible alternative current transmission system device allocation under system fluctuations due to demand and renewable generation. IEE Proceedings Generation Transmission and Distribution, 4 (6). pp. 725-735. ISSN 1350-2360

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Abstract

This study proposes two methods for the optimal placement of flexible alternative current transmission system (FACTS) devices considering variations in demand and renewable generation output. The basic optimisation technique utilised is the differential evolution algorithm and the objective is to minimise the cost of generation. The static performance of the FACTS device is considered here. Simulation shows that with renewable generation present in the network, the system state at peak demand is not always the most suitable state to use for the determination of the optimal FACTS allocation. From this, techniques based on the Monte Carlo simulation are proposed to determine the location for which the operation of FACTS device gives highest benefit in terms of saving cost of conventional generation. These techniques collectively are called renewable uncertainty-based optimal FACTS allocation techniques. This study shows the effectiveness of the techniques in the determination of the optimal FACTS placement for networks with a high penetration of renewable generation.