Fixed Speed Wind Generator Model Parameter Estimation using Improved Particle Swarm Optimization and System Frequency
F Gonzalez-Longatt, P Regulski, P Wall, V Terzija, University of Manchester, UK
From: Renewable Power Generation, Edinburgh, UK, 6-8 September 2011. Developments in renewable power generation, including applications, systems integration and other technologies with a direct role in sustainable power generation. Developments in renewable power generation, including applications, systems integration and other technologies with a direct role in sustainable power generation.
08 September 2011 Power channel
>> Play webcastIn this paper an Improved Particle Swarm Optimization (IPSO) approach is used to estimate the model parameters of a fixed speed IG based on the inertial response.
Francisco M. Gonzalez-Longatt (SIEEE'01, MIEEE'03, SMIEEE' 2009) was born in Cagua-Venezuela, on July 30, 1972. He graduated on Electrical Engineering of Instituto Universitario Politecnico de la Fuerza Armada Nacional, Venezuela (1994), and Master of Business Administration of Universidad Bicentenaria de Aragua, Venezuela (1999) and PhD of Universidad Central de Venezuela (2008). His main area of interest is integration of intermittent/variable renewable energy resources into smart grids with special interest on frequency behaviour. He is former associate professor on Electrical engineering Department of Universidad Nacional Politecnico de la Fuerza Armada Nacional, Venezuela. He is vice-president of the Venezuelan Wind Energy Association. He is currently a Post Doctoral Associate Research School of Electrical and Electronic Engineering, The University of Manchester.