Optimal Management of Reactive Power Sources in Far-offshore Wind Power Plants

Conference paper (2017)

Authors

A.M. Theologi Intelligent Electrical Power Grids - , Aristotle University of Thessaloniki

M. Ndreko Intelligent Electrical Power Grids -

José L. Rueda Intelligent Electrical Power Grids -

M.A.M.M. van der Meijden TenneT TSO B.V., Intelligent Electrical Power Grids -

Francisco Gonzalez-Longatt Loughborough University

Research Group

Intelligent Electrical Power Grids () (TU Delft)

On-load tap changer Mean-variance mapping optimization Optimal reactive power management

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http://resolver.tudelft.nl/uuid:5484d7d2-50a1-43c2-b4d0-21874b831dcc

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Published Date

2017-6

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Electrical Sustainable Energy

Research Group

Intelligent Electrical Power Grids

Abstract

This paper introduces a new approach for the optimal management of reactive power, with emphasis on offshore wind power plants. The approach follows a predictive optimization scheme (i.e. day-ahead, intraday application).
Predictive optimization is based on the principle of minimizing the real power losses, as well the number of On-load Tap Changer (OLTC) operations for daily time horizon (discretized in 24 hours). The mixed-integer nature of the problem and the restricted computing budget is tackled by using an emerging
metaheuristic algorithm called Mean-Variance Mapping Optimization (MVMO). The evolutionary mechanism of MVMO is enhanced by introducing a new mapping function, which improves its global search capability. The effectiveness of MVMO to find solutions that ensure minimum losses, minimum impact on OLTC lifetime, and well as optimal grid code compliance is demonstrated by investigating the case of a real world far-offshore wind power plant with HVDC connection.

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