Optimal management of reactive power sources in far-offshore wind power plants

This paper introduces a new approach for the optimal management of reactive power sources, which follows a predictive optimization scheme (i.e. day-ahead, intraday application). Predictive optimization is based to the principle of minimizing the real power losses, as well the number of On-load Tap C...

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Main Authors:	A.M. Theologi, M. Ndreko, Jose L. Rueda, M.A.M.M. Van Der Meijden, Francisco Gonzalez-Longatt
Format:	Default Conference proceeding
Published:	2017
Subjects:	Mechanical engineering not elsewhere classified Optimal reactive power management Mean-variance mapping optimization On-load tap changer Mechanical Engineering not elsewhere classified
Online Access:	https://hdl.handle.net/2134/25770
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id	rr-article-9549809
record_format	Figshare
spelling	rr-article-95498092017-01-01T00:00:00Z Optimal management of reactive power sources in far-offshore wind power plants A.M. Theologi (7207541) M. Ndreko (7207544) Jose L. Rueda (7206215) M.A.M.M. Van Der Meijden (7207547) Francisco Gonzalez-Longatt (1249602) Mechanical engineering not elsewhere classified Optimal reactive power management Mean-variance mapping optimization On-load tap changer Mechanical Engineering not elsewhere classified This paper introduces a new approach for the optimal management of reactive power sources, which follows a predictive optimization scheme (i.e. day-ahead, intraday application). Predictive optimization is based to the principle of minimizing the real power losses, as well the number of On-load Tap Changer (OLTC) operations for 24 time steps ahead. 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 (i.e. fast convergence and robustness against randomness in initialization and factors used in evolutionary operations) and the achievement of optimal grid code compliance are demonstrated by investigating the case of a far-offshore wind power plant, interconnected with HVDC link. 2017-01-01T00:00:00Z Text Conference contribution 2134/25770 https://figshare.com/articles/conference_contribution/Optimal_management_of_reactive_power_sources_in_far-offshore_wind_power_plants/9549809 CC BY-NC-ND 4.0
institution	Loughborough University
collection	Figshare
topic	Mechanical engineering not elsewhere classified Optimal reactive power management Mean-variance mapping optimization On-load tap changer Mechanical Engineering not elsewhere classified
spellingShingle	Mechanical engineering not elsewhere classified Optimal reactive power management Mean-variance mapping optimization On-load tap changer Mechanical Engineering not elsewhere classified A.M. Theologi M. Ndreko Jose L. Rueda M.A.M.M. Van Der Meijden Francisco Gonzalez-Longatt Optimal management of reactive power sources in far-offshore wind power plants
description	This paper introduces a new approach for the optimal management of reactive power sources, which follows a predictive optimization scheme (i.e. day-ahead, intraday application). Predictive optimization is based to the principle of minimizing the real power losses, as well the number of On-load Tap Changer (OLTC) operations for 24 time steps ahead. 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 (i.e. fast convergence and robustness against randomness in initialization and factors used in evolutionary operations) and the achievement of optimal grid code compliance are demonstrated by investigating the case of a far-offshore wind power plant, interconnected with HVDC link.
format	Default Conference proceeding
author	A.M. Theologi M. Ndreko Jose L. Rueda M.A.M.M. Van Der Meijden Francisco Gonzalez-Longatt
author_facet	A.M. Theologi M. Ndreko Jose L. Rueda M.A.M.M. Van Der Meijden Francisco Gonzalez-Longatt
author_sort	A.M. Theologi (7207541)
title	Optimal management of reactive power sources in far-offshore wind power plants
title_short	Optimal management of reactive power sources in far-offshore wind power plants
title_full	Optimal management of reactive power sources in far-offshore wind power plants
title_fullStr	Optimal management of reactive power sources in far-offshore wind power plants
title_full_unstemmed	Optimal management of reactive power sources in far-offshore wind power plants
title_sort	optimal management of reactive power sources in far-offshore wind power plants
publishDate	2017
url	https://hdl.handle.net/2134/25770
_version_	1797735408688168960

Optimal management of reactive power sources in far-offshore wind power plants

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