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A Comparative Analysis of Linear and Nonlinear Control of Wave Energy Converter for a Force Control Application
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Electricity.
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Electricity.
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Electricity.
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(English)In: International Marine Energy Journal, ISSN 2631-5548Article in journal (Refereed) Submitted
Abstract [en]

The aim of wave energy converters (WECs) is to harvest the energy from the ocean waves and convert into electricity. Optimizing the generator output is a vital point of research. A WEC behaves as a nonlinear system in real ocean waves and a control that approximates the behaviour of the system is required. In order to predict the behaviour of WEC, a controller is implemented with an aim to track the referenced trajectory for a force control application of the WEC. A neural model is implemented for the system identification and control of the nonlinear process with a neural nonlinear autoregressive moving average exogenous (NARMAX) model. The neural model updates the weights to reduce the error by using the Levenberg-Marquardt back-propagation algorithm for a single-input-single-output (SISO) nonlinear system. The performance of the system under the proposed scheme is compared to the same system under a PI-controller scheme, where the PI gains have been tuned accordingly, to verify the control capacity of the proposed controller. The results show a good tracking of dq (direct-quadrature) axes currents by regulating the stator currents, and hence a force control is achieved at different positions of the translator. The dynamic performance of the control is verified in a time domain analysis for the displacement of the translator.

Place, publisher, year, edition, pages
Southampton, UK: International Marine Energy Journal.
Keywords [en]
current control, force control, neural NARMAX, permanent magnet linear generator (PMLG), wave energy converter
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering with specialization in Automatic Control
Identifiers
URN: urn:nbn:se:uu:diva-390099OAI: oai:DiVA.org:uu-390099DiVA, id: diva2:1340459
Funder
Swedish Research Council, 2015-03126StandUpAvailable from: 2019-08-05 Created: 2019-08-05 Last updated: 2019-08-19
In thesis
1. Grid Integration and Impact of a Wave Power System
Open this publication in new window or tab >>Grid Integration and Impact of a Wave Power System
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Increasing energy consumption and concern for carbon emissions has boosted the demand for renewable energy production. The focus on renewable energy has gained much attention in wind, solar, hydro and wave power generations. Wave power has great potential due to its high energy density but there are challenges as well. This thesis addresses some of the challenges involved in the grid integration of wave energy and in maintaining power quality. In this thesis a grid connection of permanent magnet linear generator (PMLG) based wave energy converter (WEC) as a renewable energy source is evaluated at the Division of Electricity, Uppsala University.

The grid impact of a wave energy park in terms of flicker, voltage variations and harmonic distortion at the grid-connection point are investigated extensively. The short-term flicker level generated by the WEC and a wave energy park (WEP) related to the rated WEP power and grid impedance angle at the PCC are evaluated.

In this thesis, an improved control for hybrid energy storage is presented, which enhanced the efficiency and increased the battery life while smoothing the intermittent power from the WEP. The thesis, also, contributes to resolve the problem of inertia and power balance by integrating the DC-link capacitor in the control loop which reduce the size and cost of the components at the DC-link.

The work presented in the thesis has contributed for the force control of the PMLG which is predicted and controlled by regulating the stator currents of the generator. A nonlinear, neural, control is evaluated and compared to a linear, proportional-integral, control. The results from the nonlinear control show the good agreement between the referenced and the generated currents. The reduced losses enhanced the accuracy of the system.

A control and grid connection system for a WEC has been designed and installed. The thesis addresses the issue of power quality in low, steady and varying power flows of compliance with the grid code requirements.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2019. p. 116
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1842
Keywords
ANN, buck-boost converter, current control, energy storage system, force control, flicker, FPGA control, grid integartion, harmonics, linear generator, PHIL, microgrid, voltage variation, wave energy, WEC
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Engineering Science with specialization in Science of Electricity
Identifiers
urn:nbn:se:uu:diva-390133 (URN)978-91-513-0725-1 (ISBN)
Public defence
2019-10-04, 80127, Ångströmlaboratoriet, Lägerhyddsvägen 1, Uppsala, 09:15 (English)
Opponent
Supervisors
Funder
Swedish Research Council, 2015-03126
Note

We havn't got the response from the opponent yet, It will be confirmed in a few days.

Available from: 2019-09-13 Created: 2019-08-19 Last updated: 2019-10-15

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Parwal, ArvindFregelius, MartinSvensson, OlleTemiz, IrinaOliveira, Janaína Goncalves deBoström, CeciliaLeijon, Mats

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