Power fluctuations from large offshore wind farms



Similar documents
Modelling of wind power fluctuations and forecast errors. Prof. Poul Sørensen Wind Power Integration and Control Wind Energy Systems

Uncertainty of Power Production Predictions of Stationary Wind Farm Models

Translating ecological research results into wind farm practice The Danish experience. Niels-Erik Clausen. 2 Risø DTU

Modern Power Systems for Smart Energy Society

Future Offshore Wind Power Sites -2025

FLOWSTAR-Energy Validation NoordZee Wind Farm

Følgegruppe for Styring & Regulering. Den danske SmartGrids gruppe. Jeanette Møller Jørgensen Forskningskoordinator, Energinet.dk JMJ@energinet.

Energinet.dk and the Danish Energy System

GE Renewable Energy. Digital Wind Farm THE NEXT EVOLUTION OF WIND ENERGY.

Grid connection of near shore wind farms

EXPERIENCE WITH DP-SYSTEMS ON BOARD

Why wind power works for Denmark

Forecasting Wind and Solar Power Production

MAXIMISING YOUR. Offshore wind assets ASSET OPERATION & MAINTENANCE SERVICES

Sodium Sulfur Battery. ENERGY STORAGE SYSTEM for Reducing CO2 Emissions

WindScanner Research Infrastructure to measure 3D wind with scanning Lidars

Enlarged Wind Power Statistics 2010 including Denmark, Germany, Ireland and Great Britain

Title: IEC WT 01 vs. IEC Development of a new standard and innovations in certification of Wind Turbines. mike.woebbeking@gl-group.

Short-term solar energy forecasting for network stability

DONG Energy offshore wind experience

Results of wake simulations at the Horns Rev I and Lillgrund wind farms using the modified Park model

Resource Planning Opportunities

Power output of offshore wind farms in relation to atmospheric stability Laurens Alblas BSc

ACCELERATING GREEN ENERGY TOWARDS The Danish Energy Agreement of March 2012

Offshore Wind Energy Status and Future Prospects

Energy Supply Technologies: Wind Power

OFFSHORE WIND ENERGY IS GETTING CHEAPER

Context: significant penetration of DG = increased risks for system security

Current Profiles at the Offshore Wind Farm Egmond aan Zee J.W. Wagenaar P.J. Eecen

Wind Cluster Management for Grid Integration of Large Wind Power

GREEN POWER ISLAND DENMARK GOTTLIEB PALUDAN ARCHITECTS RISØ-DTU

Solar Variability and Forecasting

Design and Operation of Power Systems with Large Amounts of Wind Power, first results of IEA collaboration

The Role of a Pension Fund in Renewable Energy Investments. Transformational NAMA in the Renewable Energy Sector May 2013

Virtual Met Mast verification report:

Battery Energy Storage

System Protection Schemes in Eastern Denmark

A Brief Introduction and Discussion of R&D

Improved Bankability. The Ecofys position on LiDAR use. Summary

Field experience and best practices in managing MW scale Li-ion energy storage systems coupled to large wind and solar plants

WindREN AB IEA Task 19 national overview - Swedish activities in measurements and mapping of icing and de-icing of wind turbines Göran Ronsten,

Installation, future demands for recruitment and competencies. Speaker: Hans Schneider Date: 4 April 2013

CFD SIMULATIONS OF WAKE EFFECTS AT THE ALPHA VENTUS OFFSHORE WIND FARM

The Wind Integration National Dataset (WIND) toolkit

INSTALLATION and LOGISTICS of OFFSHORE WIND FARMS

State-of-the-art in Forecasting of Wind and Solar Power Generation

VISION MISSION ABOUT A2SEA. Stay ahead in taking wind power offshore and the future of energy in a sustainable direction.

COOLING SOLUTIONS WIND

Databases. by David Cerda Salzmann

Benchmarking of wind farm scale wake models in the EERA - DTOC project

Analysis of requirements in selected Grid Codes. Willi Christiansen & David T. Johnsen

Offshore Wind Energy: Research needs and Danish competences

Grid requirements with scattered load balancing and an open electricity market Poul Alberg Østergaard * Aalborg University

Energy Storage for Renewable Integration

Wind resources and wind turbine wakes in large wind farms. Professor R.J. Barthelmie Atmospheric Science and Sustainability

The installation and servicing

INFLUENCES OF VERTICAL WIND PROFILES ON POWER PERFORMANCE MEASUREMENTS

Austin Energy Resource, Generation and Climate Protection Plan to 2025: An Update of the 2020 Plan

EWEA CREYAP benchmark exercises: summary for offshore wind farm cases

Development and Operation of a Wind Power Based Energy System : Experiences and Research Efforts

EFFECTS OF COMPLEX WIND REGIMES ON TURBINE PERFORMANCE

ENERGY YIELD ASSESSMENT

New Insurance Solutions For On- and Offshore Wind Turbines

Danish Society for Naval Architecture and Marine Engineering, Danish Maritime Society, The Transport Innovation Network & Danish Wind Energy Group

Dansk Offshore Netværk, Lindø Industripark, 21. April 2015 The Road to Below 10 ct /kwh

Product brochure Multi Functional Switchgear PASS M kv Flexible and compact switchgear solutions for windfarms

GE Renewable Energy. GE s 3 MW Platform POWERFUL AND EFFICIENT.

Uncertainty in a post-construction energy yield estimate

ROMO Wind Juan Carlos Martínez-Amago Jornadas Técnicas - AEE September 26 th 2012

V MW. Your best option for low cost energy production at low and medium wind sites. Federico Gonzalez Vives. Director Technology.

Forecaster comments to the ORTECH Report

THE NEW GUIDELINE FOR THE CERTIFICATION OF WIND TURBINES, EDITION 2010

Advanced Electricity Storage Technologies Program. Smart Energy Storage (Trading as Ecoult) Final Public Report

Offshore Wind Development

Modeling the US Natural Gas Network

WIND ENERGY - THE FACTS PART III THE ECONOMICS OF WIND POWER

Research and Education in the Field of Wind Energy at the Technical University of Denmark

Onshore Wind Services

NORDEX CONTROL 2. The cockpit for wind power plants

A E O L I S F O R E C A S T I N G S E R V I C E S WIND FARM ENERGY ASSESSMENT - FEASIBILITY STUDY. Kees van Vliet

Center for Electric Power and Energy (CEE)

WIND TURBINE TECHNOLOGY

Karnataka Electricity Regulatory Commission. Discussion note on

Residential heat pumps in the future Danish energy system

Renewable Energies WIND

INNWIND.EU Offshore wind energy DTU Contributions to WP4.2 Technology, ecomony, trends and research. Henrik Bredmose Thomas Buhl

Wind Energy at Earth Sciences

Offshore Wind: some of the Engineering Challenges Ahead

DOES WIND KILL THE ENERGY ONLY MARKET?

Monitoring the Operation of Wind Turbines Alex Robertson, Vestas Northern Europe

Transcription:

Power fluctuations from large offshore wind farms Poul Sørensen Wind Energy Systems (VES) Wind Energy Division Project was funded by Energinet.dk PSO 2004-6506

Geographical spreading 2

Wind turbine sites in Denmark Horns Rev 3 Risø DTU, Technical University of Denmark Energinet.dk advisory meeting on control

Validation available data February 2005 January 2006 January 2006 May 2007 6152500 Horns Rev Horns Rev 160 MW 6051000 Nysted 165,6 MW 72 WT 6151500 80 WT 6050000 6150500 6049000 6149500 Wind Turbines 6048000 Wind Trubines Mast 6148500 6047000 6147500 6046000 6146500 422500 423500 424500 425500 426500 427500 428500 429500 430500 6045000 671000 672000 673000 674000 675000 676000 677000 678000 679000 - acquisition made through the control system, with 1Hz sampling frequency; - wind speed, power, power set point and yaw position used - 2-hour segments were selected, with normal operation - 1110 2-hour segments (92,5 days) in Horns Rev and 1989 (165,75 days) in Nysted - wind speeds from 1 to 19 m/s (Horns Rev) and from 1 to 24 m/s (Nysted) 4

Validation ramp rates The ramp rate * (load following) is defined as the change in the mean value from one period to another and specifies the ramp rate requiremet that the wind farm power fluctuation causes to other power plants P ramp ( n) = Pmean ( n+ 1) Pmean ( n) Three time scales were investigated: 10 min, 30 min and 1 min * This definition specifies the ramping of the wind farm power. Thus, negative ramp rate means decreasing wind power and requires positive ramping of other power plants. The result were binned according to the initial power P mean (n), because the statistics will depend strongly on the initial power. A power bin size of 0.1 p.u. has been selected. Duration curves are obtained by sorting the ramping in each power bin. 5

Validation ramp duration curves Horns Rev duration curves, 0.8-0.9 p.u. 1 min 10 min 30 min Nysted duration curves, 0.8-0.9 p.u. 6

Validation 99% percentiles ramp 10 min 30 min 1 min 7

Validation reserve requirements The reserve requirement * (regulation) is defined as the difference between the initial mean value and the minimum value in the next period. P ( n) = P ( n) P ( n + 1) res mean min P ramp ( n) = Pmean ( n + 1) Pmean ( n) Three time scales were investigated: 10 min, 30 min and 1 min * with this definition, positive reserves means decreasing wind power that requires positive reserve from other power plants The result were binned according to the initial power P mean (n), because the statistics will depend strongly on the initial power. A power bin size of 0.1 p.u. has been selected. Duration curves are obtained by sorting the ramping in each power bin. 8

Validation reserves duration curves Horns Rev duration curves, 0.8-0.9 p.u. 1 min 10 min 30 min Nysted duration curves, 0.8-0.9 p.u. 9

Validation 1% percentiles reserves 10 min period 30 min period 1 min period 10

Future potential offshore sites 11

Climate model resolution 12

Simulated wind speeds - smoothing 24 22 20 Wind speed (m/s) 18 16 14 Turbine (A1) Wind Farm Weather model 12 10 00:00 02:00 04:00 06:00 08:00 10:00 12:00 Time 13

Wind farm (aggreg.) power curve 1.2 1 0.8 Power (pu) 0.6 0.4 Simulated farm Input turbine 0.2 0 0 5 10 15 20 25 30 35 Wind speed (m/s) 14 Risø DTU, Technical University of Denmark Energinet.dk advisory meeting on control

Study cases Djursland Anholt O Djursland Anholt P Horns Rev B Horns Rev A Horns Rev 2 Horns Rev 15

Study cases - wind farms data Name Symbol Wind turbine power Total power Annual mean wind speed Horns Rev HR1 80 2.0 MW 160 MW 9.6 m/s *) Horns Rev 2 HR2 91 2.3 MW 209 MW 10.4 m/s *) Horns Rev A HRA 40 5.0 MW 200 MW 10.6 m/s *) Horns Rev B HRB 40 5.0 MW 200 MW 10.5 m/s *) Djursland Anholt O DAO 40 5.0 MW 200 MW 9.0 m/s *) Djursland Anholt P DAP 40 5.0 MW 200 MW 9.0 m/s *) 16

Simulated wind speeds (wf averages) 40 35 30 Wind speed (m/s) 25 20 15 10 HR1 HR2 HRA HRB DAO DAP 5 0 28/01-2000 29/01-2000 30/01-2000 31/01-2000 01/02-2000 Time 17

Power fluctuations the 2 cases 800 700 600 Horns Rev B Horns Rev A Horns Rev 2 Djursland Anholt O Djursland Anholt P Power (MW) 500 400 300 200 HRB HRA HR2 HR1 Horns Rev 100 0 28/1-2000 29/1-2000 30/1-2000 31/1-2000 1/2-2000 800 Time 700 600 Horns Rev B Horns Rev A Horns Rev 2 Horns Rev Djursland Anholt O Djursland Anholt P Power (MW) 500 400 300 200 DAP DAO HR2 HR1 100 0 28/1-2000 29/1-2000 30/1-2000 31/1-2000 1/2-2000 Time 18

Conclusions Efficient simulation tool for simulation of wind power fluctuations in power system region Calibration to sites should be looked more into, especially for onshore applications Applications planning of offshore sites control development 19