A Platform for Interdisciplinary Collaboration on Large Integration���of Offshore Wind Farms in Japan: ���

From My Experience in JST-CREST���Project

Yoshihiko SusukiDepartment of Electrical Engineering

Kyoto University, Japan

Japan - Norway Energy Science WeekTokyo, May 28, 2015

My Focus on…

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mainly

partly

from Program for Special Session “Met-Ocean Measurements and Modeling for Offshore Wind Energy”

Introduction to Offshore Wind Energy •  Large wind

resource remaining•  Relatively-stable

and strong wind speeds available

•  Wind Farm (WF) with a larger capacity constructed

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Ref.）EWEA, European Offshore Statistics 2014

•  “Hywind” demo in Norway–  2.3MW floating

wind turbineRef.）Statoil webpage

Integration Issues of Wind Energy in Japan

•  Heterogeneous distribution of wind potential: North and west Japan

•  Intermittency in wind energy extracted–  Complicated natural phenomenon: Chaotic!

•  How do we maintain stability and reliability of the integrated grid even in emergency situation?

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•  How do we smoothly integrate wind farms with the existing electricity grid?

Ref.) Map of Potential Wind Resource

Reported by the Ministry of the

Environment More than 8.5m/s

Ref.) FERC, Electricity Rev. Japan 2011

Purpose and Contents

1.  How did we create a platform where researchers in different domains exchanged ideas and studied together?

2.  What research problem did we study in the created platform?

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Creating a Platform for Interdisciplinary Collaboration on Large Integration of Offshore Wind Farms in Japan

Two Questions:

ü  A personal view from my experience in the JST-CREST project during 2013-2015

First Part

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1.  How did we create a platform where researchers in different domains exchanged ideas and studied together?

Wind Forecast Data by CReSS

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From 0AM (JST), January 2, 2013

Temporal Resolution: 1min.

Spatial Resolution: 2km

Data-Centric Platform for Collaboration

May 28, 2015

Modeling and

Applied Math.

Computer Science

Dependability Software

Control Technology

Decision-MakingOptimization

PowerTechnology

TransmissionDistribution

Power Electronics

Yoshihiko Susuki, Kyoto University, Japan 8

Meteorology

ForecastingFluid

Mechanics

Profs. Uyeda

Tsuboki(Nagoya Univ.)

Yoshihiko SusukiMr. Fredrik Raak(Kyoto Univ.)Dr. Chiaki Kojima (Univ. Tokyo)

Prof. Yasumasa FujisakiDr. Takayuki Wada(Osaka Univ.)

Prof. Hideharu Sugihara (Osaka Univ.)Prof. Yoshifumi Zoga (Hiroshima Univ.)

Prof. Tatsuya Tsuchiya (Osaka Univ.)

Prof.Yohei Morinishi

(Nagoya InstituteTech.)

Simulation-BasedWind Forecasting

Time

Space

sec min hour day

1 km

10 km

102 km

103 km

Turbine-Scale

Farm-Scale

Grid-Scale

Short-Term Long-Term Mid-Term

Fault Diagnosis

Optimal Power Flow and Operation

Transient Analysis

and Control

Governor Free

Load-Frequency Economic Dispatching

Emergency

Conventional Control and Operation Methods of Electricity Grids

Bird’s-Eye View of Collaborative Research

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Research Topics

PhysicalObservables

Spatial-Scale/Forecast Period

/Forecast HorizonData Format

EconomicLoad

Dispatching(Short-Term)

Wind Speed orWind Power

Grid/3 to 5 Minutes/3 to 5 Minutes

Probability Distribution

of Forecast Error

Economic���Load ���

Dispatching(Long-Term)

Wind Speed orWind Power Grid

/5 to 10 Minutes/2 to 3 Hours

Time Series andProbability Distribution of

Forecast Error

TemperatureWind VelocitySolar Radiation

Time Series

Operation���Planning

(Next Day)

Averaged Wind Output Power (over a Hour)

Grid/One Hour/One Day

Time Series andProbability Distribution of

Forecast Error

Fault DiagnosisMaintenance

Wind SpeedFailure Rate

Turbine/One Day/Day to More

Time Series

DynamicSimulation

Wind Speed Turbine to Grid

/A Few Seconds/---Time Series

Classification of Data for Wind Integration

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Second Part

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2.  What research problem did we study in the data-centric platform?

p  Robust Operation Planningp  Dynamic Simulation

Power-Flow Model of

Electricity Grid with Offshore Wind Farms

2-1. Robust Operation Planning

Global WindForecast

Data

GenerationDispatch

？

ü Robust, optimal operation planning of electricity grid under uncertain wind forecast•  Theory and numerical implementation in

optimization problem•  Practical validation

Initial conditions and parameters

(PV，PQ-buses etc.)

Energy Management System

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Robust Optimal Power-Flow Problem

•  Use of randomness for fast and tractable computation Ref.) T. Wada et al., Proc. 53rd IEEE CDC, pp.5195-5200 (2014).

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Guaranteed Generation Planning under Uncertain Wind Forecast

Power-Flow (Equality) Constraints

Cost Function

Generated power at bus i

Consumed power at bus i

Wind power at bus i

Variables can vary according to wind fluctuations.

(add.) Inequality Constraints for Voltage and Power

Randomized Algorithm

Finite Set of Wind Power Outputs

Numerical Example

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IEEJ East 30-Machine Benchmark Model Installed

Wind Farm near Ibaragi Prefecture

Wind-Speed Forecast

HOUR

Ref.) T. Wada et al., Proc. SCI’15, Osaka, Japan, May 20 (2015).

No Error

n=10% Error

n=20% Error

Cost [Yen/h] 10,991.1 10,119.1 11,178.1

Is any constraintviolated?

YES YES NO!

TIME-AVERAGE

n%error

2-2. Dynamic Simulation of Wind Farms

Local WindForecast

DataGenerated

Power

Wind FarmOutput

Initial conditionsParameters (turbine, farm, and grid)

？ Static or Dynamic Model

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ü  Dynamic Simulation of Wind Turbines and Wind Farms Incorporated with High-Resolved Wind Forecast Data–  Short-term after/during:

•  Occurrence of a fault at wind turbine•  Approach of a cold storm (see later); etc.

–  Long-term

Simulation data for surface wind speed near the west coast of Aomori prefecture

MATLAB-Based Simulation Code

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Wind ForecastData as INPUT

Refs.) F. Raak et al., Proc. SCI’15, Osaka, Japan, May 20 (2015); --- (submitted for international conference, 2015).

WF Power as OUTPUT OF SIMULATION

Numerical Examples

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Long-termw/ static model

WF

20 t

urbi

nes

Short-termw/ dynamic model

24

29

© Fredrik Raak

Summary - Two Messages

1.  The data-centric platform is the key driver for exchanging ideas to develop a new technology on the next-generation electricity grid.

2.  More work should be done and is ongoing in university-university collaborative project.

May 28, 2015 Yoshihiko Susuki, Kyoto University, Japan 18

Creating a Platform for Interdisciplinary Collaboration on Large Integration of Offshore Wind Farms in Japan

Two Messages:

ü  A personal view from my experience in the JST-CREST project during 2013-2015

Thank you for your kind attention!

Contact Info:v susuki.yoshihiko.5c@kyoto-u.ac.jp

v http://www-lab23.kuee.kyoto-u.ac.jp/susuki

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