A Platform for Interdisciplinary Collaboration on Large Integration of Offshore Wind Farms in Japan: From My Experience in JST-CREST Project

Transcription

1 A Platform for Interdisciplinary Collaboration on Large Integration of Offshore Wind Farms in Japan: From My Experience in JST-CREST Project Yoshihiko Susuki Department of Electrical Engineering Kyoto University, Japan Japan - Norway Energy Science Week Tokyo, May 28, 2015

2 My Focus on mainly partly from Program for Special Session Met-Ocean Measurements and Modeling for Offshore Wind Energy Yoshihiko Susuki, Kyoto University, Japan May 28,

3 Introduction to Offshore Wind Energy Large wind resource remaining Relatively-stable and strong wind speeds available Wind Farm (WF) with a larger capacity constructed Hywind demo in Norway 2.3MW floating wind turbine Ref.)Statoil webpage Ref.)EWEA, European Offshore Statistics 2014 Yoshihiko Susuki, Kyoto University, Japan May 28,

4 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! Ref.) Map of Potential Wind Resource Reported by the Ministry of the Environment More than 8.5m/s How do we smoothly integrate wind farms with the existing electricity grid? How do we maintain stability and reliability of the integrated grid even in emergency situation? Yoshihiko Susuki, Kyoto University, Japan Ref.) FERC, Electricity Rev. Japan 2011 May 28,

5 Purpose and Contents Creating a Platform for Interdisciplinary Collaboration on Large Integration of Offshore Wind Farms in Japan ü A personal view from my experience in the JST-CREST project during Two Questions: 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? Yoshihiko Susuki, Kyoto University, Japan May 28,

6 First Part 1. How did we create a platform where researchers in different domains exchanged ideas and studied together? Yoshihiko Susuki, Kyoto University, Japan May 28,

7 Wind Forecast Data by CReSS From 0AM (JST), January 2, 2013 Temporal Resolution: 1min. Spatial Resolution: 2km Yoshihiko Susuki, Kyoto University, Japan May 28,

8 Data-Centric Platform for Collaboration Yoshihiko Susuki Mr. Fredrik Raak (Kyoto Univ.) Dr. Chiaki Kojima (Univ. Tokyo) Modeling and Applied Math. Prof. Hideharu Sugihara (Osaka Univ.) Power Technology Prof. Yoshifumi Zoga (Hiroshima Univ.) Transmission Distribution Power Electronics Profs. Uyeda Tsuboki (Nagoya Univ.) Meteorology Forecasting Fluid Mechanics Prof. Yohei Morinishi (Nagoya Institute Tech.) Control Technology Decision-Making Optimization Computer Science Dependability Software Prof. Yasumasa Fujisaki Dr. Takayuki Wada (Osaka Univ.) Prof. Tatsuya Tsuchiya (Osaka Univ.) Yoshihiko Susuki, Kyoto University, Japan May 28,

9 Bird s-eye View of Collaborative Research Grid- Scale Farm- Scale Turbine -Scale Space 10 3 km 10 2 km 10 km 1 km Load-Frequency Governor Free Emergency Transient Analysis and Control Economic Dispatching Optimal Power Flow and Operation Simulation-Based Wind Forecasting Fault Diagnosis Conventional Control and Operation Methods of Electricity Grids sec min hour day Short-Term Mid-Term Long-Term Time Yoshihiko Susuki, Kyoto University, Japan May 28,

10 Classification of Data for Wind Integration Research Topics Physical Observables Spatial-Scale /Forecast Period /Forecast Horizon Data Format Economic Load Dispatching (Short-Term) Wind Speed or Wind Power Grid /3 to 5 Minutes /3 to 5 Minutes Probability Distribution of Forecast Error Economic Load Dispatching (Long-Term) Wind Speed or Wind Power Temperature Wind Velocity Solar Radiation Grid /5 to 10 Minutes /2 to 3 Hours Time Series and Probability Distribution of Forecast Error Time Series Operation Planning (Next Day) Averaged Wind Output Power (over a Hour) Grid /One Hour /One Day Time Series and Probability Distribution of Forecast Error Fault Diagnosis Maintenance Wind Speed Failure Rate Turbine /One Day/Day to More Time Series Dynamic Simulation Wind Speed Turbine to Grid /A Few Seconds/--- Time Series Yoshihiko Susuki, Kyoto University, Japan May 28,

11 Second Part 2. What research problem did we study in the data-centric platform? p Robust Operation Planning p Dynamic Simulation Yoshihiko Susuki, Kyoto University, Japan May 28,

12 2-1. Robust Operation Planning Initial conditions and parameters (PV,PQ-buses etc.) Global Wind Forecast Data Power-Flow Model of Electricity Grid with Offshore Wind Farms ü Robust, optimal operation planning of electricity grid under uncertain wind forecast Theory and numerical implementation in optimization problem Practical validation? Generation Dispatch Energy Management System Yoshihiko Susuki, Kyoto University, Japan May 28,

13 Robust Optimal Power-Flow Problem Guaranteed Generation Planning under Uncertain Wind Forecast Cost Function Variables can vary according to wind fluctuations. (add.) Inequality Constraints for Voltage and Power Power-Flow (Equality) Constraints Generated power at bus i Wind power at bus i Consumed power at bus i Randomized Algorithm Use of randomness for fast and tractable computation Ref.) T. Wada et al., Proc. 53rd IEEE CDC, pp (2014). Finite Set of Wind Power Outputs Yoshihiko Susuki, Kyoto University, Japan May 28,

14 Numerical Example Ref.) T. Wada et al., Proc. SCI 15, Osaka, Japan, May 20 (2015). Cost [Yen/h] Is any constraint violated? No Error n=10% Error n=20% Error 10, , ,178.1 YES YES NO! IEEJ East 30- Machine Benchmark Model Installed Wind Farm near Ibaragi Prefecture n% error TIME-AVERAGE Wind-Speed Forecast HOUR Yoshihiko Susuki, Kyoto University, Japan May 28,

15 2-2. Dynamic Simulation of Wind Farms Local Wind Forecast Data Static or Dynamic Model Generated Power Wind Farm Output? Simulation data for surface wind speed near the west coast of Aomori prefecture Initial conditions Parameters (turbine, farm, and grid) 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 Yoshihiko Susuki, Kyoto University, Japan May 28,

16 MATLAB-Based Simulation Code WF Power as OUTPUT OF SIMULATION Wind Forecast Data as INPUT Refs.) F. Raak et al., Proc. SCI 15, Osaka, Japan, May 20 (2015); --- (submitted for international conference, 2015). Yoshihiko Susuki, Kyoto University, Japan May 28,

17 Numerical Examples WF 20 turbines Long-term w/ static model Short-term w/ dynamic model Fredrik Raak Yoshihiko Susuki, Kyoto University, Japan May 28,

18 Summary - Two Messages Creating a Platform for Interdisciplinary Collaboration on Large Integration of Offshore Wind Farms in Japan ü A personal view from my experience in the JST-CREST project during 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. Yoshihiko Susuki, Kyoto University, Japan May 28,

19 Thank you for your kind attention! Contact Info: v susuki.yoshihiko.5c@kyoto-u.ac.jp v Yoshihiko Susuki, Kyoto University, Japan May 28,