1. Ryoichi Komiyama, Yasumasa Fujii University of Tokyo Assessment for Large-scale Integration of Wind Power Generation with High Time-Resolution Optimal Power Generation Mix Model 1 32nd IAEE North American Conference, July 29, 2013 Anchorage, Alaska

2. Outline 2 Introduction Optimal Power Generation Mix Model Wind Output Estimation in Japan Results - Power Generation Mix - Optimal Dispatch - Sensitivity Analysis on Battery Cost Concluding Remarks

3. Introduction: Wind Resource Map in Japan Wind Resource Wind Speed Wind Resource Wind Speed OnshoreOffshore Total Potential: 282.9 GW Hokkaido : 139.6 GW (49%) Tohoku : 72.6 GW (26%) Kyushu : 20.9 GW (7.4%) Total Potential: 1572.6 GW Hokkaido : 403.0 GW (26%) Tohoku : 224.8 GW (14%) Kyushu : 454.6 GW (29%) (Source) Ministry of Environment 3 Maximizing renewable is a key political agenda in Japan after Fukushima (Note) Total utility capacity in Japan: 202 GW

4. Objective 4 Maximum potential of installable wind power in Japan amounts to about 280 GW in onshore and around 1600 GW in offshore which is together equal to more than 9 times of Japan’s peak demand (around 200 GW) Thus in Japan, immense potential of wind power generation, 9 times of the peak demand, is expected to be exploited for the future This study investigates the potential of wind resource which could be systematically integrated into Japanese power generation mix, using a high time-resolution optimal power generation mix model Wind resource potential in Japan (Source) Ministry of the Environment in Japan, “Study of Potential for the Introduction of Renewable Energy(FY 2010)”, April 2011

5. High Time-Resolution Optimal Power Generation Mix Model Time-Resolution: 10 minutes in 365 days, 52,560 time segments ( = 6 time points per hour×24 hours per day×365 days per year) 5 Technology Coal-fired Oil-fired Gas-fired Gas-CC Geothermal Nuclear Wind PV Pumped hydro Stationary NAS battery (Sodium Sulfur battery) Stationary Li-ion battery Suppression of PV Suppression of Wind (Single period optimization) Number of Constraints: 4.0 million Number of Endogenous Variable: 1.3 million (Source) R.Komiyama, S.Shibata, Y.Nakamura and Y.Fujii: Analysis of possible introduction of PV systems considering output power fluctuations and battery technology, employing an optimal power generation mix model, Electrical Engineering in Japan, Volume 182, Issue 2, pp.9-19 (2012) (http://onlinelibrary.wiley.com/doi/10.1002/eej.22329/abstract) The model is applicable to various countries and regions other than Japan

6. Assumption of Cost and Technical Data 6 Advantage of NAS battery Abundant component resource (Na, S) availability High energy density (3 times as Lead) High charge and discharge efficiency Long lifetime, No self-discharge Maintenance is simple Disadvantage of NAS battery Heating system to maintain 300 degrees is required Component materials such as Na are flammable

7. Estimation of Wind Output by using Japanese Metrological Database (AMeDAS*) Tohoku region in Dec. 2007 (Actual & estimated output) 7 Wind output is estimated from data in 1,300 weather observation sites of Japan. *Automated Meteorological Data Acquisition System

8. Wind output in Japan 8 Wind output of Japan in 365 days at 10 minutes’ interval In Japan, the majority of onshore wind resources concentrate on Hokkaido and Tohoku regions (North part of Japan). The whole pattern of wind output in Japan is calculated using a weighted average of the derived regional wind power output in the amount of regional wind resources. Wind velocity is higher in winter & spring and lower in summer.

9. PV output in Japan 9 Time profile of PV is estimated by solar irradiance model with meteorological observation data including sunshine duration, precipitation and ambient temperature. Solar insolation intensity is higher in summer, lower in winter PV output in 365 days at 10 minutes’ interval Annual capacity factor of PV

10. Power Generation Mix 10 Generation (kWh)Capacity (kW) As installed wind power expands in Japan’s electricity system, wind mainly replaces thermal power generation, while the suppression control of wind power generation increases. Rechargeable NAS battery technology is not so much introduced, even in the massive penetration of wind power, mainly due to its more expensive cost compared with other measures such as the suppression control and quick load following of thermal power plant such as LNG combined cycle. Wind power integration in power generation mix becomes incrementally saturated, and the suppression control of wind power considerably increases as installed wind expands in the grid. Suppressed Wind Wind Nuclear Coal LNGCC Wind LNGCC Nuclear Coal Hydro PV Pumped-hydro Hydro PV Pumped(in) Pumped(out)

11. Wind Integration into the Grid 11 When wind capacity is integrated at more than a half of the scale of the peak demand or the fraction of wind power generation in total electricity demand exceeds around 20 percent, the ratio of suppressed wind power shows a significant increase On wind installed capacity at the same, double and triple of the peak demand, the ratio of suppressed output in total wind power generation shows 20%, 40% and 60% respectively. Breakdown of wind power: wind output into the grid and its suppression 0.2

12. Monthly Optimal Dispatch (May) 12 Renewable variability is technically controlled by energy storage technology such as pumped- hydro, load following operation by thermal power plant and the output suppression control of wind power. A variety kind of measures dynamically function as a whole to control the short- cycle variation of wind output. In May when wind intensity is higher, elaborate suppression control is required. In August when wind intensity is lower, suppression is not required. ⇒ Controlling seasonal imbalance is indispensable under massive penetration of wind power. May August (Wind is installed at 200GW, accounting for the same scale of peak demand, 30% of total electricity demand) May 1 May 31 August 1 August 31 Suppressed Wind Wind Nuclear LNGCC Hydro PV Coal Pumped(in) Pumped(out) Geothermal Hydro Pumped(in) Nuclear Coal LNGCC PV Wind Pumped(out)

13. Suppression Control (Curtailment) of Wind 13 Suppression rate of wind in Japan tends to become higher in winter and spring seasons, because wind velocity remains higher while the level of electricity demand is modest at those seasons. By contrast, summer season reveals the lower curtailment rate due to the lower wind intensity. In May, monthly-average wind suppression rate is observed to show 80%. (Wind is installed at 200GW, accounting for the same scale of peak demand, 30% of total electricity demand)

14. Load Factor of LNG Combined Cycle 14 Wind: 5GW Wind: 200GW (the same scale of peak demand, 30% of total electricity demand) Load factor of LNG combined cycle goes significantly down in winter and spring season when wind velocity shows higher intensity LNGCC appears to be not profitable under massive wind penetration. Who will do investment in building LNGCC ?

15. Sensitivity Analysis on Battery Cost 15 Five cases are supposed about the battery cost. Japanese official roadmap sets a target of reducing the battery cost by 90% until 2030 from the current technical level. Sensitivity analysis of battery cost shows that lower battery cost increases the installed battery capacity and decreases the suppression control of wind power, which suggests that the reason of wind power suppression instead of storing its surplus output in the battery is attributable to the higher cost of rechargeable NAS battery. Base.-25%-50%-75%-90% Unit Facility Cost [$/kW]1,200900600300120 Unit Facility Cost [$/kWh]403020104 Unit Expendable Material Cost [$/kWh]160120804016 Lifetime [cycle]4,5004,8755,2505,6256,000 Cost scenario of rechargeable sodium-sulfur (NAS) battery Power generation Nuclear Coal LNGCC PV Wind Hydro Suppressed Wind Battery(out) Battery(in) Pumped(in) Pumped(out)

16. Installed Battery Capacity 16 Power capacity (kW)Energy capacity (kWh) As the battery cost decreases, its kWh(energy)-capacity represents more rapid growth compared with its kW-capacity. In the battery cost 90% reduction case, the ratio of kWh-capacity to kW-capacity amounts to around 30 hours, which suggests that NAS battery is introduced to charge the surplus wind power in a longer time interval, such as on a weekly basis. Preparation of sufficient energy capacity (kWh) is required for realizing a massive integration of wind power in the grid.

17. SOC (state of charge) of Battery 17 May 1 May 31 NAS battery is installed for storing surplus wind power chiefly in a weekly scale. Energy loss of NAS battery is huge in a weekly scale of the battery operation. Battery cost scenario: -50% (Wind: 300GW, NAS battery: 79GW/579GWh) Battery cost scenario: -90% (Wind: 300GW, NAS battery: 79GW/579GWh) (Wind is installed at 300GW, accounting for 1.5 times the peak demand, 50% of total electricity demand) Battery Pumped-hydro Battery Pumped-hydro

18. Technical Compatibility between Wind and Battery 18 Wind intermittency in Japan shows a long-cycle variation ⇒ Energy loss of rechargeable NAS battery becomes larger ⇒ NAS battery is less technical compatibility with wind power Wind output through a year at 10-minute interval Output[p.u.]

19. Concluding Remarks 19 Wind output is suppressed when it is massively integrated When wind capacity is integrated at more than a half of the scale of the peak demand or the fraction of wind power generation in total electricity demand exceeds around 20 percent, the ratio of suppressed wind power shows a significant increase (wind power is curtailed). Rechargeable battery is an expensive option Battery is too expensive to control the intermittency, and a long- cycle variation of wind output prevents the massive introduction of rechargeable battery for compensating the wind variability. Reason of wind suppression is due to the high battery cost Lower battery cost increases the installed battery capacity and decreases the suppression rate of wind power, which suggests that the reason of wind power suppression instead of storing its surplus output in the battery is attributable to the high cost of NAS battery.

20. Thank you for your kind attention. 20 Ryoichi Komiyama Associate Professor Resilience Engineering Research Center University of Tokyo komiyama@n.t.u-tokyo.ac.jp

21. (Appendix) Performance of Rechargeable Battery 21 LeadNASNi-MHLiB Energy density (Wh/kg) 3511060120 Energy Efficiency (%) 8790 95 Lifetime (cycle) 4,500 2,0003,500 Cost ($/kW) 1,5002,4001,0002,000 Cost ($/kWh) 5002501,0002,000 (Source) METI “Current Situation on Battery Technology” (in Japanese), Feb. 2012