32nd IAEE North American Conference, July 29, 2013
Anchorage, Alaska
Assessment for Large-scale Integration of
Wind Power Generation
with High Time-Resolution Optimal Power
Generation Mix Model
Ryoichi Komiyama, Yasumasa Fujii
University of Tokyo
1
Outline




Introduction
Optimal Power Generation Mix Model
Wind Output Estimation in Japan
Results
- Power Generation Mix
- Optimal Dispatch
- Sensitivity Analysis on Battery Cost
 Concluding Remarks
2
Introduction: Wind Resource Map in Japan
Maximizing renewable is a key political agenda in Japan after Fukushima
Onshore
Offshore
Hokkaido : 139.6 GW (49%)
Hokkaido : 403.0 GW (26%)
Tohoku : 72.6 GW (26%)
Tohoku : 224.8 GW (14%)
Kyushu : 20.9 GW (7.4%)
Total Potential: 282.9 GW
Kyushu : 454.6 GW (29%)
Wind Resource
Wind Speed
Total Potential: 1572.6 GW
(Note) Total utility capacity in Japan: 202 GW
(Source) Ministry of Environment
Wind Resource
Wind Speed
3
Objective
 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
[GW]
Hokkaido
Tohoku
Tokyo
Hokuriku
Chubu
Kansai
Chugoku
Shikoku
Kyushu
Okinawa
Total Japan
Onshore
Wind
140
73
4
5
8
13
9
5
21
6
283
Offshore Total Electric
Power Capacity
Wind
403
225
79
62
39
25
152
42
455
91
1,573
7
17
64
8
33
34
12
7
20
0.2
202
(Source) Ministry of the Environment in Japan, “Study of Potential for
the Introduction of Renewable Energy(FY 2010)”, April 2011
4
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)
The model is applicable to various countries and regions other than Japan
Optimal Power Generation Mix Model
Objective function:
Technology
minimize. Annual facility cost + Annual fuel cost
Constraint:
•
•
•
•
•
•
•
•
•
(Single period optimization)
Demand and supply balances
Available power plant capacity constraint
Upper and lower installable capacity constraint
Capacity reserve constraint for electricity supply reliability
Load following capability constraint
Minimum output constraint on thermal power plant
Charge and discharge balances on battery technology
Available power plant capacity constraint on battery technology
CO2 emissions constraint
・Optimal dispatch of power generation ・Newly-building power capacity
・Power generation cost ・Fuel consumption ・CO2 emissions etc.
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)
•
•
•
•
•
•
•
•
•
•
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
5
Assumption of Cost and Technical Data
Type
Unit Construction Cost [$/kW]
Life Time [year]
Annual O&M Cost Rate
Maximum Capacity [GW]
Minimum Capacity [GW]
Maximum Increase Rate of Output [1/hour]
Maximum Decrease Rate of Output [1/hour]
Conversion Efficiency
Own Consumption Rate
Fuel Cost [cent/specific unit]
Heat Content[kcal/specific unit]
Carbon Content[kg-C/specific unit]
Seasonal Peak Availability
Annual Average Availability
Share of Daily Start and Stop
Minimum Output Level
Specific Unit
Capacity Reserve Ratio
Annual Interest Rate
Fixed Asset Tax Rate
Salvage Value Rate
0.08
0.03
0.014
0.1
Nuclear
3,500
40
0.04
34 GW
0
0
1
0.04
1.67
860
0
0.85
0.85
0
0.3
kWh
Coal
2,300
40
0.048
∞
0
0.31
0.58
0.418
0.061
8.367
6139
0.61752
0.85
0.783
0
0.3
kg
LNG GCC
1,200
40
0.036
∞
0
0.82
0.75
0.57
0.02
51.985
13043
0.7462
0.9
0.833
0.5
0.2
kg
LNG ST
1,200
40
0.036
∞
0
0.82
0.75
0.396
0.04
51.985
13043
0.7462
0.9
0.8
0.3
0.2
kg
Oil
1,900
40
0.039
∞
0
1
1
0.394
0.045
70.197
9126
0.78792
0.9
0.8
0.7
0.3
l
Biomass
3,500
40
0.048
5.5 GW
0
0.31
0.58
0.2
0.13
12.25
3585
0
0.85
0.783
0
0.3
kg
Hydro
8,500
60
0.0178
Geothermal
5,100
20
0.01
23 GW
1.2 GW
PV
4,000
17
0.01
∞
3.6 GW
Wind
2,640
17
0.02
∞
2.2 GW
Type
Unit Construction Cost [$/kW]
Life Time [year]
Annual O&M Cost Rate
Maximum Capacity [GW]
Minimum Capacity [GW]
Unit Construction Cost [$/kWh]
Life Time [year]
Annual O&M Cost Rate
Unit Consumable Material Cost [$/kWh]
Life Cycle [times]
Cycle Efficiency
Self Discharge Loss [1/hour]
Maximum kWh ratio to kW
Usage Rate
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
Pumped hydro Battery(NaS)
2,400
60
0.01
28 GW
10
60
0.01
0
∞
0.7
0.0001
6
0.9
1,200
15
0.01
∞
0
40
15
0.01
160
4,500
0.9
0.001
∞
0.9
6
Estimation of Wind Output by using
Japanese Metrological Database (AMeDAS*)
*Automated Meteorological Data Acquisition System
Wind velocity from
AMeDAS
Equivalent wind
velocity at hub height
Wind power generation
output of unit capacity
Further modification of
wind velocity
Performance curve of
wind turbine
Minimum regional
capacity usage rate
Height of AMeDAS
observation point
Height of a hub of
wind turbine
Power law
parameter
Output of Wind Power
Generation [kW]
Wind output is estimated from data in 1,300 weather observation sites of Japan.
0
Vc
10
Vr
20
Vf
30
Wind Velocity [m/sec]
Tohoku region in Dec. 2007 (Actual & estimated output)
Output [MW]
Real Wind Power Output
Estimated Wind Power Output
Day of December 2007
7
Wind output in Japan
 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.
Output of unit capacity[p.u.]
Wind output of Japan in 365 days at 10 minutes’ interval
1
0.8
0.6
0.4
0.2
0
Day of the year
Time of the day
8
PV output in Japan
 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
Annual capacity factor of PV
Output of unit capacity[p.u.]
PV output in 365 days at 10 minutes’ interval
1
0.8
0.6
0.4
0.2
0
Time of the day
Day of the year
9
Power Generation Mix
 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.
Generation (kWh)
2500
TWh
2000
1500
Pumped(out)
Suppressed Wind
PV
1000
Wind
LNGCC
500
Coal
Nuclear
0
Pumped(in)
Wind Power Capacity (Ratio to Peak Demand)
1200
Suppressed Wind
Suppressed PV
1000
Battery(in)
Pumped(in)
800
Battery(out)
Pumped(out)
Wind
600
PV
Biomass
400
Oil
Pumped-hydro
LNG
PV
200
LNG GCC
Coal
Coal
Nuclear
Nuclear
0
Hydro
Geothermal
Hydro
Power demand
GW
Wind
LNGCC
4.00
3.50
3.00
2.50
2.25
2.00
1.75
1.50
1.25
1.00
0.85
0.75
0.50
0.25
0.20
0.15
0.10
0.05
0.03
-500
4.00
3.50
3.00
2.50
2.25
2.00
1.75
1.50
1.25
1.00
0.85
0.75
0.50
0.25
0.20
0.15
0.10
0.05
0.03
Hydro
Capacity (kW)
Wind Power Capacity (Ratio to Peak Demand)
Battery
Pumped-hydro
Wind
PV
Biomass
Oil
LNG
LNG GCC
Coal
Nuclear
Geothermal
Hydro
10
Wind Integration into the Grid
 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
Wind Power Generation
(Ratio to Annual Electricity Demand)
3.0
2.5
2.0
1.5
1.0
Suppression of Wind
0.5
0.2
Wind Power Generation
0.0
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0
Wind Power Capacity (Ratio to Peak Power Demand)
11
Monthly Optimal Dispatch (May)
(Wind is installed at 200GW, accounting for the same scale of peak demand,
30% of total electricity demand)

Renewable variability is technically controlled by energy storage technology such as pumpedhydro, 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 shortcycle 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.

300
May
250
Power Generation [GW]
Pumped(out)
200
LNGCC
150
100
Coal
50
PV
-50
Wind
Nuclear
Hydro
Geothermal
0
May 1
Pumped(in)
May 31
250
Pumped(out)
August
200
Power Generation [GW]
Suppressed Wind
PV
150
100
LNGCC
Wind
Coal
50
Nuclear
0
-50
Hydro
August 1
Pumped(in)
August 31
Suppressed Wind
Suppressed PV
Battery(in)
Pumped(in)
Battery(out)
Pumped(out)
Wind
PV
Oil
LNG
LNG GCC
Biomass
Coal
Nuclear
Geothermal
Hydro
Demand
Suppressed Wind
Suppressed PV
Battery(in)
Pumped(in)
Battery(out)
Pumped(out)
Wind
PV
Oil
LNG
LNG GCC
Biomass
Coal
Nuclear
Geothermal
Hydro
Demand
12
Suppression Control (Curtailment) of Wind
(Wind is installed at 200GW, accounting for the same scale of peak demand,
30% of total electricity demand)
 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%.
Time of the day
Suppression
Rate [%]
80-100
60-80
40-60
20-40
Day of the year
31-Dec
1-Dec
1-Nov
1-Oct
1-Sep
1-Aug
1-Jul
1-Jun
1-May
1-Apr
1-Mar
1-Feb
1-Jan
0-20
13
Load Factor of LNG Combined Cycle
 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 ?
Time of the day
Suppression
Rate [%]
80-100
60-80
40-60
20-40
0-20
31Dec
1-Dec
1-Nov
1-Oct
1-Sep
1-Aug
1-Jul
1-Jun
1May
1-Apr
1-Mar
1-Feb
1-Jan
Wind: 5GW
Day of the year
Time of the day
Suppression
Rate [%]
Wind: 200GW
80-100
60-80
40-60
20-40
0-20
Day of the year
31Dec
1-Dec
1-Nov
1-Oct
1-Sep
1-Aug
1-Jul
1-Jun
1May
1-Apr
1-Mar
1-Feb
1-Jan
(the same scale of
peak demand,
30% of total
electricity demand)
14
Sensitivity Analysis on Battery Cost
 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.
Cost scenario of rechargeable sodium-sulfur (NAS) battery
Base.
1,200
40
160
4,500
Unit Facility Cost [$/kW]
Unit Facility Cost [$/kWh]
Unit Expendable Material Cost [$/kWh]
Lifetime [cycle]
-25%
900
30
120
4,875
-50%
600
20
80
5,250
-75%
300
10
40
5,625
-90%
120
4
16
6,000
Power generation
1600
1400
TWh
Battery(out)
Suppressed Wind
1200
Pumped(out)
1000
Wind
800
PV
LNGCC
Coal
600
400
Nuclear
200
Hydro
0
-200
-400
Pumped(in)
Battery(in)
Battery Battery - Battery - Battery - Battery base
25%
50%
75%
90%
Suppressed Wind
Suppressed PV
Battery(in)
Pumped(in)
Battery(out)
Pumped(out)
Wind
PV
Biomass
Oil
LNG
LNG GCC
Coal
Nuclear
Geothermal
Hydro
Demand
15
Installed Battery Capacity
 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.
Power capacity (kW)
100
90
80
70
60
50
40
30
20
10
0
Energy capacity (kWh)
3000
GW
GWh
2500
2000
1500
1000
500
0
Battery
base
Battery
-25%
Battery
-50%
Battery
-75%
Battery
-90%
Battery Battery Battery Battery Battery
base
-25%
-50%
-75%
-90%
16
SOC (state of charge) of Battery
(Wind is installed at 300GW, accounting for 1.5 times the peak demand, 50%
of total electricity demand)
 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)
3000
Stored Electricity [GWh]
2500
2000
Pumped
1500
Battery
1000
Battery
500
Pumped-hydro
0
May 1
May 31
Battery cost scenario: -90% (Wind: 300GW, NAS battery: 79GW/579GWh)
3000
Stored Electricity [GWh]
2500
Battery
2000
Pumped
1500
Battery
1000
500
Pumped-hydro
0
May 1
May 31
17
Technical Compatibility between Wind and Battery
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
Time of the day
8:00 PM
4:00 PM
12:00 PM
Output[p.u.]
0.8-1
0.6-0.8
0.4-0.6
8:00 AM
4:00 AM
0.2-0.4
0-0.2
Day of the year
31-Dec
1-Dec
1-Nov
1-Oct
1-Sep
1-Aug
1-Jul
1-Jun
1-May
1-Apr
1-Mar
1-Feb
1-Jan
12:00 AM
18
Concluding Remarks
 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 longcycle 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.
19
Thank you for your kind attention.
Ryoichi Komiyama
Associate Professor
Resilience Engineering Research Center
University of Tokyo
komiyama@n.t.u-tokyo.ac.jp
20
(Appendix) Performance of Rechargeable Battery
Energy density (Wh/kg)
Energy Efficiency (%)
Lifetime (cycle)
Cost ($/kW)
Cost ($/kWh)
Lead
35
87
4,500
1,500
500
NAS
110
90
4,500
2,400
250
Ni-MH
60
90
2,000
1,000
1,000
LiB
120
95
3,500
2,000
2,000
(Source) METI “Current Situation on Battery Technology” (in Japanese), Feb. 2012
21