El 15 de febrero de 2017 recibimos en la Fundación Ramón Areces la visita de Daniel Kammen, profesor de la Universidad de California (Berkeley), para hablar sobre 'La ciencia y la política de la energía sostenible'. Esta actividad se celebró en colaboración con Economics for energy.

1. Daniel Kammen
Energy and Resources Group, Goldman School of Public Policy
& Department of Nuclear Engineering
Director, Renewable and Appropriate Energy Laboratory
University of California, Berkeley
Science Envoy for the U. S. State Department
Economic Challenges for Energy, Madrid, Spain - February 15, 2017
The Science and Policy of
Sustainable Energy

2. http://rael.berkeley.eduhttp://rael.berkeley.edu
Takeaway message:
Scientific and technical transformations are
critical to enabling a sustainable energy
system, but it is the energy-information
nexus that provides the ‘killer app’ for
innovation and change
This is true on-grid and off-grid in
developing nations

3. A revolution in climate politics
U.S.- China Joint Announcement on Climate Change, 2014

5. 5
INDC Commitments
in the Paris Accords
Innovations
not yet envisioned

6. 6

7. http://rael.berkeley.eduhttp://rael.berkeley.edu

9. CA Peak Power: Testimony by Goldstein and Rosenfeld (Dec. 1974)

10. http://rael.berkeley.edu
10

11. 11
Summary
http://rael.berkeley.edu

12. http://rael.berkeley.eduhttp://rael.berkeley.edu

13. 13
June 2, 2016: Dubai Electricity and Water
Authority (DEWA)
800 MW of solar at 2.54 UScents/kWh
Location: Mohammed bin Rashid Al Maktoum Solar Park
Dubai’s goal: lowest carbon footprint of any city in the world

14. http://rael.berkeley.eduhttp://rael.berkeley.edu
The Solar Energy Industry is an International Partnership

15. http://rael.berkeley.eduhttp://rael.berkeley.edu

16. 16
16
Japanese “Sunshine” Program
way too much detail, but technology push/demand pull is clear

18. Federal R&D Policy
Can be Effective
From: R. Margolis and D. Kammen (1999)
Science, volume 285, pages 690 - 692,
30 July issue. Available at:
http://socrates.berkeley.edu/~rael/papers.html

19. Lack of Federal R&D policy…
leads to lack of support for energy options
From: R. Margolis and D. Kammen (1999)
Science, volume 285, pages 690 - 692,
30 July issue. Available at:
http://socrates.berkeley.edu/~rael/papers.html

20. If you think US public sector energy R&D
funding is doing poorly …
Kammen & Nemet (2005)

21. Nemet and Kammen, 2007

22. Investing in Innovation (or Not)

23. Trancik, et al, PLoS, 2014

24. http://rael.berkeley.eduhttp://rael.berkeley.edu

25. The SWITCH-WECC Model
! Optimization and data framework of the western North American SWITCH model.
http://rael.berkeley.edu/switch

26. Power System Models
http://rael.berkeley/edu/project/SWITCH
WECC (Western
North America)
5/2012
Chile
4/2014
East African
Power Pool
(EAPP):
1. Kenya
(6/2016)
2. ? (Selection
underway)
India, Planned:
1/2017
China, 4/2016
Malaysia,
1/2013
Kosovo
3/2013
Nicaragua:
6/2014

27. http://rael.berkeley.edu/project/SWITCH
• Capacity expansion deterministic linear program
• Minimizes total cost of the power system:
• Generation investment and operation
• Transmission investment and operation
Geographic:
– Western Electricity Coordinating Council
– 50 load areas
Temporal:
– 4 investment periods: 2016-2025 (“2020”); 2026-2035 (“2030”); 2036-2045
(“2040”); 2046-2055 (“2050”);
– 72 distinct hours simulated per period
• Dispatch simulated simultaneously with investment decisions
SWITCH Electricity Supply Model

28. 28
SWITCH – high resolution power systems
&
PROGRESS – first pass modeling tool
𝑚𝑖𝑛
(𝑐 𝑖)
. 𝑁𝑃𝑉
𝑖,𝑘=1
𝑛,𝑚
𝑇𝐶 𝑘 (𝑐𝑖)
𝑇𝑜𝑡𝑎𝑙 𝐶𝑜𝑠𝑡 𝑇𝐶 𝑘 = 𝐶𝑎𝑝𝑖𝑡𝑎𝑙 𝐶𝑜𝑠𝑡𝑖 ∗ 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 (𝑐𝑖) + [𝑉𝑎𝑟𝑖𝑎𝑏𝑙𝑒 𝐶𝑜𝑠𝑡𝑖 ∗ 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 (𝑐𝑖) ∗ 𝐶𝐹𝑖 ∗ ℎ𝑜𝑢𝑟𝑠]
𝑖=1
𝑛
𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 (𝑐𝑖) ∗ 𝑃𝑒𝑎𝑘 𝐶𝑜𝑛𝑡𝑟𝑖𝑏𝑢𝑡𝑖𝑜𝑛𝑖 ≥ 𝐴𝑛𝑛𝑢𝑎𝑙 𝑃𝑒𝑎𝑘 𝐷𝑒𝑚𝑎𝑛𝑑 ∗ [1 + 𝑅𝑒𝑠𝑒𝑟𝑣𝑒 𝑀𝑎𝑟𝑔𝑖𝑛]
𝑖=1
𝑛
[𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 (𝑐𝑖) ∗ 𝐶𝐹𝑖 ∗ ℎ𝑜𝑢𝑟𝑠] ≥ 𝐴𝑛𝑛𝑢𝑎𝑙 𝐿𝑜𝑎𝑑
𝐴𝑛𝑛𝑢𝑎𝑙 𝐿𝑜𝑎𝑑 ∗ 𝑆𝑝𝑖𝑙𝑙 𝐹𝑎𝑐𝑡𝑜𝑟 ≥
𝑖=1
𝑛
[𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 (𝑐𝑖) ∗ 𝐶𝐹𝑖 ∗ ℎ𝑜𝑢𝑟𝑠]
𝑇𝑜𝑡𝑎𝑙 𝑅𝑒𝑠𝑜𝑢𝑟𝑐𝑒 𝑃𝑜𝑡𝑒𝑛𝑡𝑖𝑎𝑙𝑖 ≥
𝑘=1
𝑚
𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 (𝑐𝑖)
Dispatch
Installed
capacity
http://rael.berkeley.edu

29. Seasonality and Storage

30. 2030/2050 Path Dependence Using SWITCH
How to plan efficiently?
• Today until 2030 and then until
2050?
• Or today until 2050?
Carbon cap scenarios:
• 80% reduc. by 2050
• 1.5°C
• CA executive order
(40% lower in 2030)
• Clean Power Plan
Preliminary Findings
Planning until 2030 for CPP results in:
• Later coal retirements
• Minor/no savings in periods 2020
and 2030
• More costly in 2040 and 2050
• CPP 9% more expensive in 2050

31. • Storage almost exclusively moves solar to the night
• Geothermal only remaining substantial baseload
Dispatch in 2050:
Flexibility and variable renewables dominate
-50
0
50
100
150
200
250
300
19 3 11 18 2 10 19 3 11 18 2 10 19 3 11 18 2 10 17 1 9 18 2 10 17 1 9 18 2 10 18 2 10 17 1 9 18 2 10 17 1 9 18 2 10 17 1 9 17 1 9 18 2 10 18 2 10 17 1 9 19 3 11 18 2 10 18 2 10 19 3 11
WECCElectricityDispatchin2050(GW)
Hour of Day (PST)
Nuclear Geothermal Biopower Coal
Coal CCS Gas (baseload) Gas CCS Gas (intermediate)
Gas (peaker) Storage (discharging) Hydro (non-pumped) Solar
Wind Storage (charging) Demand
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
31

32. 0%
20%
40%
60%
80%
100%
120%
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
2016
2018
2020
2022
2024
2026
2028
2030
2032
2034
2036
2038
2040
2042
2044
2046
2048
2050
CaliforniaGHG Emissions Compliance Pathways
Compared to European Union
CA historical GHGs EU historical GHGs AB 32 Correction CA 5% EU 3.5%
CA 2020 target EU 2020 target 2030 targets 2050 targets
Meeting the 2030 and 2050 targets will require 5% average annual abatement across
the entire CA economy
The EU, by contrast, already met the same 2020 target 10 years earlier and needs 3.5%
annual abatement to meet the 2050 target
5% is equivalent to GHG reductions during the Great Recession (‘08-’10); CA must do
this every year while growing the economy

34. http://rael.berkeley.eduhttp://rael.berkeley.edu
In China even aggressive wind, solar and storage
learning alone is not enough to phase out coal
http://rael.berkeley.edu/project/SWITCH
0%
20%
40%
60%
80%
100%
2020 2030 2040 2050 2020 2030 2040 2050 2020 2030 2040 2050 2020 2030 2040 2050
wind
hydro
nuclear
storage
solar
gas ccs
gas
coal ccs
coal
Business
as Usual
BAU with
Carbon cap
Current
aggressive
solar and wind
continued
IPCC 2050
(80% cut in
carbon)

35. http://rael.berkeley.eduhttp://rael.berkeley.edu

36. China: dispatch challenge for coal and
renewables
nuclear coal coal ccs gas
gas ccs solar storage-discharge hydro
Tick Marks represent 24 hr for a representative day
January Feburay March April May June July August September November DecemberOctober
3000 GW
0 24 hr
1st Day Represents Peak Day for Every Month
2nd Day Represents Average Day for Every Month
Source: He, Avrin, Nelson, Johnston, Mileva, Tian, and Kamme

39. The mathematical model of a
planning problem
• Given a control variable x, the
model maximizes discounted
utility over a long term horizon.
• A planning problem is by nature
a dynamic model, given the
time dependencies on the
equation of motion of the state
variable y.
• In general planning problems
are modeled as large scale
static optimization
mathematical programs.

40. Modeling alternatives
• Stochastic
Programming
Dynamic Programming
The difference between model results are mostly due to the
assumptions on the exogenous process and the impact on the
decisions (learning vs total uncertainty)

41. The role of learning in modeling
• The decision maker
can anticipate their
own learning before
making the decision.
• In the classical
receding horizon
problem, there is no
anticipates learning.
• This difference is
modeled by optimizing
after taking the
expected value of
future periods

42. Bartos and Chester, “Impacts of Climate Change on Electric Power
Supply in the Western United States.” Nature Climate, August 2015
42

43. http://rael.berkeley.edu/node/609

44. Borneo Says No
to Dirty Energy
By Jennifer Pinkowski Tuesday, Feb. 22, 2011

45. 45
Borneo Says No
to Dirty Energy
Two-thirds
of Bornean
Bird,
Mammal,
Tree and
Insect
Species
may lose
habitat
forever due
to reservoirs
Land Use for Development and Equity: Laikipia Kenya

47. http://rael.berkeley.eduhttp://rael.berkeley.edu
Energy Storage is Not Just Batteries
Natural gas (without & with storage)
Traditional and pumped hydropower
Flywheels
Flow batteries

48. http://rael.berkeley.eduhttp://rael.berkeley.edu
Example: the impact of Natural Gas
Leakage on carbon budgets
Johnstone and Kammen, 2017 in press

49. 49
Results - Kenya
http://rael.berkeley.edu

50. East African RiftValley is currently the world’s most
active geothermal development zone
• 10MW test well at Olkaria field in Hell’s
Gate National Park, Kenya
• KenGen’s first plant commissioned in
1985 (45MW) – now over 300MW at
Olkaria

51. 51
Results – Kenya (Energy mix for each scenario )
http://rael.berkeley.edu

52. 52
Kenya (Cumulative generation capacity expansion)
http://rael.berkeley.edu

53. Unelectrified People (and fuel based lighting
users) in Asia is Even Higher than in Africa
Source: IEA, 2010 World Energy Outlook
Africa: ̴ 600 million
Asia: ̴ 800 million
Americas: ̴ 30 million

54. Fuel Based Lighting : Expensive, Unhealthy, and
Inefficient
Kerosene for lighting is a $25 billion per
year industry globally (source: UNEP, 2013)
Fuel Based Lighting:
Displacing the Incumbent in Low-Income Areas
Photo by Evan MillsPhoto by Peter Alstone
Photo by Peter Alstone
Kammen – http://rael.berkeley.edu

55. Quantitative Assessments of the Sustainable Development Indicators
Literacy
Mortality
(Children)
Poverty
Education
Mortality
(Infants)
Sanitation
Alstone, Gershenson & Kammen, Nature Climate Change, 2015
http://rael.berkeley.edu 55

56. http://rael.berkeley.eduhttp://rael.berkeley.edu
Off-grid Electricity Enabled by Storage and Efficient Lights, but …
Impossible without secure mobile money

57. http://rael.berkeley.eduhttp://rael.berkeley.edu
Information Technology Enables
Transformative Energy Access Technologies

58. http://rael.berkeley.eduhttp://rael.berkeley.edu
Information Technology Enables
Transformative Energy Access Technologies

59. 59

60. Laudato Si
Encyclical Letter on Care for our Common Home

61. http://rael.berkeley.eduhttp://rael.berkeley.edu
http://coolclimate.berkeley.edu/maps

62. 62

63. 63

64. http://coolclimate.berkeley.edu/maps

68. (Total household energy CO2e)

74. Energy Transportation
Consumption Total
Household GHG emissions in New York Metro Region

76. New YorkSan Francisco
Bay Area
Chicago
Total
Household GHG emissions in four metro regions
Dallas

77. California Advancing Energy Efficiency

78. http://rael.berkeley.eduhttp://rael.berkeley.edu
Jones and Kammen, 2014
http://coolclimate.berkeley.edu/maps

79. http://rael.berkeley.eduhttp://rael.berkeley.edu
New York San Francisco
Bay Area
Chicago Dallas

80. http://rael.berkeley.eduhttp://rael.berkeley.edu
Jones and Kammen, 2014
http://coolclimate.berkeley.edu/maps

81. http://rael.berkeley.eduhttp://rael.berkeley.edu
Takeaway message:
Scientific and technical transformations are
critical to enabling a sustainable energy
system, but it is the energy-information
nexus that provides the ‘killer app’ for
change