advanced stochastic optimization modeling of the water ... · background model description...
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China University of Mining and Technology, Beijing
Center for Resources and Environmental Policy Research
Advanced stochastic optimization modeling of the water-energy-food
nexus for robust energy and agricultural development: Coal mining
industry in Shanxi
province, China
Xiangyang Xu1;Junlian Gao1;Cuiqing Sun1;Guiying Cao2;
Yermoliev Yurii2; Ermolieva Tatiana2;Elena Rovenskaya2;
1. Center for Resources and Environmental Policy Research
China University of Mining and Technology, Beijing
2. IIASA(International Institute for System Analysis), Austria
June 1st ,2016
Background Model description Numerical experiments Conclusion
Coal is and will continue as key source of energy in China
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20.0
40.0
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80.0
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13
%
the share of coal consuption in China
2020: 63%
2040: 55%
Source : China Statistic Yearbook ;U.S. Energy Information Administration (EIA)
Background Model description Numerical experiments Conclusion
The challenges facing by coal industry in China
• Air pollution
• Greenhouse gas emissions
• Land damage
• Water shortage
Background Model description Numerical experiments Conclusion
1) Air pollution
Relationship between the coal consumption and the days of haze
62 % of PM2.5; 93 % of SO2; 70 % of NOx
Source: Report Coal Utilization's Contribution to China's Air Pollution
Background Model description Numerical experiments Conclusion
2) CO2 Emission
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500000
1000000
1500000
2000000
2500000
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0.80
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1.80
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10
mill
ion
to
ns
ton
per capita in total
Total and per capita CO2 emissions from 1950 to 2010 in China 80% of CO2 emissions from all energy use in China
Source : Oak Ridge National Laboratory , International Energy Agency
Background Model description Numerical experiments Conclusion
3) Land damage
• Overlap areas between the coal reserve and farmland account for more than 40% of the total farmland area in China
• Damage farmland have reached 700,000 hectares
• Occupied farmland have reached 15,000 hectares
Source: Hu Z., et al. (2014)
Background Model description Numerical experiments Conclusion
4) Water shortage
Geographical mismatch between water availability and coal industry Source : China Water Risk
Background Model description Numerical experiments Conclusion
What is the future for coal industry in China? Resort to technology ? Every coins have two sides
CCSDesulfurization
technologyDenitration
technologyCoal washing Filling back
Land
damage
Water
consumption
Air pollutionCO2
emission
-+
+ +
-- -
++
-
Background Model description Numerical experiments Conclusion
A sustainable future for coal?
Background Model description Numerical experiments Conclusion
Network of coal industry system
Background Model description Numerical experiments Conclusion
Framework of the model
Output
Water resource
The optimal coal production
The portfolio of technology
Water consummation
and water storage
The optimal crop production and crop structure
Land use/food production Wheat Corn Millet Sorghum
Oats Buckwheat Bean Potato
Water supply
Coal Conversion Power
generation
Gasification
Coke
Chemical
Others
Coal Processing
Coal Wash
Dry Wash
Others
Coal Mining
Long wall face
Backfill mining
Opencast
Land subsidence
Land reclamation
Water supply
Crop structure and Irrigation technology
Water-dependent coal technology
Goal function
the production cost of a unit (i.e., ton) of coal of type in location
the transportation cost of a unit of coal of type from location to location
the conversion costs of a unit of coal of type by technology in location
the costs associated with production of a unit of the agricultural commodity
in location
the transportation cost of a unit of the agricultural commodity from location
to location
the distance form location to location
,, , , ,
Min CP CT CC AP AT
ij ijmt ijm ijmt jm imt ilmt kj kjm kjl kjm jmx y
i j k m t
c x c x d c x c y c y d
CP
ijC i jCT
ijmCi j m
CC
imtCi j m
AP
kjC k
j
AT
kjmC k j
m
jmd j m
Background Model description Numerical experiments Conclusion
Background Model description Numerical experiments Conclusion
, , , , ,
P d c
ij imlt imt ijmt kj kjm j
i m t i j t k m
w x w x w y w
, , , , ,
(1 )kj kjm ijmt j j ij ijmt ij j
k m i m t i m t
l y x r l l x g L
,
d d
ijmt ijmt m
i, j t
x D
kjm km
j
y D
,
c
ijmt ij
m t
x C
, ,
,O
ijmt j
i m t
x C m j , ,
,I
ijmt m
i j t
x C m j
2 2, ,
, ,
SO d SO C
imt ijmt m
i j t
e x ENO , ,
, ,
x xd NO C
imt ijmt m
i j t
e x E
2, 2,
, ,
CO d CO C
imt ijmt m
i j t
e x E
Constraints
1) Water
2) Farmland
3) Demand for coal conversion product
4) Demand for food
5) Production capacity
6) Transportation capacity
7) Air pollution
8) CO2
Background Model description Numerical experiments Conclusion
Constraints
9) Rate of coal process
10) Demand of coal
11) Nonnegative constrains
' '
, , ,
(1 )o jmt j ijmt
m t i m t
x x
, , ,
ijmt
i j t m
x I D
0ijmtx 0kjmy
Analysis of the uncertainties
The source of uncertainties
1)Nature
Climate change
2)Policy
Industry policy/ Environment policy
3)Market
Coal market/ Alternative energy market
4)The limitations of cognitive
Technical parameter
Background Model description Numerical experiments Conclusion
Deterministic TO Stochastic
Solutions from Deterministic model
Solutions from
Stochastic model
Integrated two-stage stochastic model
• Policy recommendations
can lead to sunk costs,
irreversibility if other
scenario occurs.
• Policy recommendations
is a robust solution
under certain security
level.
• scenarios -by-
scenarios analysis
produces set of
degenerated different
solutions
• One roboust soluton
for all water avaiable
scenarios
Background Model description Numerical experiments Conclusion
• Uncertainty of water supply
• Uncertainty of water demand
• Systemic Risks:
Shortages of coal production
Food shortages
• When will they happen– dry or wet years ?
Background Model description Numerical experiments Conclusion
Water security level • The goal function includes the security(risk) factors
• Optimal condition for is as below:
0))()((Pr,,,
' tmki
jjkjmjkijmtijtj
inv
j ZwWyWxWobCFjZ
j
inv
j
tmki
jjkjmjkijmtijt CZwWyWxWob /))()((Pr,,,
j
On the left - the probability of water shortage in the location
On the right - the ratio of investment per addition water storage to the cost/loss
associated with water shortage.
The robust solution , from the stochastic model ensures the certain water
security level .
*
ijmtx *
kjmy
j
inv
jC /
])([Pr~}])(,0[max{ ZWWyWxobZWWyWxE
- security level
),,( zyxF
Background Model description Numerical experiments Conclusion
Background Model description Numerical experiments Conclusion
Application scope of the model
1) Scale of the model
• Spatial : country, province, region, coal base
• Temporal: static
2) Boundaries of the geographical unit
• Political
• Physical
3) Precision of the forecast model
• Dependent on data
4) Application area
• Scenarios’ analysis
• Policy simulation
Background Model description Numerical experiments Conclusion
Case study area: Shanxi
• Arid and semi-arid areas
Per capita water resource in Shanxi is only around 300 m3, which is equal to 1/7 of the per capita water resource of China, 1/25 of the per capita water resource of the world.
• Largest coal basic reserve in China
90.842 billion tons, accounting 40% of the total coal reserves in China, With a coal-bearing area of 62,000 km2, which accounts for 40% of the whole province area. Out of 119 counties in Shanxi, 94 counties have coal resource distribution.
• Land damage
Land subsidence caused by coal mining and occupied by the waste of coal mining has reached 68,000 hectare and the speed of those areas is increasing by 5,000 hectare per year, of which, 40% is the farmland
Scenario analysis in STO model
• Scenario of coal demand (unit: tons)
• Scenario of crop demand(unit: tons)
• 20 years water historical data for all 11 cities-to conclude probability distribution of water availability
• Different energy/food security combination in STO model
• water security level - 90%
1(-20%) 2(-10%) 3(2012) 4(10%) 5(20%)
740340000 822600000 914000000 1005400000 1105940000
A(-20%) B(-10%) C(2012) D(10%) E(20%)
11699089 12998988 14443320 15887652 17476417
Background Model description Numerical experiments Conclusion
Result of STO model
water security 90%
Water storage is more sensitive to the food demand.
The interaction on land use between food production and coal mining is not strong.
Background Model description Numerical experiments Conclusion
Optimal Results in scenario Year 2012
Crop production Coal production
Background Model description Numerical experiments Conclusion
Compare with the actual situation
0
2
4
6
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12
Wat
er
Vo
lum
e(1
00
mill
ion
m3
)
Water for Crop
Actual Model
Total water consumption for Crop: Model: 31.21 Actual: 39.92
22% less
Background Model description Numerical experiments Conclusion
Compare with the actual situation
Taiyuan, Datong,Changzhi, Jincheng, Xinzhou and Lvliang can produce more coal.
Lvliang is not suitable for crop production due to water resource situation.
Background Model description Numerical experiments Conclusion
Different Energy/food security
The coal production in Shanix is more efficient in other province.
The more efficient solution for crop demand in shanxi is to import food from other province.
Value of Stochastic Solution
The solution stochastic model is better than that from the deterministic model.
The value of STO-goal function with deterministic solution
The value of STO-goal function with robust
solution Perc. difference
Total Cost 2.82425E+12 2.41044E+12 17.2%
The Value of Stochastic Solution (Model), VSS, estimates the importance of incorporating uncertainties and applying the stochastic model It compares the value of stochastic goal function with deterministic and with robust solutions: ),,( *** DetDetDet zyxF ~),,( *** RobRobRob zyxF
Background Model description Numerical experiments Conclusion
• The model stresses the importance of water storages for
sustainable development of coal production in water scarce
regions.
• For coal-rich area, food production could not be high level. The
policy makers may arrange an agreement on food imports with
other food producer.
• To improve the food security, advanced irrigation system should
be applied.
• The robust from solution of the stochastic model is better than
the solution from the deterministic model in terms of VSS.
Background Model description Numerical experiments Conclusion
Background Model description Numerical experiments Conclusion
Potential extensions
• Static to dynamic model
• Constraints extension
• Policy red line to Physical red line
• Link to hydrological model , land use model and
agriculture model
• Database improvement(GIS)
Background Model description Numerical experiments Conclusion
Thank you for your attention!