Post on 08-Oct-2020
A coupled energy & air quality model for lowest
cost energy solutions, respecting air quality constraints:
development and initial results
1
Dan Zachary
May 6, 2014
NOAA SEMINAR - NCWCP Conference Center College Park
Introduction to energy – air quality modeling
• The model
• An illustrative example
• Results
Daniel Zachary (Applied Physicist, Mathematician)
Ulrich Leopold (Geographer, finishing PhD)
Olivier Baume (Computer Scientist)
• Luis Alexandre Duque Moreira De Sousa (GIS, Computer Scientist, PhD student)
• Chris Eykamp (GIS expert, programer)
• Chris Braun(GIS expert, geographer)
• Lara Reis (Atmospheric scientist) - now in Milan, Italy
• Laurent Drouet (Computational scientist) – now in Milan, Italy
TUDOR Modeling Group – Research snapshot
Integrated assessment: Energy-AQ
Geospatial
analysis
Energy
projections
Bayesian risk
(atmospheric
forecasting)
AQ
Integrated assessment: Impact
Ref. Lara Reis, Ph.D. Defense
Air pollution – a major concern
A need for integrated solutions
Some models explore solutions via simulation – e.g.
(EC4MACS)
Introduction / Motivation
• The model (Energy-emissions / Air Quality)
• An illustrative example
• Results
14
Energy transition
Emissions/AQ
Geocomputation
Approaches – e.g.
optimization & coupling
Energy Technology
Environmental Model -
ETEM
GIS / geospatial analysis
tools
The integrated assessment model – the LEAQ model
http://crteweb.tudor.lu/leaq/
The ETEM model
ETEM (Energy Technology Environmental Model)
The ETEM model
###############
# #
# ETEM model #
# #
###############
# Date : 11/2008
# Version : 2.0
# Authors : L. Drouet et J. Thenie
# Language : GMPL
# command : glpsol -m model_file.mod -d data_file.dat -y display_file.txt -o
output_file.txt
# example : glpsol -m etem.mod -d geneva.dat
param nb_periods >=1;
param period_length >=1; # expressed in year.
set T := 1..nb_periods; # time periods.
set L; # localization
set S; # slice periods
set P; # processes
set C; # commodities
set DEM within C; # useful demands
set IMP within C; # imported commodities
set EXP within C; # exported commodities
set FLOW; # commodities groups labels
set FLOW_IN{P} within FLOW; # incoming flows
set FLOW_OUT{P} within FLOW; # outcoming flows
set C_ITEMS{FLOW} within C; # set of commodities
set P_MAP{L} within P; # localization of processes
Plus about 350 more lines
The ETEM data data;
# set of time slices
set S:=
WD # Winter Day
WN # Winter Night
SD # Summer Day
SN # Summer Night
ID # Intermediate Day
IN; # Intermediate Night
# set of localisations (cities)
set L:=
LUXEMBOURG
HAUTSURE
CADIOM;
# set of processes
set P:=
# Electricity Industrial
I11 # Electrical appliances # existing technology
I13 # El. savings industrial 2 # new technology
I14 # El. savings industrial 3 # new technology
I15 # El. savings industrial 4 # new technology
I1A # El. savings heat pump # new technology
I1B # El. savings clim/air # new technology
I1C # El. savings cold # new technology
I1I # El. savings compressor # new technology
I1J # El. savings pumps # new technology
I1K # El. savings fax/photocopy # new technology
# LTH Industrial Area
IA1 # Electric # new technology
Plus about 2500 more lines
The ETEM interface
Emissions
The air quality model
The air quality model – example of dynamics in a
Lagrangian model
Brownian motion
Other dynamics included - Brownian diffusion - Brownian turbulence
The air quality model – dynamics
…
• ..
33
The air quality model
O3
VOC NOX
34
Energy transition
Approaches – e.g.
optimization & coupling
Energy Technology
Environmental Model
GIS / geospatial analysis
tools
The integrated assessment model
http://crteweb.tudor.lu/leaq/
The coupled model – combining ETEM and AQ with
OBOE
Cost minimization problem: Min { (e) : AOT(e,p) AOTmax}
= min {c’x |Ax = b , x 0} p = pollution (O3 concentration in ppb) level decision variable e = emissions (tonnes per year) decision variable AOT = Accumulated Ozone exposure over a Threshold
ETEM
Introduction / Motivation
• The model (Energy-emissions / Air Quality)
• An illustrative example
• Results
Example – a very simple economy
Car of type 1 –
inexpensive, heavily
polluting, maximum
N1
Car of type 2 –
expensive, lightly
polluting, maximum
N2
Supply & demand – for 2 types of cars
Car – type 1 Car – type 2
A short overview of convex optimization
En
ergy C
ost
s
number of cars (of type 1)
cost
demand
o
Optimal cost without
AQ constraints
N1
Convex Bounds due
to non-linear AQ
constraints
A short overview of convex optimization
En
ergy C
ost
s
number of cars (of type 1)
cost
demand
Emission constraints
o Optimal cost with
AQ constraints
Optimal cost without
AQ constraints
Bounds (min, max
cars of type i)
A short overview of convex optimization
En
ergy C
ost
s
number of cars (of type 1)
convex cost curve
Bounds to cost
Select a starting
point
A short overview of convex optimization
En
ergy C
ost
s
f(x) = cost curve
number of cars (of type 1)
Bounds (min, max
cars of type i)
Bounds to cost
Select a starting
point
Simulated cost
A short overview of convex optimization
En
ergy C
ost
s
f(x) = cost curve
number of cars (of type 1)
Bounds (min, max
cars of type i)
A short overview of convex optimization
En
ergy C
ost
s
f(x) = cost curve
number of cars (of type 1)
Sub-gradient
(support plane)
Simulated cost
A short overview of convex optimization
En
ergy C
ost
s
number of cars (of type 1)
Sub-gradient
(support plane) Acceptable region
(where solution must
be found)
A short overview of convex optimization
En
ergy C
ost
s
number of cars (of type 1)
Sub-gradient
(support plane) Acceptable region
(where solution must
be found)
Geometric center of
acceptable region
A short overview of convex optimization
En
ergy C
ost
s
number of cars (of type 1)
Sub-gradient
(support plane) Acceptable region
(where solution must
be found)
Geometric center of
acceptable region
2nd suggested point
A short overview of convex optimization
En
ergy C
ost
s
number of cars (of type 1)
Sub-gradient
(support plane)
Acceptable region
(where solution must
be found)
Geometric center of
acceptable region
2nd suggested point
2nd Sub-gradient
A short overview of convex optimization
En
ergy C
ost
s
number of cars (of type 1)
Sub-gradient
(support plane)
Acceptable region
(where solution must
be found)
Geometric center of
acceptable region
2nd suggested point
2nd Sub-gradient
New lower bound
A short overview of convex optimization
En
ergy C
ost
s
number of cars (of type 1)
Sub-gradient
(support plane)
Acceptable region
(where solution must
be found)
Geometric center of
acceptable region
2nd suggested point
2nd Sub-gradient
New lower bound
A short overview of convex optimization
En
ergy C
ost
s
number of cars (of type 1)
A short overview of convex optimization
En
ergy C
ost
s
number of cars (of type 1)
A short overview of convex optimization
En
ergy C
ost
s
number of cars (of type 1)
A short overview of convex optimization
En
ergy C
ost
s
number of cars (of type 1)
A short overview of convex optimization
En
ergy C
ost
s
number of cars (of type 1)
Solution point
(in 1D)
A short overview of convex optimization
En
ergy C
ost
s
number of cars (of type 1)
Results
62
Three results
1) Emissions & Air quality management 2) Public health & planning 3) Energy policy
Results - e.g. Luxembourg (Scenario 1)
Results - e.g. Luxembourg (Scenario 2)
Results - e.g. Luxembourg region
Thank you Zachary D.S. Land cover change using an energy transition paradigm in a statistical mechanics approach, Physica A: Statistical Mechanics and its Applications, 2013. Zachary D.S. and Dobsen, S. Does urban space evolve deterministically or entropically? An exploration of urban development models for Sheffield, UK in relation to decentralized energy policies, Energy Policy (In review), 2013 Reis, L.A., Drouet L., Zachary D.S., Peters B., Melas D., Leopold U., Implementation of a full air quality model in an integrated assessment, Environmental Modeling and Software, in press, 2013 Reis L.A., Melas D., Peters D., Zachary D.S., Developing a fast photochemical Calculator for an integrated assessment model, International Journal of Environmental Pollution, Vol. 50, Nos. 1/2/3/4, 2012 Zachary D.S., Drouet L., Leopold U., Reis L.A. Trade-offs Between Energy Cost and Health Impact in a Regional Coupled Energy-Air Quality Model, Environmental Research Letters, 6(201), doi:10.1088/1748-9326/6/2/024021, 2011.
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2) Public health and planning
Without Impact
considerations
With Impact
considerations
Zachary D.S., Drouet L., Leopold U., Reis L.A. , Environmental Research Letters, 6(201), 2011.
Min{()I( ): p() - } 0 = emission (tons per year) (decision variable) = total discounted energy costs I = impact function (ozone - health) p = ozone concentration (ppb) = average ozone concentration (ppb) (decision variable