Managing Local Energy and Environment Interfaces: AIMLocal Model Applications

1
Managing Local Energy and Environment
InterfacesAIM-Local Model Applications

• P.R. Shukla

2
Introduction

• Modeling the dilemma of providing energy services
  and protecting the environment in a local region

SO2, NOX, SPM, CO2
Acid precipitation
Air pollutants
Energy Service Demand
Energy Technology
3
AIM Local Model Methodology
4
Model Formulation

• (1) Service demand constraint
• Al,j,i Service supply quantity by technologies
  and regions
• ?l,j,i Social service efficiency by
  technologies and regions
• Xl,p,i Operating quantity by technology
  combinations (l,p) and regions

5

• (2) Operating capacity constraint
• ?l,i Operating efficiency by technologies and
  regions
• Sl,p,i Stock quantity by technology
  combinations and regions

6

• (3) Energy supply constraint
• Energy consumption by fuels, technologies
  and regions
• ?k,l,i Energy efficiency improvement by
  operation style and maintenance

7

• (4) Emission constraint
• Emissions
• Emission factors
• dl,p,im Pollutant release ratio by technology
  combinations and regions

8

• (5) Cost functions
• Initial cost
• Operating cost
• Environmental cost

9

• (6) Objective function

10
Model Formulation in GAMS
An Example of Transport Problem
SETS
PARAMETERS
VARIABLES
EQUATIONS
11
AIM-Local Database System
AIM workshop 2001
12
Large Point Source and Area Source
3.Sector
Emission by point
Large Point Source
Emission by City
Emission by City and Sector
Emission by Region and Sector
Area Source
2.Region
13
Structure of AIM-Local Database
Energy service tech. (LT) Air Pollution Control
(P) - Energy Cons.(K L P T), - Service Supply
(L J T) - Fixed Cost (L P T) - Removal Rate (L
P T) etc.
Energy Service Tech.(L T)
5. Service
6.Technology
Air Pollution Control(P)
Service Demand( I J )
7.Stock
Stock Quantity ( L T0 )
Subsidy ( I L T )
10.Counter- measure
Regulation( ME M T)
Technology Selection Module (AIM-Local GAMS ver.)
Share Potential( I L J T )
8.Share
Maintenance etc.( I LT )
Operating Rate ( I L T )
9.Performance
Tax( ME M T)
I LPS or Area L Energy Device P Removal
Porcess J Service K Energy M Gas (CO2, SO2,
NO2) T Time ME Group on measure
Energy Consumption CO2 Emission SO2/NO2
Emission ( I L T )
Energy Price Emission Factor ( K T )
4.Energy
14
Input and Output

• Input
• (1) Energy
• Fuel type, Fuel price,
• Emission factors by fuels and technologies
• Energy resource constraints
• (2) Technology
• Initial cost, Operating cost
• Life-span, Capacity, Share
• Energy consumption by fuels for a unit production
• Pollutants removal technologies and combinations

15

• (3) Service demand by regions and sectors
• Historical service data
• Future service demand forecast
• Economic development plans from the local
  government
• Development plans from the local industries
• (4) Air pollutant emission constraints
• Current air pollutant emissions
• Local environmental protection policies

16

• Output
• (1) Aggregated results
• Total energy consumption by years
• Total costs by years
• Total CO2 emissions by years
• Total air pollutant emissions by years
• (2) Technology options
• CO2 emissions by technologies and years
• Air pollutant emissions by technologies and years
• Energy consumption by technologies and years

17

• (3) Service output
• Service output by regions, sectors, technologies
  and years
• (4) Energy balance table
• Energy balance table for the local region by
  years (with energy information for sectors,
  technologies and fuel types)

18
Model Features

• Simplified Structure
• Modeling local environmental constraints
• Direct benefit and co-benefit of counter measures
• Flexible model structure to cope with various
  practical situation in different regions
• GAMS programming
• GIS Interface

19
Geographical Information System (GIS)
20
Why GIS?

• Capture location sensitivity
• Provide layered information
• Analyze time slices
• Integrate location and time information in a
  consistent framework

21
Spatial Data Characteristics

• Spatial data are characterized by information
  about position, connections with other features
  and details of non-spatial characteristics
• latitude and longitude as a geographical
  reference
• connection details such as which service roads,
  lifts and ski trails would allow the
  meteorologist access to the weather station
• non-spatial (or attribute) data, for instance
  details of the amount of snowfall, temperature,
  wind speed and direction

22
Data Models
Raster data Model (sometimes referred to as
grid) Vector Data Model (an entity is a
component or building block used to help data
organization)
23
GIS Database
Integrated GIS Database
24
Examples of GIS Application to AIM-Local
25
Beijing City

• Economic Features
• Per capita GDP 3 times of the national level
• Industry 60 of GDP
• Heavy Industry 80 of industrial GDP

26
Beijing City Regional Details
27
Source Beijing Statistical Yearbook 2000.
28
Source Beijing Statistical Yearbook 2000.
29

• Sources
• Beijing Municipal Statistics Bureau (1999).
• Beijing Municipal Government (1992).
• Beijing Municipal Planning Commission (2000b).

30

• Sources
• Beijing Municipal Statistics Bureau (2000).
• Beijing Municipal Planning Commission (2000).
  
• Beijing Municipal Government (1992).

2000 2005 9.5 2006 2010 9.0 2011
2020 8.5
31

• Large Point Sources data

32

• Beijing Cement Plant

Technology dry kiln with pre-decomposition
process Capacity 2000 t/d Production 525
Portland cement, 0.74 Mt /a Location Changping
District, Beijing City
33

• Beijing Yanshan Petroleum and Chemical Group
  Corporations

Refinery
Technology heavy oil based refinery
process Capacity 6.0 Mt /a Location Fangshan
District, Beijing City
34

• Beijing Yanshan Petroleum and Chemical Group
  Corporations

Ethylene
Technology Diesel oil based process Capacity
0.45 Mt /a Location Fangshan District, Beijing
City
35

• Beijing Shijingshan Thermal Power Plant

Technology coal boiler Capacity 4000 MW
Location Shijingshan District, Beijing City
36

• Beijing Capital Steel Corporations

Capacity 8.00 Mt Location Shijingshan
District, Beijing City
37
Area source data

• Residential sector
• Commercial sector
• Transportation sector
• Other sectors

38
Results
Beijing Capital Steel Corporations
Beijing Shijingshan General Power Plant
39
1995
SO2 intensity (t-SO2/km2)
2020 (case 1)
2020 (case 8)
2020 (case 6)
40
1995
CO2 intensity (t-C/km2)
2020 (case 1)
2020 (case 6)
41
Ahmedabad City, India

• High economic and demographic growth
• Industrial base
• Growing transport demand

42
India
43
Ahmedabad District
Note Figures in brackets show Urban share
44
Ahmedabad Municipal Area
45
Ahmedabad Municipal Area (South Zone)
46
Ahmedabad Area CO2 Emissions 2030 (MT)
47
Ahmedabad Area SO2 Emissions 2030 (MT)
48
Ahmedabad LPS CO2 Emissions 2030 (kT)
49
Ahmedabad LPS SO2 Emissions 2030 (kT)