development of a new technology-rich simulation environment for
TRANSCRIPT
Dr Adam Hawkes CEng MEI
Deputy Director, Sustainable Gas Institute
Development of a new technology-rich simulation
environment for exploring energy system transitions
New SGI Spoke:
???
SGI Spoke: Gas Innovations
SGI Spoke: Energy Efficiency
PROVIDES INTEGRATING RESEARCH, TRANSLATION
AND EDUCATION ACTIVITIES
SGI Spoke: Carbon Capture,
Storage and Use
SGI HUB EDUCATION
SGI HUB KNOWLEDGE TRANSFER (TRANSLATION)
SGI HUB RESEARCH THEMES
50%
35%
15%
Gas Technology Modelling Environment
Sustainable Gas Technology
Gas and the Environment
Gas in Future Energy Systems
SGI Hub and Spoke Integration
Gas Innovations Collaboration
Gas Innovation Centre: BG Group / FAPESP / University in Brazil: $10m + $10m
Gas Innovation Fellowship Programme: BG Group / Imperial / Univ. of Sao Paulo
20 PhD students + 5 x 4 year Post-docs
ENGINEERING PROGRAMME
• Compact “low carbon” natural gas power generation
• Natural gas/hydrogen fuels for shipping
• Associated developments to optimise use of natural gas in shipping
• Techniques to measure, evaluate and reduce methane loss from gas systems
PHYSICAL CHEMISTRY PROGRAMME
• Advanced cleaner natural gas combustion
• Fuel Cell developments
• Conversion of natural gas to chemicals e.g. H2, CO & NH3
POLICY AND ECONOMICS PROGRAMME
• Policies for the development of gas in energy
systems
• Development a supply chain for natural gas for
remote areas
• What is the role of gas in future low carbon
energy systems?
• What conditions may lead to stranded assets –
why, where, when?
• What technology R&D should we invest in?
Headline questions
Working title: Modular Unified energy
system Simulation Environment
(MUSE)
Market
Clearing
Algorithm
Primary
supply
sectors
Conversion
sectors
End-use
demand
sectors
Price
Demand Demand
Price
Dem
an
d
Pric
e
• Partial equilibrium
on the energy
system (models
supply and demand)
• Engineering-led and
technology-rich
• Modular: Each
sector is modelled in
a way that is
appropriate for that
sector
• Microeconomic
foundations: all
sectors agree on
price and quantity
for each energy
commodity
• Limited foresight
decision makers
• Policy instruments
explicitly modelled
• Simple macro
feedbacks
Pric
e
Dem
an
d
Market Market Market
Pric
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em
an
d
Da
ma
nd
, p
rice
Module Module Module
Pric
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em
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Price
, d
em
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Price
, d
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Pric
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Super-loop
MUSE solve structure - foresight
Year 1 Year 2 Year 3
MUSE module high-level detail – Power sector
Existing Capacity Electricity demand projection
(inc. time-slice information)
Fuel prices and CO2e
projection
Capacity Expansion
Operation/Dispatch
Markup and/or Regulatory layer
Price (time-sliced)
Market Module
Other sectors
Fuel demand
and emissions
New tech.
characterisation
Illustrative O&G module structure and relations
Resources and Reserves
Sub-module
Extraction Operations
Sub-module
Transport Sub-module
Power Generation and Markets
Module
Electricity Price
Natural Gas Demand
Natural Gas Market Module
Crude Oil Demand
Oil Market Module
Natural Gas Price
Crude Oil Price
CO2 Price
CO2 Capture, Storage and Use
Module CO2 Production
Resource Step Functions
Extraction Profiles
Tech costs
Tech performance
Tax, Discount rates
Exogenous
Oil and Gas Module
Con
trol B
lock
Illustrative O&G module processing
Oil and Gas Module
Resources and Reserves Sub-module: Builds commodity supply curve based on resource
characteristics and lifting cost, taking inputs from extraction and transport sub-modules.
Transport Sub-module: Models technology performance and cost for transport from fields to
processing/refining, and onwards to market hub.
Extraction Operations Sub-module: Models technology performance and cost for key extraction
tasks of compression, pumping, heating and power generation.
Resource and
Stock Data Lifting Costs
Reserves (Step
Function) Transport Cost
Price
(Step)
Prime Mover Efficiency Technology Options Unit Costs and Uptake Constraints
Technology Options (e.g. LNG supply chain) Unit Costs and Uptake Constraints
WHR Technology Options Unit Costs and Uptake Constraints
Process/Site Integration Options Unit Costs and Uptake Constraints
Demand
Price
Costs breakdown Tota
l C
ost
Capital
Region-dependent
Depth associated Daywork
Fuel & Power
Water
Non-depth associated
Equipment Rental
Transportation
Accessibility
Lease
Universal Non-depth associated Supervision
Safety
Fixed Region-dependent
Administration
Royalties
Security
Universal Well servicing
Variable Region-dependent
Severance Tax
Processing (CO2/H2S)
Compression
• Well costs hard to characterise:
operating costs not correlated with
capital costs
• Main Capex driver: well depth.
total average cost
marginal cost
n = 2
1000 wells
0 20 40 60 80 100 120 14010
12
14
16
18
Q
11
Economics
Of Deep Drilling
In Oklahoma. CAER
Report 2005.
Cost
Example: Region dependent Capex
• Aggregate major contributors to depth related costs into a single depth/region-dependent parameter.
• Aggregate major contributors to Non-depth associated costs into a single region-dependent parameter.
2015 Well Cost Survey PSAC
Application 1: Technology road-mapping What a technology roadmap could look like
• Existing technology; provides a starting point. Known costs and
technology performance. TRL 9.
• Best Available Technology (BAT); defines industry-leading standard of
proven systems already in use. Known costs and technology
performance. TRL 7-8.
• Advanced concepts; known design concepts that could improve energy
efficiency, yet to be implemented. Estimated costs and modelled
technology performance. TRL 5-7.
• Speculative research; “what if” scenarios. Unknown costs with
research required to estimate performance. TRL 1-4.
Existing Tech BAT Advanced Blue skies
2014 New/retrofit 2020-2025 2025 and beyond
Cost analysis
Value analysis
Application 2: R&D prioritisation
• Prioritization of technology R&D investment for higher TRLs (industry-led)
• Tier 1 (buy): Technologies that always appear in model solutions across
ranges of analyses.
• Tier 2 (hedge): Technologies that exhibit dependencies on the
assumptions in sensitivity analyses, but offer significant value where they
materialise. University partnership can be helpful.
• Cutting edge blue sky technology research for lower TRLs (university-led)
• Tier 3 (high risk, high return): “What if” scenario assessment to test
hypotheses on the importance of more radical technological change.
Meet the team
Research PhD Masters
?
Sara -
Integrating
Daniel - Supply
PDRA - Demand
Jonny- UK
?
?
?
?
PhD – O&G
PhD – Infrastructure
PhD – Industry
PhD – Power
?
?
?
?
MSc - Transport
MSc - Power
MSc - ETL
MSc - LNG
? MSc – O&G
SGI modelling work plan
Gas Technology Modelling Environment Work Plan
2014 2015 2016
Task/Time Q3 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
Literature review
Overarching model formulation (Milestone)
Model Implementation
- Control Block
- Upstream Module
- Power Sector Module
- Industry Module
- Other Modules (stubs)
Beta Version (Milestone)
Version 1.0 (Milestone)
