1 issue d 1institute for energy engineering technical university of berlin germany 2mathematical and...
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IssueD
1 Institute for Energy EngineeringTechnical University of BerlinGermany
2 Mathematical and Computing Sciences
Victoria University of WellingtonNew Zealand
Auckland, New Zealand • 06–09 July 2004 • www.nzses.org.nz
International Conference on Sustainability Engineering and Science (ICSES)
Robbie Morrison 1, 2 Tobias Wittmann 1 Thomas Bruckner
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Energy sustainability through representative large-scale simulation : the logical and physical design of xeona
Technische Universität Berlin
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Authors
Thomas Bruckner Tobias Wittmann Robbie Morrison
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Resource processing networked systems
Typical features of resource processing networked systems:
high capital cost — and often environmental cost — of infrastructure limited natural entitlements — rivers, transmission corridors, gas fields, etc subsystems which operate in (increasingly) volatile circumstances plant performance which relates to context — ambient conditions, price, etc decentralized decision-making — whether administered or market pricing final demand is for services (rather that commodities) strong implications for biophysical sustainability and societal functioning
The energy sector as a representative example
TECHNICALISSUES
Network component(more later)
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Public interest performance
Public interest is a normative concept
Resource processing networked systems should operate, evolve, and innovate to improve public interest performance:
whole-system financial cost depletable resource use greenhouse gas emissions local environmental impacts
This presentation looks at the contribution that representative large-scale simulation can make to public interest policy development in the energy sector
Examples derive mostly from New Zealand
ETHICALISSUES
Windflow prototype, 500 kWChristchurch, NZ, 2003
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Motivation for modeling
Complex multi-party systems defy simplistic analysis
Large-scale simulation provides an alternative to econometric modeling and system dynamics
Versatile model application/interpretation, briefly:
operational mode — scenario investigation operational plus investment mode — system evolution experimentation
Potential for proactive use:
adaptive resource consents, for instance, for fresh water take (NZ issue) model-based, not trigger-based, ring-fenced generation (NZ issue) revenue redistribution among cooperating parties
Can generate important non-observable system metrics, for instance:
weather-normalized, inventory-corrected social energy efficiency
COMPLEXSYSTEMS
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Simulation environments
Object-oriented: circa 1995
Status: first use late-1995, extensive technology library
Category: high-resolution
Role: technical behavior in the presence of one internal decision-maker
License: GPL plus requests
Web: www.iet.tu-berlin.de/deeco
deeco
Object-oriented: circa 2004
Status: alpha release planned for 2005
Category: entity-oriented
Role: in addition, able to capture multi-participant domestic and commercial behavior
License: GPL plus requests
xeona
agent-basedextension
COMPUTERSCIENCE
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hydro-generator wholesale householdretail
externalcircumstances
authority
time-series
exergyresources
attribute
commercialrelationships
publicinterestsystemmetrics
Illustrative example
time interval:► one hour (say)
time horizon:► annual (operational)► decade (plus investment)
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Overlaid networks
Two foundation networks:
► mathematical graphs
Commercial associations network:
► negotiation pathways► bilateral contracts► market-mediated relationships
Physical and instrumental resources (PIR) network:
► stock and flow model► also supports instrumental
resources (including carbonpermits and flow of funds)
Optimal single interval operation: these arrangements allow use of linear or mixed integer (LP or MILP) methods to optimize subsystem operation:
► single operator (merit order)► bid-informed market (stack order)
Optimization informed simulation
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Agent-based
modeling
All actors: bounded rationality
► limited processing power► public information only
Domestic actors:
► investment responses based on lifestyle classification
Commercial actors:► commercial motivation► can call on external software
and even human support(experimental economics)
Under- recognized topic
Future refinements:
► greater analytical sophistication► learning and adaptation► cooperation and coalition stability
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Technical component
s
End-use facilities: have received limited public policy attention to date
Engineering plant: generalized entity
Component characterization:
► input-output relationships (generalized efficiency)► plant capacity constraints
(lower, upper)► cost/impact "creation" equations
Context-dependent performance:
► environmental circumstances► neighboring plant via "dialog"► internal state, tracking operating
history and inventory
Resource quality captured
Support for heat transport and storage temperatures:
► engineering controllersmimicked to determine floand return temperatures
► non-ideal storage modeledsuch that energy losscauses temperature decay
Improvedtechnical
realism
Network programming
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Policy issues (1)mostly large-scale
Licensing: merits of licensing hydro-generator stack (bidding) models
Carbon tax: efficacy assessment
Market improvement: by simulation
System (n−1) security: based on minimum cut (bottleneck) analysis
Additionality assessment: for NZ Projects Mechanism emissions units (EU) allocation, using in situ analysis
Intermittent renewables: whole of system evaluation
Extreme event functioning: including dry cold winters
HVDC link, January 2004Wind damage
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Policy issues (2)mostly dispersed
Rewarded end-user responsiveness: various demand management initiatives
Rebound: take-back effect from domestic efficiency investments
Solar hot water support: merits of accelerated domestic solar hot water uptake
Building performance: merits of tighter building standards
Resource consent (RMA) process: consideration of alternatives
Investment protection: distributed solutions tend to be vulnerable to upstream reinforcement
Whole-system public interestperformance criteria (PIPC):► financial cost► depletable resource use► greenhouse gas emissions► local environmental impact
Policytrade-offsmay berequired
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Further subsystems
Some other partsof the jigsaw
Huntly 1000 MW power station
gascoal
nuclear power
miscellaneouscomponents
neighborhood fuel cells(phosphoric acid )
gas
electricity
hot water
?
Waikato River
25ºC maxfor river
high-levelwaste
low-levelwaste
electricity
?
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Trade-off information forpolicy makers (single operator case)
Situation:
Complex municipal energy system in northern Europe modeled using deeco
Financial cost increase
–50%
0%
50%
100%
150%
200%
0% 10% 20% 30% 40% 50%
Depletable fuel savings (LHV)
cogeneration+ short distance heat grid
medium solarsmall solar
gas heat-pumps+ heat grid
oil-fired boilers +electricity imports
everything− large solar
everything
large solar + seasonal storage
Trade-off line
Business as usualreference
Source: Bruckner, Groscurth, and Kümmel (1997)
Note: LHV is lower heating value
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Key assumptions
Preamble
extensive state describes prevailing plant duty and/or inventory intensive state includes quantities like output voltage, flo and return
temperatures, and stratified storage temperatures
State orthogonality
extensive state selection has no influence on intensive state
Cross-interval operation
extensive state selection covering storage is procedural rather than optimal applies to single operator managed storage only
Efficiency curve convexity
plant efficiency increases stepwise with plant duty required where linear optimization is employed or where
a global optimum must be guaranteed
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Software design
Object-orientation (taken to include generic programming)
scientific programming — optimization solvers, ordinary differential equation solvers, implicit variables methods, and graph algorithms
orthodox object-oriented design and analysis (OODA) multi-agent simulation techniques
Physical design
modularized software architecture
XML
for persistent storage and data exchange
UML
standardized visual language for design and documentation
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Closure
Simulation is cheaper and faster than policy formulation by trial-and-error
Energy-services supply may well be headed toward smarter lighter networks and greater use of renewable and fuel-passive technologies
Large-scale simulation is indicated and other methods appear less suitable:
a single socially-motivated decision-maker is no longer appropriate econometric methods struggle to capture technical possibilities system dynamics struggles to capture network issues
Large-scale simulation may have application in other areas, such as the management of fresh water take (for hydro-generation, cooling, irrigation)
The method can yield important non-observable system metrics — essential for the proper auditing of policy efficacy
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Bruckner, Thomas, Helmuth-M Groscurth, and Reiner Kümmel. 1997. Competition and synergy between energy technologies in municipal energy systems. Energy – The International Journal. 22(10): 1005–1014.
Lindenberger, Dietmar, Thomas Bruckner, Helmuth-M Groscurth, and Reiner Kümmel. 2000. Optimization of solar district heating systems : seasonal storage, heat pumps, and cogeneration. Energy – The International Journal. 25(7): 591–608.
Morrison, Robbie, Thomas Bruckner. 2002. High-resolution modeling of distributed energy resources using deeco : adverse interactions and potential policy conflicts. In – Sergio Ulgiati et al. (eds.). 2003. Proceedings of the 3rd International Workshop in Advances in Energy Studies — Reconsidering the Importance of Energy. Held at Porto Venere, Italy, 24–28 September 2002. Padova, Italy: Servizi Grafici Editoriali. 97–107.
Morrison, Robbie, Tobias Wittmann, and Thomas Bruckner. 2003. Energy policy and distributed solutions : a model-based interpretation. Paper at the Australia New Zealand Society for Ecological Economics (ANZSEE) Think Tank. Held at University of Auckland, Auckland, New Zealand, 16 November 2003.
Bruckner, Thomas, Robbie Morrison, Chris Handley, and Murray Patterson. 2003. High-resolution modeling of energy-services supply systems using deeco : overview and application to policy development. Annals of Operations Research. 121(1–4): 151–180.
Lindenberger, Dietmar, Thomas Bruckner, Robbie Morrison, Helmuth-M Groscurth, and Reiner Kümmel. 2004. Modernization of local energy systems. Energy – The International Journal. 29(2): 245–256.
Selected references
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