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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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3

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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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