Decision Support for Life Cycle Management of Energy Supply Networks Jim Petrie 12 Ruud Kempener 1 Jessica Beck 1 Brett Cohen 2 Lauren Basson 3 1. School of Chemical & Bio-molecular Engineering, Univ. of Sydney, Australia 2. Department of Chemical Engineering, University of Cape Town, South Africa 3. Centre for Environmental Strategy, University of Surrey, United Kingdon 1 Petrie, Kempener, Beck, Cohen, and Basson, LCM 2007
System Influences on Decision Making Social embeddedness Resource scarcity Evolution Decision making process of industrial of organisation system Multiple autonomous Background systems Learning & adaptation decision makers Petrie, Kempener, Beck, Cohen, and Basson, LCM 2007
Global Vs Distributed Control Perspective for SYSTEM global control INTERACTION approach CAUSE CAUSE EFFECT CAUSE CAUSE Has to make assumptions about the CAUSE and SYSTEM INTERACTION delivering a specific EFFECT. Perspective for SYSTEM distributed INTERACTION control approach CAUSE Can make no clear prediction about EFFECT EFFECT. The EFFECT evolves based on CAUSE and SYSTEM INTERACTION. Petrie, Kempener, Beck, Cohen, and Basson, LCM 2007
Global targets – Distributed performance Desired energy Network GLOBAL CONTROL network performance APPROACH: development IRP setting pathway Attainable energy network development pathway DISTRIBUTED CONTROL APPROACH: Analysis of possible policy intervention and feasibility of Present energy desired IRP network performance Time Petrie, Kempener, Beck, Cohen, and Basson, LCM 2007
Application of Framework Simulation and optimization of industrial networks » Consideration of multiple objectives, dynamics, and uncertainty Modeling of agent behavior in industrial networks – bioenergy in developing countries; coal-based power generation Possible combined approach: » Using optimization to identify preferred trajectory » Using ABM to determine feasibility and means to narrow the gap » Applied in Beck et al., 2007; Kempener et al., 2007 (In Review) Beck, Kempener, Cohen & Petrie (2007), A Complex Systems Approach to Planning, Optimisation and Decision Making for Energy Networks: A South African Bio-energy Case Study , Energy Policy, accepted Kempener, Beck & Petrie (2007), “An Integrated Analysis of Bio-energy Technologies – A complex Adaptive Systems Approach, Eur Fed Chem E (B), PSEP, in review 5 Petrie, Kempener, Beck, Cohen, and Basson, LCM 2007
GOVERNMENT SUBSIDIES TARGETS ELECTRICITY DEMAND ELECTRICITY ELECTRICITY PRICES SUGAR MILLS INDUSTRY INFRASTRUCTURE BAGASSE ELECTRICITY FOOD BIO-ENERGY SUGAR PRICES INDUSTRY NETWORK PAPER & PULP BAGASSE TRANSPORT OIL PRICES DEMAND INDUSTRY ETHANOL INDUSTRY TECHNOLOGY DEVELOPMENT ENGINEERING/ R&D Petrie, Kempener, Beck, Cohen, and Basson, LCM 2007
Technologies considered FUEL GEL Sugar mill i Gel gel production on-site use FUEL PRODUCER Drying and hydrolysis Ethanol pelletisation GENERATOR Power Onsite (distributed) cofiring generation IPP gasification Power steam steam Power cycle cycle gasification Pulp and Paper Paper Wet bagasse Dry bagasse Ethanol Petrie, Kempener, Beck, Cohen, and Basson, LCM 2007
Units State variables ABM GDOM • Bagasse/ethanol availability or purchased (both wet & dry) • � • � Autonomous • Bagasse /ethanol for own use • � • � agents (SI, PS, • Production capacity • � • � IPP, EP) • Costs and efficiency of technologies available • � • � • � • � • Profit • � • � • Capital • � • � • Location • � • � • Farmers benefits and/or other obligations • � • � • Minimum IRR threshold • � • � • Preferred contract length • � • Market share ambitions • � • Time span for future prediction • � • Relationships • � • Economic, social & environmental weightings in decision making • � • Importance of risk, benevolence, conflict, status, past • � experience, length relationship, trust, loyalty • � • Number of municipalities • � • � Regional • Rural electricity demand (not-electrified) • � • � government • Price of grid connections • � • � • � • � • Municipal Infrastructure Grants (MIG) • Subsidies for bio-ethanol • � National • Fuel exemption • � government • Investment subsidies new technologies • � • Subsidies for green electricity • � • � • Subsidies for gel-fuel • � • Subsidies for grid connections • � • Subsidies for non-grid connections • � • Policy target for green electricity • � • Policy target for biofuels • � • MIG allocation • � • Electricity Basis Services Support Tariff Policy (EBSST) Petrie, Kempener, Beck, Cohen, and Basson, LCM 2007
Infrastructure Shifts 3. 4. 450 160 2. 400 140 ethanol (1000 m3/month electricity (GWh/month 350 120 300 100 250 80 200 60 1. 150 40 100 20 50 0 0 0 3 6 9 12 15 18 21 24 27 30 years electricity production ethanol production Petrie, Kempener, Beck, Cohen, and Basson, LCM 2007
Network Structures 1. 2. yr.9 yr.15 gel gel rural development rural development bagasse bagasse ethanol ethanol electricity electricity grid local grid local GP GP EP PS IPP EP PS IPP S 1 S 2 S 3 S 4 S 5 S 6 S 7 S 8 S 9 S 10 S 11 S 12 S 1 S 2 S 3 S 4 S 5 S 6 S 7 S 8 S 9 S 10 S 11 S 12 pel pel pel pel pel pel 3. 4. yr.18 yr.21 gel gel rural development rural development bagasse bagasse ethanol ethanol electricity electricity grid local grid local GP GP EP PS IPP EP PS IPP S 1 S 2 S 3 S 4 S 5 S 6 S 7 S 8 S 9 S 10 S 11 S 12 S 1 S 2 S 3 S 4 S 5 S 6 S 7 S 8 S 9 S 10 S 11 S 12 pel pel pel pel pel pel pel pel pel pel pel pel pel pel pel pel Petrie, Kempener, Beck, Cohen, and Basson, LCM 2007
Emergent Behaviour Network evolution under green electricity subsidies Network evolution under low IRRs 700 700 S12 S12 S10 600 S11 600 S5 S10 500 500 S8 S9 S3 S8 400 400 MW S2 MW S7 300 S11 300 S6 S1 S5 200 200 S7 S4 S6 100 S3 100 S4 S2 0 0 S9 S1 0 3 6 9 12 15 18 21 24 27 30 PS 0 3 6 9 12 15 18 21 24 27 30 PS years years market price dry bagasse ethanol production 3500 300 3000 250 2500 1000 m3/day R/MWh (eq.) 200 2000 150 1500 100 1000 50 500 0 0 0 3 6 9 12 15 18 21 24 27 30 0 3 6 9 12 15 18 21 24 27 30 years years green electricity subsidy low IRR green electricity subsidy low IRR Petrie, Kempener, Beck, Cohen, and Basson, LCM 2007
Comparison GDOM and ABM GDOM energy economic environmental social provision (billion (Mtonnes co2 (rural energy rand) averted) supply) (PJ) Environmental behaviour 0.2 308.3 0 637 Social behaviour -59.3 102.2 415.8 1219 Economic rational 12.7 226.6 0 913 ABM energy economic environmental social provision (billion (rural energy ZAR) (Mt CO2 averted) supply) (PJ) Economically rational agents 6.6 36.9 1.1 121.7 Agents who allow MCDM 3.4 186.9 16.0 355.8 Petrie, Kempener, Beck, Cohen, and Basson, LCM 2007
Comparison – no biofuels 1 0.8 0.6 0.4 0.2 env ironmental social economic 0 0 50 100 150 TWh 200 250 300 350 Petrie, Kempener, Beck, Cohen, and Basson, LCM 2007
Bio Energy Network Conclusions The bio-energy network develops only when the price of electricity rises to a factor of 3-4 above the current price in South Africa. Under a set of reasonable assumptions, this will likely happen only about 15 years from now (though sometimes as early as 5 years) There is genuine potential to address rural electrification needs by decentralised power production at the various sugar mills. Under a wide range of scenarios, Power Producers take up the bagasse resource The production of green electricity on the basis of wet bagasse is detrimental to the environment, as CO2 emissions from transport would outweigh the CO2 averted through the production of green electricity. It seems that investment subsidies are more beneficial than price subsidies. Investment subsidies would allow sugar mills to invest in pelletisers, which would allow Power Producers to produce green electricity more quickly and with higher profit margins Petrie, Kempener, Beck, Cohen, and Basson, LCM 2007
Coal Network Considered Other non-coal based electricity sources (nuclear, H 2 O CO 2 SO 2 hydro etc) PS n Adjacent Mine National electricity demand SO 2 Adjacent CO 2 Mine PS 1 Road Alternative Mine PS 2 Conveyor Road Ash Alternative Mine H 2 O Conveyor Emissions/inputs CO 2 SO 2 Coal up to “contracted” LF Additional Coal sourced In one of three ways Petrie, Kempener, Beck, Cohen, and Basson, LCM 2007
56000 51000 Cumulative capacity (MW) 46000 41000 36000 31000 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Existing system Recommisioned coal stations Open cycle gas turbine Coal fired Fluidized bed combustion (FBC) Coal-Fired Pulverized fuel combustion (PF) Pebble bed modular reactor Combined cycle gas turbine (pipeline) Advanced light water nuclear reactor Peak demand Petrie, Kempener, Beck, Cohen, and Basson, LCM 2007
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