Actors’ behaviour analysis in a decentralized energy system: The Transport, Industry and Household Sectors Mohammad Ahanchian, Isela Bailey, Audrey Dobbins
Introduction Introduction Project “Decentral”: TIMES Actors Model (TAM) IER University of Stuttgart 17-Nov-18 2
Transport Sector Agenda • Introduction • Transport sector • Actors’ characterizations • Methodology • Modelling • Industry sector • Actor characterization • Methodology • Household sector • Actor characterization • Methodology • Modelling • Outlook IER University of Stuttgart 17-Nov-18 3
Transport Sector Actors’ characteristics Actors and their investment options Households Households Bus S-Bahn Long- Actors / / U-Bahn D-Bahn distance bus tenant owner operators operators operators Medium & small renewables Uptake of low-carbon vehicles Reduce travel demand eg., Buy electricity from renewable sources teleworking Shift to more sustainable Invest in low-carbon buses/trains Investment modes options Extend network Efficient appliances Building Attract more passengers retrofit Storage Small renewable Objective Maximize surplus Minimize costs Budget restriction (Income) Technology specific discount rate IER University of Stuttgart 17-Nov-18 4
Transport Sector Methodology Data source (Heterogeneity of transport users) • The German national travel survey documents the mobility behavior of the Germans since 1994. • A broad database consisting of households’ • socio-economic characteristics, • temporal and special details of trip, • trip purpose, • mode of transport, • technical specifications of vehicle, • weather data of the survey days, • City size class • and many other parameters. • The data survey is aimed at identifying causes of transport demand changes as well as examining the effectiveness of planning and policy measures. • Heterogeneous behavioural stability of different persons by conducting survey over a period of one week and repeated over three years. • The surveyed people are targeted in a way to represent the entire German population and the results are able to reproduce the mobility demand of country by using the extrapolation factors on household and individual level and weighting factor on trip level. IER University of Stuttgart 17-Nov-18 5
Transport Sector Methodology Disaggregation of transport users in the household sector Other living costs Number of persons 8 Income group Budget restriction for Travel budget investment Owner/tenant in household 4 Age Vehicle technical Car ownership Car stock evolution 4 Engine size specification WA Fuel consumption Availability of Urban/rural Average speed infrastructure 64 Transport user Actor groups IER University of Stuttgart 17-Nov-18 6
Transport Sector Methodology Temporal and spatial characteristics of trips Urban/rural Trip length Weekday/ Trip purpose weekend Weather data of the Peak hour or not survey days??? To calculate tangible and intangible cost of transport modes IER University of Stuttgart 17-Nov-18 7
Transport Sector Methodology Modal characteristics • Tangible cost of each mode • Intangible cost of each mode • Waiting time • Access/egress time of public modes • Speed • Availability of infrastructure and capacity IER University of Stuttgart 17-Nov-18 8
Transport Sector Modeling General framework Budget restriction Availability of 64 Transport user infrastructure Actor groups in household sector Travel demand Investment options of Capacity of Mode actors (transport infrastructure Urban/Rural 3 Transport suppliers and users) suppliers Actor groups Modal characteristics Car stock evolution IER University of Stuttgart 17-Nov-18 9
Industry Sector Agenda • Introduction • Transport sector • Actor characterisation • Methodology • Modelling • Industry sector • Actor characterization • Methodology • Household sector • Actor characterization • Methodology • Modelling • Outlook IER University of Stuttgart 17-Nov-18 10
Industry Sector Industry sector Industry in Germany (Case study: Iron and Steel) Industrial Final Final Energy Consumption CO 2 Emissions Industrial CO 2 Emissions Energy Consumption 20% 21% 23% 29% 71% 77% 80% 79% Industry Rest of Energy System Iron and Steel Industry Rest of Industry IER University of Stuttgart 17-Nov-18 11
Industry Sector Industry sector Actors’ Characterization – example in the iron and steel industry IER University of Stuttgart 17-Nov-18 12
Industry Sector Industry sector Actors’ Characterization – example in the iron and steel industry Standard Level of Disaggregation IER University of Stuttgart 17-Nov-18 13
Industry Sector Industry sector Actors’ Characterization – example in the iron and steel industry The first steps consists of a bottom-up • characterization of actors in the iron and steel industry with the goal of defining ' Actors Groups ' that better represent their decision-making behaviour regarding operation and investments in various technologies, especially decentralised technologies. Standard Level of Disaggregation IER University of Stuttgart 17-Nov-18 14
Industry Sector Industry sector Actors’ Characterization – example in the iron and steel industry The first steps consists of a bottom-up • characterization of actors in the iron and steel Data Collection (Plants) industry with the goal of defining ' Actors Groups ' that better represent their decision-making behaviour regarding operation and investments in various technologies, especially decentralised technologies. Standard Level of Disaggregation Production data is collected for every plant. • IER University of Stuttgart 17-Nov-18 15
Industry Sector Industry sector Actors’ Characterization – example in the iron and steel industry The first steps consists of a bottom-up • characterization of actors in the iron and steel Data Collection (Plants) industry with the goal of defining ' Actors Groups ' that better represent their decision-making Companies (Actors) behaviour regarding operation and investments in various technologies, especially decentralised technologies. Standard Level of Disaggregation Production data is collected for every plant. • Plants belonging to the same company are added • together and considered as an ' Actor '. IER University of Stuttgart 17-Nov-18 16
Industry Sector Industry sector Actors’ Characterization – example in the iron and steel industry The first steps consists of a bottom-up • characterization of actors in the iron and steel Data Collection (Plants) industry with the goal of defining ' Actors Groups ' that better represent their decision-making Companies (Actors) behaviour regarding operation and investments in various technologies, especially decentralised New Level of Disaggregation technologies. Standard Level of Disaggregation Production data is collected for every plant. • Plants belonging to the same company are added • together and considered as an ' Actor '. • Then, according to production technology and capacity , similar actors are grouped together for a total of four ' Actor Groups ' to be modelled in the next step. IER University of Stuttgart 17-Nov-18 17
Industry Sector Industry sector Actors’ Characterization – example in the iron and steel industry Production Production Data Actors Capacity Technology Collection 5 Small 14 9 EAF Large 146 20 Companies Plants 4 Small 6 BOS 2 Large IER University of Stuttgart 17-Nov-18 32
Industry Sector Industry sector Methodology Standard Representation Other Fuels of Industrial Branches: Electricity Emissions Demand Heat Iron and Steel AP = Autoproduction hr = Hurdle Rate IER University of Stuttgart 17-Nov-18 24
Industry Sector Industry sector Methodology Standard Representation Other Fuels of Industrial Branches: Electricity Emissions Demand Heat Iron and Steel Emissions Demand Representation of Iron and Steel Actor Group 1 Industry in this Work: Actor Group 2 Actor Group 3 Actor Group 4 AP = Autoproduction hr = Hurdle Rate IER University of Stuttgart 17-Nov-18 24
Industry Sector Industry sector Methodology Standard Representation Other Fuels of Industrial Branches: Electricity Emissions Demand Heat Iron and Steel Emissions Demand Representation of Iron and Steel Actor Group 1 Industry in this Work: Actor Group 2 Actor Group 3 Actor Group 4 AP = Autoproduction hr = Hurdle Rate IER University of Stuttgart 17-Nov-18 24
Industry Sector Industry sector Methodology Standard Representation Other Fuels of Industrial Branches: Electricity Emissions Demand Heat Iron and Steel Electricity Grid AP Electricity District Heat Other Fuels CO 2 Prices Emissions AP Heat Demand Decentralized Representation of Iron and Steel Technologies Actor Group 1 Electricity Industry in this Work: Heat hr 1 Actor Group 2 Electricity Heat hr 2 Actor Group 3 Electricity Heat hr 3 Actor Group 4 Electricity Heat hr 4 AP = Autoproduction hr = Hurdle Rate IER University of Stuttgart 17-Nov-18 24
Household Sector Agenda • Introduction • Transport sector • Actor characterisation • Methodology • Modelling • Industry sector • Actor characterization • Methodology • Household sector • Actor characterization • Methodology • Modelling • Outlook IER University of Stuttgart 17-Nov-18 23
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