O slideshow foi denunciado.
Utilizamos seu perfil e dados de atividades no LinkedIn para personalizar e exibir anúncios mais relevantes. Altere suas preferências de anúncios quando desejar.

The disruption effect of digitalization on the energy sector: a multimodal approach

23 visualizações

Publicada em

The disruption effect of digitalization on the energy sector: a multimodal approach
Lidia Stermieri, Paul Scherrer Institut

Publicada em: Meio ambiente
  • Seja o primeiro a comentar

  • Seja a primeira pessoa a gostar disto

The disruption effect of digitalization on the energy sector: a multimodal approach

  1. 1. WIR SCHAFFEN WISSEN – HEUTE FÜR MORGEN The disruption effect of digitalization on the energy sector: a multimodal approach Stermieri Lidia:: PhD student :: Paul Scherrer Institut :: Energy Economics Group WINTER 2020 SEMI-ANNUAL ETSAP MEETING
  2. 2. The digital society Seite 2 E-learningE-book Teleworking E-commerce E-banking Smart buildings E-retail Smart energy Digital practices “Working from home can save energy and reduce emissions. But how much?”** “Residential energy consumption in the United States has increased by an estimated 6-8% compared with this time last year”* Rebound effect of the pandemic… *The Covid-19 Crisis and Clean Energy Progress, IEA Report, June 2020 **IEA (2020), Working from home can save energy and reduce emissions. But how much?, IEA, Paris 1. Quantify the impact of digital practices on the energy system 2. Analyze changes in user behavior “Government lockdowns triggered a fall of 50% to 75% in road traffic around the world”** How is society considered in the energy model?
  3. 3. The role of consumers’ behavior in the digital transition: an agent-based model framework Seite 3 Commuting + - … … ? Commuting Agent Social network Decision process agent Service sector Decision process service Teleworking ?Impact on energy demand Increase digital level sector Transport Residential Service
  4. 4. Agent-Based Model Seite 4 Households Socio-demographicattributes Decision process mechanism New digital trends Micro-level interactions Households Social interaction(network) Macro-levelinteractions Firms Teleworking E-learning E-commerce ABM Exogenous demand Technology share Technology cost and attribute Decision process: • Believes, ideas , opinion, preferences • Economic considerations (based on income) • Investment cost • Operation cost • Efficiency • Energy cost • Simulation on an annual basis • Time horizon: 2020-2050 • Population growth over the time horizon • Social network and interaction Selection of the best technology Households Transport Residential ServiceSector Agent Aggregate Technology Annual mileage Building type(MF,SF) Heating/Electric consumption Education Job Output Energy demand Technologies’ share Variables related to teleworking practice Income Age Education
  5. 5. Integrated modeling approach Seite 5 Agent-Based Model Analysis of micro-level factors that influence the diffusion and adoption of a technology • Social interactions • Heterogeneity of decision-making process Swiss TIMES Energy System Detailed representation of the technological, economic and environmental dimensions of the energy system Supporting long-term decision making and planning in the energy sector considering individuals’ preferences and behavioral attitudes.
  6. 6. Swiss TIMES Energy Model (STEM) Seite 6 Supply Coal Oil Gas Biomass Primary energydemand Coal Oil Gas Nuclear Hydro Bioenergy Renewables Imports& Exports Trade matrices Domestic production Transformation Refinery Gasprocessing &distribution Power generation Heat production Biomass processing Hydrogen production Syntheticfuels Final energydemand Non- energyuse Industry Transport Residential Services Agriculture Energy servicedemand Industrial production Industrialvalue added pkmtravelled tkmtravelled Househods& householdsize Valueaddedin Services CO2prices Policies Technologies GDP Population Energyflows CO2emissions Investments Leastcost approach STEM Technologies costs and attributes Exogenous demand Technology share • STEM: Optimization model • ABM: socio-economic model ABM Coupling process with STEM Aggregate technology: • Non conventional • Conventional Transport Residential Technology share Share constraints replace growth constraints ICE Gasoline ICE Diesel ICE Gas Mild Hybrid Gasoline Mild Hybrid Diesel Hybrid Gasoline Hybrid Diesel Hybrid Gas Plug-in Gasoline Plug-in Diesel Plug-in Gas Battery electric Hydrogen fuel cell Electric boilers Electric boilers with night storage Heat pumps (electric) Light fuel oil boilers Gas boilers Heat pumps (natural gas) Coal process Heat from CHPs on consumed on- site Heat from district heating networks Wood boilers Pellet boilers Solar boilers Hydrogen boilers Scenario analysis (horizon 2050) Cost and attributes for aggregate technologies in ABM Exogenous demand Dj EXIT YES NO START ∀𝐷𝑗 ∈ 𝑡𝑟𝑎𝑛𝑠𝑝𝑜𝑟𝑡, 𝑟𝑒𝑠𝑖𝑑𝑒𝑛𝑡𝑖𝑎𝑙, 𝑠𝑒𝑟𝑣𝑖𝑐𝑒 , ∀𝑡 ∈ 2030,2040,2050 𝐷𝑗,𝑡,𝑖 − 𝐷𝑗,𝑡,𝑖−1 𝐷𝑗,𝑡,𝑖−1 ≤ ε Dj energy demand t milestone year i current iteration number Ɛ tollerance ( 0.05) Iterative process
  7. 7. Case study Seite 7 Baseline scenario (BAU) Climate target scenario (CLI) 8 Mt/CO2 in 2050 • Spread of practices in society • Interdependencies between sectors • Energy implication for long-term scenarios • Society reaction to policy ( no awareness of environmental issues by society) 1. Quantify the impact of digital practices on the energy system 2. Analyze changes in users behavior How is society reflected in energy model assumption? Assumptions for teleworking (If the agent adopts the practice of teleworking): - 3 days/week of teleworking (commuting practice takes 24% of annual km in Switzerland) - +20% in the agent’s heat consumption - +10% in the agent’s electricity consumption The effect of teleworking on energy demand and user behavior in Switzerland
  8. 8. BAU: insight from ABM Seite 8 55.0 56.0 57.0 58.0 59.0 60.0 61.0 62.0 63.0 64.0 2020 2030 2040 2050 Total Bvkm (cars + public transport) BAU ABM 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 2015 2018 2030 2040 2050 Share of Teleworking practice in Swiss population ABM Swiss statistics Diffusion of teleworking: • 43% of teleworking in 2050 8% Reduction in total Bvkm Changes of transport mode due to teleworking practice 0% 2% 4% 6% 8% 10% 12% 1st iteration 2nd iteration 3th iteration Absoluteerror BAU convergence criteria Bvkm 2030 Bvkm 2040 Bvkm 2050 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 2030 2040 2050 Bpkm share for public transport BAU ABM no teleworking ABM with teleworking 13.20 13.40 13.60 13.80 14.00 14.20 14.40 14.60 14.80 15.00 15.20 15.40 2020 2030 2040 2050 Bvkm for working BAU working Bvkm ABM working Bvkm -5 Bvkm -35% Bvkm for commuting
  9. 9. Coupled model: BAU scenario Seite 9 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% BAU ABM BAU ABM BAU ABM Share of aggregate technologies in private passenger cars Conventional Hybrid Ele Hybrid vehicles not selected in the ABM Conventional vehicles replaced with electric vehicles Increase of non conventional technologies in residential sector In the ABM, the adoption of heating technology competes with the adoption of transportation technology. An agent adopting electric vehicle has less disposable income to adopt a technology for heating (natural gas boiler is the cheaper technology) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% BAU ABM BAU ABM BAU ABM Share of aggregate technologies in residential demand Conventional Non conventional 120 125 130 135 140 145 150 2020 2030 2040 Residential : Energy demands (in PJ) ABM BAU +13% 2030 2030 2040 2040 2050 2050
  10. 10. Coupled model: BAU scenario Seite 10 20 25 30 35 40 45 2015 2020 2030 2040 2050 CO2 emissions (Mt) BAU ABM +5% - The reduction in transport and services sector does not compensate for the increase in residential sector - Conservative assumptions - Need to consider interdependencies between sectors and rebound effects 651 133 128 213 232 151 149 0 100 200 300 400 500 600 700 BAU ABM Final Energy Consumption in 2050 (PJ) Industry Services Residential Transport 640 600 650 700 750 800 850 900 950 1000 2015 2020 2030 2040 2050 Primary Energy Consumption (PJ) BAU ABM +4% Quantify the impact of digital practices on the energy system
  11. 11. CLI: 8 Mt/CO2 target 2050 Seite 11 0% 20% 40% 60% 80% 100% 2020 2030 2040 2050 ABM aggregate technology: passenger cars(PJ) Conv Non conventional 0% 20% 40% 60% 80% 100% 2020 2030 2040 2050 CLI aggregate technology: passenger cars(PJ) Conv Non conv Different speed of technology adoption in transport! Seite 11 -10 -5 0 5 10 15 CLI ABM Total CO2 emissions Services Residential Transport Industry CO2 captured in power generation CO2 captured in industry CO2 captured in hydrogen CO2 captured in biogases/bioliquids Direct air capture +20% conservation in Industry 0 20 40 60 80 100 120 140 160 CLI ABM Transport total : Final consumption per fuel in PJ Hydrogen Electricity Biojet fuels Biogas Biodiesel Ethanol Natural gas Jet fuel Diesel Gasoline How to achieve 8 Mt/CO2 in 2050 +20% CO2 captured in hydrogen and biogases
  12. 12. CLI:CO2 tax and climate policy consideration Seite 12 How much the carbon tax should be to achieve CO2 reduction target and satisfy user preferences? 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 2020 2030 2040 2050 CO2 emission Mt CLI target ABM + CLI tax To achieve 8 Mt/CO2 in 2050 without considering user preferences: 2020 2030 2040 2050 CO2 tax CLI (CHF/Mt) 0.08 0.59 0.84 0.74 Considering user preference, the 8 Mt target is not achieved! How is society represented in the energy model and in its assumptions?
  13. 13. • Open for discussion… − CO2 tax must incorporate social behavior: how? − The assumptions about the acceptance and evolution of society must be reflected in the energy model: − Are we overestimating future development? − Are we underestimating cost? Discussion Seite 13 • Digital practices have a direct and indirect impact on different energy sectors • Interdependencies between sectors must be considered to avoid overestimation of impact • Consumer preference and societal acceptance play an important role
  14. 14. Seite 14 Wir schaffen Wissen – heute für morgen My thanks go to Dr. E. Panos and Dr. T. Kober for their support in my research
  15. 15. Digitalization and energy implication *V. Court and S. Sorrell, “Digitalisation of goods: A systematic review of the determinants and magnitude of the impacts on energy consumption,” Environ. Res. Lett., vol. 15, no. 4, 2020

×