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Category Behavioural aspects and the role of citizens and local authorities in energy modelling Funded by 23 Optimum structure of centralized and decentralized generation in the German energy system with enhanced odellig of ators

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Category Behavioural aspects and the role of citizens and local authorities in energy modelling

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Mohammad Ahanchian

Energy Supply Industry Households Transport Supply

Optimum structure of centralized and decentralized generation in the German energy system with enhanced

  • dellig of ators’ ivestet ehaviour

Other Consumers

Funded by

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Samrat Bose (bose@eifer.org) | 08.10.2019 1

Reinforcement Learning in Local Energy Markets

The multi-agent based model demonstrates the application of reinforcement learning (a type

  • f machine learning) for intelligent agent strategy for trading in the local energy market (LEM)

supported by Demand Response.

Figure: Simulation Setup

The model setup:

  • 100 household agents
  • 45 Agents with PV installation (Prosumers)
  • 10 Agents with mCHP installation (Prosumers)
  • 45 Agents with generation units (Consumers)
  • Merit order model market mechanism
  • Price based Demand Response
  • Intelligent Agent strategy through modified Erev-Roth algorithm
  • Sensitivity analysis
  • Increasing PV installation from 5 kWp to 25 kWp
  • Increasing peak shaving in DR from 0% to 50%

Figure: Upper and lower bounds of trading window (Regulatory scenarios)

Regulatory Scenarios Upper Limit (c€/kWh) Lower Limit (c€/kWh) PV mCHP

Public Network 29.86 36.74 35.81 Microgrid 29.86 25.01 24.09 Favorable Regulation 29.86 16.83 15.90

Result sneak-peek:

Local Sufficiency (%): Increase DR% → increase by 25-50% Increase PV → increase by 6-30% Market Closing Price: Increase DR% → no effect Increase PV → increase by 5c€/kWh Annual Peak Demand: Increase DR% → decrease by 50% Increase PV → no effect

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ODEN — URBAN N BUILDI DING NG ENERGY MODEL AND DASHBOARD D FOR SWEDISH CITIES

bit.do/oden

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Local Energy Sharing Considering Different Technologies, Individual Preferences, and Contributions

Theresia Perger, TU Wien perger@eeg.tuwien.ac.at

FRESH:COM “FaiR Energy SHaring in local COMmunities“

  • Linear optimization model
  • Local Energy Community (EC):
  • Members are Consumer, Producer, or Prosumer
  • Participants have different reasons to join an EC

(economic or ecologic aspects)

  • Fully democratic participation: voluntary

participation, willingness-to-pay for renewable energy

  • Renewable energy technologies: PV and battery

storage

  • Peer-to-peer trading via public grid
  • Grid topology: IEEE 33 Bus Distribution Network
  • Objective function: Maximizing the community's

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Changes in the energy metabolic pattern of Europe and China 2000-2016

Raúl Velasco-Fernández and Mario Giampietro

Energy consumption per hour of work vs hours p.c. in main sectors Human activity in hours per capita in main sectors

  • Characterization of changes in the performance of the economy

in biophysical terms using MuSIASEM

  • Multi-scale integrated analysis of the energy metabolic pattern
  • Alternative economic accounting based on energetics
  • Considering complexity implications for policy advice
  • Opening black-boxes and handling impredicativity

This project has received funding from the European Union's Horizon2020 research and innovation programme under grant agreement No 689669.

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Category: Energy and climate strategy, targets and scenarios

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1

S t e p 3 : C i t y S c e n a r i o s A s s e s s m e n t

By weighting their impacts, the scenarios are prioritized and the city can identify the one that best suits its objectives, being this the first step for the elaboration of an energy action plan.

Methodology for the characterization and impact assessment of energy scenarios at a city level

Iñigo Muñoz; Patxi Hernández; Eneko Arrizabalaga; Nekane Hermoso; Juan Pedrero Energy Modelling Platform for Europe 2019 EMP-E 2019 Modelling the Implementation of A Clean Planet for All Strategy

Contact Information:

Iñigo Muñoz Tel.: +34 664 119 538 inigo.munoz@tecnalia.com

S t e p 2 : C i t y E n e r g y S c e n a r i o s The model represents how energy usage in each sector could evolve resulting in a combination of different pathways that the city can face

0,00 0,50 1,00 1,50 2,00 2016 2020 2025 2030 2035 2040 2045 2050 Mton CO2eq Business as Usual Alternative scenario nº1 Alternative scenario nº2

S t e p 1 : C i t y E n e r g y C h a r a c t e r i z a t i o n

  • Top-down real consumption data supplied by the city is

disaggregated through integrating bottom-up approaches.

  • ENERKAD tool is used to disaggregate the energy consumed in

the city’s building stock.

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(*) contact author: sara.abd.alla@edu.unige.it

ADDRESSING RISING ENERGY NEEDS OF MEGACITIES IN A SUSTAINABLE WAY – CASE STUDY OF GREATER CAIRO

  • S. Abd Alla*, S.G. Simoes, V. Bianco

Ipoig uality of life ill lead to a eessay iease i eegy

  • suptio that if satisfied ith o-

eeale eegy RES soues ill alost doule the CO eissios pe apita INFA. RES ae eessay fo the sustaiale ua eegy tasitio of egaities BAU/INFA/INFB. Ua eegy syste odellig allos egaities to assess the deelopet goth ad to da sustaiale pathays to eet the apidly ieasig eegy eeds. Mai halleges ae aess to data ad deelopig

  • ust

seaios

  • deogaphy,

eooi goth ad lifestyle hages.

Mai Coclusios

GDP,

  • stutio

ad oility go as

  • ;
  • hages

i % ifoal settleets GDP,

  • stutio

ad oility go as i Caio Visio; y / 7%/% iha. ifoal settl. eloated Iteediate GDP,

  • stutio

ad oility goth; y / 7%/7% iha. ifoal settl. eloated As BAU + CO eissios itigatio ap i

  • f

% elo

  • As INFA +

CO eissios itigatio ap i

  • f

% elo

  • As INFB +

CO eissios itigatio ap i

  • f

% elo

  • BAU

INFA INFB BAUc INFAc INFBc

Fial eerg cosuptio FEC Si odelled socio-ecooic & CO2 itigatio scearios

INFBc

Depedig

  • the

soio-eooi pathay & CO itigatio aitio, FEC a go fo alues: -7% i BAU/, 9-9% i INFA/ o 9-% i INFB/.

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Using a myopic energy system model to analyse EU memeber states‘ diverging energy policies Max Fydrich Kategorie 3: Energy and climate strategy, targets and scenarios

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What market accounting governance needs to be in place to assign value to reductions of intangible commodities? Systems of demand and supply to align market accounting governance and organizational activity with societal needs and planetary boundaries. Such system are evident in energy demand reduction, demand-side response and flexibility markets. On a global level, the Paris Agreement on Climate Change contains provisions for the establishment of demand and supply systems.

Colin Nolden - EMP-E 2019, Brussels, 8-9th Oct. 2019

Collecting Silences

Noise Silences

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Titel Claire Nicolas Kategorie 3: Energy and climate strategy, targets and scenarios

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Energy Transition Pathways for Turkish Electricity System

Ere Çelei, Gökha Kirkil and Ahmet Deniz Yüekaya

The primary energy demand in Turkey is met predominantly by fossil fuels.

In 2017, total emissions in Turkey increased by 140% compared to 1990.

  • Accounting (LEAP) and

Optimization (OSeMOSYS) Models

  • Scenarios
  • Business As Usual (BAU)
  • Energy Efficiency (EE)
  • Renewable Energy (REN)

Main Insights:

  • EE_OPT scenario proved to be the

most cost-efficient scenario and the least import dependent scenario.

  • REN_OPT has the least amounts
  • f GHGs and to increase the RES

utilization in Turkey

  • improving

energy efficiency [National Energy Efficiency Action Plan (NEEAP) 2017-2023]

  • renewable

energy utilization [National Renewable Energy Action Plan (NREAP) 2014]

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Exploring European decarbonization potential with MEDEAS model

  • I. Perissi, F. Di Patti, S. Falsini, G. Martelloni and U. Bardi

The authors estimated the remaining carbon budgets at Global and EU levels, compatibile with a 2°C of global warming by 2100. We found that: Global level: 1950 GtCO2eq (2012-2100) EU-28 level: 122 GtCO2eq (2012-2100)

1 Perissi, I.; Falsini, S.; Bardi, U.; Natalini, D.; Green, M.; Jones, A.; Solé, J. Potential European Emissions Trajectories within the Global Carbon Budget. Sustainability 2018, 10, 4225

Let’s go to the poster to discuss the conclusions!

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  • 1 -
  • K. Löffler

Dresden, 12.04.2019 A Quantitative Assessment of the Stranded Asset Problem

Decarbonizing China’s energy system Modeling the transformation of the electricity, transportation, heat, and industrial sectors

Thorsten Burandt, Bobby Xiong, Konstantin Löffler, Pao-Yu Oei Technische Universität Berlin, Workgroup for Economic and Infrastructure Policy (WIP) DIW Berlin, Department Energy Transport and Environment Energy Modelling Platform for Europe (EMP-E) 2019

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  • Energy

gy se sector i is a s a ke key c contributor to gl global warmi ming g while also so affect ected ed by the he adver erse e impact cts of cl climate e cha chang nge

  • A

A power sy syst stem m exp xpansi sion mo modeling taki king g into consi sideration of clima mate cha chang nge e mitigation a n and nd adaptation o n object ectives es.

  • Met

etho hod: fiel eldwork d data co collect ection, n, W WEAP EAP a and nd LEAP EAP s software e tools

  • Cas

ase: t the J Java ava-Bali power er system em in Ind n Indones nesia, 2018 2018-2050 2050

  • Res

esul ults: the he adver erse e impact cts o

  • f cl

climate cha e chang nge e incr ncrea ease el elect ectrici city dem emand nd, ins nstalled ed ca capaci city and nd el elect ectrici city p product uction n whi hile e und under ermini ning ng cl climate cha e chang nge e mitigation m n mea easur ures es.

LINKING CLIMATE CHANGE MITIGATION AND ADAPTATION: AN INTEGRATED POWER SYSTEM EXPANSION MODELING

Kamia Handayani, Tatiana Filatova, and Yoram Krozer – University of Twente

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Why do we we use oil?

Develop a coplex tool to odel productio process

Oil is not just a commodity produced and consumed, but a resource that affects and shapes the societal functioning of modern societies. Biophysical constraints and human choices made in the production process have environmental, economic and social implication in societal consumption patterns and organization

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28/09/2019 Industrial excess heat in ambitious emission reduction scenarios for Denmark

*Stefan Petrović1, Fabian Bühler2 and Mikkel Bosack Simonsen1

1 Technical University of Denmark, Department of Technology, Management and Economics, Lyngby, Denmark 2 Technical University of Denmark, Department of Mechanical Engineering, Lyngby, Denmark

Industrial excess heat in ambitious emission reduction scenarios for Denmark

Motivation

  • Several studies agreed that district heating (DH) should the main

element of the future Danish energy system, but the role of industrial excess heat (EH) for DH production is not analysed.

  • In our previous work we addressed that, but not in ambitious

emission reduction scenarios. The suspicion:

  • Industrial energy efficiency reduces available EH,
  • The need for a quick reduction of emissions might favorize

biomass CHPs with CCS

  • Competition with waste incinerators (waste needs to be burned)
  • Risks associated with investment in EH
  • Competition of DH with individual heating and heat savings

What did we do?

  • TIMES-DK model, optimisation, all sectors of the Danish energy

system until 2050

  • 3 main scenarios:

NN - Net negative 2050 scenario 70% - 70 % emission reduction by 2030 compared to 1990 CB - Carbon budget in line with Paris Agreement's 1.5-degree target.

  • 3 sensitivity measures:

high risk on excess heat, limit biomass import, combination

Results To conclude

  • EH belongs to the future Danish energy system
  • In the CB scenario, EH share in DH goes over 30% with very

small additional costs

  • We recommend always at least one "carbon budget" scenario
  • The combination of high risk on excess heat and forbidding of

biomass import reduces the utilisation of EH in all scenarios.

* Corresponding author. E-mail: stpet@dtu.dk

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  • 1 -
  • K. Löffler

Dresden, 12.04.2019 A Quantitative Assessment of the Stranded Asset Problem

Transportation in Energy System Models – Incorporating sector-coupling, infrastructure investments, and behavioral aspects

Karlo Hainsch, K. Löffler, T. Burandt, P-Y. Oei Technische Universität Berlin, Workgroup for Economic and Infrastructure Policy (WIP) Energy Modelling Platform for Europe (EMP-E) 2019

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KOHALA: A A UN UNIT IT COMMITMENT MODEL FO FOR THE THE SI SIMULATION OF FL FLEXIBILITY NE NEEDS IN N SHO SHORT-TERM MARKETS

Irene Danti Lopez (irene.danti-lopez@ucdconnect.ie) ¤, Damian Flynn ¤, Maël Desmartin *, Marcelo Saguan *,

¤ : University College Dublin * : Électricité de France R&D

EMP-E 20 2019

  • Formulation of a model that allows the study of the trade-off between modelling complexity and computational time in the areas
  • f:
  • Dynamic constraint modelling
  • Variability modelling
  • Uncertainty modelling

for systems with different characteristics such as system size, wind and solar power shares and energy mix

  • Develop a model such that the value of flexibility in short-term dispatch may be captured

OBJECTIVES

t Net load t Net load t Pgen Pmin Pmax

VARIABILITY UNCERTAINTY ESTIMATION OF SYSTEM’S FLEXIBILITY NEEDS Sub-hourly modelling Re-forecasting and rolling planning Detailed set of dynamic constraints modelled

Are existing unit commitment models sufficiently sophisticated to capture increasing variability, uncertainty and render feasible schedules? What are the characteristics of a given system that drive the need for modelling complexity in unit commitment models?

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  • 1 -
  • K. Löffler

Dresden, 12.04.2019 A Quantitative Assessment of the Stranded Asset Problem

Pathways for Germany’s Low-Carbon Energy Transformation Towards 2050

Hans-Karl Bartholdsen, Anna Eidens, Konstantin Löffler, Frederik Seehaus, Felix Wejda, Thorsten Burandt, Pao-Yu Oei, Claudia Kemfert and Christian von Hirschhausen Technische Universität Berlin, Workgroup for Economic and Infrastructure Policy (WIP) DIW Berlin, Department Energy Transport and Environment Energy Modelling Platform for Europe (EMP-E) 2019

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