Published December 2021 | Version v1
Journal article

Application of a Stochastic Multicriteria Acceptability Analysis to support decision-making within a macro-scale energy model: Case study of the electrification of the road European transport sector

  • 1. MAHTEP Group, Department of Energy "Galileo Ferraris", Politecnico di Torino, Torino (Italy)
  • 2. TEBE Research Group, BAEDA Lab, Department of Energy "Galileo Ferraris", Politecnico di Torino, Torino (Italy)
  • 3. Consorzio RFX (CNR, ENEA, INFN, Universita, di Padova, Acciaierie Venete SpA), Corso Stati Uniti 4, 35127, Padova (Italy)

Description

Highlights: • Uncertainty assessment in optimization macro-scale energy system models addressed. • Different alternative electric vehicle fleets analyzed with EUROfusion TIMES Model. • Multicriteria Decision Analysis applied to complement minimum-cost optimization. • 4 preference criteria analyzed by Stochastic Multicriteria Acceptability Analysis. • The alternatives can be ranked according to preference criteria and weights. Energy system models based on the TIMES framework can explore possible energy futures through the construction of a network of technological processes, to satisfy a set of exogenously imposed service demands at the least-cost system configuration. This work presents a methodology aimed at supporting decision-makers in finding optimal energy-system configuration in a complex energy environment, characterized by uncertain information. First, the EUROfusion TIMES Model is used to assess the sensitivity of different long-term evolutions of the European energy system, with particular reference to the road transport sector, considering different trends for the prescribed future variations of investment cost and vehicle efficiency. In a second step, the Stochastic Multicriteria Acceptability Analysis is used to critically evaluate the alternative optimal configurations proposed by the model simulations under a set of economic and environmental criteria. The results of the analysis allow the discussion of the influence of such criteria on the different alternative cases, complementing the cost minimization approach. In the case study considered here, high penetrations of electric vehicles in the road fleet are favored by economic, environmental and energy-related priorities.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.energy.2021.121444

Additional details

Identifiers

DOI
10.1016/j.energy.2021.121444;
PII
S0360544221016923;

Publishing Information

Journal Title
Energy (Oxford)
Journal Volume
236
Journal Page Range
vp.
ISSN
0360-5442
CODEN
ENEYDS

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
54000747
Subject category
S29: ENERGY PLANNING, POLICY AND ECONOMY;
Descriptors DEI
COMPUTERIZED SIMULATION; CONFIGURATION; DECISION MAKING; EFFICIENCY; ELECTRIC-POWERED VEHICLES; ENERGY DEMAND; ENERGY MODELS; ENERGY SYSTEMS; INVESTMENT; MINIMIZATION; ROAD TRANSPORT; SENSITIVITY; STOCHASTIC PROCESSES
Descriptors DEC
DEMAND; LAND TRANSPORT; OPTIMIZATION; SIMULATION; TRANSPORT; VEHICLES

Optional Information

Copyright
Copyright (c) 2021 Published by Elsevier Ltd.