• Energy Research

For the period since 2011, the UK has been bound by European Union (EU) legislation regarding energy reduction targets to 2020. As of 2019, the UK had reduced its final energy use by 18% against a baseline projection to 2020, on track to meet its target of 18%. Whilst the rest of the EU-27 now set their own energy reduction targets to 2030, upon leaving the EU via Brexit, the UK is now free to choose its own energy targets. But what should the energy target be for 2030, and what are the socio-macroeconomic impacts and policy implications? To address this, we use two econometric energy-economy models to assess three different levels of energy reduction target, with 27%, 33% and 40% reduction in 2030 versus the baseline model projections. We find the strictest (40%) energy reduction target could deliver the largest economic and employment benefits. However, careful attention to policies are required, to ensure improvements to overall economy-wide energy efficiency whilst minimising rebound. Demand-side policies of serious scale within an ‘avoid-shift-improve’ framework are required, including massive building retrofits, significant improvements to industrial energy efficiency, switching to low energy transport modes, and moving away from meat-based diets.

Description of the open-source MEDEAS integrated assessment modeling framework, which focuses on the biophysical and economic dimensions, restrictions and interactions arising during energy transitions.

The electric vehicle (EV) transition is underway in the UK and many other countries worldwide, switching from fossil fuel powered internal combustion engine (ICE) road transport to EVs that can be powered by renewable electricity. Whilst the projected energy and carbon reduction impacts are well understood, we have only a partial view of the potential socio-macroeconomic effects of the EV transition, i.e. the impacts on GDP and jobs. Common energy-economy models feature only limited energy-economy integration, and only assign a small role for energy in economic growth. Thus whilst economic changes such as increases to investment can feed into macroeconomic impact assessment, the impacts of the energy system changes are potentially underestimated. In response, we use a novel macro-econometric model – MARCO-UK – to conduct a whole system analysis with two main scenarios: an ICE baseline (with no EV transition) and 100% EV transition scenario to 2050. We investigate the effects of the scenarios on the UK's energy system (efficiency, energy services, rebound) and economic system (employment, GDP, debt), under different conditions of investment, rebound and electricity prices. We find the most significant impacts stem from energy system changes, with annual economic growth rising from 1.71%/year (baseline) to 2.25%/year in the main EV scenario. In contrast, the impacts from economic investment changes are much lower in scale. Therefore, the socio-macroeconomic benefits of the EV transition may be underestimated. We also find that overall long-term economy-wide rebound in our central EV scenario is 76%, which means the energy savings from the EV transition may be less than hoped. Overall, our analysis identifies potential trade-offs regarding the labour market, levels of indebtedness, energy rebound and associated carbon emissions that should be taken into consideration. UK Research and Innovation-Centre for Research into Energy Demand Solutions (EP/R 035288/1) Ministerio de Ciencia, Innovación y Universidades-Margarita Salas UK Research Council (EP/R024254/1) Producción Científica

This paper reviews different approaches to modelling the energy transition towards a zero carbon economy. It identifies a number of limitations in current approaches such as a lack of consideration of out-of-equilibrium situations (like an energy transition) and non-linear feedbacks. To tackle those issues, the new open source integrated assessment model pymedeas is introduced, which allows the exploration of the design and planning of appropriate strategies and policies for decarbonizing the energy sector at World and EU level. The main novelty of the new open-source model is that it addresses the energy transition by considering biophysical limits, availability of raw materials, and climate change impacts. This paper showcases the model capabilities through several simulation experiments to explore alternative pathways for the renewable transition. In the selected scenarios of this work, future shortage of fossil fuels is found to be the most influential factor of the simulations system evolution. Changes in efficiency and climate change damages are also important determinants influencing model outcomes.

AbstractInput–output tables (IOTs) provide a relevant picture of economic structure as they represent the composition and interindustry relationships of an economy. The technical coefficients matrix (A matrix) is considered to capture the technological status of an economy; so, it is of special relevance for the evaluation of long‐term, structural transformations, such as sustainability transitions in integrated assessment models (IAMs). The A matrix has typically been considered either static or exogenous. Endogenous structural change has rarely been applied to models. The objective of this paper is to analyze energy intensity, a widely used variable in IAMs, and its role as a driver of structural change. We therefore identify the most relevant technical coefficients in the IOTs time series and estimate an econometric model based on the energy intensity of five different final end‐use energy sources. The results of this analysis show that energy intensity has a significant influence on the evolution of the A matrix and should therefore be taken into consideration when analyzing endogenous structural change in models.