Technological Learning in the Transition to a Low-Carbon Energy System

Conceptual Issues, Empirical Findings, and Use, in Energy Modeling

Martin Junginger, Atse Louwen

• Publisher: Academic Press
• Year: 2019
• Print ISBN: 9780128187623
• eBook ISBN: 9780128187630
• Topic: Physical Sciences
• Subtopic: Energy

Technological Learning in the Transition to a Low-Carbon Energy System: Conceptual Issues, Empirical Findings, and Use in Energy Modeling quantifies key trends and drivers of energy technologies deployed in the energy transition. It uses the experience curve tool to show how future cost reductions and cumulative deployment of these technologies may shape the future mix of the electricity, heat and transport sectors. The book explores experience curves in detail, including possible pitfalls, and demonstrates how to quantify the 'quality' of experience curves. It discusses how this tool is implemented in models and addresses methodological challenges and solutions.For each technology, current market trends, past cost reductions and underlying drivers, available experience curves, and future prospects are considered. Electricity, heat and transport sector models are explored in-depth to show how the future deployment of these technologies—and their associated costs—determine whether ambitious decarbonization climate targets can be reached - and at what costs. The book also addresses lessons and recommendations for policymakers, industry and academics, including key technologies requiring further policy support, and what scientific knowledge gaps remain for future research.- Provides a comprehensive overview of trends and drivers for major energy technologies expected to play a role in the energy transition- Delivers data on cost trends, helping readers gain insights on how competitive energy technologies may become, and why- Reviews the use of learning curves in environmental impacts for lifecycle assessments and energy modeling- Features social learning for cost modeling and technology diffusion, including where consumer preferences play a major role

Part I

Introduction and methods

Outline

• Chapter 1 Introduction
• Chapter 2 The experience curve: concept, history, methods, and issues
• Chapter 3 Implementation of experience curves in energy-system models
• Chapter 4 Application of experience curves and learning to other fields

Chapter 1

Introduction

Martin Junginger¹ and Atse Louwen^1,2, ¹Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, The Netherlands, ²Institute for Renewable Energy, Eurac Research, Bolzano, Italy

Abstract

The ongoing energy transition is driven by a need to mitigate climate change and switch from fossil to low-carbon fuels and renewable energy. However, while technologies such as onshore and offshore wind energy, solar energy, and batteries have made significant progress over the past decades, and they can increasingly compete directly with fossil fuels, their deployment is still only a fraction of what is needed to fully decarbonize our economy—a process that is going to take at least several more decades and is going to require major investments. Also, the intermittent character of especially wind and solar energy will require major changes in, for example, storage of energy (both heat and electricity). How this transition will play out, and which technologies will ultimately become winners and losers are highly relevant questions which this book will help to answer by providing both the individual market deployment and cost reduction trends per technology and the results of modeling a portfolio of energy technologies in various sector models and overall energy models.

Keywords

Experience curve; energy transition; energy technologies; renewables; fossil fuels; cost reductions

Chapter outline

Outline

• 1.1 Introduction 3
  • 1.1.1 Background and rationale 3
  • 1.1.2 Objectives and structure 6

1.1 Introduction

1.1.1 Background and rationale

It is clear that the further development of various energy technologies is crucial to reduce the emission of greenhouse gases (GHGs), achieve other environmental targets, limit growing global energy demand, and ultimately enable the transition to a low-carbon society—preferably at low costs. These aims can only be achieved when a large number of technologies to supply renewable energy and to save energy become commercially available and thus are at the core of most energy and climate policies worldwide. Important scenario analyses of the world’s future energy system and climate change mitigation scenarios illustrate that technological progress is key to minimizing costs of such development pathways. Given the need for drastic decarbonization, and related substantial investment needs, the political and public debate about the societal costs of this transition is increasing, making it even more important to point out possible cost reductions of novel energy technologies and ultimately the benefits of a low-carbon energy system. Furthermore, the speed of development is essential in order to meet required reductions and supply contributions on time. Many scenarios also highlight the positive economic and security impacts of strong support for research, development, demonstration and deployment of such technologies. Lastly, developing and deploying such energy technologies is seen as a major opportunity for development, (sustainable) industrial activity, and (high-quality) employment. Many (national) policies support both research and development (R&D) and market deployment of promising new energy technologies.

The latter, in particular, will require substantial investment. However, designing such policies effectively (e.g., timing and amount of incentives) has proved to be a challenge. The energy sector and manufacturing industry need strategic planning of their R&D portfolio and have to identify key market niches for new technologies (with or without policy support). Taken together, this situation makes an improved understanding of technological learning pivotal. Currently, most strategies and policies are only based to a limited extent on a rational and detailed understanding of learning mechanisms and technology development pathways. The conditions that provide efficient development routes are subject to much research, for example, in the innovation sciences. However, in addition to what may provide the optimal conditions and settings to achieve technological progress and rapid market deployment, it is clear that a detailed understanding of specific technologies, their performance, and factors influencing their performance are essential in order to design and implement effective policies and strategies. Historically, technological learning has resulted in the improvement of many technologies available to mankind, subsequent efficiency improvements and reduction of production costs, and has been an engine of economic development as a whole. Many of the conventional technologies in use today have already been continually improved over several decades, sometimes even over a century (e.g., most bulk chemical processes, cars, ships, and airplanes). Specifically for the electricity sector, coal-fired power plants have been built (and improved) for nearly a century now, while nuclear plants and gas-fired power plants have been built and developed since the 1960s and 1970s on a large commercial scale. Note that these well-established technologies are also still continuously improved, though this mainly leads to incremental improvements and concomitant cost reductions. Due to this long-term development, the established fossil fuel technologies have relatively low production costs. However, they also have a number of negative externalities, especially the emission of GHGs.

In contrast, many renewable/clean fossil fuel–energy technologies and energy-saving technologies used to have higher production costs, but lower fuel demands and GHG emissions. A few examples are electricity from biomass, offshore wind, and photovoltaics (PVs), and energy-efficient lighting and space-heating technologies. For many of these new technologies the potential for further technological development and resulting production cost reductions is deemed substantial, and relatively high-speed cost reduction occurs compared to the conventional technologies. In the past 10 years, the gap between conventional and new technologies has been (largely) closed, and in some cases breakeven points have been reached. Electricity from onshore and offshore wind parks and large amounts of PV systems already today push out fossil generation units in Germany, as these technologies have no fuel costs. Crucial questions are, however, what will happen when intermittent electricity technologies will gain an even larger market share, making backup capacity an...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• List of contributors
• Part I: Introduction and methods
• Part II: Case studies
• Part III: Application of experience curves in modeling
• Part IV: Final words
• Index