Exploring the Transition to a Low-Carbon Electricity System — Using Agent-Based Modeling
Doctoral thesis, 2023
The ability to produce electricity has profoundly shaped human lives. Over time, the sources used for electricity generation have undergone several transitions. Currently, we are navigating a pivotal shift in the electricity system – decarbonization – a journey fraught with a myriad of challenges. A key challenge is that shifting to a low-carbon electricity system necessitates vast investments. The capital allocation decisions made today will influence global electricity production and associated emissions for the coming decades.
In this thesis, we have developed and employed an agent-based model of investments in the electricity system, called the HAPPI model (Heterogeneous Agent-based Power Plant Investment). The HAPPI model underscores the importance of factoring in heterogeneity, uncertainty, financial feedback, risk aversion, and adaptivity when modeling investment decisions in low-carbon transitions. This thesis primarily analyzes the influence of five important factors on investment decisions: hurdle rate, future carbon price expectation, access to capital, risk-aversion level, and adaptability. The findings provide insights at both the system and individual agent (investor) levels.
On the system level, the research explores the evolution of generation capacity mix, electricity prices, CO2 emissions, and the distribution of revenue across diverse technologies. Results show that, with growing carbon prices, there is a notable expansion in the capacity of wind, solar, and nuclear power plants, and a gradual phase-out of coal power plants.
On the agent level, the research explores the investment decisions of heterogeneous investors and the associated financial outcomes. Key observations highlight that agents with lower hurdle rates or lower risk or loss aversion tend to invest more, thereby enhancing their profits. However, this increased investment rate is associated with elevated bankruptcy risks, underscoring the intrinsic risk-return trade-off.
Moreover, the findings reveal that the low-carbon transition accelerates when investors have more access to capital. The transition is also expedited when uncertainty around future carbon prices is reduced, expectations for future prices are higher, and aversion to risk or losses diminishes.
In this thesis, we have developed and employed an agent-based model of investments in the electricity system, called the HAPPI model (Heterogeneous Agent-based Power Plant Investment). The HAPPI model underscores the importance of factoring in heterogeneity, uncertainty, financial feedback, risk aversion, and adaptivity when modeling investment decisions in low-carbon transitions. This thesis primarily analyzes the influence of five important factors on investment decisions: hurdle rate, future carbon price expectation, access to capital, risk-aversion level, and adaptability. The findings provide insights at both the system and individual agent (investor) levels.
On the system level, the research explores the evolution of generation capacity mix, electricity prices, CO2 emissions, and the distribution of revenue across diverse technologies. Results show that, with growing carbon prices, there is a notable expansion in the capacity of wind, solar, and nuclear power plants, and a gradual phase-out of coal power plants.
On the agent level, the research explores the investment decisions of heterogeneous investors and the associated financial outcomes. Key observations highlight that agents with lower hurdle rates or lower risk or loss aversion tend to invest more, thereby enhancing their profits. However, this increased investment rate is associated with elevated bankruptcy risks, underscoring the intrinsic risk-return trade-off.
Moreover, the findings reveal that the low-carbon transition accelerates when investors have more access to capital. The transition is also expedited when uncertainty around future carbon prices is reduced, expectations for future prices are higher, and aversion to risk or losses diminishes.
investment decisions
agent-based modeling
energy system modeling
open-source model
electricity market
low-carbon transition
HA3, Hörsalsvägen 4, Chalmers. https://chalmers.zoom.us/j/66353221831?pwd=YXZ0cTRodkpTT2Q1bFRuUThubVJqUT09, Password: 1234
Opponent: Professor Karoina Safarzynska University of Warsaw, Poland.
Author
Jinxi Yang
Chalmers, Space, Earth and Environment, Physical Resource Theory
Investment dynamics in the energy sector under carbon price uncertainty and risk aversion
Energy and Climate Change,; Vol. 4(2023)
Journal article
Modelling the Transition towards a Carbon-Neutral Electricity System—Investment Decisions and Heterogeneity
Energies,; Vol. 15(2022)
Journal article
Financing the Transition Toward Carbon Neutrality—an Agent-Based Approach to Modeling Investment Decisions in the Electricity System
Frontiers in Climate,; Vol. 3(2021)
Journal article
Yang, J. , Johansson D. J., Adapting to Uncertainty: Modeling Adaptive Investment Decisions in the Electricity System
Investing in Change: Transition to low-carbon electricity systems
Electricity production has historically been associated with significant environmental impact. The combustion of fossil fuels releases large amounts of greenhouse gases, contributing to climate change. To combat this, many countries are shifting to more sustainable energy sources like wind and solar power. However, this shift is challenging; it requires substantial investments in infrastructure and technology.
This research develops and employs agent-based models to study investors' investment decisions in new power plants under climate policies, and how these decisions affect the mix of energy sources we use. The study explores how different factors like risk, uncertainty, and available funds influence these decisions and the speed at which the electricity system can shift to cleaner energy.
The findings show that when investors perceive higher risks, greater uncertainty in future carbon prices, or are more cautious with their investments, the transition towards a low-carbon system can be delayed. On the contrary, when investors expect high future carbon prices and are more accepting of risks, the transition is likely to accelerate.
This thesis sheds light on the mutual influence between investment decisions and system development, and the competition between various technologies, such as wind and nuclear, providing valuable insights for navigating the path towards a more sustainable energy future.
Electricity production has historically been associated with significant environmental impact. The combustion of fossil fuels releases large amounts of greenhouse gases, contributing to climate change. To combat this, many countries are shifting to more sustainable energy sources like wind and solar power. However, this shift is challenging; it requires substantial investments in infrastructure and technology.
This research develops and employs agent-based models to study investors' investment decisions in new power plants under climate policies, and how these decisions affect the mix of energy sources we use. The study explores how different factors like risk, uncertainty, and available funds influence these decisions and the speed at which the electricity system can shift to cleaner energy.
The findings show that when investors perceive higher risks, greater uncertainty in future carbon prices, or are more cautious with their investments, the transition towards a low-carbon system can be delayed. On the contrary, when investors expect high future carbon prices and are more accepting of risks, the transition is likely to accelerate.
This thesis sheds light on the mutual influence between investment decisions and system development, and the competition between various technologies, such as wind and nuclear, providing valuable insights for navigating the path towards a more sustainable energy future.
Subject Categories
Other Environmental Engineering
Earth and Related Environmental Sciences
Energy Systems
ISBN
978-91-7905-932-3
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5398
Publisher
Chalmers
HA3, Hörsalsvägen 4, Chalmers. https://chalmers.zoom.us/j/66353221831?pwd=YXZ0cTRodkpTT2Q1bFRuUThubVJqUT09, Password: 1234
Opponent: Professor Karoina Safarzynska University of Warsaw, Poland.