Category: Risk Pricing

Tackling the Risk of Stranded Electricity Assets with Machine Learning and Artificial Intelligence

The Paris Agreement on climate change requires nations to keep the global temperature within the 2°C carbon budget. Achieving this temperature target means stranding more than 80% of all proven fossil energy reserves as well as resulting in investments in such resources becoming stranded assets. At the implementation level, governments are experiencing technical, economic, and legal challenges in transitioning their economies to meet the 2°C temperature commitment through the nationally determined contributions (NDCs), let alone striving for the 1.5°C carbon budget, which translates into greenhouse gas emissions (GHG) gap.

This chapter focuses on tackling the risks of stranded electricity assets using machine learning and artificial intelligence technologies. Stranded assets are not new in the energy sector; the physical impacts of climate change and the transition to a low-carbon economy have generally rendered redundant or obsolete electricity generation and storage assets.

Low-carbon electricity systems, which come in variable and controllable forms, are essential to mitigating climate change. These systems present distinct opportunities for machine learning and artificial intelligence-powered techniques. This chapter considers the background to these issues. It discusses the asset stranding discourse and its implications to the energy sector and related infrastructure. The chapter concludes by outlining an interdisciplinary research agenda for mitigating the risks of stranded assets in electricity investments. Read More>>

Sustainable Energy Investment: Technical, Market and Policy Innovations to Address Risk

This book examines the technical, market, and policy innovations for unlocking sustainable investment in the energy sector. While finalizing this book, the COVID-19 pandemic is cutting a devastating swath through the global economy, causing the biggest fall in energy sector investment, exacerbating the global trade finance gap, worsening signs of growing income inequality, and devastating the health and livelihoods of millions. What is the parallel between the COVID-19 pandemic and the climate change crisis? The impacts of the global pandemic are expected to last for a few years, whereas those associated with the climate crisis will play out over several decades with potentially irreversible consequences. However, both show that the cost of inaction or delay in addressing the risks can lead to devastating outcomes or a greater probability of irreversible, catastrophic damages. In the context of sustainable energy investment and the transition to a low-carbon, climate-resilient economy, what ways can financial markets and institutions support net-zero-emission activities and the shift to a sustainable economy, including investment in energy efficiency, low-carbon and renewable energy technologies? This book provides students, policymakers, and energy investment professionals with the knowledge and theoretical tools necessary to address related questions in sustainable energy investment, risk management, and energy innovation agendas. Read More>>

Spatial Energy Efficiency Patterns in New York and Implications for Energy Demand and the Rebound Effect

The confluence of the threat of global climate change, increasing energy prices, and widespread adoption of low-carbon technologies have been cited as key drivers of the energy transition. Two of the scenarios exemplified by future rates of uptake of energy transition based on expectations of change in demand, and socially incremental choices that define the transition in terms of energy consumption and consumer behavior illustrate potential results under the current business-as-usual paradigm. An important area that has been overlooked is how spatial diffusion of energy-efficiency policies or complementarities across policy mixes can yield direct measurable benefits that improve overall energy policy design and performance measurement.

In our new paper (co-authored with Dr. John Byrne) titled Spatial Energy Efficiency Patterns in New York and Implications for Energy Demand and the Rebound Effect, published in Energy Sources, Part B: Economics Planning and Policy, we posit the inquiry of how to address this quandary as one of spatial dynamism in policy design: promoting spatial sensitivity in technology-or sector-specific energy-efficiency policies to support increased diffusion, information sharing, and accelerating the adoption rates of energy efficiency measures.

In this study, we applied the spatial modeling (i.e., spatial Durbin error model-SDEM) approach to analyze adoption trends for residential energy-efficiency measures. To do so, we evaluated the potential for local socioeconomic and building performance variables which influence the effectiveness of energy efficiency policies and diffusion patterns in each location in the long-term. We investigated this potential for New York state at a ZIP code level to show the ubiquitous promise and potential of this conceptualization to improve urban energy planning and management. To arrive at a practical strategy, we investigated the policy implications for energy demand and the rebound effect.

Our study shows the significant influence of the built environment and jurisdictional boundaries and their effect on energy transition capacities. As such, the paper makes a compelling case for a fundamental reconsideration of energy policy design in New York and target setting to account for specific conditions in the built environment that may constrain the uptake of energy-efficient technologies in a given jurisdiction.

Photo: Beijing’s financial district. Sean Pavone /Shutterstock.com
Photo: Beijing’s financial district. Sean Pavone / Shutterstock.com

In the lead-up to the 2015 Paris climate change conference, policymakers stressed the need for creation of integrated carbon markets and called for linking new climate financing mechanisms with the United Nations-organized Green Climate Fund (GCF) based in South Korea. Both the U.S. and China have committed to accelerating the transition to low-carbon development internationally. Through a $3 billion per year pledge to GCF by the U.S. and a new annual $3.1 billion climate finance guarantee by China to support other developing countries to combat climate change, the two countries have committed to enhance multilateral climate cooperation. Read more>>

Adam Savage, speaks at a TED-ED event on fascinating examples of profound scientific discoveries that essentially came from simple yet creative methods. Adam has co-hosted MythBusters, a Discovery Channel show.

Adam’s talk reminded me of Steven Johnson’s book, ‘Where Good Ideas Come From‘. What is apparent is that ideas come from everywhere; no group of people or institution can claim absolute monopoly of good ideas!

Here is Steve’s TED Talks:

“A good idea is a network. A specific constellation of neurons–thousands of them–fire in sync with each other for the first time in your brain, and in idea pops into your consciousness. A new idea is a network of cells exploring the adjacent possible of connections that they can make…an idea is not a single thing. It is more like a swarm.” Steven Johnson

 

In a recent Discussion Paper titled “A Safe and Just Space for Humanity: can we live within the doughnut?,” Oxfams’s Kate Raworth writes, “International carbon-offsetting schemes have been set up to enable high-emissions companies and individuals to buy carbon credits by financing investments, often in developing countries, which reduce net CO2 emissions.” Raworth has developed a global compass for sustainable development based on ‘doughnut economics,’ created by combining social foundation with environmental ceiling.

But countries are beginning to internalize environmental externalities by monetizing the greenhouse gas emissions through carbon offsets. For example, animated graphics of thirteen countries of life expectancy vs. carbon emissions, and income per capita vs carbon emissions, show remarkable carbon variations.

life expectancy v carbon emissions

Income per capita v carbon emissions

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