The time to combat climate change is running out.
As we scroll through the numerous Earth Day posts from last week it is important to remind ourselves that the time to simply talk about climate change has now run out. The findings of the 2022 report from the Intergovernmental Panel on Climate Change confirm how quickly climate change is happening, and that we need to ACT faster.
Most parts of the world have already begun to experience the severe impact of deteriorating environmental conditions in the form of extreme weather conditions and unexpected natural disasters like devastating wildfires - remember the crazy orange skies in San Francisco in 2019 or the 2021 floods in Europe? That was all part of climate change. Projections also indicate that extreme weather and temperature occurrences may well become the norm and render several areas irrevocably uninhabitable. This has amplified risk to inhabitants of low-lying and coastal areas, millions of whom already face displacement as Pacific Island ecosystems can no longer sustain the communities dependent on them.
This deterioration of environmental conditions can largely be attributed to the rise in emissions driven by high energy demand. Energy, including electricity generation, transport, and industry accounts for 76% of global greenhouse gas emissions. Yet, the International Energy Agency (IEA) projections show that the demand for electricity will rapidly increase in emerging economies as they become more industrialised. Thus, as also emphasised in the IEA’s Net Zero by 2050 report and the United Nations’ Sustainable Energy for All (SE for All) initiative, all stakeholders including governments, businesses, and investors need to align to leverage currently available technology including AI to craft feasible solutions to speed up clean energy transitions.
Artificial Intelligence is a powerful tool against climate change.
AI has attracted a lot of interest from governments, and investors and at the UN COP 26 in 2021 as well Sustainability and AI was an important part of the conversation to encourage countries to integrate AI in their climate change mitigation toolkits.
1. Prediction and Forecasting
One of the big areas where AI has been applicable is reliable forecasting by analysing large datasets. For example, Fujitsu Ltd. in Japan has implemented AI based technologies to analyse data on rainfall to predict floods to encourage better disaster preparedness and mitigation. This predicting and forecasting capability of AI is also very relevant for the clean energy sector.
2. AI helps with clean energy transitions
Decarbonising the grid by replacing polluting fossil fuels is a key element of slowing the rate of climate change. Apart from predicting extreme weather conditions, AI has also been useful for facilitating clean energy transitions by helping build grid resiliency and eliminating business risks for suppliers. Given the urgency of the need to reduce carbon emissions from electricity generation, countries around the world are transitioning to using renewable energy like solar and wind power. However, most renewable energy sources are intermittent in nature and the time for generating electricity from them is limited which inhibits our ability to reduce dependence on polluting baseload sources like coal and natural gas. The duck curve in California is a great example of challenges of grid management in relation to the intermittency of renewables. The duck curve represents a 24-hour snapshot of the pattern of energy demand in comparison with its generation during spring. This snapshot revealed that energy demand is at its lowest when renewable power plants peak in energy production and vice versa. This gap between supply and demand poses a significant challenge to maintaining grid reliability. Real-time predictive machine learning tools and AI have been a game changer for energy suppliers and grid operators for managing oversupply by leveraging all available resources to divert excess output to where it is most needed at competitive rates.
Source: California ISO
3. Clean Energy Asset Management and Maintenance
The competition in the renewable energy market is growing rapidly with increased interest and investment from various stakeholders. In this context, it has become more important for energy operators and suppliers to become more efficient wherever possible and managing project assets is one such key area. Advanced AI and machine learning models can help take advantage of the data created by each of these assets to allow operators to optimise their maintenance, management, and monetisation. For example, Tesla’s Autobidder is a real-time bidding AI software that helps independent power producers and utilities to configure operational strategies to maximise revenue generated from their assets.
4. Facilitating clean power project negotiation with legaltech
Clean power projects, especially those involving multi-jurisdictional entities can be extremely complex to negotiate. These projects involve negotiating at least eight or nine major contracts including Financing, EPC, O&M, and Power Purchase Agreements.
Source: DLA Piper, EPC Contracts in the Power Sector
In addition, the regulatory and compliance work for these projects can be extensive as well as repetitive. Also, in the context of transnational negotiations for these projects there is also the risk of unforeseen circumstances like miscommunication between parties as a lawyer may only be able to look at things in their own jurisdiction. Given that clean power projects are already prone to delays and cost overruns, it is important that the legal work necessary for kickstarting a them is streamlined by utilising the right technology platforms: document review, contract terms, automation, legal compliance & negotiation which ultimately help build clean energy projects faster and more efficiently.
There is no time to waste.
The threat of climate change is not merely a distant worry anymore but has started affecting the functioning of ecosystems, agricultural productivity and inhabitability of several regions. There is no time to waste when it comes to taking action to slow down the rate at which climate change is impacting our planet. But, the good news is that while there is no time to waste, there is still time. By taking a holistic approach and leveraging all the available technology that can help us implement clean power projects quickly, we may still be able to prevent severe irreversible environmental consequences. When brought into the mix, AI is a powerful tool in mitigating the impact of climate change, as well as accelerating the pace of clean energy transitions.