The Sixth Assessment Report, released by the Intergovernmental Panel on Climate Change in August 2021, and climate change such as heatwaves, floods and wildfires, which have become increasingly evident in recent years, have attracted the attention of policymakers, businesses and investors. As the twenty-sixth United Nations Conference of the Parties on Climate Change (COP26) approaches, the release of climate targets is expected to accelerate even further. The transformation of a low-carbon economy needs to be accelerated, and the energy sector is the core challenge of this process. Artificial intelligence will play an important role in promoting energy transformation.
The energy transition requires artificial intelligence
At present, the global energy system is undergoing transformation, and the potential of artificial intelligence to accelerate energy transformation is constantly being stimulated.
The energy system needs to use digital means to drive rapid transformation. To achieve deep decarbonization, CO2 emissions from the energy system need to be reduced rapidly to extremely low levels. The decarbonization and transformation of the energy system will bring about integration and electrification changes, and the interaction between power, transportation, industry, construction and other industries will be significantly enhanced, and the system will be composed of interdependent energy and telecommunications networks. In order to accelerate the transition to a broad, affordable, low-carbon energy supply, it is necessary to further optimize all aspects of the energy system and strengthen coordination and cooperation between each link. This requires better understanding and better mechanisms to monitor and control the integration and interaction between grids, buildings, industrial facilities, transportation networks, and other energy-intensive industries. Digital technologies coordinate disparate systems and facilitate information sharing in the energy sector, automating complex processes. In the future, digital technologies will play an increasingly important role, enabling new business and operating models, both within and outside traditional value chains such as power generation, transmission, distribution, trade and consumption, to improve performance and save costs.
Decarbonizing the power sector is a focal point for decarbonizing the entire energy system. Energy system transformation includes rapidly expanding the supply of renewable energy and large-scale clean electrification of heating, industry and transport. Electricity’s share of global energy demand is projected to increase by 60% from 2019 to 2050, as electric vehicle ownership increases, battery storage costs fall, and buildings and heavy industry move toward net-zero emissions. Electricity will be increasingly used for heating and cooling, transportation, and even hydrogen production. With the increasing use of electricity in various fields, it will become the core pillar of the global energy supply, which will not only bring new development opportunities to the power industry, but also provide existing power generation and transmission power in the context of energy decarbonization and transformation. , trade and distribution systems bring new challenges.
The energy transition requires significant investment. In Bloomberg New Energy Finance’s New Energy Outlook 2020, there is a long-term forecast for the transition to the future energy economy, that by 2050, 56% of electricity generation will come from solar and wind, reaching 7.6 terawatts and 4.6 terawatts, respectively . And that assumption is based on maintaining current policies, reflecting the fact that the solar, wind and energy storage economy is an important driver of rapid decarbonisation of the power sector, even without regard to high coal prices or net-zero emissions targets. According to Bloomberg New Energy Finance estimates, the transition to decarbonizing the energy system will require $15.1 trillion in solar, wind power plant construction and $14 trillion in grid construction by 2050. To achieve the goal of net-zero global emissions by 2050, at least $92 trillion in energy system infrastructure needs to be invested between 2020 and 2050.
The power system of the future will be highly decentralized. Increasing the share of renewable energy generation will allow the power system to include more power from intermittent generators and be more decentralized. At present, distributed small-scale photovoltaic power plants account for 4% of the global installed power generation capacity, and the installed capacity of medium-sized power plants is 944 MW. According to the forecast of Bloomberg New Energy Finance Energy Transformation, by 2050, the proportion of distributed small-scale photovoltaic power plants will increase to 13%, while the installed capacity of medium-sized power plants will be reduced by more than 80% to only 158 MW.
The complexity of power system management will increase significantly. Judging from the decarbonization goals and current development trends, a large number of physical devices will be connected to the power grid in the future, especially the power distribution network. In the distribution grid, current will also become increasingly dynamic and multidirectional (see Figure 1), such as small distributed devices that may generate electricity and sell back to the grid, fast charging of electric vehicles, etc. leading to a surge in demand, smart homes, etc. Such equipment may be connected to the grid without the knowledge of the grid operator, which will have a considerable impact on the stability of the current. Various dynamic changes may challenge the stable performance of the power grid, and even lead to problems such as unbalanced power supply, power outages, power cuts, or excess installed capacity. Without real-time data analytics, the complex power and energy systems of the future will become more difficult to manage.
AI can accelerate the energy transition. Artificial intelligence refers to a broader concept, not a single technology or product, but a set of algorithms that can mine useful information from large databases, perform pattern recognition, and predict potential outcomes. There are already some use cases for AI in the industry, but moving away from fossil fuels quickly, safely, and economically requires deploying AI technology on a larger scale and faster. Artificial intelligence is expected to be widely used throughout the energy industry value chain, providing companies with new business models to increase revenue streams, while helping companies save costs (such as reducing equipment replacement costs through predictive maintenance of existing equipment). ), so the economic value of AI in promoting the energy transition is difficult to estimate accurately. Given the scale of investment required to achieve the energy transition, even reducing investment or peak energy demand by just a few percentage points from AI would save the industry billions of dollars.
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