Carbon neutrality powered by AI

Synopsis: Countries like India, which are leading the adoption of climate change measures, will have to encourage energy companies to embrace higher levels of AI usage.

Introduction

As the world pushes to mitigate the impact of climate change, it will have to rely much on emerging technologies.

The foundational shift of energy transition from fossil-based to renewables will have to be done at scale for any positive impact on the environment.

A new report by World Economic Forum (WEF) says that the transition to low-carbon energy can be accelerated and deepened by focused application of artificial intelligence.

How can AI help in accelerating transition to a low-carbon economy?

Increasing efficiency: The supply of renewable energy is increasing in grids which have been built for fossil fuel-based power. The time for setting up renewable power generation is much less than for setting up transmission and distribution lines. As a result, existing electricity grids will have to be managed with far more efficiency to cope with rising supply and usage of renewable energy.

AI can help in management of existing electricity grids with more efficiency to cope with rising supply and usage of renewable energy.

Optimization of the lifecycle of existing grid infrastructure. Renewable energy is not a steady supply, since it depends on weather conditions. Solar works on sunny days and wind turbines when there is a strong breeze. Such intermittent supply of renewables poses problems for managers in maintaining stability of energy passing through the grid.

To deal with unanticipated scenarios: There are several problems which can hurt grids when intermittent power increases. These include power frequency imbalances, blackouts and brownouts, and significant capacity overbuild. With predictive analysis, AI can anticipate the amount of power that will reach the grid by combining weather conditions with supply parameters. AI will allow grid managers to be prepared rather than be impacted by unanticipated surges in supply.

Manage overloading: In future there will be vastly more physical assets connected to the power grid and the distribution grid, and power flows will become dynamic and multidirectional.

Track usage in real-time: In the future, there will be vastly more physical assets connected to the power grid. For example, the rise of energy storage in batteries means that some of this power can be reused when required. A household can have the option of switching between battery power, on-site solar source and the grid based on the situation. Similarly, for individuals, AI can help decide when to charge electric vehicles. AI can decide the charging time and duration based on peak or off-peak rates. Such switching at a large scale across millions of homes will require an AI platform to track usage in real-time.

AI can help in efficient designing and location of solar, wind and other renewable farms: According to German Energy Agency, 56% of power generation could be provided by solar and wind in 2050. This would need huge investments in power grid by 2050. Power system costs would be higher if intelligence automation systems are not used.

Source: This post is based on the article “Carbon neutrality powered by AI” published in Business Standard on 6th September 2021.

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