A.I. and Energy

The energy sector has already started utilizing technological innovations like AI, automation, and advanced analytics. In terms of organizational success, an Infosys research report indicates, 48 percent of the respondents from energy, oil, gas, and utility consider AI to be the fundamental force behind their organization’s success. Furthermore, the report argues that AI will be the primary “driver of a future sustainable energy ecosystem that includes an appropriate mix of fossil fuels and renewables” (Analytics India: 2018). According to Analytics India magazine analysis following are the benefits of harnessing AI technology for the energy sector:

1. Reliability: Powering self-healing grids and improving operations as well as ensuring the efficient use and storage of renewable resources.
2. Safety – Facilitate outage prediction and outage response.
3. Cybersecurity – Enhanced threat detection and response.
4. Optimization – Improved management of assets, maintenance, workflow, and portfolio.
5. Enhanced customer experience – Facilitate quicker and more intuitive interactive voice response, personalization, and product and service matching.

The predictive algorithms can be hugely helpful in deciding and storing energy for balancing power grids. AI is also utilized for improving the forecasting and equipment efficiency of renewable energy resources by accumulating data for wind turbines and solar panel sensors and amalgamating them with atmospheric data (ibid).

According to Niti Aayog’s report, AI in the energy sector in India will include energy system modeling and forecasting lessening the instances of unpredictability and increasing efficiency in power balancing and usage. Also, AI can enable storing energy through intelligent grids with the help of smart meters improving the reliability and affordability of photovoltaic energy. The utilization of AI in Smart cities has already started in cities like Pune. Pune has kickstarted a ‘Pune Street Light Project’ to set up energy-efficient lights that can be remotely controlled via Supervisory Control and Data Acquisition systems. In its endeavor to be a part of #AIforAll which gives a mandate for an inclusive AI, India has been at the forefront of playing a lead role in climate leadership with the signing of the Paris agreement. The agreement vows to curb carbon dioxide emissions in order to limit the global average temperature from rising above 1.5°C. In a similar vein, India has pushed for clean energy by leading International Solar Alliance and setting a target of 100GW solar energy capacity by 2022.

An interesting example of AI and machine learning in renewable energy conservation is Climate Connect. The company Climate Connect has triggered India’s rise in Global Innovation Index (GII) from 66 to 60. The platform utilizes a synchronization of energy, data science, and software technology and AI with machine learning to provide analysis, forecasts, and automated decision making for customers in energy markets in India, China, Europe, and USA. Energetica India reported, “AI companies in the energy sector are working across the value chain of forecasting techniques, Climate Connect operates at the leading edge of AI& ML revolution”. The confluence of AI and machine learning is ostensible in its solar power plant experiments. In that manner, Climate Connect is the first firm to build forecasting models for the power exchange market. Solar forecasting, most importantly, is an AI-driven model deciding whether in real-time revisions should be implemented. The forecasting analyzes past, and past data to provide an accurate picture.

AI in the power sector is bound to create a revolution in terms of collecting and synthesizing overwhelming amounts of data from millions of smart sensors, thereby, making a timely decision on how to best allocate energy resources. The advances in ‘deep learning algorithms would be useful in spotting patterns and anomalies in large data sets creating a long-term impact on both the demand and the supply side of the energy economy. In this sense, the large regional grids will be replaced by specialized microgrids which will manage local energy needs with better and finer resolution. These can be paired with new battery technologies allowing a free flow of power to and between the local communities even when the severe weather constricts the power supply.

The future of AI in the energy sector is not just significant in predictive algorithms but also in the way it will strengthen the energy economy of India. The smart grids are going to be the new brains of the energy sector. Some have also termed it as the evolution of smart grids as ‘energy cloud’. AI will be an advanced way of connecting millions of points of control in grids by efficiently reaching out millions to billions of people. In the future, AI can thus, greatly help in suggesting measures for conserving energy and optimizing the allocation of energy resources. The AI scope for enhanced economic efficiency is a crucial step towards ensuring sustainable use of resources. The role of energy in boosting the economy and meeting the needs of citizens is pivotal and AI will only revolutionize it further.

This piece is written by Anuttama Banerji. Anuttama is Associate Researcher at Govern.