By Simarpreet Singh
Governments are increasingly using renewable energy instead of fossil fuels. The process of producing electricity can be severely disrupted as a result of this. Thus, renewable energy thrives but needs stable systems designed for precisely these kinds of applications. As a result, the industry moves from commodity-based to technology-oriented markets in order to integrate renewable energy. As renewables, such as wind, solar and hydrogen, start to dominate grid-scale electricity generation, accurate power generation and net load projections will become much more important for a low-carbon, balanced system.
The Fourth Industrial Revolution has brought consumers, developers, and grid operators who use artificial intelligence (AI) for a smooth transformation process with an increasing quantity of renewables. Through predictive capabilities, AI is capable of accurately forecasting consumer demand, which allows companies to effectively allocate their assets. Moreover, automation boosts productivity, giving companies an upper hand and financial savings to shareholders. According to Research and Markets, AI for the energy and power market is forecast to be valued at $3.103 billion in 2021 and will grow at a CAGR of 24.68%, reaching $14.527 billion in 2028. However, in the time of AI-driven operational excellence, improved predicting ability and automatic power create a competitive advantage; therefore, it is necessary that all advancements and the implementation of AI be environmentally friendly while industries are undergoing transformational technology shifts.
Let’s dive into how AI is being used to improve energy efficiency across a range of industries to demonstrate how AI has the potential to promote sustainability-
Grid Management
The renewable energy industry is transforming with AI in smart grids optimizing various components like power generation, storage, and consumer demand. AI algorithms dynamically balance supply, control peak loads, and facilitate the integration of dispersed energy resources using real-time data. This optimization minimizes waste and mirrors the industry’s efficiency transformation. AI-driven forecasting enhances grid efficiency, a pivotal aspect in the broader industry transformation, dynamically balancing supply and demand through real-time data and predictive analytics.
AI-led Predictive Maintenance
AI can be used by energy businesses to predict when their equipment will break down or need maintenance in advance. Using extensive amounts of raw data collected from multiple sources, such as usage statistics, weather reports, and past maintenance records, machine learning can predict potential breakdowns beforehand, thus averting possible disruptions in production activities. It reduces repair costs and downtime and increases the total reliability of the energy system.
Energy Storage Systems
AI encourages energy storage system innovation, which is essential for the broad use of renewable energy. AI models maximize energy storage system charging and discharging cycles by examining past energy usage trends, weather data, and grid conditions. This guarantees effective use of evacuated energy, enhances grid stability, and lowers dependency on non-renewable backup energy sources.
AI and Sustainability: A Path to the Greener Future!
Energy efficiency is now driven by advanced AI, leading to a new wave of industrial transformation and sustainable corporate growth. Various sectors of business can maximize their energy use, lower costs, and decrease pollution through implementing AI. AI marks the new strategy when exploring clean and friendly fuels. When used alongside efficient consumption methods in conjunction with renewable energy resources and smart energy use, its potential can fast-track the transition to a more eco-friendly world. Hence, a clean and green world will be closer if we embrace the benefits of AI and put them into practice.
The author is executive director, Hartek Group
