AI will revolutionise the energy industry

Energy is one of the most fundamental aspects of our modern lives. Without sustainable and accessible energy, the human race wouldn’t have developed as fast as it has been doing. The discovery and use of energy has helped us develop out of our primitive forms and transform the planet.

Reliable energy supply is still a huge problem to many nations around the world. Energy consulting firms are in a prime position to make energy related business strategies and plans more effective and help results become more impactful.

Major energy corporations, operators and researchers in the energy industry have been exploring new ways to improve the infrastructure and utilisation of renewable energy resources. One route is the incorporation of artificial intelligence (AI). Artificial intelligence in renewable energy systems will revolutionize the energy industry.

1. Elimination of Errors

The increased global demand has put a burden on the limited energy resources and organisations that heavily consume energy. The professionals working in the energy and infrastructure sectors bear a heavy responsibility of paramount importance. Miscalculations and poor estimates can lead to disastrous consequences.

Sometimes power outages are planned to level out supply with demand and in other cases inadequate planning and aging infrastructure can lead to power malfunctions and blackouts. An example is South Africa and its power utility Eskom, having stated that their load shedding is caused by an increase in plant breakdowns exceeding 3,000 megawatts of capacity. AI can automatise the regulatory and operational processes to speed up decision making and actions specifically, machine learning-based PQM solutions have proven to be effective to create cost savings, improve the uptime of systems and provide more accurate predictions. Predictive maintenance has been particularly useful in pre-empting plant and equipment failures, detecting anomalies and determining when operational processes are likely to fail. Predictive models driven by AI can help support human assessments of asset lifetime and operational efficiency and aid strategic decisions for infrastructure planning. Globally, the investments in AI start-ups are rapidly increasing; UK, US, China and EU being notable investment regions. Energy monitoring and management company, Innowatts, provides a powerful smart energy data platform for forecasting, load planning and more. .

2. Reducing the Carbon Footprint

Even though AI requires a significant amount of data and energy to perform, it can play a huge role in reducing the carbon emissions from corporations. Areas that AI has a major role in include the analysis of climate change, improving the operations of electrical power grids, as well as making energy converters more efficient. For example, AI-assisted wind turbine heads reposition themselves ‘real-time’ to capture more wind. Also, in regards to weather prediction, machine learning and data science has proven effective in improving solar forecasting of capacity and irradiance – as attested by National Grid ESO’s recent programs.

3. Facilitating Energy Decentralisation

One of the greatest challenges that the energy sector faces is finding a solution to decentralise the power grid and better distribution management for renewables. It is common, for a single power plant to be responsible for powering multiple areas with high population densities.

AI can help manage the decentralization of power management systems, apply smart grid technology and coordinate connectivity between independent power suppliers, the grid, consumption devices and storage applications. With this plethora of systems and stakeholders in mind, there are millions of data points to analyse to form intelligence that can enable real-time decision making for the current, real-world market conditions. Considering a consumer perspective, AI-assisted systems could cross reference yield and capacity with load and peak demand patterns and at the right time, trigger notifications to be sent to consumers’ smart devices reminding them to adjust their thermostats. This level of sophisticated technology and processing also holds great significance for remote regions with unreliable power supply, developing countries or grids relying on ageing infrastructure with limited resources.

Knowing that AI can help with coordinating how energy is managed, when and where it is to be distributed, and how it can offer greater affordability and control among consumers – somewhat akin to the philosophy of blockchain technology, investors and corporations should prepare for the entire distributed energy value chain to transform because of AI in the next few decades.

Final Words

Climate change poses the biggest threat to our life today. In line with net-zero targets, industries are restrategising with the aim of reducing their carbon footprint. The energy sector is the biggest contributor to carbon eliminations and today has the greatest responsibility to reduce carbon emissions.

Artificial Intelligence has accelerated development in several industries and the spotlight on what it could achieve and assist with is intensifying. The energy sector is seemingly following suit and exciting opportunities lie ahead in the short term as well as this decade.

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