Technology Trends That Help the Energy Sector Thrive

How much will our demand for energy rise in the next twenty-five years? The forecasts are concerning. Globally, it’s expected to surge between 11% and 18% (according to McKinsey & Company). The sharpest increase in demand, between 66% and 95%, is expected in developing economies, i.e., the Southeast Asian countries, India, and part of the MENA region. In Europe, these numbers are lower, partly because of the deindustrialization trend. For example, the most typical scenarios project that Switzerland, with one of the most well-developed energy infrastructures, can encounter the rise of electricity consumption by around 50%.

There are several factors that impact this growth. Among them, we can name the accelerated adoption of electric vehicles and installation of heat pumps in households and industrial facilities, as well as the mounting demand from data centers that is projected to skyrocket to over twice today’s figure by 2030 (according to the International Energy Agency).

At the same time, the potential to expand hydropower and nuclear energy is limited. In European countries like Switzerland, nuclear power is scheduled to be phased out by 2045 or even earlier than that, while for hydropower, most of the potential in mountain valleys has already been tapped. How can we fill this electricity gap that will arise in the coming years and address this additional energy demand, then? The answer is: through new technologies and alternative types of energy generation.

Key trends to watch in energy digitalization

At Andersen, we see the following technology making the most impact in the sector:

Artificial intelligence

Advanced software performing human-like intelligence can make decision-making faster and more accurate by understanding future demand and streamlining grid management. Prominent use cases are:

• Maximizing turbine burner output when producing thermal power by enhancing fuel supply through AI;
• Unlocking insights from wind and operational data to mitigate high-wind hysteresis and thus, accelerate the production of renewable power;
• Tracking energy usage with smart meters equipped with machine learning and optimizing energy delivery via smart grids;
• Identifying drilling sites more accurately and streamlining drilling workflows in oil and gas operations, e.g., by bringing together flow, pressure, vibration, and environmental metrics.
• In the energy sector, the implementation of AI should always come with a policy structure around it that guarantees information security. That is, energy companies need to prevent employees from independently providing company data to these programs. A framework must be in place where AI-fueled software is used within a protected corporate setup.

Big data

By collecting and evaluating the insights from their daily activities, organizations can trim expenses, raise efficiency, and minimize downtime. Popular use cases are:

• Evaluating seismic insights to map potential oil-bearing sites and carrying out predictive maintenance;
• Adjusting flexible assets dynamically depending on the supply-demand outlook;
• Relying on advanced analytics to decrease procurement spend, perform line-clearance vegetation management, prevent service interruptions, and spot patterns in customer energy usage to upgrade company offerings.

Blockchain

In energy markets, distributed ledger technology fosters greater visibility, protection, and dependability. Direct energy trading between peers, simplified tracking of renewable energy mandatory certificates, and smart contracting are several high-value use cases of this software.

Its potential applications include:

• Distributing power in a decentralized way, which was done during a US-led pilot initiative when community residents sold off-grid solar power to each other via a blockchain-powered platform;
• Effectively running energy networks via smart contracts that trigger the system to automatically start the necessary transactions;
• Estimating power consumption and supply through advanced blockchain-based models to make better decisions on grid infrastructure funding and tariff structuring, line maintenance, etc.

To sum up

Today, energy companies can avail themselves of feature-rich software solutions. These collect ESG data, automatically draw up reports, enhance the handling of renewable energy systems, measure and minimize carbon impact, visualize data in real time and simulate possible scenarios, ensure IoT-driven predictive maintenance, keep track of environmental compliance and hazards, digitalize upstream and downstream workflows, optimize asset performance, and more. A dependable company working in the energy sector software development will design and build these platforms from scratch, ensuring superb quality and impressive results.