Key Software Solutions for Enhancing Performance in the Energy Industry

As the energy industry strives to reach decarbonization goals, meet a rising energy demand and navigate unpredictable market dynamics, companies in this sector are turning to tech solutions to drive efficiency, improve stability and automate processes. Emerging and evolutive technologies like cloud computing, Internet of Things (IoT) and artificial intelligence (AI), can help energy businesses effectively maintain their hardware, manage data and storage, as well as operationalize forecasts and analytics-driven insights. Read on to find out what software trends have been gaining traction in the energy sector and how your business can benefit from these solutions. 

Smart grids and intelligent devices empower both consumers and energy companies 

To improve the resiliency and security of their services, many energy companies are deciding to invest in digitalization and modernization efforts. An example of this combination of infrastructure and software upgrades is a smart grid. 

According to Transparency Market Research, the global smart grid market is projected to grow at 17.8% compound annual growth rate (CAGR) between 2021-2031, with its value rising to $845.6 billion USD by the end of 2031. A smart grid connects elements of infrastructure, firmware and software to create a network for effective power distribution, generation, use and storage, as well as establish communication between different parts of a system. It empowers both energy suppliers and consumers to have better control over their resources and costs and manage them more efficiently. 

Leveraging embedded systems and IoT, among other technologies, smart grids offer advanced metering, distribution automation and improved storage. The network uses various sensors, meters and other connected devices that help consumers, both individual and large-scale such as entire cities, to track their energy use and make cost-saving decisions. Companies, on the other hand, get access to accurate, real-time data that, when combined with automation, enables them to adjust distribution to changing demand and monitor the condition of equipment. Advanced monitoring and automation can also alert distributors to potential blackouts, help them mitigate overloads and quickly redirect power in the case of an outage occurring. 

Companies leverage data-driven insights to optimize operations and boost efficiency 

Systems and devices used to collect information are becoming increasingly advanced, often granting access to very granular data in real time. However, companies are not maximizing the large amounts of data available to them unless they can turn them into actionable insights. Data science, along with machine learning (ML) and AI, helps businesses optimize their operations, increase efficiency and plan infrastructure as a response to anticipated demand.  

Companies can analyze data to plan necessary blackouts and streamline energy supply processes so that power distribution is adjusted for periods of low and spiking usage. Energy companies can also use predictive analytics to create accurate power consumption forecasts or optimize infrastructure maintenance by quickly detecting malfunctions or assessing device longevity. Apart from their impact on operational efficiency, these improvements also boost customer experience, granting consumers reliable service – a key need in an increasingly electricity-dependent world. By adding automation into the mix, some businesses aim to create autonomous energy systems that can more effectively react to disasters by automatically redirecting energy from alternative sources to places that might be affected by blackouts. 

These solutions often require specialized skillsets and custom product development. According to McKinsey’s 2022 The State of AI Report, a majority of survey participants whose companies have implemented AI found it difficult to hire specialists for AI-related roles, including AI data scientists (78%), data architects (72%) and software engineers (65%). Organizations that want to quickly access specific IT talent while focusing on their core business often decide to partner with a software development company. Supported by the expertise of external engineers, energy companies can tailor evolutive products to their business goals and create solutions that meet their customers’ expectations, while also ensuring high quality and scalability of their products. 

Digital twin technology maximizes maintenance processes and supports product enhancements 

Digital twins are a virtual version of physical objects, processes and systems that function in the real world. They provide digital information about the behavior and condition of its physical counterpart by collecting data from various device sensors. This technology can be applied to monitor an energy network at different levels, from device components through interactions between assets to processes involving several systems.  

Similarly to smart grids and data science solutions, digital twin technology enables companies not only to quickly react to urgent, present situations, but also to prepare and take data-driven action for the future. Real-time information about different devices and equipment in an energy system helps energy organizations detect and understand performance issues and their correlation with other measured variables, such as weather conditions or temperature. These insights can then be used to optimize the performance of physical counterparts. 

Research from Capgemini found that businesses which are already using digital twins have improved their system performance by over 25%, with other areas like sales, turnaround time and operational efficiency improving by 15%. Because digital twin technology can be applied to products at different stages of their life cycle, it creates opportunities for companies to improve their product design, production processes and even complex interactions between different energy systems. Up-to-date monitoring is a tool for scheduling optimal maintenance checks, increasing product lifetime and determining which machine parts can be reused or repurposed once equipment no longer functions. Ultimately, tracking and analyzing digital twin data can contribute to reducing implementation or production costs and making more informed decisions on energy generation and storage.

Organizations aiming to drive innovation can use digital twins to run a range of simulations to support research and development efforts and identify areas for improvement, as well as test and refine products, enhancing the quality of the next iterations. For example, when paired with prototypes, digital twin technology can eliminate flaws before a product or process is approved for production. With the right models in place, companies can even explore how different conditions will impact their systems or processes. 

Forward-thinking technologies ensure energy grid stability and security 

Technological trends in the energy sector highlight the important relationships between hardware, firmware and software that are used to create advanced distribution networks. To keep up with the push towards renewable energy and changing consumer demands, many energy companies are looking into innovative solutions to optimize operations, maximize investments and empower customers. However, complex systems and challenges usually require a tailored approach and diverse expertise with emerging technologies. A technology partner like Software Mind provides a cross-functional team of engineers who can develop and deliver solutions designed to meet your business’s goals and your customers’ expectations. Fill out the contact form below and our experts will reach out to discuss how we can accelerate your software development life cycles.