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The development status of artificial intelligence in the power industry
The development status of artificial intelligence in the power industry
Today is the 140th anniversary of electricity being delivered to homes and businesses since humans first used it. The electricity industry has grown and become one of the most important services in people's work and life. But the industry is also currently facing a unique set of challenges, which means its previous business model will change.
These challenges include the real need for sustainability in power generation, which was highlighted at the 26th United Nations Climate Change Conference in November 2021. Countries around the world have made commitments to decarbonize their energy supplies and have reaffirmed their commitment to vigorously promote solar and wind power going forward.
This has huge implications for the world’s highly regulated power industry, which faces fines and reputational risk if it fails to deliver electricity in compliance with regulatory framework requirements. The transition from fossil fuels to sustainable energy production needs to be carefully managed when using less predictable methods.
Soaring energy prices have also had a negative impact on electricity providers around the world, with many having to shut down operations. As a result, established electricity providers had to take on thousands of new customers almost overnight, putting enormous pressure on both workers and the electricity system.
Problems caused by legacy technology
This has brought people problems with legacy IT systems. Just as the power industry struggles to update and retrofit aging infrastructure, it is difficult to find the investment to upgrade IT platforms due to a growing shortage of relevant skills and expertise.
So while initiatives such as smart metering should bring benefits by reducing costs and increasing efficiency, in practice the vast amounts of data collected are difficult to manage and analyze in any meaningful way, such as in predicting future events in real time. When energy is consumed.
While some consumers have been stripped of choice in the face of the energy pricing crisis, providing excellent levels of customer service is a key factor in reducing customer churn and gaining market share. This applies both to contracting and servicing customers, and to resolving energy supply issues.
Traditional IT systems mean that the information contact center staff need to support customers is often held in disparate systems. People are used as connectors between these systems, creating friction in processes such as address changes, billing, or failure-fix planning.
So, given the need to create value for shareholders while meeting regulatory requirements and keeping customers happy, how can power companies adapt their processes and adopt a more data-driven approach to managing their operations, rather than at scale? Replacing legacy IT systems?
Enter Intelligent Automation and Artificial Intelligence
One answer lies in the adoption of Intelligent Automation (IA) and Artificial Intelligence (AI) technologies, a technology designed to transform electricity Technology convergence in how the industry operates. A global industry is emerging that applies intelligent automation (IA) and artificial intelligence (AI) to nearly every aspect of sustainable electricity production and distribution, with large enterprises adopting automation platforms to deliver real change.
Working with power companies, it is possible to identify some areas where automation and artificial intelligence will bring clear benefits.
(1) Customer Experience – Utility companies can be greatly impacted by customer experience (CX) scores. This could result in regulators imposing huge incentives/penalties every year, which can be a painful experience if not managed well. By integrating customer relationship management (CRM) and billing systems, utilities can avoid leaving customer agents with complex systems and multiple data sources. And digital workers can do the heavy lifting of extracting data into a single view of the customer.
(2) Legacy Infrastructure - The reality faced by many enterprises is that their underlying digital environment is a combination of old and new, and having the ability to bring the two together is key. Obtaining information from decades-old customer IT systems to integrate into modern workforce management systems is still done to some extent by workers cutting and pasting from one system to another. This alone provides a wealth of improvements that can help operational response teams become more efficient. It also allows these responders to spend more time in discussions with customers, who often face more stress since most calls are for business and service-related issues.
(3) Environmental reporting – This is aligned with the climate agenda but also includes indicators such as performance reporting around regulatory targets for pollution and efficient energy production. Such reporting is critical, supporting automated systems that can manage same-day monitoring and response to provide accurate reporting on target.
(4) Intelligent Systems – The requirements for the 27 EU member states to move towards intelligent systems add an additional layer of complexity. Each energy provider has a goal that they undertake themselves or outsource. The interactions between energy provider systems and installers are complex, with numerous duplication and access issues that automation (IA) and artificial intelligence (AI) can help improve.
(5) Optimize plant maintenance - Old power generation and distribution infrastructure are some of the biggest challenges facing utility companies in developed countries. This has a huge impact on their ability to provide reliable, cost-effective and “future-proof” services to their end users. In some cases, these suppliers are using generation equipment that is more than 30 years old and looking to maximize its use by implementing IoT, intelligent automation (IA) and artificial intelligence (AI) around workflows such as predictive maintenance. life. This is where sensors on large equipment provide data to SCADA systems, and IoT, artificial intelligence, and smart automation platforms can help determine the likelihood of a failure. Based on this data, field service requests can be automatically scheduled and technicians repaired before failures occur, thereby extending service life, reducing costs and increasing efficiency.
(6)Climate Change - Almost all suppliers have targets to achieve net zero emissions within a specific time frame. Employing robotic process automation (RPA), advanced analytics and artificial intelligence can help achieve climate change goals and the growing need for clean, affordable, reliable water. For example, San Diego Gas and Electric uses sensor data as well as satellite weather data to prevent wildfires. Another example is using drones to conduct inspections of power infrastructure and solar farms, and using computer vision to detect anomalies where digital workers collect data, analyze and execute the next best action.
Removing Barriers to Use
Given the benefits that intelligent automation (IA) and artificial intelligence (AI) can bring to the power industry, why is there still a reluctance in some quarters to adopt related technologies? For everyone An enterprise that leverages first-mover advantages and sees measurable results (such as reduced customer onboarding, automated engineer scheduling, and frictionless changes to address processes), and others that have yet to take any meaningful steps to adopt intelligent automation (IA) and artificial intelligence Intelligent (AI) technology.
As a rule of thumb, barriers to adoption tend to be cultural rather than technical and budgetary. Using new technology requires buy-in not only from the senior leadership team and business units, but also from the IT team: its best results come from ongoing change programs, not just one-off ad hoc projects.
Another challenge is that businesses operating in highly competitive industries may not be willing to share best practices and measurable results from their intelligent automation (IA) and artificial intelligence (AI) planning. In industries with fierce business competition, it is difficult to achieve joint and integrated digital transformation.
Finally, utilities may worry about losing control of essential services if too many jobs are transferred from workers to digital technology. However, as many utilities are discovering, digital technology can work around the clock with greater productivity, accuracy, safety and speed than human workers.
The power industry has come a long way since the first power station opened in 1882. But due to climate change, infrastructure and aging legacy systems, we have now reached an inflection point where we need to start adopting different technologies and approaches, including the adoption of smart technology platforms built around intelligent automation and artificial intelligence.
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