AI in Business: Episode #5: AI in Energy & Utilities
AI has been a buzzword for a few years now and it doesn’t seem to be going away. In fact, the use of AI is only going to increase in different industries. One such industry is energy and utilities. AI has a lot of potential to help the challenges that this sector currently faces.
In this blog post, we will discuss 10 use cases where AI has been used in the energy and utilities sector. We will also look at some statistics around the AI market in energy and utilities sector. Finally, we will discuss what the future holds for energy and utilities sector by using AI.
Introducing AI in Energy and Utilities
Lately, there has been a lot of talk about artificial intelligence (AI).But what does it actually mean?
AI is a type of technology that allows machines to learn and work on their own. This means that they can be taught to do a certain task, and then continue doing that task without human intervention.
This is a huge advantage for the energy and utilities sector. Currently, this sector faces a number of challenges, such as managing a complex network of devices, predicting and responding to changes in demand, reducing energy consumption, maintaining compliance with government regulations and so on.
AI can help with all of these challenges. It can help by automating tasks, predicting changes, and helping to reduce energy consumption. Additionally, AI can help to maintain compliance with government regulations.
AI is quickly becoming a mainstay in the energy sector as utilities companies seek to adopt the technology to improve performance and optimize resources.
According to a recent report, the AI market in the energy and utilities sector is expected to grow from $2.13 billion in 2018 to $11.14 billion by 2025. This growth is being driven by a number of factors, including the need to improve asset performance, reduce operating costs, and increase efficiency.
Use cases of AI in Energy and Utilities
AI is being used in a number of ways in the energy and utilities sector. Some of the most common use cases are:
#1. Managing a complex network of devices:
Networks include a variety of devices such as power plants, solar panels, wind turbines, and more. These devices need to be monitored and managed in a efficient way. AI can help manage networks by providing insights that enable energy providers to make better decisions about where to allocate resources. For example, AI can be used to predict failures in power grids up to two weeks in advance.
#2: Demand Forecasting:
The energy and utilities sector needs to forecast demand changes in order to maintain a dependable, strong energy supply. This way, they can plan for investment expansion and resources. AI can help predict demand by analyzing a variety of data sources, such as weather data, energy usage patterns, the economy, news and social media data. For example, a machine learning algorithm can be used to develop a model that can accurately predict demand for electricity up to two weeks in advance.
#3: Predictive Maintainence:
Many of the energy and utilities sector’s infrastructure is aging, such as power plants and transmission lines. This poses a challenge in terms of maintenance and replacement. AI can be used to help manage aging infrastructure, such as power plants and transmission lines and predict when equipment needs to be serviced or replaced, so that repairs can be carried out before there is a breakdown. For example, AI can be used to detect anomalies in power plant data that may indicate a potential failure.
#4: Utility Efficiency:
The energy and utilities sector is under pressure to become more efficient in order to reduce costs. AI can help make the sector more efficient by providing insights that enable energy providers to make better decisions about where to allocate resources. For example, by creating models of demand, supply and cost savings, energy providers can optimize their operations to reduce costs.
#5: Energy theft prevention:
The energy and utilities sector loses billions of dollars each year to energy theft. AI can help prevent energy theft by analyzing data to identify patterns that may indicate a potential theft. For example, Pattern-detection models can be used to detect energy theft by analyzing a variety of data sources, such as billing data, power usage data, and look for anomalies that may indicate a theft.
#6: Document managment:
In utilities sectory, document management issues are a big pain point. For example, a water utility company may have millions of documents, such as customer records, invoices, and contracts. AI can help manage these documents. For example, a water utility company can use an NLP model to automatically extract customer information, such as account numbers and addresses, from invoices, perform document segmentation to identify different types of documents, and use Optical Character Recognition (OCR) to digitize paper documents.
#7: Customer Service:
The energy and utilities sector is under pressure to provide better customer service. AI can help improve customer service by providing a more personalized experience. For example, a chatbot can be used to answer customer questions about their energy bill or a virtual assistant can be used to schedule a technician visit. Also by using data analytics to understand customer energy usage patterns, and provide information on how customers can reduce their energy usage and save money.
The future of AI in energy and utilities
The use of AI in the energy and utilities sector is still a relatively new concept, but the benefits are clear. From reducing costs to improving customer service, AI has a lot to offer. We’ve looked at some of the ways that AI is being used in this industry already, and there are sure to be many more innovations on the way. With predictions that the market for AI in energy and utilities will reach $11.8 billion by 2025, it’s clear that this is an area worth watching.
