Digital transformation has become the mainstay for all businesses today and one of the drivers of this revolution is Artificial Intelligence (AI). There is no denying that AI is destroying seemingly insurmountable business barriers at an all astounding rate. Today, AI is instrumental in transforming the way all industries work – from dynamic manufacturing, healthcare industries or the rapidly evolving automotive and power sector.
All industries, especially heavy equipment industry, are undergoing a rapid digital transformation designed to meet the two objectives - faster product regeneration and systems optimization. While digital building blocks (such as DSI & MBE, IIoT platform) form the first part of achieving this transformation, the second is all about getting deeper insights from collected data, using Statistical, Machine Learning & Deep Learning techniques. Here is where AI can be a powerful tool to make a difference.
Challenges faced by Indian Power Sector
Despite the encouraging growth trajectory in the power sector over the last few years, the Indian power sector has still not been able to achieve and sustain the production capacity that matches the ever-growing power demand of the country. There are various challenges responsible for this shortfall. First among these are the unavailability of raw materials - thermal capacity addition is plagued by the growing fuel availability concerns, while gas-based capacity is idle due to non-availability of gas. In addition to this, there are AT&C losses and operational inefficiencies, coupled with financing and regulatory challenges.
India needs a balanced regulatory intervention that can resolve immediate issues to mitigate these concerns. A robust and sustainable credit enhancement mechanism for funding should be put in place and an optimal fuel mix strategy needs to be developed for both conventional and non-conventional forms of energy. Most importantly, a public private partnership model needs to be encouraged to ensure profitability so that operational efficiencies are in place.
While, some of above solutions are beyond the scope of this article; we will address the role of AI to tackle operational inefficiencies & reduce overall power tariff. As a technology, AI has proven to provide innovative solutions using creativity, problem solving, critical thinking, analytical thinking as well as systems analysis. For the issues plaguing the power sector, these attributes may be just what are needed. AI will serve to establish much higher efficiencies, agile processes and system clarity between consumers, utility companies and power OEMs.
Top 3 Areas of Power Sector that are transformed by Artificial Intelligence
AI has already been crucial to various aspects of design, development and aftermarket phases for any major product in the power sector. For product development & services, AI based apps and software act as an interface between machine and human beings, this works well in both General AI (GAI) and Applied AI (AAI) functionalities. GAI boasts of machine intelligence that allows intellectual tasks to be performed by a machine, while AAI is about in-depth machine learning and predictive analysis, to both learn as well as adapt.
The top three segments that are affected –
Low Cost, Customized Products advantage for Equipment Manufacturers:
AI can help designers, developers and product managers to create designs for steam/Gas/Wind/Solar products that will be more easily acceptable to generation companies and also offers more options in terms of product performance improvement. The need for customization and localization of products to make power generation companies comfortable can be met with AAI. For manufacturing products that are designed according to specific patterned lace with AI are more likely to reduce manufacturing trial and error cost, while ensuring the process is future ready.
AI can not only upgrade product development and manufacturing of power equipment, but also work towards stringent quality control to reduce cycle time and resource optimization, while improving production reuse.
Generation: Reduce Unplanned Downtime via Predictive Maintenance
In the power sector, the most critical aspect of a generation cycle is the downtime that could ensue due to a breakdown of systems or machinery. The process gets disrupted often without warning and the result is an exponential cycle that effects the entire supply chain. The resultant losses could run into millions of dollars!
With digital transformation, there is a data collation aspect involved for every part of the industrial process and its related systems. However, as time passes, the parts and hardware experience wear and tear, and soon small problems snowball into an exponential breakdown. Pre-empting and identifying this critical breakdown point using relevant data is a step for predictive maintenance. This could be the start of a series of activities performed for extending the lifecycle of a part or a process in a timely manner, as all technology teams are aware.
AI and ML could create algorithms to predict downtimes and pre-empt the required actions to control the losses effectively. While there are several mechanical methods to do this, with AI, the ability can be built into the processes, and can help power companies to save money and effort, resulting from downtimes and business losses.
Utilities: Smart Distribution & Consumption
AI can help reduce energy consumption in several ways. It has the ability to pre-empt and predict operational strays or energy leaks, especially for large buildings/plants. By developing such predictive models, the utility companies could build better client segments, and personalize customer offerings with relevant information. Machine Learning techniques can also be applied to detect consumption behaviors and energy use patterns.
Utilizing the True Power of AI
AI helps in optimization and speed for product design and development, from the conceptualization to detail design to production and delivery phases. OEMs in power sector need to utilize AI for their vital product developments to speed up the design prototyping process. They need to leverage Machine Learning to align the product with actual operational & flexibility requirements. Power plants can optimize asset utilization by leveraging AI based maintenance solutions and power utilities companies could gain significant competitive advantage by leveraging AI in power transmission, distribution & consumption.
Computer vision, speech recognition and natural language processing can help OEMs create models that can learn from data in any format, using ML and Deep Learning as well.
With AI in power generation & services, the future looks promising and there is no turning back!
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