Cognitive Energy Operations for Next-Generation Sustainability

Jay Gupta

Project Management Specialist, TCS DSS

Energy companies are facing challenges on multiple fronts including energy prices, supply disruptions and increasing levels of safety and environmental regulations.

Energy providers must become more agile, resilient and proactive to address these critical issues in order to stay competitive and operationally sustainable.

Now Is the Right Time

As the energy industry continues to embrace digital transformation and adopts cloud technology as a core business enabler, it is becoming necessary for information and decision-making processes to integrate data from the entire energy value chain into contextual and cognitive intelligence to achieve maximum financial performance, worker and plant safety, and net-zero emissions goals.

Our model for cognitive intelligence includes an ecosystem of technologies that augment human capabilities to sense, capture and understand information to create valuable insights and recommendations for acting on complex business problems.

Cognitively enabled operational systems can proactively identify assets, processes, and people risk, and deliver recommendations for operations set points and intelligent interventions in real-time or near real-time. This is accomplished by processing huge volumes of data from cross-functional operations. It empowers organizations to avoid expensive downtime, ensure workforce and workplace safety, and reduce emissions.

A few example use cases will help illustrate some of the key benefits of embedding cognitive intelligence into plant operations:

Asset Integrity and Predictive Maintenance: Cognitive operations can detect assets with a high probability of failure and suggest optimum asset rehabilitation strategies. This is done by analyzing data from various data sources like operation planning system, asset maintenance system and current asset status.

Enable Remote Operations Center: A cognitive operations center provides an integrated decision workspace and delivers the capability for operators to assess contextual data, such as real-time status, location, and the impact of local events from all monitored assets. It also gives workers the ability to evaluate the impact of multiple response scenarios, especially in difficult geographical terrains to improve safety and efficiency based on incoming data.

Intelligent Pipeline Management: Cognitive operations predict potential pipe bursts and detect pipe leakages with high location accuracy, thereby enabling operations teams to evaluate threats and plan responses. It also improves pipeline operations through optimal pressure valve setpoint recommendations.

GHG Emissions Monitoring and Reductions: Cognitive operations sense and predict potential emission levels by applying machine vision-based EDGE AI, like thermal imaging of storage tanks, to recognize the levels of different chemical elements stored in the tank. EDGE AI can evaluate the impact of those elements on the health and structural integrity of the tank. Additionally, cognitive operations can provide various optimization strategies to improve the energy efficiency of process and operation facilities, like fleet optimization, by designing optimal vehicle routes.

These use cases are just a few examples of the many ways cognitively enabled systems help energy companies become operational resilient, achieve operational agility, improve operational efficiency, and harness the full value of their IoT and organization data.

TCS Intelligent Urban Exchange (IUX) is a purpose-built Data & Analytics Platform for the energy industry, which brings centralized AI activation functions to enable organizations build their cognitive operations. IUX offers pre-built cognitive solutions around Intelligent Pipeline, City Command Center, Intelligent Energy, Intelligent Transport and Workplace Resilience, which help energy companies and cities with faster deployment, time-to-value, and reduced TCO. Learn more here.

Jay Gupta

With over sixteen years of experience in the product development and management primarily for Telecom and Energy industry Jay is involved in IoT, cloud, remote monitoring, M2M Communication, data analytics & AI at TCS Digital Software and Solutions.

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