By Steven Mauss, CEO and President at Knowledge Relay, Inc.
The U.S. energy sector faces a rapidly evolving landscape. While advancements in renewable energy sources such as nuclear power offer promise for a cleaner future, the current infrastructure presents significant challenges.
Power generation has historically enjoyed a fairly structured and controlled environment. Fossil fuel plants, for example, operate within well-defined parameters, allowing for precise control over energy output. This predictability has facilitated the implementation of robust Project Control methodologies, including Earned Value Management (EVM) and critical path analysis. These methodologies enable power companies to meticulously track project progress, identify potential risks and delays, and make informed decisions about resource allocation.
However, the transmission infrastructure responsible for transporting electricity from generation sources to consumers has not kept pace. The vast network of power lines, substations, and transformers stretches across diverse landscapes and includes limiting factors from weather and geography to equipment aging and regulatory constraints often beyond the power company’s control. Add to this the increasing availability of smart meters and sensors, and both the volume and complexity of the data itself makes it much more difficult to apply traditional project controls methods to transmission and effectively leverage transmission data for analysis.
Worse yet, the fragmented nature of the US transmission system—with power company ownership and operation dispersed among various entities—hinders the sharing of data and collaboration across systems, making it incredibly challenging to obtain a comprehensive view of the system’s performance to identify areas of risk and areas for improvement.
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This lack of adequate Project Controls over U.S. transmission infrastructure inevitably creates problems for decision-makers and limits the amount of power that can be delivered to consumers. Further, inadequate data analysis hinders the ability to predict future demand and so adequately plan for upgrades and investments, potentially leading to outages, price spikes, and reduced grid reliability. And with climate change ever on our minds, harnessing the power of sensors becomes even more important.
To address these growing costs and risk of electrical transmission, power companies must prioritize advanced data processing, integration of robust Project Controls, concise metrics, artificial intelligence, and advanced data analysis.
At Knowledge Relay, we recommend and provide:
- Parallelized data processing—spreading the workload among multiple servers (cloud-based or internal) to manage the increasing volumes of data from smart meters, sensors, and AI.
- Advanced Project Controls—implementing industry-recognized frameworks like EVM and what-if analysis to enable utility companies to better track project progress, identify risks, and make informed decisions about resource allocation.
- Data Alignment—ensuring that project completion status matches A/R and A/P.
- Application of AI from robust historical datasets—applying a smart data infrastructure for key insights into transmission system performance that enable proactive maintenance and optimization.
- Collaboration and data sharing—fostering collaboration among stakeholders and facilitating data sharing across the fragmented transmission system, so critical for a comprehensive view of grid performance and planning.