Joshua Mellen, Product Manager, Dominion Energy

Bhawuk Luthra, Engineering Consultant, Dominion Energy

Dominion Energy is facing considerable growth across its operating territory – much of it stemming from non-conforming load produced by technology and the EV sector. The need for improved forecasting is becoming a mandatory part of our operations and company decision making in outage planning. In this session, we will discuss strategies and tactics around long-term load forecasts (LTLF) for area, substation and transformer-level forecasting, including the development of an operating framework utilizing Seeq. We will also explore real world case studies on managing and reprioritizing outages, thus enhancing system reliability and operational efficiency.

David Tiffany, Engineer Performance Monitoring & Diagnostics, TVA

Yehiel Viner, VP Maintenance & Technology, Ormat

Yackov Yehoshua, Director Performance Engineering, Ormat

Rachel Huberman, Performance Engineer Lead, Ormat

Ormat faced challenges with manual generation forecasting, but implementing a Seeq-enabled workflow with sensor and external weather data now produces robust day-ahead forecasts, empowering the team to optimize operations and energy trading strategies.

Jordan Rutledge, Data Analyst, Deriva Energy

Bat curtailment for wind turbines is required in order to be compliant with the guidelines of the U.S. Fish and Wildlife Service. Using Seeq Data Lab, in collaboration with a data science team, this project utilizes python code in order to create capsules for active bat curtailment and missed bat curtailment. The calculations for these capsules at turbine level are then scaled for the entire wind fleet in order to produce a scorecard metric for each wind site. The scorecard metric is achieved using an OData export of all capsules to Power BI. This project gives visibility to the accuracy of bat curtailment at each wind site and allows site engineers to identify events of missed bat curtailment.

Fabian Schlieck, Performance Engineer, Uniper

The German power industry is experiencing significant changes and challenges, with a focus on ensuring a reliable energy supply. Uniper is leveraging data science, particularly using Seeq, to enhance the reliability and efficiency of its operations. Seeq enables rapid, in-depth analysis of operational data to identify and address incidents like boiler tube leaks, compare actual performance against predictions, and make adjustments as necessary. It also aids in analyzing the performance impact of hardware changes and utilizes weather forecasts to predict future asset performance. This approach improves operational decision-making and supports Uniper’s digital transformation and the strategic management of its power generation assets.

Yanging Li, Lead Condition Monitoring Engineer, RWE Generation UK

RWE’s digitalization team aims to maximize existing asset value for a business edge. A key project, Value-Based Maintenance (VBM), uses advanced algorithms to predict failures and optimize maintenance plans based on real-time risk assessment. To achieve this, a cross-functional team built MARA (Maintenance & Asset Reliability Assistant) – a digital toolset with machine learning models that assess component health and predict failures. The presentation will showcase how MARA uses bespoke Seeq models to create health scores and how these scores are integrated into MARA for practical use. Real-world examples will demonstrate the value of these models in improving equipment reliability and availability.

Madeline Jasper, Market Operations Analyst, RWE

RWE’s wind farm assets on the power grid must not only operate in accordance with internal standards but also those of the grid operators and regulators. In this session, we will discuss how RWE monitors their assets and compares asset performance to the Grid Operators Generation Resource Energy Deployment Performance (GREDP) scores. Learn how Seeq has streamlined the process, enabling easy identify of intervals of poor GREDP score resulting in faster mitigation of root causes.

Speaker: Steve Brehmer, Principal Engineer, DTE