QUALTECH SYSTEMS, INC. — Department of Energy SBIR Phase I: 15b

Description

Offshore wind turbines have the inherent drawbacks of being remotely located and subject to harsh weather conditions such as storms, snow and sleet, that subject them to operational stresses. With the growing demand for wind energy in the US, it is imperative to maximize the operational efficiencies of the wind turbines and minimize the Levelised Cost Of Energy (LCOE). Qualtech Systems, Inc. (QSI) proposes to leverage its expertise in Integrated Diagnostics and Prognostics and Data-driven techniques to develop a hardware and software based Remote Diagnostic, Prognostic and Decision Support solution for Offshore Wind Turbines that reduces overall Operations and Maintenance (O&M) costs due to unplanned downtime and increases operational availability. The solution will employ MBSE (Model Based System Engineering) techniques to reason across these operating characteristics to provide a system-wide picture of the overall system health. Additionally, real-time monitoring engines will provide actionable maintenance alerts and provide advanced warnings of impending failure so that the sustainment team can schedule a maintenance before the component fails. It is anticipated that the proposed solution will reduce the Unscheduled Maintenance events for offshore wind turbine by up to 50%, thereby reducing the O&M costs by up to 20%, ultimately reducing the levelised cost of energy (LCOE) by up to 5%. During Phase I, QSI will focus on the following tasks: 1. Build a suitable cause-effect model comprised of wind-turbine components such as gearboxes, generators, blades, electric system, rotor, pitch systems, and yaw systems. 2. Investigate current maintenance procedures to gather component failure-frequency and downtime-per- failure metrics of wind-turbine components to determine MTTF (Mean-Time-to-Failure) and MTTR (Mean-Time-to-Repair) values in the cause-effect model. 3. Investigate interfaces with SCADA system. 4. Investigate Machine Learning techniques to detect anomalies in the standard operating characteristics. Key Advantages to QSI’s Remote Diagnostic/Prognostic Solution are: Health Monitoring and Maintenance Dashboard provides real-time status of the wind-plant to the onshore maintenance crew, with customized alerts; Minimize on-site technician visits with reduced unplanned/unscheduled maintenance and fewer onsite maintenance operations; Comprehensive Workflow management allows for technicians with various skill levels and supervisors to manage work-orders; Predictive maintenance methodologies can predict premature component failures and provides advanced warnings so that they can be fixed via Scheduled maintenance; Diagnose Before Dispatch – The solution will generate an optimized troubleshooting strategy based on online health, along with anticipated service parts and necessary resources, the right technician skillset required, materials, knowledge and tools so that the problem can be corrected during the maintenance visits. At the wind-turbine site, the solution will guide the maintenance crew with step-by-step Guided Troubleshooting instructions to ensure that the problem is diagnosed, fixed and service restored in shortest possible time.Suppliers of offshore and land based wind turbines such as GE, Siemens, Vestas. Our solution, with the potential to decrease O&M costs, could help these suppliers competitively market their products. Related sectors as well as to contractors/suppliers who are involved with the development and maintenance of oil and natural gas offshore platforms. Smart grids, building and facility controls (HVAC, etc.), and various Industrial Control systems (ICS) could become the customers of developed solution.