Sustainability Targeting

SEAP Sustainability Targeting (SST)

Analyze, forecast, detect, and report on the effectiveness of changes in equipment and O&M strategies in terms of sustainability, service reliability, and workforce spend

Sustainability Targeting

The SEAP Sustainability Targeting (SST) Solution provides users with advanced capabilities to forecast, assess, and compare energy usage, CO2 emissions, and financial value from installed equipment or modified O&M methods.

SST enables the targeting of sustainability projects or actions based on actual measured and analyzed performance.

SST continuously monitors sustainability, service capability & reliability, and financial performance. Upon deviation from Key Performance Indicators SST sends out task alerts, on your terms, to investigate and take corrective action.

IPMVP and Advanced Analytics

SEAP's Sustainability Targeting (SST) solution automates process management capabilities, facilitating the efficient creation of precise and tailored sustainability monitoring and analysis of energy conservation and renewable supply efforts.

The intuitive 'what if' scenario analysis further empowers stakeholders to project the value of future investments in energy efficiency or renewable generation, allowing for strategic planning and prioritization of conservation efforts.

We've integrated IPMVP methods with our Workforce Management Solution to optimally direct and measure spending in terms of workforce time, monitoring equipment, and full installation cost for this sustainability targeted effort. This feedback loop of total spend to benefit, in comparison to having done nothing, is key to learned optimal decision making.

AI/ML based Predictive Maintenance for reduced downtime and better asset performance

SST develops and tracks weather normalized key performance indicators based on real time monitoring and analyzes when these metrics are falling too far off of their expected KPI goals.

These KPI goals include such items as sustainability, service capability & reliability, and achievable financial value given maintenance spend. This enables economical value based maintenance scheduling decisions.

Reliability based anomaly detection via our Fault Detection and Diagnostics (FDD) is based on a learned combined set of temporal based frequencies and limit based heuristics that enable otherwise unrecognizable anomalies. SST is integrated with FDD to provide one integrated visibility and alerting of asset performance for decision making.

Digital Sensor Integration and Real-Time Energy Measurement

The integration of disparate IIoT and legacy system sensor data and information stands as a pillar of SST's capabilities, enabling the conversion of complex datasets into actionable energy usage information.

The platform's ability to process real-time data conversions and create virtual point tag energy measurements (e.g. multi-electrical current and voltage sensor readings converted into totalized kWh energy) caters to the creation of a variety of energy management measurements from existing and new disparate data sources. This helps ensure that every Joule (kWh) is accounted for accurately, thereby enhancing the accuracy of energy-saving or renewable generation activities and providing a solid low cost monitoring foundation for verification, validation, and projection of sustainability efforts.

SST's continuous monitoring of the efficiency and renewable supply KPI expectation from installed assets or modified O&M strategy can automatically initiate tasks, on your terms, to review identified KPI anomalies in expected weather normalized sustainability performance over the life of the implementation.

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