ServusNet process enormous amounts of data into decisions.

HARVESTING ACTIONABLE INSIGHTS FROM MACHINE,

OPERATIONS, METEOROLOGICAL AND MARKET DATA

ASSET PERFORMANCE AND AVAILABILITY OPTIMISATION

DESCRIPTIVE AND DIAGNOSTIC ANALYTICS
Asset Performance
Is my Lost Production due to Poor Turbine Performance?
Which Turbines are Least Efficient?
How Does Wind Direction Affect Production?
Reliability and Availability
Which are my Least Reliable Turbines?
Do I have a Serial Defect in the Fleet?
Which Components Drive Down Availability?
Yield Improvement
Should I Implement Sector Management?
Will Blade Upgrades Significantly Improve Production?
What’s the Benefit of Enhanced Power Curve Characteristics?
Operational Efficiency
What are Highest Priority Tasks for my Ops Team?
Are my Warranty Services Effective?
How do I Adopt a More Proactive Maintenance Strategy?
How do Spares & Maintenance Impact Downtime?

GRID SCHEDULING AND ENERGY MARKET PARTICIPATION

MODELLING AND PREDICTION
Grid Scheduling
More Accurate Commits to System Operator
Reduced Exposure to Balancing Costs
Revenue Driven Maintenance
Fine tune Maintenance Planning by Turbine
Minimise Revenue Impact
Energy Trading
Increased Day-Ahead and Intra-Day Market Participation
Trade Higher Proportion of Output
Generation Portfolio Balancing
Schedule and Trade Mixed Fossil/ Renewables Portfolio
Optimise Fuel Mix to Reduce Costs

ServusNet Software Solutions

Improving Asset Performance, Availability and Predictability
Wind Operations Analytics Platform

Browser-based portal delivering comprehensive analytics:

  • Energy Production
  • Power Curve Characterisation
  • Turbine Efficiency
  • Performance & Site Wind Regime
  • Operational & Contractual Availability
  • Outage & Reliability Profiling
  • Alarm Profiling
  • Physical & Electrical Parameter Trending

More
Wind Power Forecasting

  • Highly Accurate Weather Forecasts Combined with Detailed Turbine and Wind Farm Models
  • Ongoing Calibration Using Continuous or Batch Turbine Data
  • Cloud-Based Solution for Efficient Deployment and Tailoring
  • Flexible Data Interfaces and Forecast Delivery Mechanisms
  • Multilevel Modelling Captures both Site-Wide and Turbine-Specific Dynamics
  • Advanced Machine Learning Algorithms Continuously Adapt to New Data
  • Extracts Fault-Free Behaviour from Historical Data

More
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Wind Operations Analytics Platform

Data Sheet
Operations

Site Performance Analysis

Complex Availability Calculations

End of Warranty Assessment

Maintenance

Identifying Performance and Outage Drivers

Isolating Serial Defects, Adverse Trends and Anomalies

Operations Team Task Prioritization

Data Management

Large Volumes and Inconsistent Quality

Multiple Data Types (Statistics, Alarms, BOP) and Conflicting Definitions

Limited Analytics Capability

Energy Production, and other User-Specific KPIs, by Turbine and Wind Farm

Performance Patterns and Site Wind Regime

Outage and Reliability by Subsystem and Component

Work Order and and Spares Consumption Integration

Data Integrity Analysis Tools

Site and Turbine Power Curve Characterisation

Operational and Contractual Availability

Alarm Correlation and Trending

Automated Regulatory Reporting

Extensive Range of Correlation and Anomaly Detection Algorithms

Quick to Deploy, Zero On-Site Hardware
Utilizes Existing SCADA, BOP & Web Services Data Sources
Role Based Access via Browser Portal
Enhanced Production

Increased Asset Performance

Higher Uptime

Quantified Revenue-Impacting Incidents

Prioritized Potential Critical Issues

Analysis and Reporting Overhead Eliminated

Operating Efficiency

Informed Decision-Making

Targeted Corrective Actions

More Effective Evaluation of Upgrade Investments

Automated Monthly and Regulatory Reporting

Better Utilization of Precious Maintenance Team Resources

Wind Power Forecasting

Data Sheet
Production Scheduling

More Accurate Commits to System Operator

Reduced Exposure to Balancing Costs

Energy Trading

Day-Ahead and Intra-Day Market Participation

Trade Higher Proportion of Output

Portfolio Balancing

Scheduling and Trading Mixed Fossil/ Renewables Portfolio

Optimising Fuel Mix to Reduce Costs

Maintenance Planning

Targeted Planning, by Turbine, to Minimize Revenue Impact

Features

Highly Accurate Weather Forecasts Combined with Detailed Turbine and Wind Farm Models

Cloud-Based Solution for Efficient Deployment and Tailoring

Flexible Data Interfaces and Forecast Delivery Mechanisms

Technology

Multilevel Modelling Captures both Site-Wide and Turbine-Specific Dynamics

Advanced Machine Learning Algorithms Continuously Adapt to New Data

Auto-Correction Using Continuous or Batch Turbine Data

Customised Delivery Schedule, Forecast Horizon and Forecast Granularity

Automated Delivery via Online Portal, Web Service, Email or FTP

Forecasts at Turbine, Wind Farm and/or Portfolio Level

Efficient Algorithm Enables Fast Setup and Continuous Calibration

Performance Tracking with Regular Accuracy Reports

Utilize Existing Weather Forecast Service Provider or Rely on one of Our Preferred Partners

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Investigative Analytics

Project-Specific Diagnostics and Investment-Driven Modelling
Post-Commissioning Verification
Verification of Production, Availability & Wind Regime Targets

In-Warranty Health Check
Analysis of Performance Against Key Performance Indicators

End-of-Warranty Assessment
Evaluation of Performance, Availability & Serial Defect Trends

Yield Improvement Investments

Estimation of Return on Yield Enhancement Investments

Data-Driven Due Diligence
Owner or Investor Transactions

Asset Health Check

Production and Availability Anomalies

Component Failure Profiles

Event Timelines and Clusters

Power Curve Anomalies

Yaw Error Distributions

Blade Condition

Fleet Behaviour Characterisation

Turbine and Site Performance Dynamics

Wind Regime Characterisation

High Wind Speed Behaviour

Micro-siting and Topographic Effects

Curtailment Rate and Curtailed Power

Decision Support

Predictive Maintenance Strategies

Performance Upgrade Investments

Sector Management Implementation

Reliability and Corrective Actions

About ServusNet

 

ServusNet was founded by a team of experienced software engineers and data scientists who understood that the energy sector was experiencing the data deluge that had already occurred in other industries.

In particular, wind turbine fleets were, and still are, generating large volumes of data, yet isolating the critical performance and reliability drivers remains a real challenge.

We created software tools and solutions to unlock the value in this data to help manage distributed energy assets more effectively and provide insights to guide fleet investment decisions.

Having successfully developed and deployed our Wind Operations Intelligence platform, we integrated Wind Power Forecasting capability built on state-of-the-art technology developed jointly with leading universities. This predictive analytics functionality extends the solution application space to support grid integration and energy market participation.

Our software solutions are complemented by an extensive range of analytics services designed to investigate specific client issues. These projects may employ diagnostic analysis and we use modelling and simulation techniques to help understand the business cases around energy scheduling and complex microgrid behaviour.

Our Team

Des Farren
CEO
Des has operated in a variety of senior technical and customer-facing roles, both in the UK and Ireland, with technology companies including Motorola and Digital Equipment Corporation. This broad experience, supporting global customers across a number of industry sectors, has proved invaluable in the multidisciplinary field of energy analytics.

Des has a DipEE from Dublin Institute of Technology, a BSc(Eng) from Trinity College Dublin and a Ph.D. from Brunel University, London.

Shane Butler
Lead Data Scientist
As an academic researcher, Shane collaborated with multinational industrial partners to develop and license advanced machine learning algorithms for condition monitoring and remaining useful life estimation of critical equipment. He now applies his expertise to the spectrum of data analytics and forecasting problems within the wind industry.

Shane has a B.Eng and Ph.D. in Machine Condition Monitoring and Failure Prognostics, both from Maynooth University, Ireland.

Simon Martin
Engineering Operations
Simon oversees our entire in-house and customer-facing data analytics framework. Through his Eonvia IT services solutions, he brings extensive experience at technical and managerial level in the computer, networking and telecoms sectors, in both hardware and software engineering. He’s qualified to Black Belt level in Digital Six Sigma and is a Chartered Engineer.

Simon holds a joint B.Eng(Hons) in Computer Science and Electronics from the University of Edinburgh, Scotland.

Tim Crowley
CFO & Director, Business Dev.
Tim has held a range of business development and finance positions in technology companies as well as a variety of roles as senior manager with PwC. He co-founded, helped grow and successfully exited a number of technology startups and has broad international experience across Europe and India.

Tim holds a B.Comm. in Finance & Economics from University College Cork, an M.Sc. in Sustainable Energy Finance from Dublin City University and is an Associate Member of the Institute of Chartered Accountants in England and Wales.

Contact Us

ServusNet Informatics Ltd.,
National Software Centre,
Mahon,
Cork,
T12 K5CY
Republic of Ireland.

Phone:   +353 21 7304649
Email:   info@servusnet.com