Energy and Utilities

Infrastructure Optimization and New Value Added Services

Condition
Monitoring

Connect existing and new assets, integrate existing and new sensors, monitor all parameters, easily set triggers to identify and report significant changes and faults.

Prescriptive
Maintenance

Monitor the condition of all your assets using sensors. Capture sensor data in real-time and use machine learning models to predict when your assets will require maintenance to prevent failures and downtime.

Asset
Tracking

Integrate all your asset information under one umbrella and track your plant materials using geo-fencing to have better control and to detect fleet and asset location anomalies.

Plant
Optimization

Connect your plant DCS systems and feed DCS data to analytics applications to build machine learning models to optimize operations.

New
Services

Implement new services and business models such as managed electric charging stations, energy management and home automation.

Smart Utilities with IoT and Edge Computing

CloudPlugs solutions for smart energy and utility companies delivers open computing capabilities where it matters most, on the machines, on the plants and at the edge.

The results are an intelligent, optimized infrastructure with:

Increased Responsiveness

Better data turns real-time insights into faster actions, fast response to service requests and better user experiences.

Increased
Reliability

All the processing elements for proper operations and optimization are on site and connectivity to headquarters or the cloud is not critical.

Reduced Operations Costs

There is no need for high-capacity cloud servers and high-volume data transfer and network capabilities. Only processed and key information is sent to headquarters.

Solution Examples

Power Plant
Asset Integration

To optimize thermal and hydro plant operations, electrical utilities need to connect and integrate their critical assets including the DCS and any new generation sensors across the plant infrastructure. This solution uses edge computing to connect and process plant data, send it to a data lake with analytics and machine learning to build plant optimization models.

Solution

  1. Edge One™ deployed on high availability server extracts real-time and historical data from OSISoft Pi DCS and from a LoRa network server.
  2. LorA sensors are deployed to track mobile assets.
  3. DCS data is processed and LoRa data is decoded before it is sent CloudPlugs IoT and to the data lake.
  4. Data is processed in the data lake and operational models are deployed on Edge One to automate and optimize the DCS operation.
  5. User dashboard that delivers real-time data and analytics KPI’s for the plant operators.

Results

  1. New, full visibility on the operation of the plant’s more important assets.
  2. 15% improvement in asset management through better asset location control.
  3. Consolidation of historian data into data lake and the use of advanced analytics helped improve operations processes by over 10%.

Prescriptive Maintenance for
Plant Motors

Scheduled maintenance is a highly inefficient process resulting in guessing when to do it and in potentially unnecessary downtime. This solution uses advanced analytics to implement prescriptive maintenance services for all the motors inside a power plant to guarantee their availability and help in the efficient management of critical assets.

Solution

  1. Edge Ones™ deployed on virtual machines running on a high availability server collects and ingests high speed temperature, vibration, and other critical data from the motors data loggers.
  2. Data is processed and delivered to a motor analytics engine through CloudPlugs IoT at rates close to 3GB/hour.
  3. The analytics engine processes the data and delivers KPI’s and recommendations for maintenance and service of the motors.
  4. User dashboard presents the analytics engine results and recommendations.

Results

  1. New insights into the operation of a plant’s most critical components through the ability to collect and ingest large volumes of data quickly and to perform advanced analysis on the data.
  2. The predictive maintenance engine helps detect defects on a motor rotor that require attention, bearing failures due to lack of lubrication and to optimize the life of turbine cooling systems.
  3. The solution improved visibility into potential problems by 25%.

Fault Prevention, Damage Mitigation and Asset Life Management

Managing the lifecycle of plant assets is a complex and highly inaccurate task. This solution is used to optimize the process of analysis of cumulative fatigue damage in critical components inside several plants to build smart, predictive maintenance models. Data is obtained from the plant’s DCS and existing and new plant instrumentation and sensor.

Solution

  1. Edge One™ deployed on high availability servers in the plants connect to OSISoft PI DCS to collect and process real-time sensor data.
  2. Data is processed and sent to a damage and fatigue mitigation analytics and predictive maintenance platform.
  3. Analytics results are fed back to Edge One and CloudPlugs IoT.
  4. User dashboard built with the Control Designer presents KPI’s, results and recommendations from the analytics engine.

Results

  1. New visibility into critical asset aging information.
  2. Reduced need for inaccurate manual inspections by 20%.
  3. Uncovered potential issues that required immediate attention in several assets.
  4. New advanced infrastructure for automated asset life management and damage mitigation.

Energy Management Services

Energy is the biggest ticket item in the operation of buildings and homes. This project delivers a modern solution to implement a managed, energy efficient infrastructure for electrical utility consumer and small and medium sized customers as well as the ability handle power interruptions due to load shedding. The solution integrates solar panels, Tesla batteries and uses energy disaggregation to report estimated energy consumption per appliance.

Solution

  1. Edge Ones™ deployed on gateway collects data from solar panel inverters, power meters, battery systems, a charging station and the energy disaggregation system.
  2. Data is processed by algorithms on an Edge One custom container to calculate production, consumption and storage and it is delivered to CloudPlugs IoT.
  3. A dashboard built with the Control Designer allows installers to perform 360° testing of the system before delivery.
  4. User dashboards allows the utility customers to see daily, weekly, monthly and yearly reports on energy produced by the system, energy used and available energy stored in the batteries.

Results

  1. New service revenue generation solution.
  2. An energy efficient solution that is easily to deploy and reduces cost of installation and testing by 60%.
  3. A green, efficient and cost effective way to deliver energy and that allows customers to have full visibility on the condition and performance of their energy generation systems.

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