Case Study – REDSTS automated data metering
Case Study - PA-AMR (Automated Meter Reading and Data Collection)
1.0 REDSTS Metering Data Storage, Visualisation and Analytics Platform and PA-AMR Head-end
PA Energy provides three key elements of meter data management; this includes the on-site data collection M2M devices (meters/loggers), PA-AMR head-end (raw meter data collector, storage and distribution) and the REDSTS cloud-based energy data to enable the automated data collection of renewable on-site energy generation to be processed, stored, visualised with custom analytic reports in Java Script. Data can be visualised and reported to clients on a daily basis.
The data is automatically collected from national and international located buildings or site located energy, water metering and environmental devices with remote data capabilities. The Platforms are Cloud based.
1.1 The PA-AMR Head End SaaS platform
PA-AMR is provided as a subscription based service. The Platform is based on .Net platform. The benefit of PA-AMR is it allows consultants, 3rd party service providers and end-users the means to have a central data repository for their device data. At any stage the client can decide to use any brand or type of device without the worry of secure data store and data import/export. This is an internet delivered service designed to receive, store and distribute time stamped readings from remote data logging devices.
Data from field devices is collected automatically from building meters and other local data devices, these can be PA-Energy/PA-Water devices or 3rd party devices and data sources e.g. FTP servers. PA-AMR is agnostic of meter data source and therefore non-proprietary in it’s operation.
Meters include Electricity, Water, Gas, Heat (LTHW/HWS/DHWS), Coolth (CHW), Photo Voltaic (PV), Combined Heat and Power (CHP), Solar Thermal, Biomass and Wind Turbines. Data can also be sourced from environmental sensors upon request.
Data is received directly from meters, wireless data loggers or secure FTP (SFTP) servers. Once data arrives at the PA-AMR Head-End, it is unpacked and scanned for errors prior to ingesting. The data is then stored and distributed to 3rd party servers such as AM&T or REDSTS and client’s 3rd party accounting systems. The system automatically completes processing of datasets and flags up any errors for the administrator. Data is then stored securely for a minimum of 5 years and distributed to 3rd parties as required by the client.
PA-AMR is agnostic of brand and model of meter or data device.
PA-AMR is a scalable platform that has been developed by some of the best in the world engineers in meter data management and head-end systems.
1.2 The REDSTS web portal
REDSTS powered by Fusion Data Management FDM provides a web portal data collector, visualisation and analytics reporting tool showing the performance of the building energy, water and renewables data. FDM and PA-AMR (store and forward) data is gathered automatically from devices or 3rd party data servers including the PA-AMR Head-End.
1.3 FDM Fusion Data Manager
Fusion Data Manager [FDM] is a cloud based platform that integrates IoT, and edge data log devices to business models, processes and documentation.
It provides capabilities to receive or pull data from any source, perform custom transformations and optimised database or cloud storage of the results.
Administrators can create a business object model to represent any physical or conceptual ‘things’ for their business or customers. These can be linked into hierarchies with one another, and to underlying data streams for analysis, visualisation and reporting. The FDM platform is based on REST API services, allowing external processes to utilise the functionality as required.
Fusion Data Manager is an IOT platform that is based on the concept that all objects are entities. The application is hosted in AWS.
The system comprises three key elements.
a. Fusion Data Hub
Manages data from various sources. e.g. IOT, BMS or static data. The hub manages the data stores and handles processes for integration of data to cloud, disks or corporate networks.
Multiple processes can be run and 3rd parties can build their own independent systems.
b. Enterprise Load Balancer Firewall Rules.
The application in terms of criticality can only be managed from a unique IP address for mission critical functions such as key changes e.g deleting databases, changing the database configuration or superuser changes. Traffic is automatically distributed across instances of the software to manage performance as configured.
c. Enterprise Load Balancer SSL Management Firewall Rules.
FDM is a web based app using REST API’s. It manages data in / out and executes code to generate visualisations.
The system can get data and map models and has the capability of integration with other platforms and processes e.g. Degree Days, Regional Weather data etc.
1.3 Amazon Web Service AWS
Amazon AWS is flexible for data extracts and gives the ability to integrate and support communications with FTP servers from multiple computers, messaging servers and processing extracts. It has many extra services which some developers may use.
Oracle Java is cross platform capable and application resources are put into an Apache Tomcat application server (Opensource).
Amazon DNS is used for optimum availability and performance.
SSL certificates are essential given new European GDPR rules.
Amazon also allows better load balancing and has IP address look up and allows us to deploy a scalable server architecture along with database management and secure file storage.
2.0 On-site Metering Services
Each building energy use or renewable generator is to be meter monitored for energy output (electricity or thermal energy) and in the case of CHP, input gas consumption is to be metered. The automated data collection and data communications devices will transmit meter data daily to the REDSTS energy data server or PA-AMR. Meters have to provide data bus (e.g. M-Bus or MODBUS) or for some applications pulse output (water and gas typically) to enable the remote data gathering. In the case of CHP gas metering is required.
2.1 Datasets and Report Services
The REDSTS portal delivers a combination of energy generation visualisations and analytic reports created utilising Oracle Java Script including:
1. Electricity and thermal generation by site and generation type showing daily, week and month trends and Data Explorer date range selection of single and multiple meters. This will give the user an option for consumption or readings.
2. Gas demand used by the boilers, processes and combined heat and power (CHP) units
3. Automated data collection system health notifications to the service provider.
4. Monthly overview and weekly condition monitoring report in accordance to client KPI's
5. Automated emailed meter read information
6. Raw meter reading time stamped data in Excel format
Typical REDSTS Energy Report – example hospital Monthly
Benefits for Building Managers
REDSTS allows building, site and environmental managers monitoring of the status/condition of buildings and renewables, generation statistics and is able to help identify building operational and plant maintenance issues early on. This ensures high on-site renewable availability factors to achieve the return on investment and to contribute substantially towards attaining environmental objectives which include reduce carbon footprint and reduction in station energy costs.
2.2 REDSTS API’s
Data can be collected from or published by any internet connected source via standard data transfer mechanisms.
REDSTS integrates with all established aM&T, data analysis and billing systems. These include TEAM, Systems-link, eSight and Optima.
Working with your existing systems
Whether using established aM&T or billing systems, or integrating with 3rd party corporate systems, integration is tailored for data export solution to fit via secure FTP server including live data, data export or bespoke reports that make the job simpler.
3. Data Storage
Once received the original data will be stored in Amazon S3 or other suitable archive for the period of the contract and minimally 5 years and any subsequent continuation agreement and made available in .csv format at the termination of agreement.
4. Transformation and Visualisation
A copy of the data will pass through a data transformation engine (Fuze DTE) to validate and prepare the data before being loaded into a relational database where calculations specified in the Definition of Service document will be performed on demand and automatically at user-login.
Data is viewed through the secure REDSTS portal including a range of standard graphical and tabular energy and water data. Custom visualisations can also be specified.
Standard reports are also provided to the user including performance and benchmarking and missing meter read reports.
Credits: FDM is a product trade name belonging to Fusion 242
Disclaimer: Please note that PA-Energy REDSTS continuously develops its systems and services and therefore this document is being amended progressively. Please discuss your critical development requirements with PA-Energy or REDSTS to ensure that you have the most up to date information from REDSTS on it’s systems and services