GRIDview Cloud Historian

by | Sep 17, 2018

Powerful Enterprise Class Historian added to GRIDview.

GRIDview as a backend for GRIDlink now has a powerful new feature that directs any data collected locally to an AWS Enterprise Class Historian hosted on GRIDview or a customer’s AWS account anywhere in the world.

GRIDview logs a limited amount of data for a few weeks as an operational tool to review Load Shed, Event Participation and Trouble Shooting.  The Historian extends storage time from a few months to years and vastly increases the amount of data and the speed in which it is processed to the database. In addition it provides a fast and efficient data retrieval and analysis using open source software.

Available now on all new GRIDlinks and as always can be updated to the many that are operational worldwide.

Custom real time analytics can be achieved such as, meter data, event participation, load shed, base line calculations and more using Amazon Kinesis.

Third party systems can access any data logged by GRIDlink through a restful API thereby increasing the access of information without the headaches of field device integration.

Any data collected over the Local Area Network can be sent to the Historian

Overview

Data Logging Overview

Data is automatically buffered locally if connection is lost

GRIDlink(s) are assigned to an individual Historian table

GRIDlink(s) are identified by a unique serial number

Data is indexed by timestamp

Tables have assigned throughput capacity

Table capacities have auto-scaling enabled

Historian tables have no practical size limit

Historian tables are replicated within an AWS region

Up to 256 tables are initially allowed within an AWS region

Data Analytics Overview

  • GRIDlink data accessible by HTTP RESTful API
  • GRIDlink data is queried by
  1. Table name
  2. serial number(s)
  3. starting/ending timestamps
  • A data API user can optionally specify
  1. Re-sampling rule to align data on a specific time boundary
  2. Missing data rules and fill limits
  3. 19 different computational operations – row or column-wise
  4. SQL statement
  • The API user can specify for Analytics such as baseline calculation
  1. Table name
  2. Serial number(s)
  3. Missing data rules and limits
  4. Variable look back
  5. SQL statement