WHY Kx FOR UTILITIES?
Powered by the world’s fastest time-series database, kdb+, the Kx platform handles millions of events and measurements per second with nanosecond precision, whilst simultaneously managing gigabytes to petabytes of historical data with ease. Designed to radically improve energy, utility, and industrial IoT applications and systems our single-stack processing and analytics platform for operations and transaction data, Kx for Sensors:
• handles massive numbers of sensors, high frequency, and low latency workloads
• supports distributed energy resources, AMI, SCADA, synchrophasors, smart home IoT
• applies analysis and ML tools to current and historical data
PERFORMANCE - FAST AND PROVEN TECHNOLOGYIdeally suited for addressing the performance and scalability challenges of high-volume data ingestion, processing, retrieval, analytics, and machine learning our platform can validate and estimate sensor and smart meter data at millions of readings per second. Kx for Sensors can also aggregate billions of measurement records in seconds and store and analyze trillions of records and diverse data sources. Customers have benefited from:
• 10x to 500x improved performance
• 90% less infrastructure
• lower total operating costs with improved scalability
• reduced time to market through our proven big data technology and expertise
ADVANCED ANALYTICS AND BITEMPORAL MODELLINGValidation-Estimation-and-Editing: Many companies today are using less than 10% of the sensor data they collect and are not able to keep up with the validation, estimation and editing (VEE) processes needed to support data analytics systems because of the high volume and velocity of data. To combat VEE system overload, Kx for Sensors has been developed as an integrated VEE and analytics solution for ingesting, validating, estimating and analyzing massive amounts of streaming, real-time and historical data from sensors, devices, and other data sources.
Bitemporal Modeling: Kx for Sensors also enables bitemporal modelling of sensor data and attributes with nanosecond precision enabling you to easily and quickly navigate through time:
• providing queries that relate to what was known to the system at a particular point in time
• enabling continuous analytics avoiding the need to pause
• supporting machine learning and predictive models
• ensuring forensic auditability and traceability of updates to data
CHANGING BUSINESS MODELS – NEW GRID MANAGEMENT CHALLENGESTraditional large-scale production of energy relied on long-distance transmission and one-way supply. Prosumers, with their unique ability to return power to the grid, have introduced a bi-directional flow of energy. That ability to inject energy back into the grid results in a great deal of supply variability and presents a challenge for utilities and grid operators.
As a result, utilities are making significant investments in advanced metering to capture and blend large amounts of different time-oriented data sets at highly frequent intervals. As big data becomes a core element of digitized energy systems it is essential that utilities and application providers can handle, process and analyze increasing sources and volumes of time-series data. This is where Kx can help.
DISTRIBUTED AND RENEWABLE ENERGY RESOURCES (DER) MANAGEMENTKx for Sensors platform is particularly useful for utilities looking to better manage DER – such as solar panels, electricity storage, electric vehicles and other controllable loads – given the intermittency and variability of the outputs. Integrated, continuous data analytics can also be used to vastly improve situational awareness for other types of energy asset management - linking SCADA, micro-phasor and behind-the-meter data, to more accurately predict the state of the power system and take action.
Due to its small footprint Kx can provide big data and analytics close to where data is collected enabling utilities and solution providers to detect and predict conditions more quickly than ever before, improving availability, optimizing maintenance and longevity of their assets.
USE CASES & APPLICATIONSDelivering a centralized information exchange for retail markets: Kx provides the MDM and settlement functions, involving large amounts of time-series data, both historic and real-time for CGI’s new Central Markets System (CMS)for FINGRID, known as Datahub
Transaction system and data warehouse: A North American utility SaaS provider, installed Kx for Sensors alongside the existing system, de-risking their project, yet still providing new services including analytics and querying capabilities to over 5 million customers on trillions of data points spanning over seven years of collection history.
Improving system reliability: As part of Survalent Technology’s ADMS platform SurvalentONE, Kx provides real-time advanced network analytics capabilities, with improved system reliability - enabling services such as ‘playback’ allowing the replay of grid sensor data and activities.
Delivering cost savings and lowering operational risk: In partnership with App Orchid, Kx has been selected by a major, US-based Fortune 500 utilities company to deliver a next-generation real-time data platform to analyze data and create business applications using AI & ML.
INTEROPERABILITY AND OPC UA CONNECTIVITIYOpen Platform Communications Unified Architecture (OPC UA) has emerged as a standard communication protocol for enabling the connectivity and communication of a wide variety of diverse industrial automation devices and systems. The Kx OPC UA Connector empowers systems to stream sensor data at high frequencies and volumes from OPC UA directly into Kx for Sensor’s kdb+ time-series database. This allows for efficient data usage enabling an immediate response to equipment and sensor conditions.
Kx technology enables integration with legacy systems and multiple data sources to either augment or replace existing historians and allowing you to extend and customize your data analytics applications to support your unique requirements. Use a connector framework to integrate with IT/OT systems, including SCADA, AMI, MDM, OMS, MDM, EMS, and ADMS
• APIs for .NET, Java, C, C++, Python, R, ODBC, Matlab, and Excel
• APIs for synchronizing master and reference data with other systems, including assets, locations, sensors and sensor measurements, with built in-audit trails