Today’s technology is not prepared to deal with the complexity of the future grid. The energy grid is transforming. It is changing from large-scale, centralized energy generation to a centralized/decentralized hybrid with the addition of small-scale decentralized generation along distribution feeders. With a mass market for Electric Vehicles, energy consumption will grow dramatically and become less predictable. We will need solutions to manage energy generation, balance supply & demand, and communicate with millions of devices in real-time. The solutions that will help us transform must be open, scalable, robust, interconnected, and data-based.
Complexity will become unmanageable, threatening operations, reliability and resiliency. Costs will rise as pressures grow to adapt rapidly under emergency conditions. Customers will flee to new innovative third-party solutions if the utility doesn’t adapt quickly, threatening the revenues that support grid operations, power supply, and reliability.
Awesense stands ready to take the hassle out of digital transformation. Awesense has invested in the tools and platform to make digitalization and work with energy data more accessible, faster and more affordable. We rapidly and affordably refine data for software implementations and data analytics. Our open Energy Data Model (EDM) makes data analytics and use case development a breeze. By removing the hassles associated with digitalization, we accelerate change and bring tomorrow’s benefits home today.
Our main clients are system integrators. However, we also work directly with utilities and solution providers.
No, it’s much more. Awesense enhances data repositories already in place, creating a data warehouse of integrated refined data. We ingest data from utility systems, structure data according to the Energy Data Model (EDM), enhance data quality, synchronize data in time and space and rapidly make data available via APIs anywhere in the system – from any device to any authorized user or software tool.
The Awesense Data Engine integrates disparate data sources, connecting geospatial and time-series data, synchronizing all data, and performing validation, estimation and error correction (VEE) on all data moving through the engine. These processes produce a cleansed, open Energy Data Model (EDM)-backed digital twin, providing significant efficiencies by avoiding data-process repetition with each new project or use case.
Awesense has APIs, connectors and integrations for a wide range of tools that can be used to build custom apps and analytics. Take advantage of integrations like PowerBI, Tableau, and Quicksight to create your charts and reports. Connect notebooking tools like Jupyter and Zeppelin to do your data science work. And connect planning and simulation tools, asset management tools, outage management systems, DERMS, and many other tools that require accurate, robust energy data.
Not necessarily, but the core value of the data model-backed digital twin is to synchronize asset data in time and space. This enhanced digital twin and many of the use cases it enables can only be built with the connectivity and topology data fundamental to GIS.
Our platform can ingest data from many GIS systems providers and is agnostic to the GIS vendor, including Smallworld and ESRI.
GIS is a system of record for a utility. If the GIS records are kept up to date, they will update in the Awesense Platform once ingested. The Awesense platform handles versioning of GIS over time and can help act as a distribution asset registry.
We work with our partners and customers to strike a balance to maintain flexibility and enhance the data model over time. In data models, there is always a tradeoff between standardization (for portability) and flexibility (for broad applicability). We strive to get in between the two extremes and focus on what results in the most impact.
Awesense works with data of different granularity and frequency. Sometimes we work with utilities with a one-time dump of data, but we can also implement ongoing data ingestions. For the latter, which is more beneficial in the long run, Awesense can work with partners to set up pipelines and systems to keep the data flowing. Ultimately we can provide near real-time analysis, but it depends on when/how the source system provides the data.
Awesense is cloud agnostic and can deploy across any cloud vendor. We are available on AWS, Microsoft Azure, Google Cloud and IBM Cloud. We deploy as SaaS, on the client’s cloud tenant or on-premise.
The business model is based on data volume computing. We have varying payment models depending on the Awesense tools and services required.
Ask Us A Question
