Use Case Design & Development

The Awesense Energy Transition Platform enables the design of Use Cases in the Sandbox Environment using synthetic data. The testing and further development of Use Cases are conducted in the Awesense Energy Transition Platform after the ingested data has been processed to provide contextual insight.

What Is A Use Case?

A Use Case is a templated, digital solution that uses utility data to solve an industry problem by enabling data-driven business decisions to adapt effectively to an evolving energy grid.

Use Case Design

Designing An Application

Waste zero time with the development process and start designing algorithms and analytics in the Awesense Sandbox Environment using realistic synthetic data while the data ingestion occurs on the Energy Transition Platform. The realistic synthetic data and the tools for development of the testing environment provide the ability to design a near-ready Use Case helping you accelerate your time-to-market of Use Case development by upwards of 90%.


Developing An Application

After the data has been ingested, cleansed, synchronized & structured according to the Awesense Energy Data Model (EDM), it is ready for use in the Energy Transition Platform through APIs. The Use Case designed in the Sandbox Environment can be fine-tuned and further developed using actual data.

The finished Use Case can be combined with custom applications to draw business insights and modernize the energy grid to support the energy transition.

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Get Started With The Energy Transition Platform.

Get Started With The Energy Transition Platform.

Awesense Use Case Library

  • All
  • Asset Management
  • Billing
  • Consumer Rates and Programs
  • Data Analysis
  • Data Quality Improvement
  • Distributed Energy Resources (DERs)
  • Electric Vehicles (EV)
  • Grid Operations and Control
  • Grid Planning
  • Multipurpose Data Analytics
  • Non-Wires (NWA)
  • Outages
  • Revenue Protection
  • Worker Safety

[UC30-01] Suspicious Patterns Identification & Analysis

Utilities can identify suspicious patterns in energy consumption profiles & investigate them further to determine non-technical losses.

[UC29-01] Non-Technical Loss Investigation Management

Creating a methodology for an effective loss reduction programme by implementing a system that performs multiple functions related to the management and performance of non-technical loss investigations.

[UC28-01] Energy Balancing for Revenue Protection

Using energy balancing to reduce losses so utilities can increase resources spent on grid modernization.

[UC25-01] Analysis for Minimizing Quantities of IoT & Meter Devices

Deploying smart meters at consumption points for a better grid overview.

[UC23-01] Analysis of Grid Segments & Elements

It is vital to have the ability to systematically create and apply analytical models to distribution grid segments and individual elements.

[UC22-01] Topological Grid Segmentation

The creation of the segmentation based on simple attributes such as tariff or type of consumer is not sufficient for a grid operations-focused department. A systematic approach to the design of topological grid segmentation is required.

[UC21-01] Geospatial Analysis of Grid Alerts & Warnings

Analyzing grid alerts & warnings geo-spatially. This capability unlocks the possibilities for further producing insights from the data.

[UC20-01] Unexpected Generation Identification

Identification and analysis of micro-generation incidents and inputs on distribution grids.

[UC19-01] IoT Health Index & Overview

IoT devices can provide utility companies with essential data for the reliable operation of today’s and future grid. It is necessary to have a proper IoT health monitoring system to gain an overview of IoT health for maximum value.

[UC18-01] Grid Alerts & Warnings

Grid Alerts for greater asset situational awareness enabling the prevention of unnecessary damages or harmful influences in the grid.

[UC17-01] Actual vs. Contracted Grid Capacity Analysis

The grid’s maximum capacity is critical to utilities because it provides information on whether an additional load can be connected at a given location.

[UC16-01] Registered PV Generation Analysis

This growing penetration of distributed PV generation in the grids poses new challenges for utilities.

[UC15-01] Utility Data Challenge Hub

Data challenges call for submitting innovative solutions to real-world utility problems. Streamlining the data collection & aggregation process provides credibility to the utilities making the call for submissions and allowing them to attract higher-quality challenge participants resulting in optimized solutions.

[UC14-01] Onsite Generation & Ghost Load Analysis

Accurately forecasting the load, including the potential for ghost loads, is crucial for optimized grid management. Indicators of ghost loads, like total generation per circuit or % of the circuit’s load covered by renewables, are fundamental building blocks for correct load forecasting.

[UC13-01] Master Circuit Breaker Value vs. Measured Values Analysis

Inaccurate high-master circuit breaker values impact both consumers & electric utilities. Accurate analysis can benefit all parties & result in savings.

[UC10-01] Connected Loads [kW] vs. Actual Phase Balance Analysis

Errors in meter-to-phase assignation can result from inaccurate data about the phase the energy consumer connects. Such errors adversely influence grid operations & outage management.

[UC09-01] EV Charging & Use of Reserved Capacity Analysis

Utilities must have accurate insight into grid load growth due to the rapid rise in EV chargers. For such analysis, data cleansing and correction are usually required.

[UC08-01] Asset Management – Substations

Substation management is crucial for utilities & if managed efficiently, can increase utility savings; however, this requires accurate data.

[UC07-01] Asset Management – Cables & Lines

Asset management is crucial for utilities but is a considerable investment and operating cost; however, if managed with an efficient process can increase utility savings.

[UC06-01] GIS Grid Connectivity Validation & Correction

With “clean” data, a utility can perform insightful analysis requiring asset situational awareness and better address the challenges of managing the energy transition and improving grid reliability.

[UC05-01] Reversed Power Flow & PV Capacity Analysis

This use case simulates and quantifies the additional amount of PV generation (PV capacity) allowed on each Low Volt grid before reaching a state of reversed power flow.

[UC04-01] Transformer Capacity Analysis for EV Charging

Identifying how much EV Charging infrastructure can be accommodated given transformer load capacity is a new reality with the rise in EV use.

[UC03-02] Phase Balance Analysis

Identifying which phase is more or less loaded, adjusting accordingly and thus optimizing the grid & lowering investment costs.

[UC02-01] Power Factor Analysis

A use case for analyzing power factor values and how to manage these for an optimized grid.

[UC27-01] IoT Sensor Billing

Utilize alternative sensors located in the grid for customer billing purposes where metering data is not reliable.

[UC24-01] Analysis of Planned Outage for Assets Upgrades

Analyze transformers downstream from where a planned outage will occur to identify opportunities for asset upgrades

[UC01-01] Coincident Peak & Non-Coincident Peak Analysis

Ability to calculate Coincident Peak (CP) and Non-Coincident Peak (NCP) at various levels of aggregation and geographies.

[UC11-01] Unserved Energy Due To Outages Analysis

Understand the impact outages are having on customers and how they have impacted revenue

Transformer Loading Analysis

Analyze transformer loading patterns and health across all transformers in the service territory.

[UC12-01] Grid Temperature Monitoring

The impacts of extreme temperatures on grid components can range from financial losses, increased emissions and customer dissatisfaction to wildfires, extended outages and other damaged assets. These impacts are preventable with accurate insights.