Awesense Use Case Library

An ability analyze and asses the wildfire risks associated with electric utility assets.

An ability to dispatch, execute and manage the work orders related electrical power grid.

The ability to analyze the impact of Time-of-Use (ToU) rates on consumption patterns, consumption peaks and utilities’ income.

Ability to conduct electric vehicle (EV) and appliance desegregation analysis to pinpoint hidden loads of interest.

An use case for analyzing smart meter flags to detect energy theft and identify patterns of abnormal usage.

A use case incorporating the DLR to evaluate line operating capacity based on actual conditions, improving grid reliability and efficiency while supporting renewable energy integration.

A use case for effective load capacity analysis of feeders and laterals to find out where the loads exist and where they pose the biggest bottlenecks.

A use case for visualizing data from the feeder’s voltage monitoring equipment to improve the power quality and reliability of an electrical system. It enables engineers to identify patterns, trends, and anomalies in the data, which aids in problem detection and diagnosis.

A use case for integrating and contextualizing power quality measurement data from different sources for better diagnosis, improved reliability, compliance, safety, and cost savings.

A use case for verification of proper billing in the presence of instrumental potential transformer and instrumental current transformer.

A use case to accurately assess load changes to avoid unnecessary costs, such as replacing transformers earlier than necessary.

A tool for mitigating imbalanced feeders by suggesting locations of the grid and loads which can be reconnected (shifted) to different phase.

A use case for accurate load forecasting for utilities to operate efficiently, ensure reliable power supply, and lower costs.

A use case for easy, fast and inexpensive meter-to-transformer association data verification and correction.

A use case for estimation of increased load from EV growth and grid locations identification where the impact of this load will be concerning.

A use case for analytical approach to reveal incorrect meter wiring connection.

A use case to check and ensure that the phase identification data in the system of records is aligned with the actual field wiring.

Load profile estimation is used when real profile data are missing to obtain a realistic energy consumption profile. These load profiles have various uses, such as short-term analysis, grid load estimates, energy balances, and load flows.

Optimizing the grid by reconnecting medium/low voltage stations to high/medium voltage stations is a cost-effective solution. Automation and data analysis are necessary for efficient optimization.

Outages in electricity distribution have negative impacts on utilities and its customers. A data visualization approach that shows outages on a map and provides detailed information from multiple systems can help prioritize and quickly repair outages, leading to improved reliability and increased profits.

A use case to geospatially visualize grid asset data and grid’s time series data. Apply data-driven approach for addressing electricity distribution challenges with data visualization.

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

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.

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

A use case for maximizing the value of deploying smart meters and IoT devices in the grid and at consumption locations.

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

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.

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

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

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.

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

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.

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

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.

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.

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

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.

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.

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

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.

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.

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.

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

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

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

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

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

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

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

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

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.