Energy Data Analytics
Go to the next level:
from basic parameter monitoring to advanced analysis, algorithms, forecasting, and cost simulation.
Iot | Electrical Power Supply Parameters | RestAPI | JSON | Aggregation | SQL Database | Grafana | Real-time Dashboards
The opportunities offered by Energy Data Analysis.
Energy data, such as power supply parameters, transmission parameters, energy consumption, and operational data of powered machines and processes, contain a huge amount of information. Their proper use enables further optimization, cost reduction, and increased safety and continuity of installation operation. Additionally, this becomes particularly important during the ongoing energy transformation. The use of advanced algorithms using data collected in real-time from measuring devices, historical data, as well as external data, including energy prices and supplier tariffs, opens up new perspectives for energy engineers in the field of supervision and analysis of the power system, the results of which constitute the basis for making optimal actions and decisions.
The use of the InDriver system platform, SQL database, and Grafana dashboard system for these purposes ensures maximum flexibility and openness of the implemented analytical solutions while minimizing the costs of the entire system. This is a significant difference compared to existing monitoring solutions, both in terms of the quality of analyses and the availability and openness of the system for the customer.
System Architecture
We integrate modern technologies to create the perfect ecosystem for energy data analysis. We combine our InDriver with an SQL database, an optional virtual machine from Microsoft Azure*, and dashboards from Grafana.
Meet the Energy Data Analytics Algorithms.
Group: Consumption, Costs, Past, Forecast, Tariff Comparison
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Energy Consumption with Forecast
Energy consumption chart for past periods and forecasts, e.g., the current year with monthly forecasting until the end of the year.
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Energy Cost with Forecast
Energy cost chart for past periods and forecasts.
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Energy Cost Simulation with Forecast at Available Tariffs
Energy cost simulation for defined available tariffs for past periods and forecasts.
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Energy Cost in Dynamic Tariff
Energy cost analysis and simulation for dynamic tariff.
Group: Realtime
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Real-time Power Profile
Chart showing the total power consumption for the last 24 hours, for every 15 minutes, with maximal, average, and minimal temporary peaks. The chart's analytics may indicate potential disruptions, such as extraordinary load switches.
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Current Energy Parameters
Real-time Power, Current, and Voltage breakdown for three phases, Total Power and Energy Consumption Chart in the last 24 hours.
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Power Profile Analytics
Correlation between the Expected Power Profile, derived from past data, and the Current Power Profile for automated detection and assessment of disruptions.This analysis can trigger real-time alerts to prevent losses or damages.
Group: Currents, Voltages, Power
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Overcurrent Protection
Histogram for three phases, with the maximal and average 1-minute current, indicating the duration when the current exceeds safe limits with alerting when the cumulated values approach limits that may be dangerous and could lead to breakdowns, production stops, or even fires.
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Overvoltage Protection
Histogram for three phases, with the maximal and average 1-minute current, indicating the duration when the voltage exceeds safe limits.
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Power Load
Chart displaying the breakdown of power usage for three phases, showing the load for each phase and potential asymmetry in power load.
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Power Guard
Chart showing the breakdown of ordered versus consumed energy for each 15 minutes, along with the Optimal Ordered Energy Level calculation and related potential cost savings.
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Reactive Power Guard
Chart displaying the level of reactive power and its disruption, triggering an alarm when the limit is exceeded with disruption costs calculation.
Group: Data Processing
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Time Synchronization
Measurement data is captured at real-time-synchronized intervals, including every full minute, 15 minutes, hour, or day, ensuring consistent in-time analysis.
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Interpolation
To maintain data continuity, each missing sample is interpolated.
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Aggregation
Measurement data is typically aggregated into time series of 1 minute, 15 minutes, 1 hour, and 1 day, with the statistical values calculated, such as minimum, maximum, average, and delta values calculated for each period. These aggregated data sets form the base for analytic algorithms.
Group: Efficiency, Losses, Leakage
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Compressors Efficiency
Chart illustrating the energy consumption required to produce 1 Nm³ of compressed air, compared with past periods to indicate the health of the compressor and its accessories. For multiple compressors, it includes computation of load hours, frequency of compressor switching, and pressure stability control.
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Pipeline Leakages
For pipelines carrying compressed air, water, gas, heat, and cool, the algorithm calculates the input-to-output difference when feasible, or computes the minimum flow in past periods and compares it to the current period's minimum flow. This comparison serves as an indicator of any decrease in the tightness of pipelines and installations.
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General Machine (Process) Efficiency
This general algorithm correlates machine output, cycles, products, working time, and downtime with energy consumption, providing insights into energy efficiency compared to past periods, production conditions, machine setups, and more.
How do we implement our Energy Analytics System?
Energy Analytics System Architecture
We install Edge Devices (Windows Industrial Computers) equipped with InDriver Software at the plant, connecting them to meters, sensors, measuring instruments, or existing systems (databases). Depending on the implementation requirements, these computers come with Ethernet and serial RS 485/422/232, M-Bus, and I/O Ports for direct connection to existing or additional measurement devices. The InDriver Software installed on the Edge Device allows remote configuration to acquire and process data from the connected measurement devices.
Example of Mini PC - Edge Computer for Energy Analytics Systems
Cloud Solution - The Preferred Choice with Maximum Benefits
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Edge Devices Integration: Edge Devices are linked to Cloud Servers, like Azure Database for PostgreSQL and the Grafana Dashboard. For more complex applications, an additional Azure Virtual Machine can be utilized for running advanced data analytics algorithms.
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Accessibility: Users can log into Grafana from any computer or mobile device to access analytics data seamlessly.
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Implementation and Support: Inquire your IT department about managing connections between Microsoft Azure and Grafana.
Advantages:
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Remote System Management: InAnalytics offers remote implementation and ongoing support, ensuring efficient operation.
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Universal Dashboard Access: Users can access the dashboard from any location, using any computer or mobile device, providing flexibility and convenience.
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Minimal Maintenance: The system is hosted on secure cloud servers, supported by 24-hour assistance, reducing the need for extensive maintenance.
On-premises Option - For Those Preferring Local Hosting
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Connection: Edge Devices are linked to a local database and Grafana server, requiring direct management by the company's IT department.
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Administration: The company's IT personnel should manage the local servers. Access permissions are necessary for the InAnalytics Support Team to provide remote implementation and support.
Consideration: This approach is suited for companies that opt out of cloud solutions, preferring to keep their data and analytics processes within their local infrastructure for various reasons, including security, control, or compliance with specific regulations.
On-line demo
In this example solution, electricity parameters from the Shelly 3EM smart meter are collected and processed by InDriver.
As a result of the tasks performed by InDriver, the data is fully completed, synchronized with the clock, and aggregated into 1-minute, 15-minute, 1-hour, and 1-day series and then saved in the SQL database. With the Time Series API (TSAPI), data can be easily visualized with Grafana and shared on the Internet via web browsers.
Dashboards gallery
Monitor power consumption in real time.
Prevent circuit off, overload, breakdown, even wire ignition, and serious damage.
Plan your budget thanks to graphs with projected energy consumption and costs.
