I write frequently about the coordinated technological innovation required to make Software-Defined Electricity a reality and not so much focus on the extraordinary data and analytics advantages provided by embedding intelligence and control into power networks.
It boils down to electrical signature modeling. The core advantage of 3DFS Technology lies in the proprietary data processing system and unlimited computing capacity it delivers. Access to unlimited computing capacity opens up new possibilities for sensing and data acquisition, sufficiently advancing the capabilities of electrical signature modeling.
3DFS has pioneered a new method of intelligent sensing that guarantees the delivery of error free data by creating a new data processing layer at the point of sensing, before the point of data input into the system. The flexibility of Task Oriented Optimal Computing allows for significant oversampling of the sensor data inputs relative to the system data need and drills down to the error free data point by completing all of the necessary filtering, acquisition, conversion, normalization, ranging, etc. by the time the system requires the data input.
For example, if a system input data point is required every millisecond, the intelligent sensing must be accomplished within that 999 microsecond window in order to deliver error free data consistently at the millisecond frequency. If the system requires an input data point every microsecond, the intelligent sensing must be completed during the 999 nanosecond window.
This is a transformative advancement over the unintelligent way sensors are presently used, which are as rough data point reporting devices. It is an area of new data science and modeling.
With intelligent sensing, all data inputs can be perfectly synchronized by timing at the point of input, resulting in the most accurate Real-Time snapshot of how an entire system is operating at that moment in time. Software-Defined Electricity requires 26 separate channels to be synchronized in 24 bit resolution at MHz frequencies.
Noise Free Power Networks
Using this approach, the technological advancement of error free measurement of electricity is possible. For the first time in the history of electrification, a true picture of electrical power flow can be analyzed. This is an historical achievement and one of the most significant advancements in electrification since its inception.
We are all familiar with the term Garbage IN = Garbage OUT and when it comes to electrical signature analysis, this term exquisitely applies because one enormous challenge is in dealing with electrical noise which frequently distorts the signals in unknowable ways.
This is where electrical signature modeling with Software-Defined Electricity leapfrogs conventional methods of electrical signature analysis. It starts with the control and balancing of power as it flows. This creates a noise free baseline electrical environment, making it much easier to detect changes in the network.
This is akin to being at a crowded party and attempting to speak to another person from across the room. All of the chatter and ambient noise of the environment make your conversation harder, however if you yelled out for everybody to stop talking (and they do), it would be much easier to carry on that conversation.
With the combination of clean and balanced electricity, error free sensing and unlimited computing, absolutely everything that consumes power in a network can be detected and tracked, all in Real-Time.
Advanced Electrical Signature Modeling
The 3DFS approach to electrical signature modeling is comprehensive, tracked with 26 different parameters in Real-Time, revealing the total, most complete signature possible.
With the advantage of this intense electrical signature modeling coupled with the requisite computing power, SDE instantly begins building models of every single load in the power network once activated.
Machines are designed to do repetitive tasks. Electrical and mechanical components wear out over time, slightly altering their electrical consumption signatures. SDE compares and tracks the slight deviation of the electrical signatures that occur over time updating the model every time a load operates.
Automatically maintaining this precision Real-Time model of load power consumption is the only way to instantly detect when abnormal events occur within a power network. Whether the need is to detect cyber attacks, or predictive analytics, or verifying repairs were performed properly, or monitoring load tampering, or tracking process improvement, identifying power theft, and the list goes on and on, this layer of data is critical.
The entire industry must get beyond monitoring power flow with external sensors delivering individual data points, like voltage and current, forcing engineers to analyze data after the fact to discover any problems.
The world’s need for visibility into our grid and power networks has far surpassed this method and it shows with every brownout, every outage and every fire. It is time to upgrade the way we monitor and control the power flow within the wires and that can only be done with intelligence embedded into the power network.
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