This disclosure generally relates to an apparatus for facilitating the collection of electrical data derived from electrical equipment through a sensor and transmitting that data to a computer over Wi-Fi at varying time intervals in the field of energy management technology.
Energy monitoring devices currently available on the market suffer from several issues. Expensive energy monitors that provide real time energy monitoring technology can cost $1000 or more without any software. This can make it difficult for clients to invest heavily in monitoring all electrical equipment for electrical issues. Only select equipment will use the more expensive energy monitoring technology. There are cheaper energy monitors, but are limited in amount of energy that can be metered, making them difficult for being used in an industry setting where current can reach much higher amperages than what a typical home consumes altogether.
Such monitors also do not provide real time energy monitoring functionality. In many cases, they collect data in intervals of several minutes rather than seconds, making it difficult to get a better understanding of the health of electrical equipment when immediate issues occur.
Further, all of these devices use proprietary means of data transmission through either proprietary radio or wire transmissions. In terms of power access, these devices can only be powered in one way. In many cases, it can either be battery powered or powered by AC/DC power supply, but can not be interchanged or expanded as needed without purchasing more expensive power supplies for every monitor, taking up much needed electrical real estate at electrical plugs, etc. This also can make making energy monitoring of hard to reach equipment impossible.
An energy monitor typically requires a current transformer for measuring electrical properties. Current transformers (CTs) are sensors that measure alternating current, and have a primary winding, a core and a secondary winding, although some transformers, including current transformers, use an air core.
The alternating current in the primary produces an alternating magnetic field in the core, which then induces an alternating current in the secondary. See
CTs are specified by their current ratio from primary to secondary. The rated secondary current is normally standardized at 1 or 5 amperes. For example, a 4000:5 CT secondary winding will supply an output current of 5 amperes when the primary winding current is 4000 amperes.
An energy monitor typically uses “split core” type CTs for detecting the AC currents, which can be opened and closed over a wire. The split core type is particularly suitable for DIY use, as it can be clipped onto either the live or neutral wire coming into the building, without the need to do any high voltage electrical work. Like any other transformer, a current transformer has a primary winding, a magnetic core, and a secondary winding.
The alternating current flowing in the primary produces a magnetic field in the core, which induces a current in the secondary winding circuit. The current in the secondary winding is proportional to the current flowing in the primary winding:
I
secondary
=CT
turnsRatio
×I
primary
CT
turnsRatio=Turnsprimary/TURNSsecondary
The number of secondary turns in the CT is for example 2000, so the current in the secondary is one 2000th of the current in the primary.
Normally, this ratio is written in terms of current in Amps, e.g. 100:5 (for a 5 Å meter, scaled 0-100 Å). The ratio for the CT above would normally be written as 100:0.05.
Currently the energy monitoring devices do not have Ethernet-ready capability that facilitates connection/programming the device through Ethernet. Also, the energy monitoring devices on the market use either a battery as the power source or power directly from the wall socket, thus are more limited in terms of applicability under different conditions.
Energy monitoring devices, systems and methods are described. A single sensor unit has a current transformer as the voltage sensor through induction to measure an analog voltage value, a processor for converting the analog value to a digital value and subsequently transmitting it to a remote device for recording and/or analysis. A housing encloses both the current transformer and the processor and typically has an Ethernet or other connector connecting to the housing for electrical and data coupling to the processor. The Ethernet connector can provide power to the processor by Power over Ethernet, and also facilitates Internet connection when no WiFi or Radio connection is available. Other powering and communication methods are possible. Preferably a number of sensors are deployed to available electric devices, and the sensors collect data for transmission to a remote processor, which analyzes the data, compares it against expected norms or historical data, and initiates any warnings or remedial actions needed.
The invention includes any one or more of the following embodiments, in any one or more combinations thereof:
An energy monitoring system for measuring the electrical energy usage of a plurality of devices powered by a plurality of load conductors connected to a power source, the system comprising:
An energy monitoring system tor measuring the electrical energy usage ot a plurality of electrically driven devices, the system comprising a plurality of sensor units, each sensor unit comprising:
Any system or sensor unit herein described, further comprising a heat sink within the housing for dissipating heat.
Any system or sensor unit herein described, wherein said processor is powered by a Power over Ethernet (PoE) cable.
Any system or sensor unit herein described, wherein said processor is powered by a PoE cable connecting to an RJ-45 port.
Any system or sensor unit herein described, further comprising an iBeacon protocol for location sensing.
Any system or sensor unit herein described, wherein said processor further comprises a wireless connection module using WiFi (802.11 a. b, g. n, ac, ad, ah, aj, ax, ay), Bluetooth or radiofrequency to connect either directly to said remote data processor or indirectly to said remote data processor through a proxy.
Any system or sensor unit herein described, further comprising a cantilever heat sink within said housing for dissipating heat, said cantilever heat snk comprising a leg having two ends, a first end joining a circuit board inside the housing, a second end at about a right angle to said first end and having a non-planar surface for increasing a surface area thereof.
Any system herein described, wherein said remote data processor further comprises means for an emergency cutoff functionality to shut down a device wherein a malfunction was detected.
Any system herein described, wherein said remote data processor is capable of detecting when the energy monitoring system is malfunctioning or shutoff.
Any system herein described, wherein said remote data processor is capable of detecting when the device powered by a given load conductor is malfunctioning or shut off.
Any system or sensor unit herein described, wherein said power over Ethernet connector in an RJ-45port.
Any system or sensor unit herein described, wherein said processor further comprises a wireless connection module using WiFi (802.11 a, b, g, n, ac, ad, ah, aj, ax, ay). Bluetooth or radiofrequency to optional wireless communication with said remote data processor.
Any system or sensor unit herein described, said heat sink being a cantilever heat sink comprising a leg having two ends, a first end joining a circuit board Inside the housing, a second end at about a right angle to said first end. and said second end being non-planar so as to increasing surface area thereof.
Any system herein described, wherein said remote data processor further comprises means for an emergency cutoff functionality to shut down any electrically driven device wherein a malfunction was detected.
Any system herein described, wherein the water usage WP (acre-foot water) is measured by the following equation:
WP=PP / (Factor A)
wherein PP is pump power (kW/hour), and Factor A is the power needed to lift one acre-foot of water (kW/hour/acre-foot water), and wherein the Factor A is calculated by the following equation:
Factor A=(LP×LD)/E
wherein LP is lift power (kW/hour) needed to lift one acre-fool of water given an efficiency of 100% (1.024 kW/hour), LD is lift depth—the depth of the water pump underground, and E is overall efficiency of the pump as a decimal.
A method of monitonng energy consumption of a load connector, comprising:
Any method as herein described, wherein said remote data processor can provide instructions to said senor unit(s).
Any method as herein described, said remote data processor companng said digital electrical values to expected electrical values and detecting any discrepancy as a malfunction, and alerting a user as to said malfunction.
Any method as herein described, wherein if said malfunction is a serious malfunction and said remote data processor directly or indirectly instructs a malfunctioning load conductor to reduce power or shut off. Preferably, if said malfunction is a serious malfunction a visual or auditory warning signal is transmitted to one or more users. Even more preferred, the method including changing at least one setting on a device with a detected deviation.
Any method as herein described, further comprising displaying an energy status of each device on a map.
Any method as herein described, wherein the method is used to monitor water usage by converting energy usage of a water pump to water usage, wherein the water usage WP (acre-foot water) is measured by the following equation:
WP=PP/(Factor A)
wherein PP is pump power (kW/hour), and Factor A is the power needed to lift one acre-foot of water (kW/hour/acre-foot water), and
Factor A=(LP×LD)/E
wherein LP is lift power (kW/hour) needed to lift one acre-foot of water given an efficiency at 100% (1.024 kW/hour), LD is lift depth—the depth of the water pump underground, and E is overall efficiency of the pump as a decimal.
Any method as herein described, wherein the method is used to monitor water usage of a water pump, compnsing the steps of:
F
o
=F
e
×T
wherein Fe is Predictive Flow rate in Gallons/Minuta. Fo is predictive flow output in Gallons, and T is the amount of time in minute that the water pump has been operational; and
v) comparing the predicted flow output to the recorded flow rate to calibrate the predicted flow output.
A method of displaying a plurality of energy monitoring systems on a map interface, comprising:
A method for using user input to determine malfunctions present in electrical devices being monitored, comprising:
Any method herein described, wherein causes of said malfunctions are either self-detected by each said energy monitoring system or manually entered by an inspecting professional.
The use of the word “a” or “an” when used in conjunction with the term “comprising” in the claims or the specification means one or more than one, unless the context dictates otherwise.
The term “about” means the stated value plus or minus the margin of error of measurement or plus or minus 10% if no method of measurement is indicated.
The use of the term “or” in the claims is used to mean “and/or” unless explicitly indicated to refer to alternatives only or if the alternatives are mutually exclusive.
The terms “comprise”, “have”, “include” and “contain” (and their variants) are open-ended linking verbs and allow the addition of other elements when used in a claim.
The phrase “consisting of” is closed, and excludes all additional elements.
The phrase “consisting essentially of” excludes additional material elements, but allows the inclusions of non-material elements that do not substantially change the nature of the invention.
The following abbreviations are used herein:
The invention is composed of the following physical features: a current transformer 10 (as shown in
Also needed are a circuit board (not shown) containing all required electrical components to measure and augment sensor values, including a processor (further detailed in
The current transformer 10, as shown in
In order to power the energy monitor, a user needs to connect the energy monitor to an Ethernet or equivalent cable or an internal power source, such as a battery. The other end of the cable will then be connected to a hub that can supply regulated or unregulated DC power to the device. The Power over Ethernet standard is a preferred means of powering the energy monitor. A battery or AC/DC converter may be used interchangeably to supply power to the device through the Ethernet jack, and depending on the plant layout, both methods could be used.
Power over Ethernet or “PoE” describes any of several standardized or ad-hoc systems that pass electrical power along with data on Ethernet cabling. This allows a single cable to provide both data connection and electrical power to devices such as wireless access points or IP cameras. Unlike standards such as Universal Serial Bus (USB), which also power devices over the data cables, PoE allows long cable lengths. Power may be carried on the same conductors as the data, or it may be carried on dedicated conductors in the same cable.
There are several common techniques for transmitting power over Ethernet cabling. Two of them have been standardized by IEEE 802.3. Since only two of the four pairs are needed for 10BASE-T or 100BASE-TX, power may be transmitted on the unused conductors of a cable. In the IEEE standards, this is referred to as “Alternative B.” Power may also be transmitted on the data conductors by applying a common-mode voltage to each pair. Because twisted-pair Ethernet uses differential signaling, this does not interfere with data transmission. The common mode voltage is easily extracted using the center tap of the standard Ethernet pulse transformer. This is similar to the phantom power technique commonly used for powering audio microphones. In the IEEE standards, this is referred to as “Alternative A.”
A webserver on the energy monitor will be available to connect a mobile device/computer to the energy monitor. This system is in place to allow one to make modifications to settings on the device if it has not yet established a connection to an external Wi-Fi connection. The mobile device's GPS and other software functionality will be used to supplement missing features from the energy monitor in order to define geographic location without the need for an integrated GPS unit and establish that the energy monitor is functioning properly and obtain the necessary configuration information. Alternatively, sensor-to-sensor technology, such as the iBeacon protocol by Apple could be used to establish the location of each sensor unit. Such components are readily available for inclusion in the sensor units.
At start-up, the energy monitor will attempt to connect to a local router to obtain internet access. If it is the very first time starting up, the energy monitor will connect to a local router pre-defined by the user through a mobile application. The mobile app will allow the user to input equipment and environmental values to learn more about the system. For example, such values could include RPM, HP, Voltage, Insulation Rating, GPS coordinates of the equipment's location. The energy monitor will attempt to connect to the internet/local area network and attempt to register itself with a computer. This computer will identify the device by providing a unique ID that will be saved by the energy monitor for annotating future data transmissions. Once a permanent Wi-Fi configuration is supplied by the computer, the energy monitor will restart. From here the energy monitor will function in the following manner.
The current transformer will be attached to the electrical equipment that will be measured for current. One electrified wire from the equipment will need to run through the hole in the center of the current transformer. When an electrical current passes through the current transformer, it will induce a current proportional to the equipment's current usage. The current derived is transformed into an analog voltage value, which will then read by an analog digital converter from a processor in the circuit board.
This microcontroller collects the analog voltage values from the current transformer. In sampling, a set of data samples are collected in succession over the course of 100 ms or more. This list of successive values are then made available through Wi-Fi/radio. Using oversampling, we accomplish gathering different sets of successive voltage values at varying sampling rates. In doing so, we can observe changes in the monitored equipment through external computer software. Oversampling will reduce the energy monitors effective sampling rate, but will extend the overall length of time of collected voltage values.
This data will be sent over Wi-Fi/radio to a software service through the HTTP protocol. The data is preferably structured in the form of the JSON text format to structure and annotate electrical values. This data can be collected by a computer over the internet or local area network. Using the unique identifier given to the energy monitor earlier, the computer will annotate the data as having been received from a specific energy monitor. The transmitted data may be stored by the computer for immediate or later retrieval and analysis. The collected data can be compared with expected data for each device being monitored, and any discrepancies flagged for handling. No electrical data is stored on the energy monitor in preferred embodiments. This reduces size and expense.
If the energy monitor cannot establish a connection with a local area network (LAN) through WiFi/radio, it will attempt to locate another energy monitor within the area, it can then obtain login information and if necessary, send annotated electrical information with the other energy monitor acting as a hub to transmit energy data to the computer on behalf of the other energy monitor.
In the event of internet loss, a local computer/server on the premises can be used to collect energy data indefinitely until a connection can be reestablished. This local computer/server will collect data on behalf of the online service to reduce loss of electrical data. If a connection is lost between online computer and local computer on the premises, a message will be sent through either email or SMS messaging or its equivalent to someone in charge of facility about the internet connectivity issue and recommendations on how the issue may be fixed. This local server/computer's main purpose is to act as a buffer against loss of data before being received over internet. The device in
In other embodiments, a large plant may be controlled and monitored entirely by local servers, and internet connectivity avoided. This may be an attractive option for security sensitive plants, such as power plants. LANs or WiFi can still be used for wireless communication inside the plant, as desired.
In regards to internal equipment, as shown in
The heat sink 101 can be made of any heat conductor, preferably metals, for relatively low cost, such as copper, aluminum, or alloys thereof. Other dielectric materials may also be used for different design needs.
Restrained by the heat generated from the power supply and the current transformer and its small form factor, traditional finned heat sinks would not fit on the device for desired heat dissipation. This cantilever design 101 offers the greatest amount of surface area by the use of stamped channels that increase effective surface area of the metallic material.
By “cantilevered” what is meant is any rigid structural member projecting from a vertical support, especially one in which the projection is great in relation to the depth, so that the upper part is in tension and the lower part in compression. The cantilevered heat sink herein is roughly L shaped (e.g., the two ends are at roughly right angles), wherein at least one of the arms is wavy to provide greater surface area.
As shown in
The ribbed protruding corners are used to provide structural rigidity in light of the thinner sides, especially in the case where it is manufactured through 3D printing, but in addition allow the energy monitor to rest more easily along the length of the monitored equipment's shielded wire. However, other shapes are possible.
The number, length and height of channels in the heat sink may be varied to improve heat dissipation properties depending on the available form factor. The heat sink is easier to manufacture by using stamping equipment on flat metal blanks, but molds may be made using traditional metals or 3D printed molds. Our prototype was made using a 3d printed mold that clamps above and below the metal blank and compresses the metal blank into the shape seen in
By employing the energy monitoring device of this disclosure, the energy monitor costs $10-15 to produce and manufacture compared to what more expensive energy monitors offer at prices starting from $1000+. Thus, such monitors can be extensively used to monitor complex manufacturing operations at an affordable cost. Existing monitors of similar cost do not provide the real time energy monitoring capability that the inventive monitor can, while still utilizing less than 80 mA of current during normal operation. This device is optimized to collect and transmit the greatest amount of data in near real time to an external computer for later processing and filtering. The device has a greater range of current monitoring capability than lower end energy monitors.
Since the device uses Power Over Ethernet, we are able to provide different options to power the device without having to change the device internally. Using Power Over Ethernet, we can for example use one AC/DC power supply or battery pack in order to supply power to 8 or more energy monitors at the same time. Power can be centrally distributed through Ethernet and be made available through varying lengths of Ethernet cable to each device. Remote monitoring can be done in this way to ensure the device receives power but can still function in remote locations.
Also, the device can be easily accessed either over a Wi-Fi hotspot that is generated by the energy monitor itself or through a network. Either method can allow the user to collect electrical data that can be access by a variety of software and hardware technologies. As long as Wi-Fi can be accessed, information may travel freely through the HTTP protocol. Modifications can be made directly to the device by accessing the energy monitors internal webserver to make adjustments onsite or remotely. Devices can be updated for new Wi-Fi passwords, software upgrades and other settings over Wi-Fi.
We required a few iterations of the energy monitoring technology to get to the results shown herein. In our market research we found that companies were struggling to use the energy monitors already in the market for the reasons stated in the background. The first two prototypes exhibited many of the characteristics of other energy monitors and required experimentation in order to solve and find better ways to make it easier to use and integrate in industry, be cost-effective and have a small form factor.
Two additional designs are further described, each having different form factors that utilize the same methods described in the device described above. The main difference between these two devices and the one discussed above is size and the ability to use the electrical data to control the electrical devices connected to the internal plug on the energy monitor through the use of a relay.
In the design shown in
An alternative design, as shown in
These compiled results are readily accessible to an authorized client by using a mobile interface on a mobile device or by using a remote client on a computer 111. The accessed data can then be visualized.
All energy monitors will show up on a map interface. When a marker is selected, it will indicate the statistical findings from the analysis stage inside our service. For example, if the compute stage (processor) determines that the device it is monitoring is off or malfunctioning, then the associated marker will be highlighted red and indicate what the likely problem is. As used herein, a “malfunction” is an unacceptable deviation from expected norms. The tolerance for variance can be user set, and is expected to vary with the device being monitored and or the hazard risk of its operation.
If the processor is unable to identify a cause for any flagged malfunction, the user may input when the issue occurred, what type of issue it was and on what device it occurred, and eventually input a cause or likely cause. In doing so, the user will be able to annotate the data with further information about any new issues that arise. When the system encounters this malfunction again in the form of a similar Fast Fourier distribution, it will use this user reported historical data to help identify the issue.
In the event of dangerous malfunctions, a warning can be sent to a user, a user's mobile device, a centralized alarm system etc. For particularly hazardous issues, an automatic shut off, power down or power reduction can be programmed.
As seen in
In
The processor used herein is ESP8266EX by Espressif Systems (ESP32 may also be used), but other processors or chips could be used. Preferably the processor has small footprint, low cost and low power consumption in order for continued operation. The processor also preferably has integrated Wi-Fi, Bluetooth or other wireless connectivity to be able to remotely transmit data and receive instruction for control. The current transformer used herein is SCT013 by YHDC Electronics, but again others could be used. The energy monitoring device preferably has a rechargeable lithium-ion battery by any manufacturer, so that when there is no external power source the monitoring device can still be operational. Power over Ethernet may still be used to remain operational if no battery is present.
Another application for the devices and systems described herein, is water/gas monitoring through a pump. Given the kW/h usage of a pump/motor as derived by the current, it is also possible to provide an estimate of a production facilities water/gas usage that has flowed through the system. This is made possible by the real time nature of the device. If we know the motors energy usage over time in fine detail, then it is possible to estimate the water/gas flow output passing through a pump.
This method works when the electric meter does not serve uses other than measuring power consumption by the well. Calculating water pumpage using this method requires the energy monitoring system's collected information on the electric pump.
LD—Lift Depth: The depth of the pump underground. This information can then be supplied to the energy monitoring system program through its interface (measured in feet in U.S Customary).
Acre-foot: Defined as the volume of one acre of surface area at a height of one foot (325,851 gallons in U.S customary units).
LP—Lift Power: Kw/hrs needed to lift one acre-foot of water given an efficiency of 100% (1.024 kW in U.S customary units).
PP—Pump Power: kW/hr used by the pump. This number is calculated by the energy monitoring system given the collected data current and voltage input into the pump as collected from the motor plate.
E—Energy: Overall efficiency of the pump as a decimal.
Units—U.S customary units are used for the calculation as its readily used in US measurements, but it may be exchanged for metric units if requested by the user through the system.
Factor A is the kW/h needed to lift one acre-foot of water (units: kW/h/Acre-Foot):
Factor A: (LP×LD)/E
Water Pumped=WP=PP/(Factor A) [Acre-foot in U.S Customary Units]
Therefore:
Water pumped=PP/((LP×LD)/E))=PP×E/LP×LD
Another method to estimate water and gas flow rate is through use of a predictive model that is defined through an artificial neural network. Artificial neural networks (ANNs) are a computational model used in computer science and other research disciplines, which is based on a large collection of simple neural units (artificial neurons), loosely analogous to the observed behavior of a biological brain's axons. Each neural unit is connected with many others, and links can enhance or inhibit the activation state of adjoining neural units. Each individual neural unit computes using summation function. The goal of the neural network is to solve problems in the same way that the human brain would.
Three sets of data are collected to build a predictive water/gas model. First, an energy monitor is connected to one phase of an irrigation or industrial pump to monitor for AC electrical signals and the times they were generated. These analog signals are converted to digital electrical values and then are sent to be processed and broken down to frequency intervals using the fast Fourier transform. This signature is then inserted into a row inside a data base. This database will contain historical frequency intervals and derived features from collected AC electrical signals.
The second set of data that will be collected will be the flow rate. This value may be collected manually by viewing the flow meter reading on an irrigation pump tubing near the filter. This second value is composed of a flow rate and the time of occurrence. This second value is then fed into a separate database that is established based on a set of a features defined in the preceding paragraph. The second value will be collected in 10 minute intervals over two or three hour periods or when drastic changes have been made to the distribution of irrigated water. Once an acceptable amount of data is inserted it may be processed by the deep learning system. The system will require these two specific pieces of data so that it may find a correlation between the amount of current consumed by irrigation pump and the expected flow rate for the given current consumed.
The third value collected is the water pressure that the irrigation pump is running at to provide more information about the current operational state of the pump. The water pressure may be collected manually or, preferably, through a sensor. This value will be collected in 10 minute intervals over two or three hour periods or when drastic changes have been made to the distribution of irrigated water.
The training data that is collected will be composed of a variety of different irrigation pumps and will be used to normalize and identify the expected flow rate. When the system discovers a new current consumption usage pattern it will ask the user, “what is the current flow rate and water pressure?” The computer system will remember the corresponding correlation between current output, flow rate and water pressure. Once a sufficient amount of data is inserted into the artificial neural network, any new subsequent pieces of data will be analyzed and will return a prediction of the expected flow rate Fe. Then the predictive total flow output Fo can be estimated by the following equation:
F
o
=F
e
×T
wherein
Fe is Predictive Flow rate in Gallons/Minute, obtained from the predictive model or may be provided as training data;
Fo is Predictive Flow output in Gallons, meaning the volume of water received; and
T is the amount of time in minute that the electric motor has been operational.
In the event that it predicts incorrectly, the user may update the predictive value with the actual value and the system will recognize the inaccuracy and attempt to correct itself when it sees that specific current usage pattern again for the given user. The AC signal data will be the primary source to derive predicted flow rates with pressure being another possible predictive value that can be used to identify correct functionality and accuracy.
The predicted flow output will then be used to predict a total flow output when only a water flow rate is available or measured briefly due to some reason. This is especially useful when there is no other means of measuring water usage at the water pump, and the estimation obtained from the energy monitoring system would be a good approximation for further analysis.
Each of the following is incorporated by reference herein in its entirety for all purposes:
U.S. Pat. No. 4,965,513 Motor current signature analysis method for diagnosing motor operated devices
U.S. Pat. No. 8,447,541 Energy usage monitoring with remote display and automatic detection of appliance including graphical user interface
US20080255782 Devices, Systems, and Methods for Monitoring Energy Systems
US20120303554 Energy Monitoring System and Method
U.S. Pat. No. 8,996,188 System and method for home energy monitor and control
This application claims priority to U.S. Ser. No. 62/322,158, filed Apr. 13, 2016, and 62/373,718, filed Aug. 11, 2016, each of which is incorporated by reference herein in its entirety for all purposes.
Number | Date | Country | |
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62322158 | Apr 2016 | US | |
62373718 | Aug 2016 | US |