Abstract
Appliances that use this inventions method of Demand Side Management will be autonomous and intelligently self-controlled and will learn how to manage their own energy use, change with the seasons, and adapt to changing power profiles, without the need of any external control from the power companies, or the user. All this will be done in the background, saving power, with little, or no noticeable change in performance to the user. This method does away with all the infrastructure and cost associated with prior art methods resulting in a method that is so simple and inexpensive that it can be affordably incorporated into almost any electronic device.
Claims
1. A method of controlling appliances by reducing power consumption during high demand periods, and increasing power consumption during low demand periods, by monitoring the frequency of the power line, and using this information to predict power trends and schedule power use proactively, which will result in lower energy costs for the consumer.
2. The present invention provides all the benefits of prior art Demand Side Management, but at virtually no cost to the power companies, due to its simplicity and lack of the requirement to be remotely controlled and internet connected.
3. Appliances that use this control method will be autonomous and intelligently self-controlled and will learn how to manage their own energy use, change with the seasons, and adapt to changing power profiles, without the need of any external control from the power companies, or the user.
4-18. (canceled)
20. (canceled)
Description
BRIEF DESCRIPTION OF THE DRAWINGS
[0047] FIG. 1 is a block diagram of an exemplification of an appliance control system incorporating the present invention, in this case a refrigerator control.
[0048] FIG. 2 is a flow chart of the input hardware circuit.
[0049] FIG. 3 is a flow chart of the averaging algorithm, showing how the line frequency is measured and interpreted.
[0050] FIG. 4 a flow chart of the present inventions operation in a refrigerator application.
[0051] FIG. 5 Block diagram for short term stability and demand response, short term measurement and actions. Example of refrigerator responding to disruptions on the grid.
[0052] FIG. 6 is a flow chart showing averaging, binning and peak period determination and actions in an adaptive methodology.
[0053] FIG. 7 is a chart showing the typical electricity price variations during the summer. This is an actual snapshot of the hourly electricity demand and real-time energy prices in East Kentucky, from Jul. 13 to Jul. 19, 2013. Notice that the price of electricity on Saturday morning was nearly $0.00/MWh versus Thursday afternoon which was nearly $475.00/MWh. This clearly demonstrates the potential huge cost benefits of this invention.
[0054] FIG. 8 is a chart showing line frequency variations throughout the day. Excerpt of actual AC line data and averaging algorithm implemented in MS excel. Dotted line is binned data from April 7.sup.th, in 32 periods. In this case midnight is at 0 and noon is at 16. The solid line is an average of BINs from previous 8 days.
[0055] This chart clearly demonstrates that the frequency in the morning is higher when there is less demand and the frequency in the afternoon is lower when there is greater demand. Higher frequencies=lower demand, and lower frequencies=higher demand. A simple algorithm would assign a 4 to 6 hour peak period for each.
[0056] FIG. 9 is a chart that shows how easily a short-term grid event can be detected, even though the cause occurred hundreds of miles away. The largest drop occurred on Apr. 7, 2015 and was caused by a generator going down on the east coast (causing the White House to switch to a backup generator), but was captured in the Chicago area. This demonstrates that the use of control chart lines would easily capture an event for action.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0057] Referring to FIG. 1, an exemplification of an appliance control system incorporating the present invention, in this case a refrigerator control, is indicated generally at 10 and has a printed circuit board 11, which may or may not be mounted in a housing 12 indicated by dashed outline, which has mounted thereon a power supply circuit 13 connected to AC input power lines denoted by L1 and N and provides low voltage power through a rectifier circuit 14 to the microprocessor circuit 15. The microprocessor receives input signals from the door position switch 50, from which it can make decisions on the operation of the lamp 25, and possibly the circulating fan, operation. The input signals from the temperature sensor 51, which may for example be a thermistor, can be used to make decisions about the operation of the compressor 21, and condenser fan 20, in cooling the refrigerator and freezer compartments. The input from the user interface 52, which may be for example, a potentiometer, encoder, or plurality of switches, is used to operate and program the refrigerator. The optional Blue tooth transceiver 53, and near field communication transceiver 54, are both available for communicating with the utility company 58, via a cell phone application 56. The optional Wi-Fi transceiver 55, can provide a full internet connection through a wireless internet router 57, with the utility company 58. Note that these optional communication modules are wholly unnecessary for the normal operation of the appliance, and the function of the present invention. These optional features are provided to be compliant with current prior art methods until these prior art methods are rendered obsolete. When obsolete, the appliance will automatically transition to the new method offered by the present invention. The line frequency detector 60, filter 61, and Schmidt trigger circuits 62, which are configured to receive and process the line frequency which is indicative of the operating state of the associated utility. The microprocessor provides outputs to the load controlling relays 20 thru 25, turning off and on loads as required for the normal operation of the refrigerator and for optimizing power consumption for best economy. The optional audio alarm 30, and a visual display 40, are for indicating the operating state and status of the appliance.
[0058] In this exemplification of an appliance control system, the present invention is designed and incorporated into a complete appliance control system that will take over the function of, and replace the existent appliance control in its entirety. This is necessary, in this exemplification, in order to gain full control of all the loads and functions of the appliance. This is also the most economical approach, avoiding the cost of redundant circuitry, hardware, software and interconnection. This will also produce the simplest and most reliable end product.
[0059] The operation of this demand managed refrigerator control is as follows: Referring to FIG. 1, AC line voltage is applied to the appliance control power supply 13. The control will operate the refrigerator as any normal refrigerator and energize relays powering the condenser fan 20, compressor 21, circulation fan 22, until the set temperature is achieved.
[0060] Simultaneously while performing the normal operation of the appliance, the control will start reading the frequency of the power line 201 (refer to FIG. 2) via the line frequency detector 202. This signal is then refined by the filter circuits 203 and 204 and squared up by the Schmidt trigger circuit 205, so the line frequency can be read by the microprocessor 15.
[0061] A stable time base 207, is necessary to keep track of when the high and low demand periods occur, however this time base does not have to be synchronized with real time, nor be very accurate, since the target is the middle of the high, or low demand periods, which are generally several hours long, so accuracy down to minutes, or seconds, is not necessary.
[0062] The microprocessor 15, will start processing the information from FIG. 3 301 by counting cycles 302, binning a predetermined amount 303, in this example 64, and measuring the time of each bin 304 and using this data to determine if there is currently a short term grid stability problem requiring immediate response 305, or if not, simply averaging and storing the bins for predicting future high and low demand periods 306, and then continue with the normal operation of the appliance 307. After several days of monitoring the line frequency, enough data will have been recorded in the Microprocessors internal, or external memory, FIG. 6607, so that now the microprocessor can start making scheduling decisions, an example of which is shown in the flow charts FIGS. 4 and 6, and adjusting loads to ameliorate disruptions in the grid shown in FIG. 5. Some heavy loads are of a low priority, such as defrosting and ice making 417, and can be scheduled to operate only at times of low demand, or shut off entirely if needed 415, 510, as shown in FIGS. 4 and 5.
[0063] FIG. 6 is a flow chart showing averaging, binning and peak period determination and actions in an adaptive methodology. The line frequency is continually monitored 601, binned 602, and averaged 603, updated 606 and stored 607. This information is used to continuously update the peak period prediction 610 and the low demand period prediction 609, thus allowing this control to follow power consumption trends, change with the seasons, and adapt to changing power profiles, without the need of any external control from the power companies, or the end user. The control is constantly optimizing its power consumption for optimum economy for the user, as well as for optimum efficiency for the power companies.
