Method and apparatus for automatic interleaving of cycling loads in a microgrid - Patents.com

Abstract

A method and apparatus for autonomous automatic interleaving of cycling loads coupled to a grid. In one or more embodiments, the method includes: (i) determining, by a smart load coupled to a grid, a first grid stress value; (ii) comparing, by the smart load, the first grid stress value to an activation threshold; (iii) waiting, by the smart load, a delay period when the first grid stress value is lower than the activation threshold; (iv) determining, by the smart load, a second grid stress value after the delay period expires; (v) comparing, by the smart load, the second grid stress value to the activation threshold; and (iv) activating, by the smart load, when the second grid stress value is lower than the activation threshold.

Description

[Technical field]

[0001] FIELD OF THE DISCLOSURE Embodiments of the present disclosure relate generally to smart loads in a microgrid, and more particularly, to autonomous automatic interleaving of cycling smart loads in a microgrid. [Background technology]

[0002] A conventional microgrid typically includes at least one energy generator, at least one energy storage device, and at least one energy load. In small microgrids, the lack of load diversity can result in large peak-to-average power ratios due to a small collection of large but intermittent loads cycling on and off. Many of these loads are extremely flexible in when they can cycle on and off with little or no impact to the user. For example, a refrigerator can delay its on cycle for 5 minutes with negligible temperature drop. Loads that fit this category include refrigerators / freezers, well pumps (with pressure tanks), water heaters (non-tankless), air conditioners, and furnaces.

[0003] In small microgrid systems (e.g., less than 10 homes), a significant reduction in peak power requirements can be achieved by coordinating the activation and deactivation of these types of loads so that they are interleaved. This in turn allows for a lower cost system because it can be designed for lower peak power levels. While such coordination can be achieved in a relatively straightforward manner using communications, the additional network equipment and controllers required add cost, complexity, and hinder robustness of the system. Summary of the Invention [Problem to be solved by the invention]

[0004] Therefore, there is a need in the art for techniques to coordinate duty cycle operations that use an autonomous distributed control architecture. [Means for solving the problem]

[0005] Embodiments of the invention generally relate to automatic interleaving of cycling loads in a microgrid as shown in and / or described with respect to at least one of the figures.

[0006] These and other features and advantages of the present disclosure can be understood from consideration of the following detailed description of the disclosure in conjunction with the accompanying drawings, in which like reference numerals refer to like parts throughout.

[0007] Thus, in a manner in which the above-mentioned features of the invention can be understood in detail, a more particular description of the invention briefly summarized above can be had with reference to embodiments, some of which are illustrated in the accompanying drawings. It should be noted, however, that the accompanying drawings illustrate only typical embodiments of the invention, the invention being capable of admitting other equally effective embodiments, and therefore should not be considered as limiting the scope of the invention. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a block diagram of a power system in accordance with one or more embodiments of the present invention. [Diagram 2] FIG. 1 is a block diagram of a smart load controller in accordance with one or more embodiments of the present invention. [Diagram 3] FIG. 2 is a diagram of grid stress calculation logic in accordance with one or more embodiments of the present invention. [Figure 4] FIG. 13 is a diagram of the logic employed by a smart load in determining whether to activate. [Diagram 5] 2 is a block diagram illustrating multiple behind-the-meter connections in accordance with one or more embodiments of the present invention. [Figure 6] FIG. 2 is a diagram of grid stress calculation logic for a power system including a secondary control system and a tertiary control system in accordance with one or more embodiments of the present invention. [Figure 7] 1 is a flow diagram of a method for autonomously automatically interleaving cyclically operating loads coupled to a grid in accordance with one or more embodiments of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Embodiments of the present invention generally relate to methods and apparatus for autonomous automatic interleaving of cycling loads in a microgrid. In one or more embodiments, a distributed autonomous non-communicating technique is utilized by multiple cycling smart loads in a microgrid to reduce the likelihood that two or more of the more than one cycling loads will activate simultaneously, thereby increasing the level of stress on the grid above a desired threshold.

[0010] Loads employing the techniques described herein, which may be referred to as "smart loads," typically operate at low duty cycles (e.g., refrigerators, well pumps, furnaces in well-insulated homes, etc.) and often draw very high power (e.g., electric dryers, dishwashers, etc.). The techniques described herein use locally measured information about grid conditions (i.e., locally measured grid stress indicators) to enable smart loads to activate (i.e., turn on) and deactivate (i.e., turn off) autonomously and opportunistically while reducing the likelihood of multiple loads on the same grid activating simultaneously, and in various embodiments, without any external communication. In an embodiment, the smart load may additionally measure one or more local smart load parameters indicative of the smart load's current status, e.g., an air conditioner may measure room temperature and utilize the measured information in determining when to increase the relative likelihood of air conditioner activation and / or deactivation when grid stress is low enough to permit activation and / or deactivation.

[0011] In one or more embodiments, a large but intermittent smart load employs a historical droop curve and is programmed to be permitted to turn on below a first threshold of grid stress (which may also be referred to as a turn-on threshold or activation threshold) and to be turned off above a second threshold of grid stress (which may also be referred to as a turn-off threshold or deactivation threshold). Once a smart load is permitted to turn on, it delays its activation for some period of time, such as a random time (e.g., 5 seconds) during a delay window. If the grid stress rises above its permitted turn-on threshold during the time window period (e.g., if another load has an opportunity to turn on during that time period), the smart load must wait for the next opportunity for the grid stress to reach the turn-on threshold. In general, the delay is a function of the number of missed opportunities during the time period that the desired smart load is waiting to turn on, e.g., the delay can be decreased each time the smart load misses an opportunity to turn on. The delay window can be dynamically adjusted to increase or decrease the likelihood of turning on the smart load during an acceptable window period. For example, if a refrigerator misses one or more opportunities to turn on and its internal temperature increases, the refrigerator may begin to shorten its turn-on window (and / or lower its grid stress turn-on threshold) to increase the likelihood that the refrigerator will turn on.

[0012] Typically, smart loads employ simplified droop control techniques, but in some embodiments, the system uses generalized droop control. In this case, "frequency" actually represents "modified frequency," which is a function of frequency and voltage. Smart loads can use locally measured grid voltage and / or locally measured grid frequency to determine the state of the grid (i.e., grid stress). In one or more alternative embodiments, the power system can include secondary / tertiary control systems that use system-wide communications to re-center voltage and frequency. In such embodiments, these biases are included in the grid stress calculation.

[0013] The techniques described herein provide a distributed, hierarchical means of regulating smart loads on a grid, allowing for reduction in peak power demand for small systems, which in turn facilitates lower overall system costs (e.g., fewer power converters are required). By incorporating a delay period as described herein, smart loads can be differentiated from one another and priority can be given to smart loads that have been waiting to turn on but have missed some opportunities over loads that have already had an opportunity to turn on or have not been waiting long to turn on. Additionally or alternatively, priority to turn on can be given to loads based on their urgency.

[0014] 1 is a block diagram of a power system 100 in accordance with one or more embodiments of the present invention. The diagram merely represents one variation of countless possible system configurations. The present invention can function in a variety of environments and systems.

[0015] The power system 100 includes a power company 102 (such as a conventional commercial power company) and multiple microgrids 150-1, 150-2, ..., 150-X (collectively referred to as microgrids 150) coupled to the power company 102 via a power grid 104. Through connections to the power grid 104, each microgrid 150 can receive energy from and put energy onto the power grid 104 as a whole. Each microgrid 150 can operate without energy provided by the power company 102 and can cover a neighborhood, a village, a small city, etc., as the term "microgrid" is not intended to imply a particular system size. Although only microgrid 150-1 is depicted in detail in FIG. 1 and described herein, microgrids 150-2 through 150-X are similar to microgrid 150-1, however the number and / or type of various microgrid components may vary among microgrids 150.

[0016] Microgrid 150-1 includes multiple microgrid members 152-1, 152-2, ..., 152-M (collectively referred to as microgrid members 152), each coupled to a local grid 132, which in turn is coupled to the power grid 104 via an island interconnect device (IID) 134 for disconnecting / connecting to the power grid 104. The local grid 132 may be a main part of the power grid 104 or may be a local grid dedicated for microgrid 150-1. Although only microgrid member 152-1 is depicted in detail in FIG. 1 and described herein, microgrid members 152-2 through 152-M are similar to microgrid member 152-1, however the number and / or type of various microgrid member components may vary among microgrid members 152.

[0017] Microgrid member 152-1 includes a building 116 (e.g., a residence, a commercial building, etc.) coupled to a load center 126 that may be within the building 116 or outside the building 116. The load center 126 is coupled to a local grid 132 via an electricity meter 120 (measuring energy inflow and outflow for the microgrid member 152-1) and a local IID 122 for disconnecting / connecting to the local grid 132, and is further coupled to a distributed energy resource (DER) 106 and one or more smart loads 118.

[0018] The DER 106 includes power regulators 110-1, ..., 110-N, 110-N+1 coupled in parallel to a bus 124 that is further coupled to a load center 126. Generally, the power regulators 110 are bidirectional power regulators, where the power regulators 110 in a first subset of the power regulators 110 are coupled to DC energy sources 112 (e.g., renewable energy sources such as wind, solar, hydro, etc.), while the power regulators 110 in a second subset of the power regulators 110 are coupled to energy storage devices 114 (e.g., batteries, flywheels, compressed air storage, hot water heaters, electric vehicles, etc.). The combination of the DC energy sources 112 and the corresponding power regulators 110 may be referred to herein as a DER generator. In an embodiment where the power regulators 110 are DC-AC inverters, the power regulators 110 and the corresponding energy storage devices 114 may be referred to herein together as an AC battery 180. Each of the power regulators 110 includes a controller for operating the corresponding power regulator 110 .

[0019] The DER 106 comprises a DER controller 108 coupled to the bus 124 and communicating with the power regulator 110 (e.g., via power line communications (PLC) and / or other types of wired and / or wireless techniques) for sending command and control signals, receiving data (e.g., status information, data related to power conversion, etc.), etc. In some embodiments, the DER controller 108 is further coupled to a master controller or gateway (not shown) via a communications network (e.g., the Internet) for communicating / receiving data (e.g., system performance information, etc.) to / from the master controller via wireless and / or wired techniques.

[0020] Each of the power regulators 110 is a droop controlled power regulator such that when microgrid member 152-1 is disconnected from the local grid 132 and / or the power network 104, the power regulators 110 employ droop control techniques for parallel operation without the need for any common control circuitry or communication between the power regulators 110. Each of the power regulators 110 includes a power regulator controller having at least one processor, support circuitry, and memory including an operating system (if necessary), as well as a droop control module for implementing the droop control techniques, thereby enabling the power regulators 110 to share the load in a safe and stable manner.

[0021] Each of the smart loads 118 is typically a cycling load that often operates at a low duty cycle (e.g., refrigerators, well pumps, furnaces in well-insulated homes, etc.) and draws very high power available through the load center 126 (e.g., electric dryers, dishwashers, etc.). Although depicted within the building 116, one or more of the smart loads 118 may be located outside the building 116.

[0022] Each of the smart loads 118 includes one or more components for measuring grid parameters such as grid frequency and / or grid voltage, as well as a component controller 128, described in further detail below with respect to FIG. 2 for implementing the techniques described herein, in some embodiments, the component controller 128 may measure the grid frequency and / or voltage.

[0023] In accordance with one or more embodiments of the present invention, each of the smart loads 118 autonomously determines the degree of stress on the local grid and autonomously determines when to activate (turn on) and / or deactivate (turn off), as described in more detail below, so as to reduce or eliminate the likelihood of multiple loads on the local grid 132 activating simultaneously to prevent the level of grid stress from exceeding a desired threshold.

[0024] 2 is a block diagram of a smart load controller 128 according to one or more embodiments of the present invention. The smart load controller 128 (which may be simply referred to as the "controller 128") includes support circuits 204 and memory 206, each coupled to a central processing unit (CPU) 202. The CPU 202 may include one or more conventionally available microprocessors or microcontrollers, or the CPU 202 may include one or more application specific integrated circuits (ASICs). The component controller 128 may be implemented using a general purpose computer, which when executing specific software becomes a dedicated computer for implementing various embodiments of the present invention. In one or more embodiments, the CPU 202 may be a microcontroller with internal memory for storing controller firmware that, when executed, provides the controller with the functionality described herein.

[0025] The support circuits 204 are well known circuits used to facilitate the functionality of the CPU 202. Such circuits include, but are not limited to, cache, power supplies, clock circuits, buses, input / output (I / O) circuits, etc.

[0026] The memory 206 may comprise random access memory, read-only memory, removable disk memory, flash memory, and various combinations of these types of memory. The memory 206 may be referred to as main memory and may be used in part as cache memory or buffer memory. The memory 206 typically stores an operating system (OS) 208 of the controller 128, which may be supported by the power of the CPU, if necessary. In some embodiments, the OS 208 may be one of several commercially available operating systems, such as, but not limited to, LINUX, Real-Time Operating System (RTOS), etc.

[0027] The memory 206 stores various forms of application software, such as an auto-interleaving module 210, which, when executed, performs the techniques described herein to autonomously determine the activation and / or deactivation of corresponding smart loads.

[0028] The memory 206 additionally stores a database 212 for storing data related to the operation of the corresponding smart load and / or the invention described herein, such as, for example, one or more thresholds (e.g., thresholds for grid stress, activation, and deactivation).

[0029] 3 is a diagram of grid stress calculation logic in accordance with one or more embodiments of the present invention. The logic depicted in FIG. 3 may be implemented by the smart load controller 128.

[0030] Each smart load 118 employs droop control based techniques and performs grid stress calculations to determine whether the grid can manage grid activation at that particular time without exceeding a particular grid stress level (i.e., grid stress level threshold, sometimes referred to as grid stress threshold or simply stress threshold). Although both grid voltage and grid frequency are utilized in indicating grid stress at a given time, in some other embodiments, only one or the other is used to determine grid stress.

[0031] As depicted in FIG. 3, the measured grid voltage and the measured grid frequency are each compared to a corresponding reference signal (at 302 and 304, respectively), which provides an indication of the amount of grid voltage and frequency droop, and the resulting outputs are each multiplied by a corresponding coefficient (G1 and G2, respectively) that is similar to a droop gain. The resulting outputs are added together at summer 306 to generate an indication of the amount of active current that will be injected onto the grid by the generator employing droop control. The greater the amount of active current injected, the greater the stress on the grid. The calculated amount of active current is then compared to the reference stress value to obtain a degree of grid stress (which may also be referred to as a grid stress value or calculated grid stress) in units of a percentage of grid capacity. For example, a grid stress value of 100% indicates that the system is operating at maximum capacity. In other embodiments, the grid stress indicator may be a function of active, reactive, or apparent current / power (where the apparent 2 = Valid 2 + Disabled 2 ).

[0032] In one or more embodiments where the AC power system utilizes a first-order regulation technique and the generating resources are programmed to be V / F responsive, the value of G1 can be set to the Watts vs. Voltage total response in % / V and G2 can be set to the Watts vs. Hz total response in % / Hz. For example, in an embodiment where the system only has frequency regulation action on the generating resources (i.e., the system is only doing frequency droop) and has one 100 kW generator doing a 20 kW / Hz droop action and one 50 kW generator doing a 15 kW / Hz droop action, G1=0 since they are just doing frequency droop (i.e., voltage is not of interest), and G2 is the sum of the two system generators, and the sum of the generator droop actions is divided by the sum of the total capacities to get the total percentage of frequency action. G2=(20kW / Hz+15kW / Hz) / (100kW+50kW)=23% / Hz

[0033] The grid stress threshold is set such that load activation (i.e., turning on the load) does not force the system beyond its rated capacity. For example, with a capacity of 150 kW and a load of 10 kW, the maximum stress threshold would be equal to (150-10) / 150=93.3%. That is, to turn on the load without running the system above its rated capacity, the system would need to operate at a minimum of 140 kW. In one or more embodiments, a margin may be added to the grid stress threshold, for example on the order of 5-10%. In an embodiment, the grid stress threshold margin may be dynamically determined.

[0034] By utilizing the techniques described herein, smart loads (e.g., well pumps, motors, etc.) that have some flexibility as to when they can be turned on without an immediate urgency to turn on have an automated means by which they can be strategically turned on when the system has enough power to support them. Each load can independently and autonomously assess the stress on the grid at a particular time to determine if the grid has enough power for the load to operate at that time.

[0035] For example, a neighborhood of five homes that all operate off-grid and are all interconnected together might all operate wells, where a switch turns on the home's well pump when the well pressure tank drops below a certain pressure and turns the pump off when the pressure reaches a certain threshold. For example, the well pump might turn on at 40 PSI and turn off at 70 PSI. To prevent all the well pumps from activating at the same time, thereby increasing grid stress above a desired level, each well pump employs techniques described herein to automatically ensure that they do not turn on at the same time and are automatically interleaved, so that the system does not have to support them all turning on at the same time.

[0036] 4 is a diagram of logic employed by a smart load in determining whether to activate in accordance with one or more embodiments of the present invention. The logic depicted in FIG. 4 may be implemented by the smart load controller 128.

[0037] As shown in FIG. 4, the calculated grid stress and the grid stress threshold (which may be referred to as the activation threshold) are input to a comparator circuit 402, which outputs an indication of when the grid has enough power to support the load (i.e., when the calculated grid stress is below the grid stress threshold). When it is desired to activate the load, the comparator output is provided to an AND gate 404 along with a request to turn on. Continuing with the well pump example described above, the load's request to turn on would occur when the tank pressure falls below a lower pressure threshold, e.g., 40 PSI. Rather than the load turning on whenever the well pump pressure falls below the lower pressure threshold, the load first determines if the grid has enough power to support the load. A positive logic output of the AND gate 404 indicates that the grid has enough power to allow the load to turn on when it wishes to turn on.

[0038] The output of the AND gate 404 is fed to the enable input of a latch 406, a first counter. The latch 406 acts as a delay and starts counting when the enable input is high (i.e., when the load wants to turn on and the grid has enough power to allow the load). The count is reset (e.g., to zero) when the enable input is zero, which occurs when one or both of the grid stresses are above the grid stress threshold or when the load does not want to activate. By starting the delay when the load wants to activate and the grid can tolerate it (which can be called a turn-on delay), the resulting randomization reduces or eliminates the chances of the loads turning on at the same time and driving the grid stress above the desired threshold. The output of the first counter 406 is fed to the non-inverting input of a second comparator 414.

[0039] A second counter 408 receives the output from the grid stress threshold comparator 402 (i.e., an indication of whether the grid can support the load when it wants to turn on) at its clock input and the load turn-on request at its reset input. The second counter 408 is reset when the load no longer wants to turn on. The second counter 408 increments to indicate the number of times these missed turn-on opportunities occurred when the grid was able to support the load when it wanted to turn on, but the amount of power on the grid changed (e.g., due to activation of one or more other loads) during the turn-on delay period such that the grid can no longer support the load. The resulting number of missed turn-on opportunities is provided to a look-up table 410, the output of which is provided to a random number generator 412.

[0040] The lookup table 410 can adjust the turn-on delay based on the number of missed opportunities to turn on. For example, the first time a load wants to turn on, a relatively long delay can be assigned, and each time the load misses an opportunity to turn on, subsequent delays are successively shorter. By successively decreasing the length of subsequent delays, the likelihood that the load will be able to turn on increases the longer the load waits. The random number generator 412 reduces the likelihood that multiple loads will turn on at the same time. For example, it reduces the likelihood that multiple loads using identical lookup tables in the same system (e.g., all made by the same manufacturer) will select the same value in the lookup table and turn on at the same time. The output of the random number generator 412 is provided to an inverting input of a second comparator 414.

[0041] In an embodiment, depending on the type of smart load, an adaptive state-dependent turn-on delay can be provided using adaptive control based on the current state of the smart load (e.g., refrigerator temperature, tank water pressure, ambient temperature, etc.). For example, as depicted in FIG. 4, the output 416 of such adaptive control is fed into a look-up table. Continuing with the water pump example, when the pressure drops to a first lower threshold, e.g., 40 PSI, the water pressure may still be sufficient for the user, so the turn-on delay can be relatively long. If the water pressure drops below a second lower threshold, e.g., 30 psi, while waiting to turn on, the need to turn on becomes more urgent as there is an increased risk that the water pressure will drop too low to be usable. At such a time, the turn-on delay can be appropriately adjusted to a lower amount. For example, in a smart load that is a refrigerator compressor, the load can measure the internal temperature of the refrigerator and increase the urgency to turn on if the temperature rises to a point where food may spoil. Other examples of smart loads that can determine their current state and delay turn-on accordingly include HVAC devices (thermostats, air conditioners, heaters, etc.), hydraulic devices, and the like.

[0042] 5 is a block diagram illustrating multiple behind-the-meter connections in accordance with one or more embodiments of the present invention. As seen in FIG. 5, multiple smart loads 118-1, 118-2, ..., 118-K, each with a corresponding controller 128-1, 128-2, ..., 128-K, and an energy storage unit 502 are behind the meter 120 and coupled to the load center 126. Although depicted within the building 116, one or more of the loads 118-1, 118-2, ..., 118-K and the energy storage unit 502 may be located outside the building 116.

[0043] As previously described, smart loads 118-1, 118-2, ..., 118-K typically operate at low duty cycles and often draw very high power, such as, for example, refrigerators, well pumps, furnaces, air conditioners, electric dryers, dishwashers, etc. The energy storage unit 502 may be any suitable device capable of storing and delivering energy. In some embodiments, the energy storage unit 502 may also have a controller, similar to the controller 128, for controlling the unit's energy storage and / or delivery. Although a single energy storage unit 502 is shown, other embodiments may have additional energy storage units 502 or no energy storage unit 502.

[0044] In an embodiment, one or more of the loads 118-1, 118-2, ..., 118-K and the energy storage unit 502 can be connected to similar smart loads and / or energy storage units in another microgrid member 152 via electrical connections that are not part of the power grid 104 / local grid 132, such that the flow of power between the loads and / or energy storage units bypasses the power grid. For example, the load center 126 and a similar load center in another microgrid member 152 can be coupled to each other via an electrical cable separate from the power grid, such that energy can bypass the power grid and flow between the components (e.g., the DER 105, the load 118, the energy storage device 502) of the different microgrid members 152. In some such embodiments, one or more of the DER 105, the load 118, the energy storage device 502 can control the flow of energy across the electrical cable, while in other such embodiments, a separate device can be utilized to control the flow of energy across the electrical cable. For example, each participating microgrid member 152 may include an energy flow control device for controlling such energy flows. In some of these embodiments, the energy flow control devices may be coupled to (or may be part of) the load centers of their corresponding microgrids to control the flow of energy, while in others of these embodiments, the energy flow control devices may be coupled to components of their corresponding microgrid members and to each other without the use of load centers.

[0045] 6 is a diagram of grid stress calculation logic for a power system including a secondary control system and a tertiary control system in accordance with one or more embodiments of the present invention. The logic depicted in FIG. 6 may be implemented by the smart load controller 128.

[0046] The grid stress calculation logic shown in Figure 6 differs from that shown in Figure 3 in that the power system corresponding to Figure 6 includes secondary / tertiary control systems that use system-wide communications to re-center voltage and frequency, and these biases are included in the grid stress calculation as depicted in Figure 6. As shown in Figure 6, at summer 602, the voltage bias from the secondary control system is added to the output from 302 and the result is multiplied by a coefficient G1 and coupled to summer 306. At summer 604, the frequency bias from the secondary control system is added to the output from 304 and the result is multiplied by a coefficient G2 and coupled to summer 306. At summer 308, the output from summer 306 is added to the reference stress from the tertiary control system. The output from summer 308 is the calculated grid stress.

[0047] 7 is a flow diagram of a method 700 for autonomously automatically interleaving cycling loads coupled to a grid in accordance with one or more embodiments of the present invention. Method 700 is an implementation of auto-interleaving module 210. In some embodiments, a non-transitory computer-readable medium includes a program that, when executed by a smart load controller, performs method 700 described below. In various embodiments, smart loads coupled to a grid employ techniques described below to reduce the likelihood that more than one load will activate simultaneously, thereby increasing the level of stress on the grid above a desired threshold.

[0048] Method 700 begins at step 702 and proceeds to step 704. In step 704, a local grid stress value for the load that has a request to activate is determined, as previously described. The method proceeds to step 706 where a determination is made whether the local grid stress value is below an activation threshold. The activation threshold is a grid stress threshold, determined as described above. If the result of the determination is no, i.e., the local grid stress level is not below the activation threshold (i.e., the grid does not have enough power to support the load at the time), method 700 proceeds to step 707 where a determination is made whether the load still has a request to activate. If the determination in step 707 is yes, i.e., the load still should be activated, method 700 returns to step 704. If the determination in step 707 is no, i.e., the load still should not be turned on, the method proceeds to step 730, where the method ends.

[0049] At step 706, if the determination result is yes, i.e., the local grid stress value is less than the activation threshold, method 700 proceeds to step 708. At step 708, a delay period is activated where the load waits for the delay time as described above. Method 700 proceeds to step 710 where an updated local grid stress value is determined. In some embodiments, the local grid stress value is updated periodically (e.g., continuously or near-continuously) based on current local grid conditions.

[0050] At step 712, the updated local grid stress value is compared to the activation threshold. In some embodiments, the value of the activation threshold may be updated periodically, such as when changes occur to the grid. If at step 712 the determination is no, i.e., the local grid stress level is no longer below the activation threshold, method 700 proceeds to step 714.

[0051] At step 714, a determination is made whether the load still has a request to activate. If at step 714 the determination is yes, i.e., the load should still be activated, then method 700 proceeds to step 716 where the count of activation attempts is incremented. Method 700 then returns to step 708 where a delay period is entered which can be variably set as described above.

[0052] If, in step 714, the result of the determination is no, i.e., the load no longer has a request to activate and should not be turned on, then method 700 proceeds to step 718, where a count of the number of activation attempts is zeroed, and method 700 proceeds to step 730, where the method ends.

[0053] If the determination at step 712 is yes, i.e., the updated local grid stress value is less than the activation threshold, then method 700 proceeds to step 720 where the load is activated. At step 722, a determination is made whether the load is desired to remain active. If the determination at step 722 is no, i.e., the load should not remain active, then method 700 proceeds to step 728 where the load is deactivated and then to step 730 where method 700 ends.

[0054] If, at step 722, the determination is yes, i.e., the load should remain active, then method 700 proceeds to step 724 where an updated local grid stress value is determined. Method 700 proceeds to step 726 where a determination is made whether the updated local grid stress value is lower than a deactivation threshold. The deactivation threshold indicates a level of grid stress such that the load can no longer be supported by the grid and may be determined utilizing the same techniques used to determine the activation threshold. In some embodiments, the activation threshold and the deactivation threshold may be the same.

[0055] If the determination in step 722 is yes, i.e., the updated local grid stress value is less than the deactivation threshold, then method 700 returns to step 722. If the determination in step 722 is no, i.e., the updated local grid stress value is not less than the activation threshold, then method 700 proceeds to step 728, where the load is deactivated, and then to step 730, where method 700 ends.

[0056] While the forgoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, the scope of the invention being defined by the following claims. [Explanation of symbols]

[0057] 100 Power Systems 102 Electric Power Company 104 Power grid 106 Distributed Energy Resources, DER 108 DER Controller 110 Power regulator 110-1 Power controller 110-N power regulator 110-N+1 Power regulator 112 DC Energy Source 114 Energy Storage Devices 116 Buildings 118 Smart Load, Load 118-1 Smart Load, Load 118-2 Smart Load, Load 118-K Smart Load, Load 120 Power Meter 122 Local IID 124 Bus 126 Load center 128 Component Controller, Smart Load Controller, Controller 132 Local Grid 134 Island Interconnect Device, IID 150 Microgrid 150-1 Microgrid 150-2 Microgrid 150-X Microgrid 152 Microgrid Members 152-1 Microgrid Member 152-2 Microgrid Member 152-M Microgrid Member 180 AC battery 202 CPU 204 Support Circuit 206 Memory 208 Operating System, OS 210 Auto Interleave Module 212 Database 306 Adder 308 Adder 402 Comparator circuit, grid stress threshold comparator 404 AND Gate 406 Latch, First Counter 408 Second Counter 410 Lookup Table 412 Random Number Generator 414 Second Comparator 416 Adaptive Control 502 Energy storage device, energy storage unit 602 Adder 604 Adder

Claims

1. 1. A method for autonomous automatic interleaving of cycling loads coupled to a grid, comprising: determining a first grid stress value by a smart load coupled to the grid; comparing, by the smart load, the first grid stress value to an activation threshold; waiting, by the smart load, a delay period when the first grid stress value is less than the activation threshold, the delay period being a function of the number of times the smart load misses an opportunity to turn on during a period of time the smart load is waiting to turn on; determining, by the smart load, a second grid stress value after the delay period expires; comparing, by the smart load, the second grid stress value to the activation threshold; activating, by the smart load, when the second grid stress value is less than the activation threshold. A method comprising:

2. The method of claim 1 , wherein the delay period is a random amount of time within a delay window.

3. The method of claim 1 , wherein the delay period is dynamically adjusted based on a condition of the smart load.

4. The method of claim 1 , wherein the activation threshold is determined such that activation of the smart load does not cause a system in which the smart load operates to operate beyond its rated capacity.

5. The method of claim 1 , wherein the activation threshold is dynamically determined.

6. 2. The method of claim 1, wherein the first and second grid stress values ​​are calculated utilizing a frequency bias, a voltage bias, and a reference stress bias from a control system that re-centers voltage and frequency using system-wide communications.

7. 1. An apparatus for autonomous automatic interleaving of cyclically operated loads coupled to a grid, comprising: CONTROLLER FOR GRID-TIED SMART LOADS - Patent application the controller comprises one or more processors and a memory, the memory being configured by the one or more processors to: determining a first grid stress value; comparing the first grid stress value to an activation threshold; waiting a delay period when the first grid stress value is less than the activation threshold, the delay period being a function of the number of missed opportunities for the smart load to turn on during a time period waiting for the smart load to turn on; determining a second grid stress value after the delay period has expired; comparing the second grid stress value to the activation threshold; Activating the smart load when the second grid stress value is less than the activation threshold. An apparatus comprising instructions executable for:

8. The apparatus of claim 7 , wherein the delay period is a random amount of time within a delay window.

9. The apparatus of claim 7 , wherein the delay period is dynamically adjusted based on a condition of the smart load.

10. 8. The apparatus of claim 7, wherein the activation threshold is determined such that activation of the smart load does not cause a system in which the smart load operates to operate beyond its rated capacity.

11. The apparatus of claim 7 , wherein the activation threshold is dynamically determined.

12. 8. The apparatus of claim 7, wherein the first and second grid stress values ​​are calculated utilizing a frequency bias, a voltage bias, and a reference stress bias from a control system that re-centers voltage and frequency using system-wide communications.

13. A computer readable medium having encoded thereon instructions executable by one or more processors for performing the method of any one of claims 1 to 6.

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