Methods and apparatus for providing protection for electric vehicle supply equipment and electric vehicle charger

Abstract

A method for providing protection for electric vehicle supply equipment (EVSE) and electric vehicle (EV) chargers is provided herein. The method comprises calculating a grid stress, comparing a calculated grid stress with a requested EV power and selecting a minimum of the calculated grid stress or the requested EV power, and transmitting the minimum to the EV for setting a charging threshold of the EV to ensure that EV charging does not stress the grid and / or implement a disconnect function within the EVSE, by opening a relay, to ensure that EV charging does not stress the grid.

Description

METHODS AND APPARATUS FOR PROVIDING PROTECTION FOR ELECTRIC VEHICLE SUPPLY EQUIPMENT AND ELECTRIC VEHICLE CHARGERBACKGROUNDField of the Disclosure

[0001] Embodiments of the present disclosure relate generally to methods and apparatus configured for use with electric vehicles, and, for example, to methods and apparatus for providing intelligent protection systems for electric vehicle supply equipment (EVSE) and electric vehicle (EV) chargers.Description of the Related Art

[0002] Electrical vehicles (EVs) are a mobile distributed energy resource, e.g., mobile storage. The EVs can be charged from a grid, from private energy sources (e.g., photovoltaics (PV) and energy storage systems (stationary)), or from a public energy source (e.g., electric vehicle supply equipment (EVSE)). In some instances, EV chargers can be on-board the EV (e.g., for J1772 level 2 chargers, which is the most common form of EV charger). While such EV chargers are suitable for their intended use, there are some instances where a user experience can be less than satisfactory. For example, a) when batteries are not installed at a user home and a power conversion system to which an EV is connected is performing sunlight back-up + EV, b) when only a small amount of batteries are installed at a user home and a power conversion system to which an EV is connected is performing backup + EV, c) when the EV is connected to a street or suburb microgrid, and / or d) a weak grid. In such scenario’s there is a need to modulate the EV charge power to match a solar output power. For example, a standard approach can include the EV charger being controlled by an optimization engine that dispatches a desired power. The reaction of the optimizer, however, may be slow to local events (5 to 15 minutes), which can result in poor user experience and, in the short term, may place a burden on high bandwidth internet connection.

[0003] Thus, there is a need for improved methods and apparatus for providing intelligent protection systems for electric vehicle supply equipment (EVSE) and electric vehicle (EV) chargers.SUMMARY

[0004] Methods and apparatus configured for providing protection for electric vehicle supply equipment (EVSE) and electric vehicle (EV) chargers are provided herein. For example, in accordance with some aspects of the disclosure, a method for providing protection for electric vehicle supply equipment (EVSE) and electric vehicle (EV) chargers comprises calculating a grid stress, comparing a calculated grid stress with a requested EV power and selecting a minimum of the calculated grid stress or the requested EV power, and transmitting the minimum to the EV for setting a charging threshold of the EV to ensure that EV charging does not stress the grid.

[0005] In accordance with some aspects of the disclosure, a non-transitory computer readable storage medium has instructions stored thereon which when executed by a processor perform a method for providing protection for electric vehicle supply equipment (EVSE) and electric vehicle (EV) chargers. The method comprises calculating a grid stress, comparing a calculated grid stress with a requested EV power and selecting a minimum of the calculated grid stress or the requested EV power; and transmitting the minimum to the EV for setting a charging threshold of the EV to ensure that EV charging does not stress the grid.

[0006] In accordance with some aspects of the disclosure, an apparatus for providing protection for electric vehicle supply equipment (EVSE) and electric vehicle (EV) chargers comprises a controller configured to calculate a grid stress, compare a calculated grid stress with a requested EV power and select a minimum of the calculated grid stress or the requested EV power, and transmit the minimum to the EV for setting a charging threshold of the EV to ensure that EV charging does not stress the grid.

[0007] These and other features and advantages of the present disclosure may be appreciated from a review of the following detailed description of the present disclosure, along with the accompanying figures in which like reference numerals refer to like parts throughout.BRIEF DESCRIPTION OF THE DRAWINGS

[0008] So that the manner in which the above recited features of the present disclosure can be understood in detail, a more particular description of the disclosure,briefly summarized above, may be had by reference to embodiments, some of which are illustrated in the appended drawings. It is to be noted, however, that the appended drawings illustrate only typical embodiments of this disclosure and are therefore not to be considered limiting of its scope, for the disclosure may admit to other equally effective embodiments.

[0009] Figure 1 is a block diagram of a power system in accordance with one or more embodiments of the present disclosure;

[0010] Figure 2 is a block diagram of a smart load controller in accordance with one or more embodiments of the present disclosure;

[0011] Figure 3 is a depiction of grid stress calculation logic in accordance with one or more embodiments of the present disclosure;

[0012] Figure 4 is a depiction of the logic employed by a smart load in determining whether to activate in accordance with one or more embodiments of the present disclosure;

[0013] Figure 5 is a block diagram depicting a plurality of behind-the-meter connections in accordance with one or more embodiments of the present disclosure;

[0014] Figures 6A and 6B are depictions of grid stress calculation logic with respect to a power system that includes a secondary and tertiary control system in accordance with one or more embodiments of the present disclosure;

[0015] Figure 7 is a flow diagram of a method for autonomously and automatically interleaving cycled loads coupled to a grid, in accordance with one or more embodiments of the present disclosure; and

[0016] Figure 8 is a flowchart of a method for providing protection for electric vehicle supply equipment (EVSE) and electric vehicle (EV) chargers, in accordance with one or more embodiments of the present disclosure.DETAILED DESCRIPTION

[0017] Embodiments of the present disclosure generally relate to improved methods and apparatus for providing intelligent protection systems for electric vehicle supply equipment (EVSE) and electric vehicle (EV) chargers. For example, a method for providing protection for electric vehicle supply equipment (EVSE) and electric vehicle (EV) chargers comprises calculating a grid stress, comparing a calculated grid stresswith a requested EV power and selecting a minimum of the calculated grid stress or the requested EV power, and transmitting the minimum to the EV for setting a charging threshold of the EV to ensure that EV charging does not stress the grid.

[0018] Figure 1 is a block diagram of a power system (a system 100) in accordance with one or more embodiments of the present disclosure. This diagram only portrays one variation of the myriad of possible system configurations. The present disclosure can function in a variety of environments and systems.

[0019] The system 100 comprises a utility 102 (such as a conventional commercial utility) and a plurality of microgrids 150-1 , 150-2, ..., 150-X (collectively referred to as microgrids 150) coupled to the utility 102 via a utility grid 104. Through the connections to the utility grid 104, each microgrid 150 as a whole may receive energy from the utility grid 104 or may place energy onto the utility grid 104. Each microgrid 150 is capable of operating without energy supplied from the utility 102 and may cover a neighborhood, a village, a small city, orthe like, as the term microgrid is not intended to imply a particular system size. Although only the microgrid 150-1 is depicted in detail in Figure 1 and described herein, the microgrids 150-2 through 150-X are analogous to the microgrid 150-1. The number and / or type of various microgrid components, however, may vary among the microgrids 150.

[0020] The microgrid 150-1 comprises a plurality of 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 utility grid 104 via an island interconnect device (IID) 134 for disconnecting from / connecting to the utility grid 104. The local grid 132 may be a trunk of the utility grid 104 or it may be a specifically designed local grid for the microgrid 150-1 . Although only the microgrid member 152-1 is depicted in detail

[0021] in Figure 1 and described herein, the microgrid members 152-2 through 152- M are analogous to the microgrid member 152-1 , although the number and / or types of various microgrid member components may vary among the microgrid members 152.

[0022] The microgrid member 152-1 comprises a building 116 (e.g., a residence, commercial building, or the like) coupled to a load center 126 which may be within or outside of the building 1 16. The load center 126 is coupled to the local grid 132 via a utility meter 120 (which measures the ingress and egress of energy for the microgridmember 152-1) and a local HD 122 for disconnecting from / connecting to the local grid 132, and is further coupled to a DER 106 (distributed energy resource) and one or more smart loads 118. Each of the smart loads 118 is a cycled load that typically runs at low duty cycles (e.g., refrigerators, well pumps, furnaces in well-insulated homes, and the like) and often pull very high power (e.g., electric dryers, washing machined, and the like), obtained via the load center 126. Although depicted within the building 116, one or more of the smart loads 118 may be located outside of the building 116. Each of the smart loads 118 comprises one or more components for measuring grid parameters, such as grid frequency and / or grid voltage, and a component controller (e.g., a smart load controller 128), described in detail further below with respect to Figure 2, for implementing the techniques described herein. In some embodiments, the smart load controller 128 may measure the grid frequency and / or voltage.

[0023] The DER 106 comprises power conditioners 1 10-1 ... 110-N, 110-N+1 coupled in parallel to a bus 124 that is further coupled to the load center 126. Generally the power conditioners 110 are bi-directional power conditioners and those power conditioners 110 in a first subset of power conditioners 110 are coupled to DC energy sources 112 (for example, renewable energy sources such as wind, solar, hydro, and the like) while the power conditioners 110 in a second subset of power conditioners 110 are coupled to energy storage devices 1 14 (e.g., batteries, flywheels, compressed air storage, hot water heaters, electric cars, or the like). The combination of a DC energy source 112 and a power conditioner 1 10 may be referred to herein as a DER generator. In embodiments where the power conditioners 110 are DC-AC inverters, a power conditioner 110 and the energy storage device 114 may together be referred to herein as an AC battery 180. Each of the power conditioners 110 comprises a controller for operating the power conditioner 1 10.

[0024] The DER 106 comprises a DER controller 108 that is coupled to the bus 124 and communicates with the power conditioners 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, and the like), and the like. In some embodiments, the DER controller 108 is further coupled, by wireless and / or wired techniques, to a master controller (system controller) or gateway (not shown) via a communicationnetwork (e.g., the Internet) for communicating data to / receiving data from the master controller (e.g., system performance information and the like). In at least some embodiments, the DER controller 108 can be configured as the system controller and / or the gateway.

[0025] Each of the power conditioners 110 is a droop-controlled power conditioner such that when the microgrid member 152-1 is disconnected from the local grid 132 and / or the utility grid 104, the power conditioners 110 employ a droop control technique for parallel operation without the need for any common control circuitry or communication between the power conditioners 110. Each of the power conditioners 110 comprises a power conditioner controller having at least one processor, support circuits, and a memory comprising an operating system (as needed) and a droop control module for implementing the droop control techniques, thereby allowing the power conditioners 110 to share the load in a safe and stable manner.

[0026] As noted above, each of the smart loads 118 is a cycled load that typically runs at low duty cycles (e.g., refrigerators, well pumps, furnaces in well-insulated homes, and the like) and often pull very high power (e.g., electric dryers, washing machined, and the like), obtained via the load center 126. Although depicted within the building 116, one or more of the smart loads 118 may be located outside of the building 116.

[0027] Each of the smart loads 118 comprises one or more components for measuring grid parameters, such as grid frequency and / or grid voltage, and the smart load controller 128, described in detail further below with respect to Figure 2, for implementing the techniques described herein. In some embodiments, the smart load controller 128 may measure the grid frequency and / or voltage.

[0028] In accordance with one or more embodiments of the present disclosure, each of the smart loads 118 autonomously determines a measure of local grid stress and autonomously determines when to activate (turn on) and / or deactivate ( turn off) as described in detail below such that the likelihood of multiple loads on the local grid 132 activating at the same time is reduced or eliminated in order to prevent the level of grid stress from exceeding a desired threshold.

[0029] Figure 2 is a block diagram of the smart load controller 128 in accordance with one or more embodiments of the present disclosure. The smart load controller 128 (which may simply be referred to as “controller 128”) comprises support circuits 204and a memory 206, each coupled to a CPU 202 (central processing unit). The CPU 202 may comprise one or more conventionally available microprocessors or microcontrollers. Alternatively, the CPU 202 may include one or more application specific integrated circuits (ASICs). The smart load controller 128 may be implemented using a general purpose computer that, when executing particular software, becomes a specific purpose computer for performing various embodiments of the present disclosure. In one or more embodiments, the CPU 202 may be a microcontroller comprising internal memory for storing controller firmware that, when executed, provides the controller functionality described herein.

[0030] The support circuits 204 are well known circuits used to promote functionality of the CPU 202. Such circuits include, but are not limited to, a cache, power supplies, clock circuits, buses, input / output (I / O) circuits, and the like.

[0031] 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 is sometimes referred to as main memory and may, in part, be used as cache memory or buffer memory. The memory 206 generally stores the OS 208 (operating system), if necessary, of the smart load controller 128 that can be supported by the CPU capabilities. In some embodiments, the OS 208 may be one of a number of commercially available operating systems such as, but not limited to, LINUX, Real-Time Operating System (RTOS), and the like.

[0032] The memory 206 stores various forms of application software, such as an automatic interleaving module 210 for, when executed, implementing the techniques described herein to autonomously determine activation and / or deactivation of the corresponding smart load.

[0033] The memory 206 additionally stores a database 212, for example for storing data related to the operation of the corresponding smart load and / or the disclosure described herein, such as one or more thresholds (e.g., thresholds for grid stress, activation, and deactivation), and the like.

[0034] Figure 3 is a depiction of grid stress calculation logic in accordance with one or more embodiments of the present disclosure. The logic depicted in Figure 3 may be implemented by the smart load controller 128 (or by the DER controller 108).

[0035] Each smart load 118 employs a droop control based technique to perform a grid stress calculation to determine whether the grid can manage its activation or requires its deactivation at that particular time so as not to exceed a particular grid stress level (i.e. , a grid stress level threshold, which may also be referred to as a grid stress threshold or simply a stress threshold). Both grid voltage and grid frequency are utilized in indicating the grid stress at a given time, although in some other embodiments one or the other alone is used in determining the grid stress.

[0036] As depicted in Figure 3, measured grid voltage and measured grid frequency are each compared (at 302 and 304, respectively) to a corresponding reference signal, which provides an indication of the amount the grid voltage and frequency drooping, and the resulting outputs are each multiplied by a corresponding coefficient (G1 and G2, respectively) analogous to a droop gain. The resulting outputs are added together at adder 306 to generate an indication of an amount of active current that would be injected onto the grid by a generator employing droop control. The greater the amount of active current that would be injected, the greater the stress of the grid. The computed amount of active current is then compared with a reference stress value to obtain a measure of grid stress (which may also be referred to as a grid stress value or computed grid stress) in units of percent 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 the active, reactive, or apparent current / power (where apparent2= active2+ reactive2).

[0037] In one or more embodiments where the AC power system utilizes a primary regulation technique where generation assets are programmed to respond to V / F, the value of G1 may be set to the Watts-to-Volts aggregate response in %N, and G2 may be set to the Watts-to-Hz aggregate response in % / Hz. For example, in embodiments where the system only has frequency governing action on generation assets (i.e., the system is only running frequency droop) and having one 100 kW generator with 20 kW / Hz droop action and one 50 kW generator with 15 kW / Hz droop action, G1 = 0 since only frequency droop is being run (i.e., voltage is not being addressed), and G2 is the aggregate of the two system generators where the sum of the droop action of the generators is divided by the sum of the total capacity to obtain the total percentage of frequency action:G2 = (20kW / Hz + 15kW / Hz) I (1 OOkW + 50kW) = 23% / Hz.

[0038] The grid stress threshold is set such that activation of a load (i.e., turning on the load) does not push the system over its rated capacity. For example, for a capacity of 150 kW and a 10 kW load, the maximum stress threshold would equal (150-10) / 150 = 93.3% - i.e., if the system would need to be operating at a minimum of 140 kW in order for the load to turn on without driving the system above its rated capacity. In one or more embodiments, a margin may be added to the grid stress threshold, for example on the order of 5-10%; in certain embodiments, the grid stress threshold margin may be dynamically determined.

[0039] By utilizing the techniques described herein, smart loads not having an immediate urgency to turn on and having some flexibility as to when they can turn on (e.g., well pumps, motors, and the like) have an automated means by which they can strategically turn on when the system has sufficient power to support them. Each load can independently and autonomously evaluate the stress on the grid at a particular time and determine whether the grid has sufficient power for the load to operate at that time.

[0040] For example, a neighborhood of five homes all running off-grid and all interconnected together may all be running a well, where a switch turns on a home’s well pump when the well’s pressure tank drops below a certain pressure and turns off the pump when the pressure reaches a particular threshold, e.g., the well pump may turn on at 40 PSI and turn off at 70 PSI. In order to prevent all of the well pumps from activating at the same time and thereby increasing the grid stress above a desired level, each well pump employs the techniques described herein to automatically ensure they’re not turning on at the same time and are automatically interleaved so that the system isn’t required to support them all being on at the same time.

[0041] Figure 4 is a depiction of the logic employed by a smart load in determining whether to activate in accordance with one or more embodiments of the present disclosure. The logic depicted in Figure 4 may be implemented by the smart load controller 128 (or the DER controller 108).

[0042] As shown in Figure 4, the computed grid stress and the grid stress threshold (which may be referred to as an activation threshold) are inputs to a comparator 402 (e.g., grid stress threshold), with the comparator circuit output indicating when the gridhas sufficient power to support the load (i.e. , when the computed grid stress is less than the grid stress threshold). The comparator output is fed to an AND gate 404 along with a request to turn on when the load would like to activate. Continuing the well pump example described above, the load 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 whether the grid has sufficient power to support the load. A logical high output of the AND gate 404 indicates that the grid has sufficient power to accept the load turning on at the time that the load wants to turn on.

[0043] The output of the AND gate 404 is fed into the enable input of a latch, i.e., a first counter 406, which acts as a delay and begins counting up when the enable input is high (i.e., when the load wishes to turn on and the grid has sufficient powerto accept the load). When the enable input is zero -i.e., when one or both of the grid stress being above the grid stress threshold or the load not wanting to activate occurs- the count is reset (e.g., to zero). By initiating a delay (which may be referred to as a turnon delay) when a load wants to activate and the grid can accept it, the resulting randomization reduces or eliminates the likelihood of loads turning on at the same time and driving the grid stress above a desired threshold. The output of the first counter 406 is fed into the non-inverting input of a second comparator 414.

[0044] A second counter 408 receives the output from the comparator 402 (i.e., the indication of whether the grid can support the load at the time it wishes to turn on) to its clock input and the load turn-on request to its reset input. The second counter 408 is reset when the load no longer wants to turn on. When the grid is able to support the load at the time it wishes to turn on but during the turn-on delay the amount of power on the grid has changed (e.g., due to one or more other loads activating) such that the grid can no longer support the load, the second counter 408 increments to indicate the number of these missed turn-on opportunities that occur. The resulting number of missed turn-on opportunities is fed into a lookup table 410, the output of which is fed to a randomizer 412.

[0045] The lookup table 410 enables the turn-on delay to be adjusted based on the number of missed turn-on opportunities. For example, the first time the load wants toturn on it can be assigned a relatively long delay, and subsequent delays are made successively shorter each time a turn-on opportunity is missed by the load. By continually reducing the length of subsequent delays, the likelihood that the load will be able to turn on increases the longer the load waits. The randomizer 412 decreases the likelihood that multiple loads will turn on at the same time. For example, it decreases the likelihood that multiple loads within the same system and using identical lookup tables (e.g., all made by the same manufacturer) will select the same value in the lookup tables and turn on at the same time. The output of the randomizer 412 is fed to the inverting input of the second comparator 414.

[0046] In embodiments, depending on the type of smart load, adaptive control based on a current state of the smart load (e.g., refrigerator temperature, tank water pressure, air temperature, and the like) may be used to provide an adaptive, statedependent turn-on delay (e.g., as depicted in Figure 4, the output of such adaptive control 416 may be fed into the lookup table). Continuing the example of the water pump, when the pressure drops to a first low threshold, e.g., 40 PSI, the water pressure may still be satisfactory to users and so the turn-on delay can be relatively high. If the water pressure falls below a second low threshold while waiting to turn on, e.g., 30 psi, the need to turn on becomes more urgent as the danger increases of the water pressure dropping so low that it’s not usable. At such time, the turn-on delay can be suitably adjusted to a lower amount. For example, for a smart load that is a refrigerator compressor, the load may measure the internal temperature of the refrigerator and raise the urgency for turning on if the temperature rises to a point where the food might spoil. Other examples of smart load that can make a determination of its current state and according adjust a turn-on delay include HVAC devices (thermostats, air conditioners, heaters, and the like), water pressure devices, and the like.

[0047] Figure 5 is a block diagram depicting a plurality of behind-the-meter connections in accordance with one or more embodiments of the present disclosure. As shown in Figure 5, a plurality of smart loads 118-1 , 118-2...118-K, each having a corresponding controller 128-1 , 128-2. ,.128-K, and an energy storage unit 502 are behind the utility meter 120 and are coupled to the load center 126. Although depictedwithin the building 116, one of more of the smart loads 118-1 , 118-2...118-K and the energy storage unit 502 may be located outside of the building 1 16.

[0048] As previously described, the smart loads 118-1 , 118-2...118-K typically run at low duty cycles and often pull very high power, e.g., refrigerators, well pumps, furnaces, air conditioners, electric dryers, washing machines, and the like. The energy storage unit 502 may be any suitable device that can store and deliver energy. In some embodiments, the energy storage unit 502 may also have a controller, analogous to the smart load controller 128, for controlling the unit’s energy storage and / or delivery. Although a single energy storage unit is shown, other embodiments may have additional energy storage units or no energy storage unit.

[0049] In embodiments, one or more of the smart loads 118-1 , 118-2...118-K and the energy storage unit 502 may be connected to analogous smart loads and / or energy storage units in another microgrid member 152 via an electrical connection that is not part of the utility grid 104 / local grid 132 such that the flow of power between loads and / or energy storage units bypasses the utility grid. For example, the load center 126 and an analogous load center in another microgrid member 152 may be coupled to one another via an electrical cable, separate from the utility grid, such that energy may bypass the utility grid and flow between components of the microgrid members 152 (e.g., DERs 106, smart loads 118, energy storage units 502). In some of such embodiments, one or more of the DERs 106, smart loads 118, and energy storage units 502 may control the energy flow over the electrical cable, while in other such embodiments a separate device may be utilized to control the energy flow over the electrical cable. For example, the microgrid member 152 may comprise an energy flow control device for controlling such energy flow. In some of these embodiments, the energy flow control devices may be coupled to the load centers (or may be part of the load centers) of their corresponding microgrids for controlling the energy flow. In other embodiments, the energy flow control devices may be coupled to components of their corresponding microgrid members and to one another without the use of a load center.

[0050] As noted above, improved methods and apparatus for providing protection for electric vehicle supply equipment (EVSE) and electric vehicle (EV) chargers are provided herein. For example, Figures 6A and 6B are depictions of grid stresscalculation logic with respect to a power system that includes a secondary and tertiary control system in accordance with one or more embodiments of the disclosure. The logic depicted in Figures 6A and 6B may be implemented by the smart load controller 128 (or the DER controller 108). For example, to alleviate the poor user experience related to the standard approach, the inventors provide a two-level control and protection scheme for use with EVSE and / or EV chargers.

[0051] For example, the grid stress calculation logic shown in Figure 6A differs from that shown in Figure 3 in that the power system corresponding to Figure 6A includes a secondary / tertiary control system which re-centers the voltage and frequency using system wide communications, and these biases are included in the grid stress calculation. For example, as shown in Figure 6A, at adder 602 the voltage bias from the secondary control system is added to the output from 302. The result is multiplied by the coefficient G1 and coupled to the adder 306. At adder 604 the frequency bias from the secondary control system is added to the output from 304. The result is multiplied by the coefficient G2 and coupled to the adder 306. At adder 308, the output from the adder 306 is added to a reference stress from the tertiary control system. The output from the adder 308 is the computed grid stress.

[0052] Next, an upper level requested power from a system optimizer 606 (which can be stored in the DER controller 108 or the gateway and / or the cloud connected to the DER controller 108) is compared to the translation of grid stress to stress based maximum power. A minimum function module 607 determines the minimum of the upper level requested power and the stress based maximum power. The minimum is then sent to an EV 608, thus providing slow microgrid protection ensuring that the EV 608 charging never stresses the grid much. Additionally, the local algorithm of Figure 6A ensures good user experience irrespective of optimization signal update times, or local changes that a system controller (e.g., the DER controller 108) has yet to react to, e.g., such as clouding. Additionally, a transform G3 can be connected to the minimum function module 607 and maps a grid stress level to desired EV power based upon the system aggregate droop response and the specific EV charger rated power. For example, in at least some embodiments, the transform G3 can use mathematical scaling or conversion on the grid stress received from the adder 306 and / or the adder 308 and can input the mapped stress based maximum power to the minimum functionmodule 607 to determine the minimum of the upper level requested power and the stress based maximum power.

[0053] With reference to Figure 6B, a second level of protection is the instantaneous opening of a contactor (e.g., a relay 610) in the EVSE that connects to the EV 608. For example, in at least some embodiments, opening the relay 610 can be determined by comparing at a comparator 611 the computed grid stress with a preset system grid stress disconnect reference 612, which can be configurable via system software (e.g., provided in the smart load controller 128 and / or the EVSE) that can be configured for use with various systems (e.g., the system 100 and similar systems). In some cases, multiple grid stress disconnect references are stored locally in the EVSE and one value is selected based on the system configuration i.e., on-grid, off-grid, microgrid etc. The system controller performance is guaranteed by the EVSE, so multiple different EVs can be connected without worrying about specific EV on-board electronics settings. In at least some embodiments, a hysteresis module 614 determines hysteretic behavior and can be used for the re-enablement of the EVSE.

[0054] Figure 7 is a flow diagram of a method for autonomously and automatically interleaving cycled loads coupled to a grid, in accordance with one or more embodiments of the present disclosure. The method 700 is an implementation of the automatic interleaving module 210; in some embodiments, a non-transitory computer readable medium comprises a program that, when executed by a smart load controller, performs the method 700 that is described below. In various embodiments, smart loads coupled to a grid employ the technique described below to decrease the likelihood that more than one of the loads will activate at the same time and thereby increase the level of stress on the grid above a desired threshold.

[0055] The method 700 starts at step 702 and proceeds to step 704. At step 704, a local grid stress value for a load having 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 less than an activation threshold. The activation threshold is a grid stress threshold, determined as described above. If the result of the determination is no, that the local grid stress level is not less than the activation threshold (i.e., the grid does not have sufficient power to support the load at that time), the method 700 proceeds to step 707, where a determination is madewhether the load still has a request to activate. If the result of the determination at step 707 is yes, that the load should still activate, the method 700 returns to step 704; if the results of the determination at step 707 is no, that the load should not still turn on, the method proceeds to step 730 where it ends.

[0056] If, at step 706, the result of the determination is yes, that the local grid stress value is less than the activation threshold, the method 700 proceeds to step 708. At step 708, a delay period is activated where the load waits a delay time as described above. The method 700 then proceeds to step 710, where an updated local grid stress value is determined; in some embodiments, local grid stress value is periodically (e.g., continuously or near-continuously) updated based on current local grid conditions.

[0057] 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 periodically updated, for example when changes to the grid occur. If, at step 712, the result of the determination is no, that the local grid stress level is no longer less than the activation threshold, the method 700 proceeds to step 714.

[0058] At step 714, a determination is made whether the load still has a request to activate. If, at step 714, the result of the determination is yes, that the load should still activate, the method 700 proceeds to step 716 where a count of the number of activation attempts is incremented. The method 700 returns to step 708, where a delay period, which may be modified as described above, is entered.

[0059] If, at step 714, the result of the determination is no, that the load no longer has a request to activate and should not turn on, the method 700 proceeds to step 718 where the count of the number of activation attempts is zeroed out, and the method 700 proceeds to step 730 where it ends. In at least some embodiments, steps 714 to 718 of the method 700 can be omitted.

[0060] If, at step 712, the result of the determination is yes, that the updated local grid stress value is less than the activation threshold, the method 700 proceeds to step 720 where the load activates. At step 722, a determination is made whether it is desired that load remain active. If, at step 722, the result of the determination is no, that the load should not remain active, the method 700 proceeds to step 728 where the load deactivates, and then to step 730 where the method 700 ends.

[0061] If, at step 722, the result of the determination is yes, that the load should remain active, the method 700 proceeds to step 724 where an updated local grid stress value is determined. The method 700 proceeds to step 726, where a determination is made whether the updated local grid stress value is less 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.

[0062] If, at step 722, the result of the determination is yes, that the updated local grid stress value is less than the deactivation threshold, the method 700 returns to step 722. If, at step 722, the result of the determination is no, that the updated local grid stress value is not less than the deactivation threshold, the method 700 proceeds to step 728 where the load deactivates, and then to step 730 where the method 700 ends.

[0063] Figure 8 is a flowchart of a method for providing protection for electric vehicle supply equipment (EVSE) and electric vehicle (EV) chargers, in accordance with one or more embodiments of the present disclosure.

[0064] For example, at 802, the method 800 comprises calculating a grid stress. For example, the grid stress can be calculated by the DER controller 108 using the method 700. As noted above, the steps 714-718 of the method 700 can be omitted, such as when the method 700 is used in conjunction with the method 800 to calculate the grid stress.

[0065] In at least some embodiments, the method 700 can be omitted, as such a) the method 800 and logic in Figure 6A is used in parallel with b) the logic in Figure 6B. In parallel, both algorithms a) and b) are running simultaneously.

[0066] Next, at 804, in at least some embodiments, the method 800 comprises comparing the translation of grid stress to stress based maximum power with a requested EV power and selecting a lessor of the calculated stress based maximum power or the requested EV power (e.g., a minimum value). For example, at 804 an upper level requested power (e.g., desired EV power based on EV rated power) from the system optimizer 606 (at the gateway or the cloud) can be compared to the computed grid stress (e.g., a stress based maximum power) at the minimum functionmodule 607 that determines a minimum of the upper level requested power and the stress based maximum power.

[0067] Next, at 806, the method 800 comprises transmitting the minimum value (e.g., charging threshold) to the EV for setting the charging threshold of the EV to ensure that EV charging does not stress the grid. In at least some embodiments, the system controller (e.g., at the gateway or the cloud) sets the EV power by setting a pulse width modulation (PWM) to a reduced rate on a control pilot of the EVSE or the EV or zeroing the control pilot. For example, the system optimizer 606 can send, via the gateway (or cloud), optimization set points (e.g., the calculations) to the DER controller 108 which can then send the optimization set points to the EVSE and / or EV charger. In at least some embodiments, the system optimizer 606 can send, via the gateway (or cloud), optimization set points directly to the EVSE and / or EV charger. For example, in at least some embodiments, such as when the EV is in a car park with multiple TCP / IP connected EVSE’s in a microgrid, the system optimizer 606 can send the optimization set points directly to the EVSE and / or EV charger.

[0068] In at least some embodiments, at 804, the method 800 can comprise mapping a grid stress level to a desired EV power based on EV rated power and the aggregate of the systems online DER generators (e.g., the power conditioner 1 10).

[0069] For example, as noted above, mapping can comprise mathematical scaling or conversion to a stress based maximum power, e.g., the minimum function module 607 can use the mapped stress based maximum power (e.g., the mapped grid stress level) to determine the minimum of the upper level requested power and the stress based maximum power. Accordingly, in at least some embodiments, the system controller (e.g., at the gateway or the cloud) is further configured to monitor the grid stress and open a relay if the grid stress is equal to or greater than a preset system grid stress and / or after a specific time frame.

[0070] In at least some embodiments, the method 800 can comprise (e.g., using circuitry of Figure 6B) monitoring the grid stress and opening a relay if the grid stress is equal to or greater than a preset system grid stress and / or after a specific time frame. For example, in at least some embodiments, the DER controller 108 can be configured to open the relay 610 if, after comparing at the comparator 611 , the computed grid stress is equal to or exceeds a preset system grid stress disconnectreference 612 and / or for a predetermined amount of time, e.g., shorter than brown out conditions, such as for example 80 ms.

[0071] While the foregoing is directed to embodiments of the present disclosure, other and further embodiments of the disclosure may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.

Claims

WHAT IS CLAIMED IS:1 . A method for providing protection for electric vehicle supply equipment (EVSE) and electric vehicle (EV) chargers, comprising: calculating a grid stress; comparing a calculated grid stress with a requested EV power and selecting a minimum of the calculated grid stress or the requested EV power; and transmitting the minimum to the EV for setting a charging threshold of the EV to ensure that EV charging does not stress the grid.

2. The method of claim 1 , wherein setting the charging threshold of the electric vehicle (EV) comprises at least one of setting a PWM to a reduced rate on a control pilot of the EVSE or the EV or zeroing the control pilot.

3. The method of claim 1 , further comprising monitoring the grid stress and opening a relay if the grid stress is equal to or greater than a preset system grid stress and / or after a specific time frame.

4. The method as in any of claims 1 to 3, further comprising mapping a grid stress level to desired EV power based on a system aggregate droop response and a specific EV charger rated power and using the mapped grid stress level when comparing the calculated grid stress with the requested EV power.

5. A non-transitory computer readable storage medium having instructions stored thereon which when executed by a processor perform a method for providing protection for electric vehicle supply equipment (EVSE) and electric vehicle (EV) chargers, comprising: calculating a grid stress; comparing a calculated grid stress with a requested EV power and selecting a minimum of the calculated grid stress or the requested EV power; and transmitting the minimum to the EV for setting a charging threshold of the EV to ensure that EV charging does not stress the grid.

6. The non-transitory computer readable storage medium of claim 5, wherein setting the charging threshold of the electric vehicle (EV) comprises at least one of setting a PWM to a reduced rate on a control pilot of the EVSE or the EV or zeroing the control pilot.

7. The non-transitory computer readable storage medium of claim 5, further comprising monitoring the grid stress and opening a relay if the grid stress is equal to or greater than a preset system grid stress and / or after a specific time frame.

8. The non-transitory computer readable storage medium as in any of claims 5 to 7, further comprising mapping a grid stress level to desired EV power based on a system aggregate droop response and a specific EV charger rated power and using the mapped grid stress level when comparing the calculated grid stress with the requested EV power.

9. An apparatus for providing protection for electric vehicle supply equipment (EVSE) and electric vehicle (EV) chargers, comprising: a controller configured to: calculate a grid stress; compare a calculated grid stress with a requested EV power and select a minimum of the calculated grid stress or the requested EV power; and transmit the minimum to the EV for setting a charging threshold of the EV to ensure that EV charging does not stress the grid.

10. The apparatus of claim 9, wherein when setting the charging threshold of the electric vehicle (EV), the controller is further configured to at least one of set a PWM to a reduced rate on a control pilot of the EVSE or the EV or zeroing the control pilot.

11. The apparatus of claim 9, wherein the controller is further configured to monitor the grid stress and open a relay if the grid stress is equal to or greater than a preset system grid stress and / or after a specific time frame.

12. The apparatus as in any of claims 9 to 11 , wherein the controller is further configured to map a grid stress level to desired EV power based on a system aggregate droop response and a specific EV charger rated power and use a mapped grid stress level when comparing the calculated grid stress with the requested EV power.

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