Systems and methods for dynamically prioritized allocation and real-time smart charge management of electric vehicles ensuring minimal impact to utility and vehicles

Abstract

A controller system with a smart charging algorithm for managing charging of EVs in a fleet at a utility customer site is provided. The utility customer site has the ability to connect and disconnect from the utility power grid and to also receive power from a number of distributed energy resources (DERs). The controller system prioritizes the following control objectives: (1) charging all EVs to their desired state of charge within available dwell time; (2) keeping active power imports from the grid lower than the utility's contractual interconnection agreement; (3) maintaining active power imports from the grid with ramp-rate limits at the point of common coupling; (4) optimizing the use of DERs (e.g., minimizing curtailment of a PV system and keeping a battery energy storage system charged for future use ensuring minimal degradation); and (5) minimizing charging energy cost, i.e., addressing demand charges and time of use based energy cost.

Description

P24-1478(GOV)WOQ1SYSTEMS AND METHODS FOR DYNAMICALLY PRIORITIZED ALLOCATION AND REAL-TIME SMART CHARGE MANAGEMENT OF ELECTRIC VEHICLES ENSURING MINIMAL IMPACT TO UTILITY AND VEHICLESCROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Patent Application Serial No. 63 / 728,280, filed December 5, 2024 entitled, “Systems And Methods For Dynamically Prioritized Allocation And Real-Time Smart Charge Management Of Electric Vehicles Ensuring Minimal Impact To Utility And Vehicles” the disclosure of which is incorporated herein by reference.GOVERNMENT CONTRACT

[0002] This invention was made with government support under Other Transaction for Prototype Agreement number W9132T239C015 awarded by the U.S. Government. The government has certain rights in the invention.FIELD OF THE INVENTION

[0003] The disclosed concept relates generally to electric vehicles, and in particular, to systems and methods for optimizing charging of electric vehicles.BACKGROUND OF THE INVENTION

[0004] The U.S. transportation sector, a major greenhouse gas emitter, needs to transition to electric vehicles (EVs) in order to meet climate goals. While much attention has been focused on passenger EVs, there is significant opportunity in electrifying vehicle fleets for further reduction of emissions. However, this transition presents several challenges. One challenge is that an existing vehicle fleet site may have insufficient charging capacity: considering the size of a typical vehicle fleet, an existing vehicle fleet site may only be able to accommodate a limited number of EV chargers and have limited feeder capacity such that there is a likelihood that not all of the vehicles in a vehicle fleet can be fully charged within their dwell time constraints if the entire fleet is converted to EVs. Another challenge is increased peak power demands: equipping an existing vehicle fleet site to accommodate EV charging could cause the EV charging at the site to add significantly to the power demand (on the order of megawatts), potentially coincidingP24-1478(GOV)WOQ1 with the utility distribution feeder’s peak load, thereby worsening the overall peak demand. The utility may then enforce maximum demand limits that the site would be required to comply with. Another challenge is distribution feeder strain: increased peak demand may strain the distribution feeder, necessitating costly upgrades or curtailments. Another challenge is grid ramp-rate violations: EV charging ramp-rates may violate grid ramp-rate requirements, introducing voltage fluctuations and other power quality issues, thus affecting quality of power supply and reliability issues, and potentially leading to power outages. Another challenge is operational costs: unmanaged fleet charging could lead to higher operational costs due to demand charges and time-of-use (ToU) tariffs.

[0005] There is thus room for improvement in methods and systems for charging electric vehicle fleets.SUMMARY OF THE INVENTION

[0006] These needs, and others, are met by embodiments of a controller system equipped with a smart charging algorithm for managing charging of EVs in an EV fleet at a utility customer site. Based on the operation mode of the fleet power distribution system at the utility customer site (either grid-connected mode or islanded mode) and several other input parameters, the smart charging algorithm dynamically prioritizes allocation of chargers to specific EVs and then sends commands to the site operator to respectively connect and disconnect uncharged and charged EVs to / from specific chargers. The input parameters can include: constraints from grid interconnection data (such as peak demand, maximum ramp-up rate, maximum ramp-down rate), vehicle data for each EV (such as battery size, maximum charging rate, real time state of charge), and DER data (such as maximum charge / discharge settings and current output power). The smart charging algorithm then generates setpoints for the grid rectifier, chargers, DERs, and other non-EV site loads. The setpoints always fall in one of the seven categories at any time step.

[0007] In one embodiment of the disclosed concept, a controller system configured to manage charging of a plurality of EVs in a fleet at a utility customer site is provided. The utility customer site comprises a plurality of entities, the plurality of entities including: a fleet power distribution system, a grid interface serving as a point of common coupling that connects the utility customer site to a utility power grid, a plurality of EV chargers electrically connected toP24-1478(GOV)WOQ1 the fleet power distribution system, a number of DERs, a fleet site operator, and a number of site loads that are not EVs. The fleet power distribution system is configured to be connected and disconnected from a plurality of power sources, the plurality of power sources including the utility power grid and the number of DERs. The fleet power distribution system is configured to supply power to the EV chargers. The controller system comprises a smart charging algorithm and is configured to communicate with the plurality of entities at the utility customer site. By executing the smart charging algorithm, the controller system is configured to: identify which EV in the fleet to next allocate to an available EV charger of the plurality of EV chargers; determine a rate of charging of each EV in real time while monitoring power imported from all of the power sources to the fleet power distribution system, the power sources including the utility power grid, the number of DERs, and any of the EVs operating in export mode; and for a given one of the EVs, identifying when the given EV is charged.

[0008] In another embodiment of the disclosed concept, a method for managing charging of a plurality of EVs in a fleet at a utility customer site is provided. The utility customer site comprises a plurality of entities, the plurality of entities including: a fleet power distribution system, a grid interface serving as a point of common coupling that connects the utility customer site to a utility power grid, a plurality of EV chargers electrically connected to the fleet power distribution system, a number of DERs, a fleet site operator, and a number of site loads that are not EVs. The fleet power distribution system is configured to be connected and disconnected from a plurality of power sources, the plurality of power sources including the utility power grid and the number of DERs. The fleet power distribution system is configured to supply power to the EV chargers. The method comprises: providing a controller system configured to communicate with the plurality of entities at the utility customer site, the controller system comprising a smart charging algorithm; and executing the smart charging algorithm with the controller system. Executing the smart charging algorithm comprises: identifying, with the controller system, which EV in the fleet to next allocate to an available EV charger of the plurality of EV chargers; determining, with the controller system, a rate of charging of each EV in real time while monitoring power imported from all of the power sources to the fleet power distribution system, the power sources including the utility power grid, the number of DERs, and any of the EVs operating in export mode; and for a given one of the EVs, identifying with the controller system when the given EV is charged.P24-1478(GOV)WOQ1BRIEF DESCRIPTION OF THE DRAWINGS

[0009] A full understanding of the invention can be gained from the following description when read in conjunction with the accompanying drawings in which:

[0010] FIG. 1 is a symbolic diagram showing an innovative controller system according to an example embodiment of the disclosed concept in communication with the charging infrastructure required to charge a fleet of EVs at a utility customer site; and

[0011] FIG. 2 is a flow chart of a smart charging algorithm executed by the controller system of FIG. 1 , in accordance with an example embodiment of the disclosed concept.DETAILED DESCRIPTION OF THE INVENTION

[0012] Directional phrases used herein, such as, for example, left, right, front, back, top, bottom and derivatives thereof, relate to the orientation of the elements shown in the drawings and are not limiting upon the claims unless expressly recited therein.

[0013] As used herein, the singular form of “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise.

[0014] As employed herein, employed herein, when ordinal terms such as “first” and “second” are used to modify a noun, such use is simply intended to distinguish one item from another, and is not intended to require a sequential order unless specifically stated.

[0015] As employed herein, the term “controller” shall mean a programmable analog and / or digital device that can store, retrieve and process data; a processor; a control circuit; a computer; a workstation; a personal computer; a microprocessor; a microcontroller; a microcomputer; a central processing unit; a mainframe computer; a mini-computer; a server; a networked processor; or any suitable processing device or apparatus.

[0016] As employed herein, the term “number” shall mean one or an integer greater than one (i.e., a plurality).

[0017] Disclosed herein is an innovative controller system 100 for managing charging of an EV fleet that addresses the challenges of EV fleet charging iterated earlier herein. FIG. 1 depicts the disclosed innovative controller system 100 in communication with the charging infrastructure required to charge a fleet of EVs at a utility customer site, in accordance with an exemplary embodiment of the disclosed concept. In FIG. 1, the EVs currently being charged areP24-1478(GOV)WOQ1 numbered 1A and the EVs waiting to be charged are numbered IB, but any of the EVs 1A or IB can be referred to generally with the reference number 1. The EVs 1 are located at a utility customer site 2. Also located at the utility customer site 2 are various entities with which the controller 100 is configured to communicate, including: a plurality of EV chargers 5, a fleet power distribution system 10, a grid interface 11 that serves as the point of common coupling (PCC) to connect the utility customer site 2 to the utility power grid 12 (referred to hereinafter as the “grid 12” for brevity), a number of distributed energy resources (DERs) 13 such as a battery energy storage system (BESS) 14 and a photovoltaic (PV) system 16, a fleet site operator 20, and other site loads 30. It is noted that the utility customer site 2 can utilize onsite energy storage 14 of a form other than battery without departing from the scope of the disclosed concept. The fleet site operator 20 is a human machine interface (HMI) that enables the person(s) overseeing the charging of the EVs 1 to provide input to and receive input from the controller system 100. The other site loads 30 are the power consuming loads at the utility customer site 2 other than the EVs 1.

[0018] The fleet power distribution system 10 is configured to be electrically connected to a plurality of power sources, such as the grid 12 (through the grid interface 11) and the DERs 13, and the EV chargers 5 are electrically connected to the fleet power distribution system 10 in order to transmit power supplied by the plurality of power sources to any connected EVs 1 A. It is noted that, for any of the EVs 1 that have V2X (vehicle-to-everything) technology, those EVs 1 can act as a power source as necessary, by operating in export mode when connected to the fleet power distribution system 10 via a charger 5. It will be appreciated that the fleet power distribution system 10 includes a grid rectifier in order convert grid-supplied AC power to DC power for charging the EVs 1. It will be apparent from the description of the controller system 100 provided hereinafter that the controller system 100 is configured to adapt to there being different combinations and quantities of power sources to charge the EVs other than the specific combination of the grid 12, BESS 14, and PV system 16 shown in FIG. 1. For example, a utility customer site 2 can have more than one BESS 14 or more than one PV system 16 connected to the fleet power distribution system 10, and additional illustrative examples of specific types of DERs 13 include diesel generators and V2X-enabled EVs 1 operating in export mode. As such, it should be understood that the particular combination shown in FIG. 1 is provided as a nonlimiting illustrative example of the power sources that a fleet power distribution system 10 canP24-1478(GOV)WOQ1 have available to supply charging power to a fleet of EVs 1.

[0019] As used herein, the term “dwell time” refers to the time between an EV l’s arrival and departure from the utility customer site 2. Because the disclosed controller system 100 is configured to communicate with all of the entities at the utility customer site 2 as shown in FIG. 1, a utility customer site 2 equipped with the disclosed controller system 100 is expected to be able to comply with applicable utility interconnection agreements, sufficiently charge an EV fleet within the dwell time, reduce peak demand at the utility customer site 2, enhance utility feeder power quality and reliability, and minimize site operation related costs, particularly for EV fleets having megawatt-scale demand. The controller system 100 processes inputs such as EV fleet data, site design parameters, utility enforced requirements, and real-time power supply and demand measurements.

[0020] As will be detailed further in connection with the smart charging algorithm 200 shown in FIG. 2, the controller system 100 computes setpoints for chargers 5 connected to specific EVs 1 to charge said EVs 1 at specific rates, dispatches the on-site BESS 14, curtails the PV system 16 when needed, dispatches available V2X-enabled EVs 1 that are connected to a charger 5, and controls net power import from the grid 12. The controller system 100 prioritizes the following control objectives: (1) charging EVs 1 to their desired state of charge (SOC) within available dwell time; (2) keeping active power imports from the grid 12 lower than the utility’s contractual interconnection agreement; (3) maintaining active power imports from the grid with ramp-rate limits at the point of common coupling (PCC); (4) optimizing the use of DER systems (for example, minimizing curtailment of the PV system 16, keeping the BESS 14 charged for future use ensuring minimal degradation, and ensuring that any V2X-enabled EV 1 in export mode can be charged during dwell time); and (5) minimizing charging energy cost, i.e., addressing demand charges and time of use (ToU) based energy cost.

[0021] FIG. 2 is a flow chart of a smart charging algorithm 200 for an EV fleet executed by the controller system 100, in accordance with an exemplary embodiment of the disclosed concept. The smart charging algorithm 200 defines a lower limit (LL) and an upper limit (UL) for power import from the grid 12, based on the utility’s contractual power limit and ramp-rate requirements. This approach treats these limits as hard constraints, ensuring the reliability and quality of the electrical grid’s power supply. The controller system 100 takes real-time input data such as grid monitoring data, dispenser and chargers’ data, PV data, BESS data, EVs data,P24-1478(GOV)WOQ1 and control priority options. The controller system 100 then pre-processes the input data and passes the pre-processed input data to the smart charging algorithm 200. Additionally, the controller system 100 relays constraints such as grid interconnection requirements, chargers and dispenser constraints, PV and BESS constraints, and EV fleet requirements to the smart charging algorithm 200. As will become apparent from the discussion of the smart charging algorithm 200 that follows herein, the smart charging algorithm 200 ensures that all EVs 1 in the fleet are charged to their desired state of charge during their dwell time. This ensures that all EVs 1 can complete their next scheduled trip without depletion. The controller system 100 prioritizes the EV 1 to be charged next and computes the rate of charging for connected EVs 1A based on their dwell time and charging energy needs.

[0022] At a high level, the smart charging algorithm 200 sends commands to the site operator 20 to connect or disconnect uncharged / charged EVs 1 to / from specific chargers 5. It is noted that the algorithm 200 is configured to address operating mode-specific needs for each of a grid-connected mode and an islanded mode of the fleet power distribution system 10. The grid- connected mode is a mode in which the fleet power distribution system 10 is electrically connected to and able to receive power from the grid 12. The islanded mode is a mode in which the fleet power distribution system 10 is electrically isolated from the grid 12 and thus unable to receive power from the grid 12. In the present disclosure, it should be assumed that the fleet power distribution system 10 is configured to receive power from the DERs 13 (including from any V2X-enabled EVs 5 operating in export mode) when the fleet power distribution system 10 is in the islanded mode. It is noted that the BESS 14, the PV system 16, and any V2X-enabled EVs 1 operating in export mode, either individually or together, are only used to charge the EVs 1 when grid power is not available or when it is a peak price period and the cost of importing power from the grid 12 is higher than a predetermined acceptable threshold (which may be set, for example and without limitation, by the fleet site operator 20).

[0023] Based on the operating mode of the fleet power distribution system 10, i.e. either the grid-connected mode or the islanded mode, the algorithm 200 generates mode-specific setpoints for all of the power-supplying and power-consuming entities at the utility customer site 2, including the chargers 5, the BESS 14, the PV system 16, any V2X-enabled EVs 1 operating in export mode, the grid rectifier, any other DERs 13, and the other site loads 30. The setpoints always fall in one of the seven categories at any time step, and these seven categories areP24-1478(GOV)WOQ1 provided in FIG. 2 after the end of the flow chart. In the description of the setpoint categories shown in FIG. 2, the EV charging rate is indicated as either “max. rates” or “lower rates”; the status of the BESS 14 is indicated as either charging, idle, or discharging; and the status of the PV system 16 is indicated as either MPPT mode or curtailment mode. Regarding EV charging rate, the term “max. rates” indicates that a charger 5 connected to an EV 1 is configured to charge at the charger 5’s highest possible rate, and the term “lower rates” indicates that the charger 5 is configured to charge at a rate lower than the charger 5’s highest possible rate. Regarding the status of the BESS 14, the status of “charging” indicates that the BESS 14 is receiving power from another power source connected to the fleet power distribution system 10, the status of “discharging” indicates that the BESS 14 is outputting power to the fleet power distribution system 10, and the status of “idle” indicates that the BESS 14 is neither charging nor discharging. When the status of the BESS 14 is indicated to be charging or discharging at the max rate, this indicates that the BESS 14 is respectively being charged or discharged at its highest possible rate. Regarding the status of the PV system 16, “MPPT mode” indicates that the PV system 16 is operating in maximum power point tracking mode, meaning that the PV system 16 is continually adjusting the operating point (i.e. voltage output and current output) of each individual solar panel in accordance with the solar panel’s test voltage-current curve to ensure that the individual solar panels within the PV system 16 are operating at their optimal power output. The “curtailment mode” indicates that generation of power by the PV system 16 is deliberately being restricted.

[0024] Prior to discussing the smart charging algorithm 200 in detail, a few terms used in FIG. 2 will be explained. The term EVi is used to refer to the specific individual EV 1 that is being evaluated by the controller system 100 at a given moment in time. Time step t should be understood to refer to the time step that includes the present moment in time. Time step t- 1 should be understood to refer to the time step immediately preceding the present time step.

[0025] The smart charging algorithm 200 begins at step 201 , where the controller system 100 reads all data available that affects the state of the fleet power distribution system 10 and thus affects the charging of the EVs 1, including: measured grid power at time step t-1 (Pgt. i); target state of charge for EVi (SoC_tarEVi); kWh rating of EVi’s battery (BattEVi), i.e. the battery capacity of EVi; current state of charge of EVi’s battery (SOCEVO; current state of charge for the BESS 14 (SOCBESS); charger 5 operating status; PV array 16 charging status; time of useP24-1478(GOV)WOQ1 tariffs (ToU); demand charges cost (DCC). It is noted that the field corresponding to step 201 states “etc.”, and it should be understood that additional factors affecting the state of the fleet power distribution system 10 can be read by the controller system 100. For example, inputs from the fleet site operator 20 can be provided to the controller 100 at step 201, such as vehiclespecific details for each individual EV 1 including: vehicle arrival time to the utility customer site 2, scheduled departure time from the utility customer site 2, the state of charge (SOC) upon arrival at the utility customer site 2, the target / desired SOC, and vehicle ID, as well as electricity tariffs and electricity demand charges.

[0026] The algorithm 200 progresses from step 201 to step 202, where the controller system 100 creates a priority list for all uncharged EVs 1 parked at the utility customer site 2. That is, the controller system 100 ranks all EVs 1 requiring charging in a sequential order such that the EV 1 at the front of the priority list (the highest priority EV 1) should be charged prior to any other EV 1 on the list and such that the EV 1 at the end of the priority list (the lowest priority EV 1 ) should be charged after every other EV 1 on the list.

[0027] The algorithm 200 progresses from step 202 to step 203, where the controller system 100 determines whether any EV chargers 5 are available to charge the highest priority EVi on the priority list created at step 202. If there are any chargers 5 available at step 203, the algorithm 200 progresses from step 203 to step 204, where the highest priority EVi on the priority list is connected to the next available charger Chi. The algorithm 200 then returns to step 203 to step 204.

[0028] If there are no chargers 5 available at step 203, then the algorithm 200 progresses to step 205. It will be appreciated that at step 205, all chargers 5 capable of charging an EV 1 are presently charging an EV 1. At step 205, the controller system 100 updates its internal accounting of the state of the utility customer site 2, including updating the constraints of charging all uncharged EVs 1 based on the present system conditions. The parameters of lower limit (LL) and upper limit (UL) for power import from the grid 12 are updated. The lower limit and upper limit are updated to reflect predicted net demand on the grid 12. The lower limit value is updated to be the greater value (maximum) of either: (1) measured grid power at time step t-1 (Pgt-i) minus the product of ramp rate (RR) and time elapsed from time step t-1 to the present (At); and (2) zero. The upper limit value is updated to be the lowest value (minimum) of either: (1) measured grid power at time step t-1 (Pgt-i) plus the product of ramp rate (RR) and timeP24-1478(GOV)WOQ1 elapsed from time step t-1 to the present (At); (2) monthly demand charge threshold limit (DCT) (where DCT = N_blocks x block_size, with N_blocks being the subscribed number of blocks for monthly demand charges cost and block_size being the size of each block); and (3) contractual power import limit for the site per utility interconnection agreement (Pcontract).

[0029] Still referring to step 205, the controller system 100 also determines the number of EVs 1 (NEV) that are connected to EV chargers 5 and whose current state of charge (SOCEVO is less than their target state of charge (SoC_tarEVi). The controller system 100 then creates an updated priority list based on NEV, displays a message to the fleet site operator 20 indicating which EVs 1 are charged and can be unplugged, and displays a message to the fleet site operator 20 indicating which EVs 1 on the updated priority list should be connected to which EV chargers 5. Whenever the term “updated priority list” is referenced hereinafter, it should be understood that this term refers to the updated priority list generated at step 205. The algorithm 200 then proceeds from step 205 to step 206.

[0030] At step 206, if NEV is greater than zero, then the algorithm 200 proceeds from step 206 to step 207. At step 207, for each EV 1 on the updated priority list, the charging setpoint (PEW) for EVi is set to be the lesser (minimum) of: (1) the rated power of the charger to which EVi is connected to (Pch_rated), and (2) charging setpoint computed based on the charge acceptance curve of EVi (PCPCV). The charge acceptance curve for each EV 1 is a function showing how fast an electric vehicle's battery accepts charging power (kilowatts) at different levels of battery charge (state of charge) over a charging session.

[0031] At step 207, for each EVi currently being charged in accordance with updated priority list, the controller system 100 sets the charging setpoint (PEVO for the EVi based on: (1) the rated power of the charger to which EVi is connected to (PCh_rated) being at its lowest / minimum level, and (2) the charging setpoint being computed based on the charge acceptance curve of the EVi (PCPCV). The algorithm 200 then proceeds from step 207 to step208. At step 208, the controller system 100 determines whether it is peak price hours for the grid 12. If it is not peak price hours for the grid 12, then the algorithm proceeds from step 208 to step209. At step 209, the controller system 100 determines whether the difference of the sum of the charging setpoints for all EViS (£ PEVI) and the power setpoint for the PV system 16 (Ppv) is less than the upper limit (UL) that was set at step 205. At step 209, if £ PEVt - Ppv is less than the upper limit, then the algorithm 200 returns to step 206 from step 209.P24-1478(GOV)WOQ1

[0032] At step 208, if the controller system 100 determines that it is peak price hours for the grid 12, then the algorithm proceeds from step 208 to step 210. At step 210, the controller system 100 sets the upper limit (UL) to zero. The algorithm 200 then proceeds from step 210 to step 211. In addition, at step 209, if £ PEVt - Ppv is not less than the upper limit, then the algorithm 200 proceeds to step 211 from step 209. At step 211, the controller system 100 determines whether the state of charge of the BESS 14 (SOCBESS) is greater than the BESS 14’s minimum state of charge (SoCmin). If the controller system 100 determines at step 211 that SOCBESS is not greater than SoCmin, then the controller system 100 proceeds to step 225F and sets the setpoints for the chargers 5, BESS 14, and PV system 16 according to setpoint category #5.

[0033] At step 211, if SOCBESS is greater than SoCmin, then the algorithm 200 proceeds from step 211 to step 212. At step 212, the controller system 100 discharges the BESS 14 with a power setpoint equal to the upper limit (UL) set at step 205 minus the difference of: (1) the sum of the charging setpoints for all EViS (£ PEvt) and (2) the power setpoint for the PV system 16 (Ppv). The algorithm then proceeds to step 213 from step 212. At step 213, the controller system 100 determines whether the power discharge setpoint for the BESS 14 (PBESS) is less than the rated discharge power (i.e. maximum discharge rate) for the BESS 14 (Prated). If PBESS is less than (Prated), then the algorithm 200 returns to step 206. If PBESS is not less than (Prated), then the algorithm 200 proceeds to step 225G and sets the setpoints for the chargers 5, BESS 14, and PV system 16 according to setpoint category #6.

[0034] At step 206, if NEV is not greater than zero, then the algorithm 200 proceeds from step 206 to step 214. At step 214, the controller system 100 determines whether the difference of the sum of the charging setpoints for all EVs on the updated priority list (£ PEvi) and the power setpoint for the PV system 16 (Ppv) is greater than the lower limit (LL) set at step 205. At step 214, if PEVi- Ppv is not greater than the lower limit, then the algorithm 200 proceeds to step 215 from step 214. At step 215, the controller system 100 determines whether the state of charge of the BESS 14 (SOCBESS) is less than the BESS 14’s maximum state of charge (SoCmax). If the controller system 100 determines at step 215 that SOCBESS is not less than SoCmax, then the algorithm 200 proceeds from step 215 to step 225D and sets the setpoints for the chargers 5, BESS 14, and PV system 16 according to setpoint category #3.

[0035] At step 215, if SOCBESS is less than SoCmax, then the algorithm 200 proceeds from step 215 to step 216. At step 216, the controller system 100 charges the BESS 14 at a powerP24-1478(GOV)WOQ1 setpoint (PBESS) equal to the lower level (LL) set at step 205 minus the difference of: (1) the sum of the charging setpoints for all EViS (£ PEvi.) and (2) the power setpoint for the PV system 16 (Ppv). The algorithm 200 then proceeds from step 216 to step 217.

[0036] At step 217, the controller system 100 determines whether the power charge setpoint for the BESS 14 (PBESS) is less than the rated charge power (i.e. maximum charge rate) for the BESS 14 (Prated). If the controller system 100 determines at step 217 that PBESS is less than Prated, then the controller system 100 proceeds to step 225 A and sets the setpoints for the chargers 5, BESS 14, and PV system 16 according to setpoint category #0. If the controller system 100 determines at step 217 that PBESS is not less than Prated, then the controller system 100 proceeds to step 225E and sets the setpoints for the chargers 5, BESS 14, and PV system 16 according to setpoint category #4.

[0037] At step 214, if PEVt - Ppv is greater than the lower limit, then the algorithm 200 proceeds to step 218 from step 214. At step 218, the controller system 100 determines whether the BESS 14 is discharging. If the BESS 14 is discharging, then the algorithm 200 proceeds to step 225C and sets the setpoints for the chargers 5, BESS 14, and PV system 16 according to setpoint category #2. If the BESS 14 is not discharging, then the algorithm 200 proceeds to step 219.

[0038] At step 219, the controller system 100 determines whether the state of charge of the BESS 14 (SOCBESS) is less than the BESS 14’s maximum state of charge (SoCmax). If SOCBESS is not less than SoCmax, then the algorithm 200 proceeds from step 219 to step 225B and sets the setpoints for the chargers 5, BESS 14, and PV system 16 according to setpoint category #1. At step 219, if SOCBESS is less than SoCmax, then the algorithm 200 proceeds from step 219 to step 220.

[0039] At step 220, the controller system 100 determines whether it is peak price hours for the grid 12. If it is peak price hours for the grid 12, then the algorithm proceeds from step 220 to step 221. At step 221, the controller system 100 sets the upper limit to zero. The algorithm 200 then proceeds from step 221 to step 222. At step 220, if it is not peak price hours for the grid 12, then the algorithm proceeds directly to step 222 from step 220.

[0040] At step 222, the controller system 100 charges the BESS 14 at a power setpoint (PBESS) equal to the lower (minimum) of: (1) the rated charge / discharge power for battery storage system (Prated); and (2) the difference of the (a) upper limit set at step 205, and (b) the differenceP24-1478(GOV)WOQ1 of the sum of the charging setpoints for all EViS and the power setpoint for the PV system 16 (S PEVI " PPV). The algorithm 200 then proceeds to step 225A from step 222 and sets the setpoints for the chargers 5, BESS 14, and PV system 16 according to setpoint category #0.

[0041] After the algorithm 200 proceeds to and completes one of the setpoint setting steps 225 (i.e. any of the steps 225A-225G, all of which can be referred to generally with the reference number 225) the algorithm 200 proceeds to 230. At 230, the controller system 100 determines that the grid power for time step t (Pg) is equal to the sum of the charging setpoints for all EViS (£ PEVI) minus the power setpoint for the PV system 16 (PPV) plus the power setpoint for the BESS 14 (PBESS). The algorithm 200 then returns to step 201 from step 230.

[0042] In sum, the disclosed controller system 100 with the smart charging algorithm 200 a versatile solution, adaptable to all EV fleets and charging infrastructure types (AC or DC) and levels, charger specifications (number and rating of chargers), feeder limits (MW and kW / min), site configurations (either having or lacking DERs such as a BESS or PV system), and rate structures (e.g., flat rate, ToU tariffs, demand charges, etc.).

[0043] While specific embodiments of the invention have been described in detail, it will be appreciated by those skilled in the art that various modifications and alternatives to those details could be developed in light of the overall teachings of the disclosure. Accordingly, the particular arrangements disclosed are meant to be illustrative only and not limiting as to the scope of disclosed concept which is to be given the full breadth of the claims appended and any and all equivalents thereof.

Claims

P24-1478(GOV)WOQ1What is claimed is:

1. A controller system configured to manage charging of a plurality of EVs in a fleet at a utility customer site, the utility customer site comprising a plurality of entities, the plurality of entities including: a fleet power distribution system, a grid interface serving as a point of common coupling that connects the utility customer site to a utility power grid, a plurality of EV chargers electrically connected to the fleet power distribution system, a number of DERs, a fleet site operator, and a number of site loads that are not EVs; wherein the fleet power distribution system is configured to be connected and disconnected from a plurality of power sources, the plurality of power sources including the utility power grid and the number of DERs; wherein the fleet power distribution system is configured to supply power to the EV chargers; wherein the controller system comprises: a smart charging algorithm; wherein the controller system is configured to communicate with the plurality of entities at the utility customer site, wherein, by executing the smart charging algorithm, the controller system is configured to: identify which EV in the fleet to next allocate to an available EV charger of the plurality of EV chargers; determine a rate of charging of each EV in real time while monitoring power imported from all of the power sources to the fleet power distribution system, the power sources including the utility power grid, the number of DERs, and any of the EVs operating in export mode; and for a given one of the EVs, identifying when the given EV is charged.

2. The controller system of claim 1 , wherein the number of DERs includes onsite energy storage.

3. The controller system of claim 2, wherein the onsite energy storage is a battery energy storage system.

4. The controller system of claim 1 ,P24-1478(GOV)WOQ1 wherein the number of DERs includes a PV system.

5. The controller system of claim 1, wherein, by executing the smart charging algorithm, the controller system is also configured to: for each EV arriving at the utility customer site, determining a priority for charging the EV based on: arrival time of the EV to the utility customer site, battery state of charge of the EV, scheduled departure time of the EV, and desired battery state of charge for a scheduled departure time.

6. The controller system of claim 1 , wherein, for each given EV in the plurality of EVs, an interval of time between arrival of the given EV at the utility customer site and commencement of charging of the EV is a wait time, wherein, by executing the smart charging algorithm, the controller system is also configured to: dynamically allocate each given EV to an available EV charger of the plurality of EV chargers during the wait time based on factors including: electricity demand charges, time of use rates, power rating of the available EV charger, and predicted net demand on the utility power grid.

7. The controller system of claim 1, wherein, by executing the smart charging algorithm, the controller system is also configured to: ensure adequate charging of all EVs in the fleet within a defined dwell time by adjusting, for each EV in the fleet: a charging schedule according to predefined preferences for vehicle usage, energy costs, and impact on the utility power grid.

8. The controller system of claim 1, wherein, by executing the smart charging algorithm, the controller system is also configured to:P24-1478(GOV)WOQ1 dynamically adjust power demand of the fleet to ensure compliance with power limit and ramp-rate limits of the utility power grid.

9. A method for managing charging of a plurality of EVs in a fleet at a utility customer site, the utility customer site comprising a plurality of entities, the plurality of entities including: a fleet power distribution system, a grid interface serving as a point of common coupling that connects the utility customer site to a utility power grid, a plurality of EV chargers electrically connected to the fleet power distribution system, a number of DERs, a fleet site operator, and a number of site loads that are not EVs; wherein the fleet power distribution system is configured to be connected and disconnected from a plurality of power sources, the plurality of power sources including the utility power grid and the number of DERs; wherein the fleet power distribution system is configured to supply power to the EV chargers; the method comprising: providing a controller system configured to communicate with the plurality of entities at the utility customer site, the controller system comprising a smart charging algorithm; executing the smart charging algorithm with the controller system, and by executing the smart charging algorithm: identifying, with the controller system, which EV in the fleet to next allocate to an available EV charger of the plurality of EV chargers; determining, with the controller system, a rate of charging of each EV in real time while monitoring power imported from all of the power sources to the fleet power distribution system, the power sources including the utility power grid, the number of DERs, and any of the EVs operating in export mode; and for a given one of the EVs, identifying with the controller system when the given EV is charged.

10. The method of claim 9, wherein the number of DERs includes onsite energy storage.

11. The method of claim 9, wherein the number of DERs includes a PV system.P24-1478(GOV)WOQ112. The method of claim 9, further comprising: for each EV arriving at the utility customer site, determining with the controller system a priority for charging the EV based on: arrival time of the EV to the utility customer site, battery state of charge of the EV, scheduled departure time of the EV, and desired battery state of charge for a scheduled departure time.

13. The method of claim 9, wherein, for each given EV in the plurality of EVs, an interval of time between arrival of the given EV at the utility customer site and commencement of charging of the EV is a wait time, wherein the method further comprises: dynamically allocating, with the controller system, each given EV to an available EV charger of the plurality of EV chargers during the wait time based on factors including: electricity demand charges, time of use rates, power rating of the available EV charger, and predicted net demand on the utility power grid.

14. The method of claim 9, wherein the method further comprises: ensuring, with the controller system, adequate charging of all EVs in the fleet within a defined dwell time by adjusting, for each EV in the fleet: a charging schedule according to predefined preferences for vehicle usage, energy costs, and impact on the utility power grid.

15. The method of claim 9, wherein the method further comprises: dynamically adjusting, with the controller system, power demand of the fleet to ensure compliance with power limit and ramp-rate limits of the utility power grid.

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