# US 10,483,760 B2 · Energy storage peak shaving of electrical power for facilities > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,483,760 B2 - Document ID: US10483760B2 - Status: Granted - Kind: B2 - Application number: 13/828,016 - Filed: 2013-03-14 - Published: 2014-09-18 - Granted: 2019-11-19 - Earliest claimed: 2013-03-14 - Assignees: Raytheon Company - Applicants: Raytheon Company - Inventors: William R. Faries; Scott M. Baron; John B. Rivera-Poventud; Mike Anderson; Alf L. Carroll, III - Web page: https://patentgrep.com/patent/US10483760B2 ## CPC - H02J 3/32: using batteries or super capacitors with converting means - H02J 3/003: {Load forecast, e.g. methods or systems for forecasting future load demand} - H02J 2105/55: according to an economic condition, e.g. tariff-based load management - Y02B 70/3225: Demand response systems, e.g. load shedding, peak shaving - Y04S 20/222: Demand response systems, e.g. load shedding, peak shaving - Y04S 50/10: Energy trading, including energy flowing from end-user application to grid - H02J: ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY - Y02B: CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS - Y04S: SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS ## Abstract A method of shaving peak power consumption by a facility includes determining a target peak demand setpoint for a facility and measuring power consumed by the facility. An electrical storage system (ESS) is charged when the measured power consumption is below the target peak demand setpoint. Additionally, the ESS is discharged and provides power to the facility when the measured power consumption is above the setpoint. Further, as data for the facility and ESS changes, the target peak demand setpoint is updated. ## Claims ### Claim 1 A method of shaving peak power consumption by a facility, the method comprising: determining a target peak demand setpoint for the facility, wherein the target peak demand setpoint is determined for a billing cycle; measuring power consumed by the facility; causing an electrical storage system (ESS) to be charged with power from a utility when the measured power consumption is below the target peak demand setpoint; causing the ESS to discharge and provide power to the facility while the facility simultaneously receives power from the utility when the measured power consumption is above the target peak demand setpoint; and dynamically updating, during the billing cycle, the target peak demand setpoint based on one or more changed conditions; wherein the target peak demand setpoint is determined initially by (i) determining a first optimal target peak demand setpoint using first demand load data from a time period immediately prior to a current billing cycle, (ii) determining a second optimal target peak demand setpoint using second demand load data from a billing cycle from a historical time period, and (iii) weighting the first and second optimal target peak demand setpoints; and wherein each of the first and second optimal target peak demand setpoints is determined using a process that (i) determines an initial target peak demand setpoint value by filtering out selected time segments and a nominal load from at least one of the first and second demand load data, (ii) iteratively modifies the initial target peak demand setpoint value according to one or more efficiency characteristics of the ESS until the modified target peak demand setpoint value is not economically feasible in view of the one or more efficiency characteristics of the ESS and one or more utility rates associated with the utility, and (iii) uses a last economically feasible target peak demand setpoint value among prior iterations as the first or second optimal target peak demand setpoint. ### Claim 2 (depends on 1) The method of claim 1, wherein the one or more changed conditions include a demand projection for the facility, a state of charge projection for the ESS, and a projection that demand is increasing. ### Claim 3 (depends on 1) The method of claim 1, wherein the target peak demand setpoint is further determined based on attempts at peak shaving in prior billing cycles. ### Claim 4 (depends on 1) The method of claim 1, wherein the target peak demand setpoint is further determined based on weather forecasting data. ### Claim 5 (depends on 1) The method of claim 1, wherein the target peak demand setpoint is determined based on at least one of: an energy capacity, a round trip efficiency, or a maximum power output of the ESS. ### Claim 6 (depends on 1) The method of claim 1, wherein the target peak demand setpoint is dynamically updated as data, concerning at least one of the facility or the ESS, changes. ### Claim 7 A system for shaving peak power consumption by a facility, the system comprising: a controller configured to: determine a target peak demand setpoint for the facility, wherein the controller is configured to determine the target peak demand setpoint for a billing cycle; measure power consumed by the facility; cause an electrical storage system (ESS) to be charged with power from a utility when the measured power consumption is below the target peak demand setpoint; cause the ESS to discharge and provide power to the facility while the facility simultaneously receives power from the utility when the measured power consumption is above the target peak demand setpoint; and dynamically update, during the billing cycle, the target peak demand setpoint based on one or more changed conditions; wherein the controller is configured to initially determine the target peak demand setpoint by (i) determining a first optimal target peak demand setpoint using first demand load data from a time period immediately prior to a current billing cycle, (ii) determining a second optimal target peak demand setpoint using second demand load data from a billing cycle from a historical time period, and (iii) weighting the first and second optimal target peak demand setpoints; and wherein the controller is configured to determine each of the first and second optimal target peak demand setpoints using a process that (i) determines an initial target peak demand setpoint value by filtering out selected time segments and a nominal load from at least one of the first and second demand load data, (ii) iteratively modifies the initial target peak demand setpoint value according to one or more efficiency characteristics of the ESS until the modified target peak demand setpoint value is not economically feasible in view of the one or more efficiency characteristics of the ESS and one or more utility rates associated with the utility, and (iii) uses a last economically feasible target peak demand setpoint value among prior iterations as the first or second optimal target peak demand setpoint. ### Claim 8 (depends on 7) The system of claim 7, wherein the one or more changed conditions include a demand projection for the facility, a state of charge projection for the ESS, and a projection that demand is increasing. ### Claim 9 (depends on 7) The system of claim 7, wherein the controller is further configured to determine the target peak demand setpoint based on attempts at peak shaving in prior billing cycles. ### Claim 10 (depends on 7) The system of claim 7, wherein the controller is further configured to determine the target peak demand setpoint based on weather forecasting data. ### Claim 11 (depends on 7) The system of claim 7, wherein the controller is configured to determine the target peak demand setpoint based on at least one of: an energy capacity, a round trip efficiency, or a maximum power output of the ESS. ### Claim 12 (depends on 7) The system of claim 7, wherein the controller is configured to dynamically update the target peak demand setpoint as data, concerning at least one of the facility or the ESS, changes. ### Claim 13 (depends on 1) The method of claim 1, wherein the target peak demand setpoint is further determined based on weather data associated with at least some of the first or second demand load data. ### Claim 14 A non-transitory computer readable medium containing instructions that when executed cause at least one processing device to: determine a target peak demand setpoint for a facility, wherein the target peak demand setpoint is determined for a billing cycle; measure power consumed by the facility; cause an electrical storage system (ESS) to be charged with power from a utility when the measured power consumption is below the target peak demand setpoint; cause the ESS to discharge and provide power to the facility while the facility simultaneously receives power from the utility when the measured power consumption is above the target peak demand setpoint; and dynamically update, during the billing cycle, the target peak demand setpoint based on one or more changed conditions; wherein the target peak demand setpoint is determined initially by (i) determining a first optimal target peak demand setpoint using first demand load data from a time period immediately prior to a current billing cycle, (ii) determining a second optimal target peak demand setpoint using second demand load data from a billing cycle from a historical time period, and (iii) weighting the first and second optimal target peak demand setpoints; and wherein each of the first and second optimal target peak demand setpoints is determined using a process that (i) determines an initial target peak demand setpoint value by filtering out selected time segments and a nominal load from at least one of the first and second demand load data, (ii) iteratively modifies the initial target peak demand setpoint value according to one or more efficiency characteristics of the ESS until the modified target peak demand setpoint value is not economically feasible in view of the one or more efficiency characteristics of the ESS and one or more utility rates associated with the utility, and (iii) uses a last economically feasible target peak demand setpoint value among prior iterations as the first or second optimal target peak demand setpoint. ### Claim 15 (depends on 14) The non-transitory computer readable medium of claim 14, wherein the one or more changed conditions include a demand projection for the facility, a state of charge projection for the ESS, and a projection that demand is increasing. ### Claim 16 (depends on 14) The non-transitory computer readable medium of claim 14, wherein the target peak demand setpoint is further determined based on attempts at peak shaving in prior billing cycles. ### Claim 17 (depends on 14) The non-transitory computer readable medium of claim 14, wherein the target peak demand setpoint is further determined based on weather forecasting data. ### Claim 18 (depends on 1) The method of claim 1, wherein the target peak demand setpoint is determined based on at least some of the first or second demand load data, a pricing rate schedule from the utility, and one or more properties of the ESS. ### Claim 19 (depends on 1) The method of claim 1, wherein the process further considers technical feasibility of the ESS when iteratively modifying the initial demand setpoint value. ### Claim 20 (depends on 7) The system of claim 7, wherein the process further considers technical feasibility of the ESS when iteratively modifying the initial demand setpoint value.