# US 12,181,848 B2 · Building energy storage system with planning tool > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,181,848 B2 - Document ID: US12181848B2 - Status: Granted - Kind: B2 - Application number: 18/337,230 - Filed: 2023-06-19 - Published: 2024-02-15 - Granted: 2024-12-31 - Earliest claimed: 2017-03-06 - Assignees: Con Edison Battery Storage, LLC - Applicants: Con Edison Battery Storage, LLC - Inventors: Mohammad N. Elbsat; Michael J. Wenzel; Kirk H. Drees - Web page: https://patentgrep.com/patent/US12181848B2 ## CPC - G05B 19/042: using digital processors (G05B19/05 takes precedence) - G06Q 50/06: Energy or water supply - H02J 3/00: Circuit arrangements for AC mains or AC distribution networks - H02J 3/003: {Load forecast, e.g. methods or systems for forecasting future load demand} - H02J 3/32: using batteries or super capacitors with converting means - H02J 4/25: for transfer of electric power between AC and DC networks, e.g. for supplying the DC section within a load from an AC mains system - G05B 2219/2639: Energy management, use maximum of cheap power, keep peak load low - H02J 3/381: {Dispersed generators} - H02J 3/40: Synchronisation of generators for connection to a network or to another generator - H02J 7/34: Parallel operation in networks using both storage and other DC sources, e.g. providing buffering (H02J7/14 takes precedence) - H02J 2101/20: Dispersed power generation using renewable energy sources - H02J 2103/30: Simulating, planning, modelling, reliability check or computer assisted design [CAD] of electric power networks - Y02E 60/00: Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation - Y04S 10/50: Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications - Y04S 40/20: Information technology specific aspects, e.g. CAD, simulation, modelling, system security - G05B: CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS (systems for controlling or regulating non-electric variables G05D; systems for regulating electric or magnetic variables G05F; control devices or systems insofar as characterised by mechanical features only G05G) - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR - H02J: ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY - Y02E: REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION - 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 An energy storage system for a building includes a battery asset configured to store electricity and discharge the stored electricity for use in satisfying a building electric load. The system includes a planning tool configured to identify one or more selected functionalities of the energy storage system and generate a cost function defining a cost of operating the energy storage system over an optimization period. The cost function includes a term for each of the selected functionalities. The planning tool is configured to generate optimization constraints based on the selected functionalities, attributes of the battery asset, and the electric energy load to be satisfied. The planning tool is configured to optimize the cost function to determine optimal power setpoints for the battery asset at each of a plurality of time steps of the optimization period. ## Claims ### Claim 1 An energy storage system for a building, the system comprising: a battery asset configured to store energy for satisfying a building energy load; and an energy storage controller including a computer readable medium and a processor, the energy storage controller including computer executable instructions stored in the computer readable medium for implementing a resource allocation planning tool to: estimate the building energy load to be satisfied for a time step during an optimization period based on one or more functions of the energy storage system, the one or more functions including accounting for revenue generated by using the battery asset to participate in an incentive program during the optimization period; generate a cost function corresponding to a cost of operating the energy storage system over the optimization period based on one or more battery power setpoints for the battery asset; determine optimal battery power setpoints for the time step based on the estimated building energy load; and generate a control signal configured to control the energy stored to or discharged from the battery asset based on the optimal battery power setpoints. ### Claim 2 (depends on 1) The energy storage system of claim 1, wherein the incentive program is a frequency regulation (“FR”) program. ### Claim 3 (depends on 2) The energy storage system of claim 2, wherein the cost function includes at least one term related to FR revenue. ### Claim 4 (depends on 1) The energy storage system of claim 1, wherein the incentive program is an economic load demand response (“ELDR”) program. ### Claim 5 (depends on 4) The energy storage system of claim 4, wherein the cost function includes at least one term related to ELDR revenue. ### Claim 6 (depends on 4) The energy storage system of claim 4, wherein the ELDR program is a day-ahead market. ### Claim 7 (depends on 1) The energy storage system of claim 1, the energy storage controller further comprising computer executable instructions stored in the computer readable medium for implementing the resource allocation planning tool to: shift the optimization period forward in time a predetermined number of time steps during a planning period; determine optimal battery power setpoints for each time step of the planning period; and estimate the cost of operating the energy storage system over the planning period based on the optimal battery power setpoints for each time step of the planning period. ### Claim 8 (depends on 1) The energy storage system of claim 1, the energy storage controller further comprising computer executable instructions stored in the computer readable medium for implementing the resource allocation planning tool to: obtain historical data related to the one or more functions of the energy storage system, wherein the historical data is used as an input to the cost function. ### Claim 9 (depends on 1) The energy storage system of claim 1, wherein the one or more functions of the energy storage system include determining an optimal size for the battery asset. ### Claim 10 (depends on 9) The energy storage system of claim 9, wherein the cost function accounts for an initial purchase cost of the battery asset and an operating cost of the battery asset. ### Claim 11 (depends on 10) The energy storage system of claim 10, wherein the initial purchase cost of the battery asset and the operating cost of the battery asset are functions of a battery size variable in the cost function. ### Claim 12 (depends on 11) The energy storage system of claim 11, the energy storage controller further comprising computer executable instructions stored in the computer readable medium for implementing the resource allocation planning tool to: determine an optimal value for the battery size variable. ### Claim 13 (depends on 11) The energy storage system of claim 11, the energy storage controller further comprising computer executable instructions stored in the computer readable medium for implementing the resource allocation planning tool to: scale the battery size variable based to a duration of the optimization period. ### Claim 14 (depends on 9) The energy storage system of claim 9, wherein the cost function accounts for a financial metric that includes at least one of a net present value, an internal rate of return, and a simple payback period. ### Claim 15 (depends on 1) The energy storage system of claim 1, wherein: the one or more functions of the energy storage system include accounting for a demand charge during a demand charge period; and the demand charge is based on a cost of an amount of electricity purchased during the demand charge period. ### Claim 16 (depends on 15) The energy storage system of claim 15, the energy storage controller further comprising computer executable instructions stored in the computer readable medium for implementing the resource allocation planning tool to: apply a demand charge mask to the demand charge to cause the planning tool to disregard the electricity purchased outside the demand charge period. ### Claim 17 (depends on 15) The energy storage system of claim 15, the energy storage controller further comprising computer executable instructions stored in the computer readable medium for implementing the resource allocation planning tool to: scale the demand charge based on a duration of the optimization period. ### Claim 18 (depends on 1) The energy storage system of claim 1, wherein the one or more functions of the energy storage system include accounting for a peak load contribution (“PLC”) charge. ### Claim 19 (depends on 18) The energy storage system of claim 18, wherein the cost function accounts for a PLC cost based on an amount of electricity purchased during coincidental peak (“CP”) hours of the optimization period. ### Claim 20 (depends on 19) The energy storage system of claim 19, the energy storage controller further comprising computer executable instructions stored in the computer readable medium for implementing the resource allocation planning tool to: apply a peak hours mask to the PLC cost to cause the planning tool to disregard the electricity purchased outside of projected peak hours.