# US 2017/0288399 A1 · Machine learning of electrical power system behavior, and related systems, apparatuses, and methods > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2017/0288399 A1 - Document ID: US20170288399A1 - Status: Published application - Kind: A1 - Application number: 15/474,729 - Filed: 2017-03-30 - Published: 2017-10-05 - Earliest claimed: 2016-04-01 - Assignees: Enel X North America, Inc. - Applicants: Demand Energy Networks, Inc. - Inventors: John Michael Fife - Web page: https://patentgrep.com/patent/US20170288399A1 ## CPC - G06Q 10/06313: {Resource planning in a project environment} - G01R 31/367: Software therefor, e.g. for battery testing using modelling or look-up tables - G01R 31/392: Determining battery ageing or deterioration, e.g. state of health - G05B 13/021: {in which a variable is automatically adjusted to optimise the performance} - G05B 13/0265: {the criterion being a learning criterion} - G05B 13/041: {in which a variable is automatically adjusted to optimise the performance} - G05B 13/048: {using a predictor} - G05B 17/02: electric - G05F 1/66: Regulating electric power - G06Q 10/06315: {Needs-based resource requirements planning or analysis} - G06Q 30/0206: {Price or cost determination based on market factors} - G06Q 50/06: Energy or water supply - H02J 3/00: Circuit arrangements for AC mains or AC distribution networks - H02J 3/004: {Generation forecast, e.g. methods or systems for forecasting future energy generation} - H02J 3/14: by switching loads on to, or off from, the networks, e.g. progressively balanced loading - H02J 3/28: Arrangements for balancing of the load in networks by storage of energy - H02J 3/46: Controlling the sharing of generated power between the generators, sources or networks - H02J 13/00: Circuit arrangements for providing remote monitoring or remote control of equipment in a power distribution network - H02J 13/1337: {involving the use of Internet protocols} - H02J 7/585: {Sequential battery discharge in systems with a plurality of batteries} - H02J 13/10: characterised by displaying of information or by user interaction, e.g. supervisory control and data acquisition [SCADA] systems - H02J 2103/30: Simulating, planning, modelling, reliability check or computer assisted design [CAD] of electric power networks - H02J 2105/55: according to an economic condition, e.g. tariff-based load management - Y02B 10/30: Wind power - 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 - 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 - G01R: MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES (indicating correct tuning of resonant circuits H03J3/12) - 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) - G05F: SYSTEMS FOR REGULATING ELECTRIC OR MAGNETIC VARIABLES - 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 The present disclosure is directed to machine learning of electrical power system behavior, and related systems, apparatuses, and methods. A controller of an electrical power system includes a data storage device configured to store model data indicating a model load power consumed by loads of the electrical power system. The controller also includes a processor configured to determine current data including current load power consumed by the loads, modify the model data by aggregating the model data with the current data, and determine a set of control values for a set of control variables to effectuate a change to operation of the electrical power system based, at least in part, on the model data. ## Claims ### Claim 1 A controller of an electrical power system, the controller comprising: a data storage device configured to store model data indicating, for time points of a time period of operation of the electrical power system, a model load power for one or more loads of the electrical power system, a model generator power for one or more generators of the electrical power system, or a combination of the model load power and the model generator power; and a processor operably coupled to the data storage device and configured to: determine, based on information received from one or more sensors of the electrical power system, current data including a current load power of the one or more loads of the electrical power system, a current generator power of the one or more generators of the electrical power system, or a combination of the current load power and the current generator power for time points of a current time period of operation of the electrical power system, the current time period corresponding to the time period of the model data stored by the data storage device; modify the model data by aggregating the model data with the current data; and determine a set of control values to effectuate a change to operation of the electrical power system based, at least in part, on the model data. ### Claim 2 (depends on 1) The controller of claim 1, wherein the model data includes an aggregation of a plurality of sets of previous data, each of the plurality of sets of previous data including data indicating, for time points of a different previous time period of operation of the electrical power system, a previous load power consumed by the one or more loads, a previous generator power provided by the one or more generators, or a combination of the previous load power and the previous generator power. ### Claim 3 (depends on 2) The controller of claim 2, wherein the aggregation of the plurality of sets of previous data includes an average of the plurality of sets of previous data. ### Claim 4 (depends on 3) The controller of claim 3, wherein the average of the plurality of sets of previous data comprises a weighted average of the plurality of sets of previous data. ### Claim 5 (depends on 1) The controller of claim 1, wherein the model data includes a user-defined estimate of a typical load power consumed by the one or more loads of the electrical power system, a typical generator power provided by the one or more generators of the electrical power system, or a combination of the typical load power and the typical generator power for the time points of the time period. ### Claim 6 (depends on 1) The controller of claim 1, wherein the processor is configured to aggregate the model data with the current data by determining a weighted average between the model data and the current data. ### Claim 7 (depends on 5) The controller of claim 5, wherein the model data is weighted more heavily than the current data in the weighted average. ### Claim 8 (depends on 1) The controller of claim 1, wherein: a number of the time points of the period of time corresponding to the model data is different from a number of the time points of the current period of time corresponding to the current data; and the processor is configured to interpolate the current data to include the same number of time points as the model data before aggregating the model data with the current data. ### Claim 9 (depends on 1) The controller of claim 1, wherein at least one of the time points or the current time points are spaced at non-uniform time intervals. ### Claim 10 (depends on 1) The controller of claim 1, wherein at least one of the time points or the current time points are spaced at uniformly spaced intervals comprising a range of five (5) minute to 120 minute intervals. ### Claim 11 (depends on 1) The controller of claim 1, wherein the processor is configured to aggregate the model data with the current data using an infinite impulse response (IIR) filter. ### Claim 12 (depends on 11) The controller of claim 11, wherein a coefficient of the IIR filter multiplied by the model data is 0.95 and a coefficient of the IIR filter multiplied by the current data is 0.05. ### Claim 13 (depends on 1) The controller of claim 1, wherein the time period and the current time period each correspond to one day. ### Claim 14 An electrical power system, comprising: one or more loads; one or more sensors operably coupled to the one or more loads and configured to measure power consumed by the one or more loads; and a controller operably coupled to the one or more sensors, the controller configured to: store model data indicating, for time points of a time period of operation of the electrical power system, a model load power consumed by the one or more loads; determine, based on information received from the one or more sensors, current data indicating a current load power consumed by the one or more loads for time points of a current time period of operation of the electrical power system, the current time period corresponding to the time period of the model data stored by the data storage device; update the model data based, at least in part, on the current data; and determine a set of control values to effectuate a change to operation of the electrical power system based, at least in part, on the model data. ### Claim 15 (depends on 14) The electrical power system of claim 14, further comprising: one or more generators operably coupled to the one or more sensors and configured to provide power; wherein: the one or more sensors are configured to measure the power provided by the one or more generators; the model data also indicates, for the time points of the time period, a model generator power provided by the one or more generators; and the current data also indicates a current generator power provided by the one or more generators for the time points of the current time period. ### Claim 16 (depends on 15) The electrical power system of claim 15, wherein the one or more generators include one or more of a solar photovoltaic (PV) system, a wind generator, a combined heat and power (CHP) system, or a diesel generator. ### Claim 17 (depends on 14) The electrical power system of claim 14, wherein the one or more loads include one or more of an air conditioning system, a motor, or an electric heater. ### Claim 18 A method of operating an electrical power system, the method comprising: storing model data indicating, for time points of a time period of operation of the electrical power system, a model load power consumed by one or more loads of the electrical power system, a model generator power provided by one or more generators of the electrical power system, or a combination of the model load power and the model generator power; determining, based on information received from one or more sensors of the electrical power system, current data including a current load power consumed by the one or more loads of the electrical power system, a current generator power provided by the one or more generators of the electrical power system, or a combination of the current load power and the current generator power for time points of a current time period of operation of the electrical power system, the current time period corresponding to the time period of the model data; updating the model data by modifying the model data with the current data; and determine a set of control values to effectuate a change to operation of the electrical power system based, at least in part, on the model data. ### Claim 19 (depends on 18) The method of claim 18, wherein updating the model data includes determining a weighted average between the model data and the current data. ### Claim 20 (depends on 19) The method of claim 19, wherein determining a weighted average between the model data and the current data includes weighing the model data more heavily than the current data in the weighted average.