# US 2017/0285678 A1 · Extended control in control systems and methods for economical optimization of an electrical system

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- Number: US 2017/0285678 A1
- Document ID: US20170285678A1
- Status: Published application
- Kind: A1
- Application number: 15/414,552
- Filed: 2017-01-24
- Published: 2017-10-05
- Earliest claimed: 2016-04-01
- Assignees: Demand Energy Networks, Inc.
- Applicants: Demand Energy Networks, Inc.
- Inventors: John Michael Fife
- Web page: https://patentgrep.com/patent/US20170285678A1

## 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 systems and methods for economically optimal control of an electrical system. Some embodiments employ generalized multivariable constrained continuous optimization techniques to determine an optimal control sequence over a future time domain in the presence of any number of costs, savings opportunities (value streams), and constraints. Some embodiments also include control methods that enable infrequent recalculation of the optimal setpoints. Some embodiments may include a battery degradation model that, working in conjunction with the economic optimizer, enables the most economical use of any type of battery. Some embodiments include techniques for load and generation learning and prediction. Some embodiments include consideration of external data, such as weather.

## Claims

### Claim 1

A controller to control an electrical system, the controller comprising:
a communication interface to provide a communication path with an electrical system; and
one or more processors to:
receive, via the communication interface, one or more measurements of a state of the electrical system, each measurement designated as a value for a process variable in a set of process variables;
obtain a set of control parameters to be applied for an extended time segment, each parameter of the set of control parameters specifying a behavior of a control law of the controller;
apply the control law by comparing the set of process variables to the set of control parameters to determine a value for each control variable of a set of control variables, each control variable controlling a component of the electrical system, the value of each control variable determined by the control law; and
provide the values for the set of control variables to the electrical system, via the communication interface, to effectuate a change to one or more components of the electrical system.

### Claim 2 (depends on 1)

The controller of claim 1, wherein the one or more processors obtain the set of control parameters by determining optimal values for the set of control parameters with an objective of economically optimizing operation of the electrical system during the extended time segment.

### Claim 3 (depends on 1)

The controller of claim 1, further comprising an economic optimizer computing device to determine optimal values for the set of control parameters with an objective of economically optimizing operation of the electrical system during the extended time segment, wherein the economic optimizer computing device electronically communicates the optimal values for the set of control parameters to the one or more processors.

### Claim 4 (depends on 1)

The controller of claim 1, wherein the one or more processors receive the process variables by reading the measurements of the electrical system repeatedly during the time segment at a time interval,
wherein the one or more processors apply the control law upon each reading of the measurements at the time variable to determine a value for each control variable, and
wherein the values of the set of control variables are communicated to the electrical system at least upon a change in a given value of a given control variable from a previous time interval.

### Claim 5 (depends on 1)

The controller of claim 1, wherein a parameter of the set of control parameters specifies an upper limit of a process variable.

### Claim 6 (depends on 1)

The controller of claim 1, wherein a parameter of the set of control parameters specifies a lower limit of a process variable.

### Claim 7 (depends on 1)

The controller of claim 1, wherein a parameter of the set of control parameters specifies a nominal value at which a process variable is to be directed to the extent that other constraints specified by other parameters are not violated.

### Claim 8 (depends on 1)

The controller of claim 1, wherein the set of control parameters includes a first parameter that specifies an upper limit of a process variable, a second parameter that specifies a lower limit of the process variable, and a third parameter that specifies a nominal value at which the process variable is to be directed to the extent that other constraints specified by the first parameter and the second parameter are not violated.

### Claim 9 (depends on 8)

The controller of claim 8, wherein the set of control parameters further includes a fourth parameter that specifies a constraint value that the process variable is not to exceed, if a pre-specified condition is met.

### Claim 10 (depends on 1)

The controller of claim 1, wherein the set of process variables include a measurement of a load on the electrical system.

### Claim 11 (depends on 1)

The controller of claim 1, wherein the set of control variables includes one or more variables to control one or more of battery charging and battery discharging.

### Claim 12 (depends on 1)

The controller of claim 1, wherein the set of control variables includes one or more variables to control a power generation component of the electrical system.

### Claim 13

A method of a controller of an electrical system, the method comprising:
obtaining a set of control parameters to be applied for an extended time segment, each parameter of the set of control parameters specifying a behavior of a control law of the controller;
receiving a set of process variables that provide one or more measurements of a state of the electrical system;
applying the control law, including comparing the set of process variables to the set of control parameters according to the control law, to determine a value for each control variable of a set of control variables, each control variable controlling a component of the electrical system, the value of each control variable determined by the control law; and
providing the values for the set of control variables to the electrical system to effectuate a change to one or more components of the electrical system.

### Claim 14 (depends on 13)

The method of claim 13, wherein obtaining the set of control parameters comprises determining a value for each control parameter in the set of control parameters by:
receiving a set of configuration elements specifying one or more constraints of the electrical system and defining one or more cost elements associated with operation of the electrical system;
preparing a cost function to operate based on the set of control parameters, the cost function including the one or more constraints and the one or more cost elements associated with operation of the electrical system; and
executing a generalized minimization of the cost function to determine optimal values for the set of control parameters with an objective of economical optimization of the electrical system during the extended time segment.

### Claim 15 (depends on 13)

The method of claim 13, wherein obtaining the set of control parameters comprises receiving values for the set of control parameters from an economic optimizer computing device that determines optimal values for the set of control parameters to economically optimize operation of the electrical system during the extended time segment.

### Claim 16 (depends on 13)

The method of claim 13, wherein receiving the process variables comprises reading the process variables repeatedly during the time segment at a time interval,
wherein applying the control law comprises determining a value for each control variable upon each reading of the process variables at the time variable, and
wherein providing the set of control variables comprises communicating the values of the set of control variables to the electrical system at least upon a change in a given value of a given control variable from a previous time interval.

### Claim 17 (depends on 13)

The method of claim 13, wherein a parameter of the set of control parameters specifies an upper limit of a process variable.

### Claim 18 (depends on 13)

The method of claim 13, wherein a parameter of the set of control parameters specifies a lower limit of a process variable.

### Claim 19 (depends on 13)

The method of claim 13, wherein a parameter of the set of control parameters specifies a default value at which a process variable is to be directed to the extent that other constraints specified by other parameters are not violated.

### Claim 20 (depends on 13)

The method of claim 13, wherein a parameter of the set of control parameters specifies a constraint value that a process variable is not to exceed if a pre-specified condition is met.

### Claim 21 (depends on 13)

The method of claim 13, wherein a parameter of the set of control parameters specifies a constraint value that a process variable is limited, if a pre-specified condition is met.

### Claim 22 (depends on 13)

The method of claim 13, wherein the set of control parameters includes a first parameter that specifies an upper limit of a process variable, a second parameter that specifies a lower limit of the process variable, and a third parameter that specifies a nominal value at which the process variable is to be directed to the extent that other constraints specified by the first parameter and the second parameter are not violated.

### Claim 23 (depends on 13)

The method of claim 13, wherein the set of process variables includes a measurement of a load on the electrical system.

### Claim 24 (depends on 13)

The method of claim 13, wherein a control variable of the set of control variables is to control one or more of battery charging and battery discharging.

### Claim 25 (depends on 13)

The method of claim 13, wherein a control variable of the set of control variables is to curtail a power generation component of the electrical system.