# US 2025/0085682 A1 · Sensitivity Analysis for a System and Method for Optimizing an Energy Management

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 2025/0085682 A1
- Document ID: US20250085682A1
- Status: Published application
- Kind: A1
- Application number: 18/827,992
- Filed: 2024-09-09
- Published: 2025-03-13
- Earliest claimed: 2023-09-07
- Assignees: ABB Schweiz AG
- Applicants: ABB Schweiz AG
- Inventors: Arzam Muzaffar Kotriwala; Bernhard Primas; Ido Amihai; Georg Gutermuth; Matthias Schloeder; Matthias Biskoping
- Web page: https://patentgrep.com/patent/US20250085682A1

## CPC

- G05B 19/042: using digital processors (G05B19/05 takes precedence)
- G06Q 10/04: Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202)
- G06Q 50/06: Energy or water supply
- 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
- G05B 2219/2639: Energy management, use maximum of cheap power, keep peak load low
- H02J 2103/30: Simulating, planning, modelling, reliability check or computer assisted design [CAD] of electric power networks
- 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

## Abstract

A system for optimizing an energy management of a site, comprising: an energy optimizer, wherein the energy optimizer determines one or more optimization goals based on an optimization algorithm, a data variator adapted to provide at least one first energy data input and at least one second energy data input, different to the first energy data input, to the energy optimizer, wherein the energy optimizer receives the first and second energy data inputs from the data variator, and to determine, based the first and second energy data inputs, respective at least one first and second energy data outputs via the optimization algorithm, wherein a data sensitivity of the energy optimizer is determined with respect to the first and second energy data inputs and the first and second energy data outputs.

## Claims

### Claim 1

A system for optimizing an energy management of a site, the system comprising:
an energy optimizer adapted to determine one or more optimization goals based on an optimization algorithm;
a data variator adapted to provide at least one first energy data input and at least one second energy data input, different to the first energy data input, to the energy optimizer;
wherein the energy optimizer is adapted to receive the first and second energy data inputs from the data variator, and
to determine, based the first and second energy data inputs, respective at least one first and second energy data outputs via the optimization algorithm,
wherein a data sensitivity of the energy optimizer can be determined with respect to the first and second energy data inputs and the first and second energy data outputs.

### Claim 2 (depends on 1)

The system according to claim 1, wherein the system comprises a parameter variator additionally or alternatively to the data variator, wherein the parameter variator is adapted to provide at least one first energy parameter input and at least one second energy parameter input, different to the first energy parameter input and, wherein the energy optimizer is adapted to:
receive the first and second parameter inputs from the parameter variator, and to
determine, based the first and second energy parameter inputs, respective at least one first and second energy parameter outputs via the optimization algorithm,
wherein a parameter sensitivity of the energy optimizer can be determined with respect to the first and second energy parameter inputs and the first and second energy parameter outputs.

### Claim 3 (depends on 2)

The system according to claim 2, wherein system comprises the data variator and the parameter variator, and wherein a combined data and parameter sensitivity of the energy optimizer can be determined with respect to combination of the first and second energy data inputs and the first and second energy data outputs, as well as the first and second energy parameter inputs and the first and second energy parameter outputs.

### Claim 4 (depends on 1)

The system according to claim 1, wherein the at least one first energy data input is based on historical energy data, and wherein the data variator is adapted to vary the historical energy data to create and provide the second energy data input.

### Claim 5 (depends on 4)

The system according to claim 4, wherein the historical energy data is based on energy data of at least one energy consumer and/or at least one energy producer.

### Claim 6 (depends on 2)

The system according to claim 2, wherein the first energy parameter input is based on an energy parameter, and wherein the parameter variator is adapted to vary the energy parameter to create and provide, based on the varied energy parameter, the second energy parameter input.

### Claim 7 (depends on 6)

The system according to claim 6, wherein the energy parameter is one or more of the following:
an initial state-of-charge of each battery storage system;
a limit/capacity of each battery storage system;
a charge rate and efficiency of each battery storage system;
a limit of energy that can be taken from the electrical grid; and/or
a look-ahead time of the forecasting algorithm.

### Claim 8 (depends on 1)

The system according to claim 1, further comprising an explainer unit adapted to provide explanations about the sensitivity of the energy optimizer based on the energy data inputs/outputs and/or the energy parameter inputs/outputs.

### Claim 9

A method for optimizing an energy management of site, comprising:
providing to an energy optimizer at least one first and second energy data inputs and/or at least one first and second energy parameter inputs,
determining, by the energy optimizer, based on the first and second energy data inputs and/or the first and second energy parameter inputs, respective at least one first and second energy data outputs, and/or at least one first and second energy parameter outputs, and
determining a data sensitivity and/or parameter sensitivity of the energy optimizer based on the energy data inputs and/or the energy parameter inputs, and based on the energy data outputs and/or the energy parameter outputs.

### Claim 10 (depends on 9)

The method according to claim 9, wherein the first energy data input is formed by historical energy data, the method further comprising:
determining, by the energy optimizer, a first energy data forecast based on the historical energy data,
providing the first energy data forecast to an optimization algorithm,
determining by the optimization algorithm, a first optimization goal based on the first energy data forecast and an optimization parameter,
providing ground truth data to the optimization algorithm, and
determining by the optimization algorithm, a second optimization goal based on the ground truth data and the optimization parameter.

### Claim 11 (depends on 10)

The method according to claim 10, further comprising:
varying the historical energy data;
providing the varied energy data to the energy optimizer;
determining by the energy optimizer one or more varied energy data forecasts based on the varied energy data;
providing the one or more varied energy data forecasts to the optimization algorithm; and
determining by the optimization algorithm one or more varied data optimization goals based on the one or more varied energy data forecasts, wherein the optimization parameter is kept constant.

### Claim 12 (depends on 11)

The method according to claim 11, further comprising:
determining at least one forecast difference between the ground truth data and each of the one or more energy data forecasts; and
determining at least one optimization goal difference between the second optimization goal based on a ground truth data and each of the optimization goals based on each of the energy data forecasts.

### Claim 13 (depends on 9)

The method according to claim 9, wherein the first energy data input is formed by historical energy data, the method further comprising:
determining by the energy optimizer a constant energy data forecast based on the historical energy data;
providing the constant energy data forecast to an optimization algorithm;
determining by the optimization algorithm a first optimization goal based on the constant energy data forecast and a optimization parameter;
varying the optimization parameter;
providing the varied optimization parameter to the energy optimizer, and
determining by the optimization algorithm one or more varied optimization goals based on the constant energy data forecast and the one or more varied optimization parameters.