IP Library › Granted Patent US 12,633,745
Granted Patent B2
US 12,633,745 · App. 18/016,724 · Granted May 19, 2026

Method and device for predicting an energy service offering and software program product

Inventor: Matthias Dürr (Nuremberg, GB)
Assignee: Siemens Aktiengesellschaft
H02J3/003G05B15/02G05F1/66H02J3/17H02J3/28H02J2105/12H02J2105/52
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Quick Facts
Patent No.
US 12,633,745
App. No.
18/016,724
Granted
May 19, 2026
Kind
B2
Abstract

A predictor that projects the service offering available at a point in time on the basis of the agreed technical and contractual rules is provided. The predictor further makes the same available to the operating and scheduling systems of the industrial company and optimizes the prediction parameters by observing and comparing the real situation with the calculated situation, or else indicates unused potential.

Claims (31)

1 . A method for predicting an available energy service offer or existing energy service limits at a time or over a period of time, the method comprising:

ascertaining a maximum available supply power at the time or in the period of time;

dynamically modelling, by a rule generator of a device, individual conditions that influence the energy service offer to provide modelled conditions, wherein the modelled conditions that influence the service offer are weighted, and wherein the weighting of the modelled conditions that influence the service offer is dynamically applied so that the condition is provided with a higher weighting with increasing proximity to the time of execution;

calculating, by a predictor of the device, a superposition by overlaying the individual conditions; and

ascertaining, by the predictor, a power range at the time or the period of time using the dynamic modelling, therein reducing an amount of energy reserves needed to be held by an industrial production plant in comparison to an industrial production plant having no dynamic modelling.

2 . The method of claim 1 , wherein the conditions that influence the energy service offer are a limitation based on an atypical grid use that takes place at regularly occurring recurrent times.

3 . The method of claim 1 , wherein service limits that adversely affect use of the maximum service offer are taken into consideration, and

wherein an exceeding of a previous maximum service offer leads to adaptation of previously set conditions.

4 . The method of claim 1 , wherein a condition that influences the energy service offer is an employment of available energy stores or a possibility of internal supplementation of the energy service offer.

5 . The method of claim 1 , wherein the modelled conditions that influence the service offer are applied based on logic rules.

6 . The method of claim 1 , wherein an actually available power range at the time or the period of time is compared with the power range ascertained by prediction, and

wherein a difference in the comparison, together with events that influence the power range, is fed back via a correction function.

7 . The method of claim 6 , wherein, when an expected supply by a store or an internal electricity generator at the time or the period of time is not achieved, a weighting of the modelled conditions that influence the service offer is decreased for future predictions.

8 . The method of claim 1 , further comprising:

providing energy, by the industrial production plant, based on the ascertained power range.

9 . A device for predicting an available energy service offer or existing energy service limits at a time or over a period of time, the device comprising:

a rule generator configured to dynamically model individual conditions that influence the energy service offer, wherein the modelled conditions that influence the service offer are weighted, and wherein the weighting of the modelled conditions that influence the service offer is dynamically applied so that the condition is provided with a higher weighting with increasing proximity to the time of execution; and

a predictor configured to:

calculate a superposition based on a maximum available supply power at the time or in the period of time by overlaying the individual conditions with a power range available at the time or the period of time; and

ascertain the power range at the time or the period of time using the dynamic model, therein reducing an amount of energy reserves needed to be held by an industrial production plant in comparison to an industrial production plant having no dynamic modelling.

10 . The device of claim 9 , wherein the rule generator is configured to take into consideration a limitation based on an atypical grid use that takes place at regularly occurring recurrent times for the individual conditions that influence the energy service offer.

11 . The device of claim 9 , wherein the rule generator is configured to take into consideration service limits that adversely affect use of a maximum service offer for the individual conditions that influence the energy service offer, and

wherein an exceeding of a previous maximum service offer is configured to lead to an adaptation of previously set conditions.

12 . The device of claim 9 , wherein the rule generator is configured to take into consideration that the available energy service offer is influenced by an internally connectable energy supply through an employment of available previously stored energy or internal supplementation of the energy service offer by power generation.

13 . The device of claim 9 , wherein the rule generator is configured to apply the modelled conditions based on logic rules.

14 . The device of claim 9 , further comprising:

a corrector configured to compare, by prediction, an actually available power range at the time or the period of time with the power range ascertained for the time or the period of time, and

wherein a difference in the comparison, together with events that influence the power range, are configured to be fed back to the rule generator.

15 . The device of claim 14 , wherein the corrector is further configured to detect a difference between an expected supply and an actual supply by a store or an internal electricity generator at the time or the period of time, and

wherein a weighting of the modelled conditions that influence the service offer is configured to be decreased for future predictions.

16 . The device of claim 9 , wherein energy is configured to be provided by the industrial production plant based on the power range.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 24, 2023
From: DÜRR, MATTHIAS
To: SIEMENS AKTIENGESELLSCHAFT
Reel/Frame 063419/0672 →
Continuity (1)
Related Publication 20230299584A1 · Sep 21, 2023
References Cited (17)
US 7881889B2 · Barclay et al. · 2011 [cited by applicant]
US 8670874B2 · Edwards · 2014 [cited by applicant]
US 9633401B2 · Curtis · 2017 [cited by applicant]
US 11029652B2 · Blackhall · 2021 [cited by examiner]
US 20170038786A1 · Asghari et al. · 2017 [cited by applicant]
US 20210044109A1 · Spiecker · 2021 [cited by applicant]
CN 107895241A · 2018 [cited by examiner]
CN 110635476A · 2019 [cited by applicant]
DE 102006002407A1 · 2007 [cited by examiner]
DE 202017007300U1 · 2020 [cited by examiner]
EP 3561983A1 · 2019 [cited by applicant]
ES 2622113T3 · 2017 [cited by examiner]
KR 20210042898A · 2021 [cited by examiner]
WO 2006037734A2 · 2006 [cited by applicant]
WO 2019206473A1 · 2019 [cited by applicant]
PCT International Search Report and Written Opinion of International Searching Authority mailed Apr. 19, 2021 corresponding to PCT International Application No. PCT/EP2020/070804. [cited by applicant]
Wen Jianfeng et al., “Analysis on Charging Demand of EV Based on Stochastic Simulation of Trip Chain,” Power System Technology, vol. 39 No. 6, Jun. 2015, pp. 1477-1484. [cited by applicant]