[특허]Electrical energy storage system with battery power setpoint optimization using predicted values of a frequency regulation signal

Electrical energy storage system with battery power setpoint optimization using predicted values of a frequency regulation signal 원문보기

IPC분류정보
국가/구분	United States(US) Patent 등록
국제특허분류(IPC7판)	G01R-031/36 G06Q-050/06 H02J-003/32 G05B-013/04 H02J-003/38 H02M-007/44 H02J-003/00
출원번호	US-0247777 (2016-08-25)
등록번호	US-10197632 (2019-02-05)
발명자 / 주소	Wenzel, Michael J. Drees, Kirk H.
출원인 / 주소	Taurus DES, LLC
대리인 / 주소	Foley & Lardner LLP
인용정보	피인용 횟수 : 0 인용 특허 : 87

초록 ▼

A frequency response optimization includes a battery that stores and discharges electric power, a power inverter that uses battery power setpoints to control an amount of the electric power stored or discharged from the battery, and a frequency response controller. The frequency response controller receives a regulation signal from an incentive provider, predicts future values of the regulation signal, and uses the predicted values of the regulation signal to generate the battery power setpoints for the power inverter.

대표청구항 ▼

1. A frequency response optimization system comprising: a battery configured to store and discharge electric power;a power inverter configured to use battery power setpoints to control an amount of the electric power stored or discharged from the battery; anda frequency response controller configured to: receive a regulation signal from an incentive provider in a frequency response (FR) program, wherein the regulation signal indicates a proportion of a regulation award power amount to add to or remove from an electric grid relative to a frequency response midpoint,predict future values of the regulation signal for each time within an optimization time period,use the predicted values of the regulation signal to generate the battery power setpoints for the power inverter for each time within the optimization time period; andoperate the power inverter using the generated battery power setpoints to cause the battery to store or discharge the electric power. 2. The system of claim 1, wherein the frequency response controller is configured to use an autoregressive model to predict the future values of the regulation signal based on a history of past values of the regulation signal. 3. The system of claim 1, wherein the frequency response controller comprises a low pass filter configured to filter the predicted values of the regulation signal; wherein the frequency response controller is configured to use the filtered values of the regulation signal to generate the battery power setpoints. 4. The system of claim 1, wherein the frequency response controller is configured to generate an objective function comprising: an estimated amount of frequency response revenue that will result from the battery power setpoints; andan estimated cost of battery degradation that will result from the battery power setpoints. 5. The system of claim 4, wherein the frequency response controller is configured to: use dynamic programming to select scaling coefficients for the regulation signal; andadjust the scaling coefficients to achieve an optimal value for the objective function. 6. The system of claim 1, wherein the frequency response controller is configured to: calculate a frequency response performance score that will result from the battery power setpoints; anduse the frequency response performance score to estimate an amount of frequency response revenue that will result from the battery power setpoints. 7. The system of claim 1, wherein the frequency response controller is configured to: use a battery life model to estimate an amount of battery degradation that will result from the battery power setpoints; anduse the estimated amount of battery degradation to determine a cost of the battery degradation. 8. The system of claim 7, wherein the battery life model comprises a plurality of variables that depend on the battery power setpoints, the variables comprising at least one of: a temperature of the battery;a state of charge of the battery;a depth of discharge of the battery;a power ratio of the battery; andan effort ratio of the battery. 9. The system of claim 1, wherein the frequency response controller comprises: a high level controller configured to generate filter parameters based on the predicted values of the regulation signal; anda low level controller configured to use the filter parameters to filter the predicted regulation signal and generate the battery power setpoints using the filtered regulation signal. 10. The system of claim 1, further comprising a campus having a campus power usage and a point of intersection at which the campus power usage combines with the electric power discharged from the battery; wherein the frequency response controller is configured to generate the battery power setpoints based on both the campus power usage and the predicted future values of the regulation signal. 11. A method for generating battery power setpoints in a frequency response optimization system, the method comprising: receiving a frequency regulation signal from an incentive provider in a frequency response (FR) program, wherein the frequency regulation signal indicates a proportion of a regulation award power amount to add to or remove from an electric grid relative to a frequency response midpoint;predicting future values of the frequency regulation signal for each time within an optimization time period;using the predicted values of the frequency regulation signal to generate battery power setpoints for each time within the optimization time period;providing the battery power setpoints to a power inverter; andusing the battery power setpoints to control an amount of electric power stored or discharged by the battery in response to the frequency response signal. 12. The method of claim 11, wherein predicting the future values of the frequency regulation signal comprises using an autoregressive model to predict the future values of the frequency regulation signal based on a history of past values of the frequency regulation signal. 13. The method of claim 11, further comprising: filtering the predicted values of the regulation signal using a low pass filter; andusing the filtered values of the frequency regulation signal to generate the battery power setpoints. 14. The method of claim 11, further comprising generating an objective function comprising: an estimated amount of frequency response revenue that will result from the battery power setpoints; andan estimated cost of battery degradation that will result from the battery power setpoints. 15. The method of claim 14, further comprising using dynamic programming to select scaling coefficients for the regulation signal and adjust the scaling coefficients to achieve an optimal value for the objective function. 16. The method of claim 11, further comprising: calculating a frequency response performance score that will result from the battery power setpoints; andusing the frequency response performance score to estimate an amount of frequency response revenue that will result from the battery power setpoints. 17. The method of claim 11, further comprising: using a battery life model to estimate an amount of battery degradation that will result from the battery power setpoints; andusing the estimated amount of battery degradation to determine a cost of the battery degradation. 18. The method of claim 17, wherein the battery life model comprises a plurality of variables that depend on the battery power setpoints, the variables comprising at least one of: a temperature of the battery;a state of charge of the battery;a depth of discharge of the battery;a power ratio of the battery; andan effort ratio of the battery. 19. The method of claim 11, further comprising: using a high level controller to generate filter parameters based on the predicted values of the frequency regulation signal; andusing a low level controller to filter the predicted future values of the frequency regulation signal based on the filter parameters and determine the optimal battery power setpoints using the filtered predicted future values of the frequency regulation signal. 20. The method of claim 11, wherein the frequency regulation system comprises a campus having a campus power usage and a point of intersection at which the campus power usage combines with the electric power discharged from the battery; the method further comprising determining the optimal battery power setpoints based on both the campus power usage and the predicted future values of the frequency response signal.

이 특허에 인용된 특허 (87)

Seem, John E., Adaptive real-time optimization control.
상세보기
Seem, John E., Adaptive real-time optimization control.
상세보기
Seem, John E., Adaptive real-time optimization control.
상세보기
Fan,Junqiang; Backstrom,Johan U., Apparatus and method for coordinating controllers to control a paper machine or other machine.
상세보기
Renfro, Jeffrey G.; Lu, Joseph Z., Apparatus and method for model predictive control (MPC) of a nonlinear process.
상세보기
Fan, Junqiang; Stewart, Gregory E., Automated tuning of large-scale multivariable model predictive controllers for spatially-distributed processes.
상세보기
Fan, Junqiang; Stewart, Gregory E., Automatic tuning method for multivariable model predictive controllers.
상세보기
Stewart, Greg; Borrelli, Francesco; Pekar, Jaroslav, Configurable automotive controller.
상세보기
Stewart,Gregory E.; Shahed,Syed M.; Borrelli,Francesco, Coordinated multivariable control of fuel and air in engines.
상세보기
Martin,Gregory D.; Boe,Eugene; Piche,Stephen; Keeler,James David; Timmer,Douglas; Gerules,Mark; Havener,John P., Dynamic controller for controlling a system.
상세보기
Prett David M. (Houston TX) Ramaker Brian L. (Houston TX) Cutler Charles R. (Katy TX), Dynamic matrix control method.
상세보기
Attarwala, Fakhruddin T, Dynamic model predictive control.
상세보기
Morshedi Abdol M. (Houston TX) Cutler Charles R. (Houston TX) Fitzpatrick Thomas J. (Katy TX) Skrovanek Thomas A. (Houston TX), Dynamic process control.
상세보기
Stewart, Gregory E.; Rhodes, Michael L., Emissions sensors for fuel control in engines.
상세보기
Stewart,Gregory E.; Rhodes,Michael L., Emissions sensors for fuel control in engines.
상세보기
Kramer, Robert A., Energy management system and methods for the optimization of distributed generation.
상세보기
Dillon, Jim; Blagus, Ronald; Parr, Stephen; Iyer, Venkat; Houghton, Alan, Energy optimization system.
상세보기
Stewart, Gregory E.; Rhodes, Michael L., Engine controller.
상세보기
Fan,Junqiang, Fast performance prediction of multivariable model predictive controller for paper machine cross-directional processes.
상세보기
Drees Kirk H. ; Ben-Aissa Nebil ; Seem John E., Feedback controller.
상세보기
Shelton, John C.; Kathpal, Praveen, Frequency responsive charge sustaining control of electricity storage systems for ancillary services on an electrical power grid.
상세보기
Koc, Hakan, Generalized predictive control (GPC) based position control method for an axle.
상세보기
Ahmed, Osman, Integrated building environment data system.
상세보기
Mehta,Ashish; Wojsznis,Peter; Wojsznis,Wilhelm K.; Blevins,Terrence L.; Thiele,Dirk; Ottenbacher,Ron; Nixon,Mark, Integrated model predictive control and optimization within a process control system.
상세보기
Wojsznis,Wilhelm; Blevins,Terry; Nixon,Mark, Integrated model predictive control and optimization within a process control system.
상세보기
Vouzis, Panagiotis; Bleris, Leonidas; Arnold, Mark G.; Kothare, Mayuresh V., Iterative matrix processor based implementation of real-time model predictive control.
상세보기
Rettger, Philip; Keshner, Marvin; Pligavko, Alexandra Katrina; Moore, Jackson; Littmmann, Bodo W., Local power tracking for dynamic power management in weather-sensitive power systems.
상세보기
Boe, Eugene; Piche, Stephen; Martin, Gregory D., Method and apparatus for attenuating error in dynamic and steady-state processes for prediction, control, and optimization.
상세보기
Frerichs,Donald Karl; Toth,Frank Marvin, Method and apparatus for detecting faults in steam generator system components and other continuous processes.
상세보기
Laskow, Paul Ira, Method and apparatus for effecting temperature difference in a respective zone.
상세보기
Egedal, Per; Rubak, Rune; Stiesdal, Henrik, Method and apparatus for prediction-based wind turbine control.
상세보기
Nikitin, Alexei V., Method and apparatus for signal filtering and for improving properties of electronic devices.
상세보기
Montalvo, Rey, Method and system for automatically adapting end user power usage.
상세보기
Pekar, Jaroslav; Strewart, Greg; Kihas, Dejan; Borrelli, Francesco, Method and system for combining feedback and feedforward in model predictive control.
상세보기
Gorinevsky, Dimitry, Method and system for diagnostics of apparatus.
상세보기
Stewart, Gregory E., Method and system for using a measure of fueling rate in the air side control of an engine.
상세보기
Stewart,Gregory E., Method and system for using a measure of fueling rate in the air side control of an engine.
상세보기
Piche Stephen ; Havener John P. ; Semrad Donald, Method for on-line optimization of a plant.
상세보기
Liepold, Helmut; Metzger, Michael, Method for optimizing the functioning of a plurality of compressor units and corresponding device.
상세보기
Lu Zhuxin J. (Glendale AZ) MacArthur J. Ward (Scottsdale AZ) Horn Brian C. (Phoenix AZ), Method of multivariable predictive control utilizing range control.
상세보기
Lu Zhuxin J. (Glendale AZ), Method of optimal controller design for multivariable predictive control utilizing range control.
상세보기
Kirchhof, Darrin Glen, Methods and apparatus for model predictive control in a real time controller.
상세보기
Pekar, Jaroslav; Borralli, Francesco; Stewart, Gregory, Methods and systems for the design and implementation of optimal multivariable model predictive controllers for fast-sampling constrained dynamic systems.
상세보기
Iino Yutaka (Kawasaki JPX) Ohya Junko (Kawasaki JPX), Model predictive control apparatus.
상세보기
Nishira,Hikaru; Kawabe,Taketoshi, Model predictive control apparatus.
상세보기
Cawlfield David W. (Cleveland TN), Model predictive control apparatus and method.
상세보기
Sayyar-Rodsari, Bijan, Model predictive control system and method for reduction of steady state error.
상세보기
Backstrom, Johan U.; He, Pengling, Model predictive controller for coordinated cross direction and machine direction control.
상세보기
Fuller,James W., Model predictive controller with life extending control.
상세보기
Thiele, Dirk, Model predictive controller with tunable integral component to compensate for model mismatch.
상세보기
Wojsznis,Wilhelm K.; Blevins,Terrence L.; Mehta,Ashish, Multiple-input/multiple-output control blocks with non-linear predictive capabilities.
상세보기
Stewart,Gregory E.; Kolavennu,Soumitri N.; Borrelli,Francesco; Hampson,Gregory J.; Shahed,Syed M.; Samad,Tariq; Rhodes,Michael L., Multivariable control for an engine.
상세보기
Fuller, James W., Multivariable control system.
상세보기
Butoyi, Firmin, Multivariable process controller and methodology for controlling catalyzed chemical reaction to form phthalic anhydride and other functionalized aromatics.
상세보기
Mathur Anoop K. (Shoreview MN) Gopinath Ravi S. (Troy NY), Neural net based disturbance predictor for model predictive control.
상세보기
Thiele, Dirk; Wojsznis, Wilhelm K., On-line adaptive model predictive control in a process control system.
상세보기
Alan J. Hugo, Performance assessment of model predictive controllers.
상세보기
Collins, Kevin; Curtis, Bruce; Baldwin, Jr., Robert R., Photovoltaic power plant output.
상세보기
Thisted, Jan, Power interchange system for interchanging electric energy between a battery and an electric grid, method for interchanging electric energy between a battery and an electric grid and application of the power interchange system.
상세보기
Provanzana, John H.; Schneider, John M.; Nourai, Ali; Walborn, Warren W.; Ware, Brendan J., Power load-leveling system and packet electrical storage.
상세보기
Gallestey,Eduardo Alvarez; Stothert,Alec, Process control system.
상세보기
Z. Joseph Lu, Process facility control systems using an efficient prediction form and methods of operating the same.
상세보기
Modi, Yash; Matsuoka, Yoky; Malhotra, Mark, Radiant heating controls and methods for an environmental control system.
상세보기
Sloup, Charles J.; Karnes, Daniel; Henze, Gregor P., Real-time global optimization of building setpoints and sequence of operation.
상세보기
Das,Indraneel; Fuller,James W., Real-time quadratic programming for control of dynamical systems.
상세보기
MacArthur J. Ward (Minneapolis MN) Wahlstedt David A. (Minneapolis MN) Woessner Michael A. (Minneapolis MN) Foslien Wendy K. (Minneapolis MN), Receding horizon based adaptive control having means for minimizing operating costs.
상세보기
Geinzer, Jay; Shelton, J. Christopher; Meersman, Steven, Regulation of contribution of secondary energy sources to power grid.
상세보기
Thiele, Dirk, Robust adaptive model predictive controller with tuning to compensate for model mismatch.
상세보기
Rawlings,James B.; Pannocchia,Gabriele; Laachi,Nabil, SISO model predictive controller.
상세보기
Jelinek Jan (Plymouth MN), Single input single output rate optimal controller.
상세보기
Fuller,James W., Square root method for computationally efficient model predictive control.
상세보기
Lu, Joseph; Morningred, John Duane, System and method for continuous supply chain control and optimization using stochastic calculus of variations approach.
상세보기
Liu, Yan; Garces, Luis Jose; Bose, Sumit, System and method for controlling ramp rate of solar photovoltaic system.
상세보기
Das,Indraneel; Rey,Gonzalo, System and method for exploiting a good starting guess for binding constraints in quadratic programming with an infeasible and inconsistent starting guess for the solution.
상세보기
Sisk, Brian C., System and method for optimizing the storing of vehicular energy.
상세보기
Das,Indraneel, System and method of accelerated active set search for quadratic programming in real-time model predictive control.
상세보기
Lu Zhuxin J., System and methods for globally optimizing a process facility.
상세보기
Wenzel, Michael J.; Turney, Robert D., System identification and model development.
상세보기
Rund, Anthony K, System, method and program for dynamic control and optimization of a process having manipulated and controlled variables.
상세보기
Forbes, Jr., Joseph W., System, method, and apparatus for settlement for participation in an electric power grid.
상세보기
Asmus, Matthew J., Systems and methods for controlling a chiller plant for a building.
상세보기
Wenzel, Michael J.; Drees, Kirk H., Systems and methods for controlling energy use in a building management system using energy budgets.
상세보기
Lu Zhuxin J., Systems and methods using bridge models to globally optimize a process facility.
상세보기
Baramov, Lubomir, Target trajectory generator for predictive control of nonlinear systems using extended Kalman filter.
상세보기
Cheng, Xu, Two-stage model predictive control technique.
상세보기
Attarwala, Fakhruddin T, Universal model predictive controller.
상세보기
Alles,Harold Gene, Zone climate control.
상세보기

IPC	Description
A	생활필수품
A62	인명구조; 소방(사다리 E06C)
A62B	인명구조용의 기구, 장치 또는 방법(특히 의료용에 사용되는 밸브 A61M 39/00; 특히 물에서 쓰이는 인명구조 장치 또는 방법 B63C 9/00; 잠수장비 B63C 11/00; 특히 항공기에 쓰는 것, 예. 낙하산, 투출좌석 B64D; 특히 광산에서 쓰이는 구조장치 E21F 11/00)
A62B-1/08	.. 윈치 또는 풀리에 제동기구가 있는 것

내보내기 구분	파일저장 인쇄 메일전송
구성항목	기본정보 상세정보 관리번호, 국가코드, 자료구분, 상태, 출원번호, 출원일자, 공개번호, 공개일자, 등록번호, 등록일자, 발명명칭(한글), 발명명칭(영문), 출원인(한글), 출원인(영문), 출원인코드, 대표IPC 관리번호, 국가코드, 자료구분, 상태, 출원번호, 출원일자, 공개번호, 공개일자, 공고번호, 공고일자, 등록번호, 등록일자, 발명명칭(한글), 발명명칭(영문), 출원인(한글), 출원인(영문), 출원인코드, 대표출원인, 출원인국적, 출원인주소, 발명자, 발명자E, 발명자코드, 발명자주소, 발명자 우편번호, 발명자국적, 대표IPC, IPC코드, 요약, 미국특허분류, 대리인주소, 대리인코드, 대리인(한글), 대리인(영문), 국제공개일자, 국제공개번호, 국제출원일자, 국제출원번호, 우선권, 우선권주장일, 우선권국가, 우선권출원번호, 원출원일자, 원출원번호, 지정국, Citing Patents, Cited Patents
저장형식	Text(ASCII format) Excel format PIAS분석(.xls)
메일정보	받는사람 (필수) @ 보내는사람 (선택) @ 제목 내용 KISTI 검색결과 이메일 서비스
안내	총 건의 자료가 검색되었습니다. 다운받으실 자료의 인덱스를 입력하세요. (1-10,000) 검색결과의 순서대로 최대 10,000건 까지 다운로드가 가능합니다. 데이타가 많을 경우 속도가 느려질 수 있습니다.(최대 2~3분 소요) 다운로드 파일은 UTF-8 형태로 저장됩니다. 파일의 내용이 제대로 보이지 않을실 때는 웹브라우저 상단의 보기 -> 인코딩 -> 자동선택 여부를 확인하십시오. ~ Text(ASCII format) Excel format

연합인증

Electrical energy storage system with battery power setpoint optimization using predicted values of a frequency regulation signal 원문보기

초록 ▼

대표청구항 ▼

연구과제 타임라인

이 특허에 인용된 특허 (87)

관련 콘텐츠

특허 원문 보기

IPC 상위 출원인

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

선택된 텍스트

연합인증

Electrical energy storage system with battery power setpoint optimization using predicted values of a frequency regulation signal 원문보기

초록 ▼

대표청구항 ▼

연구과제 타임라인

전체(0) 논문(0) 특허(0) 보고서(0)

전체(0) 논문(0) 특허(0) 보고서(0)

이 특허에 인용된 특허 (87)

관련 콘텐츠

특허 원문 보기

IPC 상위 출원인

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

선택된 텍스트