Forecasting market prices for management of grid-scale energy storage systems

US2016055507A1 · US · A1

Patent metadata
FieldValue
Publication numberUS-2016055507-A1
Application numberUS-201514831650-A
CountryUS
Kind codeA1
Filing dateAug 20, 2015
Priority dateAug 21, 2014
Publication dateFeb 25, 2016
Grant date

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  5. First independent claim

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Abstract

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Systems and methods for forecasting energy usage data for one or more markets, including providing energy variable input data for one or more energy variables, transforming the energy variable input data using functions of the energy variable input data to generate transformed functions, modeling the transformed functions as one or more time series models, the time series models representing energy usage over time and energy usage predictions, and generating forecasted energy usage data based on the one or more time series models for management of one or more energy resources.

First claim

Opening claim text (preview).

What is claimed is: 1 . A computer implemented method for forecasting energy usage data for one or more markets, comprising: providing energy variable input data for one or more energy variables; transforming the energy variable input data using functions of the energy variable input data to generate transformed functions; modeling the transformed functions as one or more time series models, the time series models representing energy usage over time and energy usage predictions; and generating forecasted energy usage data based on the one or more time series models for management of one or more energy resources. 2 . The method of claim 1 , wherein the one or more time series models include a Locational Marginal Price (LMP) time series model and a voltage regulation time series model. 3 . The method of claim 1 , wherein the energy variable input data includes historical energy market price, forecasted load and generation data, and historical voltage regulation data. 4 . The method of claim 1 , further comprising actively controlling power to dispatch at least one of batteries, diesel power, or other localized generation and controllable loads automatically to provide a plurality of services, the services including energy, frequency and voltage regulation and improve system reliability. 5 . The method of claim 1 , wherein the one or more time series models are generated based on 2-3 days of historical data. 6 . The method of claim 1 , wherein the functions of the energy variable input data include logarithm, exponential, and derivative functions of the energy variable input data. 7 . The method of claim 1 , wherein the energy resources include one or more of batteries, diesel generation or other local resources, and controllable loads. 8 . A system for management of one or more energy storage systems (ESSs), comprising: a forecaster for predicting energy usage data for one or more markets, the forecasting being further configured to: provide energy variable input data for one or more energy variables; transform the energy variable input data using functions of the energy variable input data to generate transformed functions; model the transformed functions as one or more time series models, the time series models representing energy usage over time and energy usage predictions; and generate forecasted energy usage data based on the one or more time s series models; and a controller to apply the forecasted energy usage data for the management of the one or more energy resources. 9 . The system of claim 8 , wherein the one or more time series models include a Locational Marginal Price (LMP) time series model and a voltage regulation time series model. 10 . The system of claim 8 , wherein the energy variable input data includes historical energy market price, forecasted load and generation data, and historical voltage regulation data. 11 . The system of claim 8 , wherein the energy resources include one or more of batteries, diesel generation or other local resources, and controllable loads. 12 . The system of claim 8 , wherein the one or more time series models are generated based on 2-3 days of historical data. 13 . The system of claim 8 , wherein the functions of the energy variable input data include logarithm, exponential, and derivative functions of the energy variable input data. 14 . The system of claim 8 , wherein the forecasted energy usage data is employed for battery size determination in one or more ESSs. 15 . A computer-readable storage medium comprising a computer readable program, wherein the computer readable program when executed on a computer causes the computer to perform the steps of: providing energy variable input data for one or more energy variables; transforming the energy variable input data using functions of the energy variable input data to generate transformed functions; modeling the transformed functions as one or more time series models, the time series models representing energy usage over time and energy usage predictions; and generating forecasted energy usage data based on the one or more time series models for management of energy resources. 16 . The computer-readable storage medium of claim 15 , wherein the one or more time series models include a Locational Marginal Price (LMP) time series model and a voltage regulation time series model. 17 . The computer-readable storage medium of claim 15 , wherein the energy variable input data includes historical energy market price, forecasted load and generation data, and historical voltage regulation data. 18 . The computer-readable storage medium of claim 15 , further comprising actively controlling power to dispatch ESSs automatically to maintain system voltage in an ESS within a normal range. 19 . The computer-readable storage medium of claim 15 , wherein the one or more time series models are generated based on 2-3 days of historical data. 20 . The computer-readable storage medium of claim 15 , wherein the energy resources include one or more of batteries, diesel generation or other local resources, and controllable loads.

Assignees

Inventors

Classifications

  • Energy or water supply · CPC title

  • Market surveys; Market polls · CPC title

  • Price or cost determination based on market factors · CPC title

  • Physics · mapped topic

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What does patent US2016055507A1 cover?
Systems and methods for forecasting energy usage data for one or more markets, including providing energy variable input data for one or more energy variables, transforming the energy variable input data using functions of the energy variable input data to generate transformed functions, modeling the transformed functions as one or more time series models, the time series models representing en…
Who is the assignee on this patent?
Nec Lab America Inc
What technology area does this patent fall under?
Primary CPC classification G06Q30/0206. Mapped technology areas include Physics.
When was this patent published?
Publication date Thu Feb 25 2016 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).