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Researchers Submit Patent Application, “Battery Energy Storage Control Systems And Methods”, for Approval (USPTO 20190157869)

Source: 
Energy Business Daily

2019 JUN 10 (NewsRx) -- By a News Reporter-Staff News Editor at Energy Business Daily -- From Washington, D.C., NewsRx journalists report that a patent application by the inventors Gadh, Rajit (Los Angeles, CA); Nazaripouya, Hamidreza (Sherman Oaks, CA); Chu, Chi-Cheng (Aliso Viejo, CA), filed on November 16, 2018, was made available online on May 23, 2019.

The patent’s assignee is University of California (Oakland, California, United States).

News editors obtained the following quote from the background information supplied by the inventors: “The technology of this disclosure pertains generally to battery power management and more particularly to battery power management using both local and remote controllers connected through the internet.

“Battery Management Systems (BMS) have been studied extensively in the literature. A BMS usually provides features such as Cell monitoring, Battery Safety and Protection, State of Charge (SOC) Estimation, State of Health (SOH) Estimation, Cell Balancing, Thermal Management, Charging Control. The BMS technology should not be confused with the technology of the presented disclosure.

“Energy Management Systems (EMS) are another area of research which gained huge amount of attraction. Energy management researches are divided in two different areas. The first area is related to building and organizational energy management system. In this category, the goal of EMS is to match energy generation with consumer needs. In fact, this problem is optimization problem, where the anticipation control layer tries to maximize the total satisfaction of services and, at the same time, minimize the total energy cost.

“The second area investigates large scale EMS (whole system EMS), such as micro-grid energy management or utility owned EMS. Whole system EMS refers to managing systems generation, transmission, distribution, and loads to fulfill operator’s needs. Whole system EMS is what utility companies do to ensure that their power stations and renewable energy sources generate enough energy to meet the demand. It also refers to techniques for managing and controlling customer’s levels energy. In addition, it is a major part of controlling and optimizing Micro-grids operation.

“Under this context, the EMS might not necessary include the storage systems such as battery to be controlled. In addition, EMS systems are involved with scheduling optimization and normally do not take to the account the dynamic of the system and real time control.

“Battery energy storage system control is also investigated in the literature. Several control strategies and configurations for battery energy storage system have been proposed to smooth power fluctuation or enhance power quality. Battery energy storage systems recently have begun to be controlled for multiple applications such as frequency regulation, voltage regulation, grid stabilization, transmission loss reduction, diminished congestion, increased reliability, wind and solar energy smoothing, spinning reserve, peak-shaving, load leveling, uninterruptible power sources, grid services, electric vehicle (EV) charging stations, and others.”

As a supplement to the background information on this patent application, NewsRx correspondents also obtained the inventors’ summary information for this patent application: “This disclosure pertains generally to battery energy storage control systems and methods, and more particularly to a top level controller that manages the behavior of an entire battery storage system. In various embodiments, the technology may manage battery modules, and power electronics in a grid. The technology may also be configured to communicate with BMS as one component of the system.

“In another embodiment, the technology focuses on real time dynamic control of a battery energy storage system (BESS).

“By way of example, this technology as referred to as ‘battery dynamic power flow control’. Aspects of this technology may include, but are not limited to, the following: (1) this system addresses the localization of solar renewable energy sources; (2) the system optimizes the size of battery capacity; (3) the system both shifts the power consumption pattern and shapes the power consumption profile in real time; and (4) the system provides the grid services including but not limited to voltage regulation.

“In one embodiment, the battery dynamic power flow control system described herein transforms a battery storage system from a passive component in the grid to an active and smart component which is able to benefit grid and users automatically. The control system may address needs of the following targets, as well as others, by controlling the power flow to:

“1. Customers: including residential, commercial, and enterprise entities: Reducing the electricity bills, localize and increase the solar utilization, participate in arbitrage; Demand charge reduction, Backup power, Time-of-use bill management;

“2. Utilities: maximum utilization of renewables, providing the spinning reserve; resource adequacy, transmission deferral, distribution deferral, transmission congestion relief; and

“3. Grid Operators: frequency regulation, voltage support, energy arbitrage, spin/non-spin reserve, black start, shifting the peak demand, shaping demand, balancing renewables, load leveling.

“There are some products in the market that are performing energy battery energy storage control such as STEM, RepositPower, Green Charge Networks and Coda Energy products. Although they may appear similar, they (1) do not address the localization of solar, (2) are not optimized the size of battery capacity, and (3) are not shaping the power consumption profile, but only shifting the power consumption pattern.

“Further aspects of the technology described herein will be brought out in the following portions of the specification, wherein the detailed description is for the purpose of fully disclosing preferred embodiments of the technology without placing limitations thereon.”

The claims supplied by the inventors are:

“1. A battery energy storage system (BESS), the system comprising: (a) a central controller computer; (b) a non-transitory memory storing instructions executable by the central computer; © a local controller computer; (d) a non-transitory memory storing instructions executable by the local computer; (e) wherein said central controller instructions and said local controller instructions, when respectively executed by the central controller computer and the local controller computer allow for a communications interface configured for network communications therebetween; (f) a control system computer comprising the local controller computer and the central controller computer; (g) a grid tie inverter, comprising: (1) a port for connection to an electrical grid; (2) a port for connection to a battery; and (3) a communications interface configured for communications with the control system; and (h) wherein said central controller and said local controller instructions, when executed among the local controller computer and the central controller memory, form a set of operational instructions performing steps comprising: (1) controlling communication between the central controller computer and the local controller computer; (2) executing a safety features control section; and (3) executing an operation control and monitoring section.

“2. The battery energy storage system (BESS) of claim 1, wherein the control system computer is configured to monitor and control criteria for the safe operation of the battery.

“3. The battery energy storage system (BESS) of claim 2, wherein the monitor and control criteria for the safe operation of the battery are selected from the group of criteria consisting of: (a) detecting battery over-temperature; (b) detecting battery overcurrent charging; © detecting battery overcurrent discharging; (d) detecting battery undervoltage; (e) detecting battery overvoltage; (f) detecting battery ventilation control; (g) detecting battery ventilation fault; (h) detecting battery cell imbalance; (i) detecting degraded battery state of health; (j) detecting battery short circuit; (k) detecting arc fault; and (l) detecting ground fault.

“4. The battery energy storage system (BESS) of claim 1, wherein the control system computer is configured to monitor and control criteria for the safe operation of the grid.

“5. The battery energy storage system (BESS) of claim 4, wherein the monitor and control criteria for the safe operation of the grid are selected from the group of criteria consisting of: (a) monitoring and controlling of the BESS in real time; (b) providing grid support by leveling loads on the electrical grid; © regulating electrical grid voltage; (d) improving power quality of the electrical grid; (e) improving transient and phase stability of the electrical grid; (f) compensating for unbalanced loads on the electrical grid; and (g) providing spinning reserves for the grid.

“6. The battery energy storage system (BESS) of claim 1, comprising: a second grid tie inverter, the second grid tie inverter comprising: (1) a second port for connection to an electrical grid; (2) a second port for connection to a battery; and (3) a second communications interface configured for communications with the control system.

“7. The battery energy storage system (BESS) of claim 1, wherein said set of operational instructions are configured to manage system operational modes selected from the group consisting of: a battery charging mode, a battery discharging mode, a current leading mode, and a current lagging mode.

“8. The battery energy storage system (BESS) of claim 1, comprising: a second grid tie inverter, the second grid tie inverter comprising: (1) a second port for connection to an electrical grid; (2) a second port for connection to a high current direct current (HCDC) charging station for an electric vehicle; and (3) a second communications interface configured for communications with the control system.

“9. The battery energy storage system (BESS) of claim 1, comprising: a second grid tie inverter, the second grid tie inverter comprising: (1) a second port for connection to an electrical grid; (2) a second port for connection to a photovoltaic system; and (3) a second communications interface configured for communications with the control system.

“10. The battery energy storage system (BESS) of claim 1, wherein the set of operational instructions further performs steps comprising: (a) collecting an historical power series; (b) decompositing the historical power series into a constitutive series through wavelet transformations; © modeling each of the constitutive series by a plurality of Auto-Regressive Moving Average (ARMA) models for recognition of their linear patterns, whereby a plurality of ARMA models are produced; (d) recompositing an estimated series obtained from the plurality of ARMA models for each constitutive series through an inverse wavelet transform; and (e) compensating for an error of the wavelet transformation and ARMA model predictions by recurrent neural networks through capturing of nonlinear patterns buried in a difference between the historical power series and the estimated series, whereby a time series estimate is produced.

“11. A non-transitory medium storing instructions executable by a computer processor, said instructions when executed by the computer processor performing steps comprising: (a) collecting an historical power series; (b) decompositing the historical power series into a constitutive series through wavelet transformations; © modeling each of the constitutive series by a plurality of Auto-Regressive Moving Average (ARMA) models for recognition of their linear patterns, whereby a plurality of ARMA models are produced; (d) recompositing an estimated series obtained from the plurality of ARMA models for each constitutive series through an inverse wavelet transform; (e) compensating for an error of the wavelet transformation and ARMA model predictions by recurrent neural networks through capturing of nonlinear patterns buried in a difference between the historical power series and the estimated series, whereby a time series estimate is produced.

“12. A method for performing a hybrid optimization, the method comprising: (a) collecting an historical power series; (b) decompositing the historical power series into a constitutive series through wavelet transformations; © modeling each of the constitutive series by a plurality of Auto-Regressive Moving Average (ARMA) models for recognition of their linear patterns, whereby a plurality of ARMA models are produced; (d) recompositing an estimated series obtained from the plurality of ARMA models for each constitutive series through an inverse wavelet transform; and (e) compensating for an error of the wavelet transformation and ARMA model predictions by recurrent neural networks through capturing of nonlinear patterns buried in a difference between the historical power series and the estimated series; (f) wherein said method is performed by a computer processor executing instructions stored on a non-transitory computer-readable medium.

“13. A non-transitory medium storing instructions executable by a computer processor, said instructions when executed by the computer processor performing steps comprising: (a) designing a low-pass finite impulse response (FIR) filter with minimum-length, minimum-phase, and low-group-delay; (b) initializing a cut-off frequency .omega.sub.c a maximum possible filter length N.sub.max, and an error bound ; © solving the problem: minimize N subject to .parallel.A.sub.kx.parallel.sub.2.ltoreq.0.7079 (-3 dB) k I, I={k|.omega.sub.k.gtoreq.omega.sub.c} as a quasiconvex optimization problem by using a bisection feasibility problem method; (d) solving a second-order cone programming (SOCP) problem by defining parameters min.sub.h[n](t.sub.1+.alpha.t.sub.2) such that, |A.sub.kx.parallel.sub.2.ltoreq.t.sub.1 .parallel.Bx.parallel.sub.2.ltoreq.t.sub.2.parallel. Cx=d where 0.ltoreq.omega.sub.1.ltoreq.omega.sub.2.ltoreq. . . . .ltoreq.omega.sub.k.ltoreq.pi., k=1, . . . , M; (1) by initially setting .alpha.=0; (2) solving the SOCP problem; (3) incrementing .alpha. by 1 until all zeroes are inside the unit circle; (4) determining if the group delay (grd) of max ( grd ) = r 1 + r ##EQU00020## is feasible; (i) if feasible, then setting u=t; (ii) if not feasible, then setting l=t; and (5) repeating until u-l.ltoreq. .

“14. A method for designing a low-pass finite impulse response (FIR) filter with minimum-length, minimum-phase, and low-group-delay, the method comprising: (a) initializing a cut-off frequency .omega.sub.c, a maximum possible filter length N.sub.max, and an error bound ; (b) solving the problem: minimize N subject to .parallel.A.sub.kx.parallel.sub.2.ltoreq.0.7079 (-3 dB) k I, I={k|.omega.sub.k.gtoreq.omega.sub.c)} as a quasiconvex optimization problem by using a bisection feasibility problem method; © solving a second-order cone programming (SOCP) problem by defining parameters min.sub.h[n](t.sub.1+.alpha.t.sub.2) such that. |A.sub.kx.parallel.sub.2.ltoreq.t.sub.1 |Bx.parallel.sub.2.ltoreq.t.sub.2.parallel. Cx=d where 0.ltoreq.omega.sub.1.ltoreq.omega.sub.2.ltoreq. . . . .ltoreq.omega.sub.k.ltoreq.pi., k=1, . . . , M; (1) by initially setting .alpha.=0; (2) solving the SOCP problem; (3) incrementing a by 1 until all zeroes are inside the unit circle; (4) determining if the group delay (grd) of max ( grd ) = r 1 + r ##EQU00021## is feasible; (i) if feasible, then setting u=t; (ii) if not feasible, then setting l=t; and (5) repeating until u-l.ltoreq. ; (d) wherein said method is performed by a computer processor executing instructions stored on a non-transitory computer-readable medium.

“15. A battery energy storage system (BESS), comprising: (a) a control system computer; (b) a non-transitory memory storing instructions executable by the control system computer; © a grid tie inverter, comprising: (1) a port for connection to an electrical grid; (2) a port for connection to a battery; and (3) a communications interface configured for communications with the control system; and (d) wherein said instructions executable by the control system computer perform steps comprising: (1) executing a safety features control section; and (2) executing an operation control and monitoring section.

“16. The battery energy storage system (BESS) of claim 15, wherein the control system computer comprises: (a) a local controller computer; and (b) a central controller computer.

“17. The battery energy storage system (BESS) of claim 16, wherein said instructions executable by the control system computer perform steps comprising: controlling communication between the central controller computer and the local controller computer.

“18. The battery energy storage system (BESS) of claim 15, wherein the control system computer is configured to monitor and control criteria for the safe operation of the battery.

“19. The battery energy storage system (BESS) of claim 18, wherein the monitor and control criteria for the safe operation of the battery are selected from the group of criteria consisting of: (a) detecting battery over-temperature; (b) detecting battery overcurrent charging; © detecting battery overcurrent discharging; (d) detecting battery undervoltage; (e) detecting battery overvoltage; (f) detecting battery ventilation control; (g) detecting battery ventilation fault; (h) detecting battery cell imbalance; (i) detecting degraded battery state of health; (j) detecting battery short circuit; (k) detecting arc fault; and (l) detecting ground fault.

“20. The battery energy storage system (BESS) of claim 15, wherein the control system computer is configured to monitor and control criteria for the safe operation of the grid.

“21. The battery energy storage system (BESS) of claim 20 wherein the monitor and control criteria for the safe operation of the grid are selected from the group of criteria consisting of: (a) monitoring and controlling of the BESS in real time; (b) providing grid support by leveling loads on the electrical grid; © regulating electrical grid voltage; (d) improving power quality of the electrical grid; (e) improving transient and phase stability of the electrical grid; (f) compensating for unbalanced loads on the electrical grid; and (g) providing spinning reserves for the grid.”

For additional information on this patent application, see: Gadh, Rajit; Nazaripouya, Hamidreza; Chu, Chi-Cheng. Battery Energy Storage Control Systems And Methods. Filed November 16, 2018 and posted May 23, 2019. Patent URL: http://appft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PG01&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.html&r=1&f=G&l=50&s1=%2220190157869%22.PGNR.&OS=DN/20190157869&RS=DN/20190157869

 

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