Method for operating an energy storage system

Abstract

The present disclosure is a method of operating an energy storage system, wherein the energy storage system is configured to supply power to the power grid at time tb over a predetermined operating time window. The method includes determining a current state of charge, SoC, of the energy storage system at time t0; estimating a total energy usage by the energy storage system between time t0 and time tb; determining a predicted SoC of the energy storage system at time tb based on the current SoC and the estimated total energy usage; inputting the predicted SoC, at least one operating constraint, and one or more system parameters into an optimization algorithm, wherein the at least one operating constraint is an operating condition to be satisfied by the energy storage system during the predetermined operating time window, and the one or more system parameters are parameters specific to the energy storage system; using the optimization algorithm to determine a plurality of power values each corresponding to a time step during the predetermined operating time window, wherein each power value is decomposed into an integer component and a floating-point component; and selecting one or more power values from the plurality of power values having a zero floating-point component to form an operating baseline for the energy storage system to operate during the predetermined operating time window.

Description

Technical Field

[0001] The present technology relates to a method of operating an energy storage system and an energy storage system for implementing the method.

Background Art

[0002] Frequency response services attempt to correct imbalances between power generation and demand in the power grid in real time. For example, a frequency response service may increase electrical demand or reduce its generation in response to an increase in the AC (alternating current) frequency indicating an over-generation of electricity, and may reduce electrical demand or increase its generation in response to a decrease in the AC frequency indicating an under-generation of electricity. In practice, the actual speed and magnitude of such responses vary by service.

[0003] The approach of frequency response services in the UK is a dynamic containment service (DC) that takes into account energy storage (batteries) in addition to systems for energy generation and energy supply. This service enables the specification of a "baseline" prior to the energy storage system that provides the frequency response service. The baseline is the power level set for the energy storage system applied in addition to the power supply service, and describes the proportion of energy (positive or negative power) imported or exported over time while the energy storage system is providing the frequency response service. By changing the baseline, the operator of the energy storage system can manage the state of charge of the energy storage system and buy and sell power in different markets without interrupting the provision of the frequency response service.

[0004] When providing frequency response, the energy storage system needs to supply power at a predetermined speed. Generally, the provision of the service is determined according to real-time system events, such as requests by the system operator or changes in the power generation or consumption balance, as well as market prices. Therefore, the calculation of the baseline of the energy storage system has several conflicting objectives, for example, · State of Charge (SoC) management, · The ability to supply power to the power market on demand, · Compatibility with a set of frequency response service rules (such as ramp rate limits, minimum / maximum response speeds, etc.) has many problems arising therefrom.

[0005] Control loops may be used to correct SoC imbalances, but methods without appropriate optimization are subject to various constraints arising from device limits such as power and response speed, as well as service requirements such as ramp rate, smooth power supply when adding to other services, and possible simultaneous operation between one service and another service. To accurately determine the baseline of the energy storage device, it is insufficient. Failure to address these constraints may damage the device due to inaccurate control, may interrupt the services provided by the device, and may result in the energy of the device being used sub-optimally, leading to higher costs.

[0006] One approach to SoC balancing is to use numerical approximation or gradient descent. Another approach is to use a complex and non-generalizable geometric method that analytically calculates the required power. However, this method requires significant re-engineering even for small changes when changes are made to the details of the service or device. Therefore, it is desirable to provide an improved method for operating an energy storage system.

Summary of the Invention

[0007] In view of the above, the present technology is a method of operating an energy storage system, wherein the energy storage system is configured to supply power to the power grid at time tb over a predetermined operating time window, the method comprising determining a current state of charge, SoC, of the energy storage system at time t0; estimating a total energy usage by the energy storage system between time t0 and time tb; determining a predicted SoC of the energy storage system at time tb based on the current SoC and the estimated total energy usage; inputting the predicted SoC, at least one operating constraint, and one or more system parameters into an optimization algorithm, wherein the at least one operating constraint is an operating condition to be satisfied by the energy storage system during a predetermined operating time window, and the one or more system parameters are parameters specific to the energy storage system; using the optimization algorithm to determine a plurality of power values, each corresponding to a time step during a predetermined operating time window, wherein each power value is decomposed into an integer component and a floating-point component; and selecting one or more power values from the plurality of power values having a zero floating-point component to form an operating baseline for the energy storage system to operate during a predetermined operating time window.

[0008] To ensure the overall efficiency of continuous operation and service provision, it is important for an energy storage system to provide effective SoC balancing for the stability of the energy storage system while it is providing energy services. By setting a baseline for the energy storage system before energy supply, the continuity of the service is guaranteed. By changing the baseline, the operator of the energy storage system can manage the SoC of the energy storage system so that the energy storage system can import or export power without interrupting service provision. When determining the baseline, the power value specified in the baseline must be an integer value (e.g., in megawatts MW) aligned with a specified time step (e.g., 1 minute or multiple minutes). According to embodiments of the present technology, a plurality of power values are determined using an optimization algorithm based on a predicted SoC, at least one operating constraint, and one or more parameters representing the energy storage system. Each power value corresponds to a time step during a predetermined operating time window. Each power value is decomposed into an integer component and a floating-point component. Then, one or more power values from the plurality of power values having a zero floating-point component are selected to form an operating baseline. Thus, embodiments of the present technology can determine a baseline for the operation of an energy storage system using only integer values with improved accuracy. Therefore, the present technology enables the energy service by the energy storage system / device to be provided smoothly with little or no interruption, thereby improving the overall efficiency of the operation of the power grid or power supply system.

[0009] In some embodiments, the method may further include determining an average energy usage by the energy storage system at time t0.

[0010] In some embodiments, the total energy usage by the energy storage system between time t0 and time tb may be estimated based on the average energy usage.

[0011] In some embodiments, the method may further include measuring the energy usage during a period preceding time t0.

[0012] In some embodiments, the total energy usage by the energy storage system between time t0 and time tb may be estimated based on the energy usage during a period preceding time t0.

[0013] In some embodiments, the period preceding time t0 may be the period immediately preceding time t0 or any period preceding time t0, and the period preceding time t0 may be 1 hour or a multiple of 1 hour.

[0014] In some embodiments, the one or more system parameters may include one or more of the storage capacity of the energy storage system, the minimum SoC, the maximum SoC, the minimum power, the maximum power, and the relationship between the energy storage system SoC and power.

[0015] In some embodiments, the minimum SoC may be 5% and the maximum SoC may be 95%.

[0016] In some embodiments, at least one operation constraint may include one or more of the target power at a predetermined time within a predetermined operation time window, the minimum power at time tb, the maximum power at time tb, the minimum power at the end time of the predetermined operation time window, and the maximum power at the end time of the predetermined operation time window.

[0017] In some embodiments, the one or more power values may be selected from a plurality of power values based on an energy storage system operating under one or more criteria.

[0018] In some embodiments, one or more criteria may include satisfying a target energy amount supplied over a predetermined operating time window, satisfying a target energy amount received over a predetermined operating time window, operating below a maximum rate of change of power, and the power at which the energy storage system operates not changing from negative to positive or from positive to negative within a single time step.

[0019] In some embodiments, the method may further include operating the energy storage system according to an operating baseline during a predetermined operating time window.

[0020] In some embodiments, the method may further include operating the energy storage system according to an operating baseline in addition to providing a frequency response service during a predetermined operating time window.

[0021] In some embodiments, the predetermined operating time window may include a plurality of time steps, and each time step may correspond to 1 minute, 2 minutes, 3 minutes, 4 minutes, 5 minutes, or a multiple of 1 minute.

[0022] In some embodiments, the optimization algorithm may be a mixed integer linear programming problem algorithm.

[0023] Implementations of the present technology each have at least one of the objectives and / or aspects described above, but do not necessarily have all of them. It should be understood that some aspects of the present technology that result from attempting to achieve the above-described objectives may not satisfy this objective and / or may satisfy other objectives not specifically listed herein.

[0024] Additional and / or alternative features, aspects, and advantages of implementations of the present technology will become apparent from the following description, the accompanying drawings, and the appended claims.

Brief Description of the Drawings

[0025] Next, embodiments will be described with reference to the accompanying drawings.

Figure 1

Figure 2

Figure 3

Figure 4A

Figure 4B

DETAILED DESCRIPTION OF THE INVENTION

[0026] Effective state of charge balancing is important for the stability of an energy storage system while the energy storage system is providing an energy service in order to ensure uninterrupted operation. A baseline is set for the energy storage system and submitted to the power grid before energy supply, and the power imported or exported by the energy storage system during the service can be set. Therefore, by changing the baseline, the operator of the energy storage system can manage the SoC of the energy storage system. The power value specified by the baseline needs to be an integer value (e.g., in megawatts MW) aligned with a specified time step (e.g., 1 minute or multiple minutes). Embodiments of the present technology determine a plurality of power values by applying an optimization algorithm that uses a predicted SoC, at least one operation constraint, and one or more parameters representing the energy storage system. Each power value is decomposed into an integer component and a floating-point component. Then, one or more power values from the plurality of power values having a zero floating-point component are selected to form an operation baseline. By doing so, embodiments of the present technology can determine a baseline for the operation of the energy storage system with improved accuracy using only integer values. Thus, the present technology enables the energy storage system / device to smoothly provide energy services with little or no interruption, thereby improving the overall efficiency of the operation of the power grid.

[0027] According to this embodiment, the baseline of the energy storage system is submitted to the power grid by each operator before the baseline becomes active, that is, before the energy storage system starts providing an energy service. The mechanism used to notify the power grid can vary depending on the specific energy storage system and the service it provides, and the period specified by the baseline can also vary. For example, this period may be 30 minutes, 1 hour, more than 1 hour, etc.

[0028] An embodiment of a method for operating an energy storage system (e.g., a battery for storing renewable energy, a battery from an electric vehicle, etc.) for energy supply using a baseline is shown in FIG. 1. The method may be implemented as software, hardware, or a combination of both. According to this embodiment, the energy usage (e.g., the amount of energy used) in a period preceding the current time is recorded at 102. The preceding period may be the period immediately preceding time t0, or any period preferred at t0. Optionally, a period of any suitable length, such as 30 minutes, 1 hour, multiple hours, etc., may be used. By obtaining the current charge state of the energy storage system at 101, the recorded past energy usage can be used to predict the energy usage between the current time t0 and the time tb when the baseline becomes active over a predetermined operating time window. The predetermined operating time window may be any suitable period, such as 30 minutes, 1 hour, multiple hours, etc., as desired by the operator of the energy storage system and / or in accordance with an agreement with the operator of the power grid.

[0029] For the energy storage system to remain operational, it is necessary to maintain its state of charge between approximately 5% and approximately 95%. When the energy storage system is operating, for example, during a given operating time window, its SoC varies depending on whether the energy storage system is importing or exporting energy and the rate at which it does so. Therefore, a robust and accurate baseline is desirable to enable the energy storage system to provide uninterrupted services while participating in other energy markets. For example, control of the energy storage system to determine an appropriate baseline and operate the energy storage system according to the determined baseline may be performed by a control system. The control system may be integrated into the energy storage system or may be a control system independent of the energy storage system that communicates with the energy storage system via an appropriate communication channel. The control system may be specific to the energy storage system or may be configured to communicate with multiple energy storage systems and operate the multiple energy storage systems simultaneously.

[0030] In this embodiment, at the current time t0, the control system acquires the current SoC of the energy storage system at 101. Further, the control system records the energy usage by the energy storage system over the period preceding the current time t0. The control system is configured with definitions for determining the SoC of the energy storage system to operate the energy storage system at a given power. Using the recorded past energy usage and the current SoC at t0, the control system predicts, at 103, the energy usage between the current time t0 and the time tb when the baseline becomes active, and calculates a target power at which the energy storage system operates at each given period while maintaining the SoC of the energy storage system within the normal operating range. The target power depends on the current SoC.

[0031] Once the predicted energy usage (or predicted SoC) is determined, the control system identifies (104) one or more operating constraints that can affect the baseline. For example, a contractual obligation to supply power at a set time and a set power, or ending a service at a given power to enable a smooth transition to the next service. In this example, these operating constraints can be identified from a service schedule database 104 obtained from the operator of the power grid.

[0032] The identified operating constraints are then input into an optimization routine (algorithm) along with a set of system specifications 105 that define parameters specific to the energy storage system that describe the behavior of the energy storage system, and restrictions applied by the operator of the power grid based on service rules 106 (e.g., restrictions on power fluctuations faster than a speed limit (ramp rate)).

[0033] In this embodiment, a mixed-integer linear programming problem (MILP) approach is used in the optimization routine. Other approaches are possible. Using the MILP approach, the control system inputs the SoC prediction, the identified operating constraints, the system parameters, and any specific limits based on the service rules into a baseline curve optimizer 107 to determine a plurality of power values for operating the energy storage device during a predetermined operating time window, and outputs a baseline every minute at 108.

[0034] By identifying the operating constraints and system parameters, the resulting baseline enables the energy storage system to operate, for example, as follows: - Reach a specific energy import or export during the optimization window, - Meet a specific start power and a specific end power, - The rate of change of power does not exceed a rate threshold (note that there may be different limits for import and export), - The operating power at any given time does not change from positive to negative or vice versa within a single time step (i.e., no spikes).

[0035] Figure 2 shows a schematic example of a baseline that defines the power at which an energy storage system operates at a given time. Positive power values represent the export of energy by the energy storage system, and negative values represent the import of energy.

[0036] The baseline specifies the power at which the energy storage system operates in a given time step. For a power value to be used in the baseline, the power value must be an integer value (e.g., in MW) and must be aligned with the time step (e.g., minute steps). Thus, baseline optimization, e.g., baseline curve optimizer 107, is configured to output a plurality of power values corresponding to time (e.g., per minute) and select one or more integer power values corresponding to integer times (e.g., at that minute).

[0037] Figure 3 shows the technique of the present disclosure in which multiple power values are determined during baseline optimization. In this technique, the power value is output or decomposed into two components, namely, an integer component 310 and a floating-point component 320. A time step at which the floating-point component of the power value is 0 is called a vertex 330. Additional rules may be programmed into the baseline optimization algorithm to limit vertices from being too close in time and to require a monotonic ramp.

[0038] In some embodiments, the optimization algorithm may be configured to prefer a simpler baseline curve with a shallower ramp. By biasing the optimization algorithm towards a simpler baseline curve, the energy storage system can more accurately follow the resulting baseline.

[0039] An example of baseline optimization is shown in FIG. 4A. As shown, a plurality of power values including positive and negative power values are determined by a baseline optimization algorithm for each time step, and each power value is output as an integer component and a floating-point component. A power value having a zero floating-point component indicated by "x" is selected as the vertex.

[0040] FIG. 4B shows a baseline generated from the power values of FIG. 4A. By this baseline optimization routine, all the power values specified by the baseline in FIG. 4B have integer values and are aligned with the time steps.

[0041] As will be understood by those skilled in the art, the present technique can be embodied as a system, method, or computer program product. Accordingly, the present technique may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware.

[0042] Furthermore, the present technique may take the form of a computer program product embodied in a computer-readable medium in which computer-readable program code is embodied. The computer-readable medium may be either a computer-readable signal medium or a computer-readable storage medium. The computer-readable medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of these.

[0043] The computer program code for performing the operations of the present technique may be written in any combination of one or more programming languages including object-oriented programming languages and conventional procedural programming languages.

[0044] For example, the program code for executing the operations of the present technique may include source, object, or executable code of a conventional programming language such as C (interpreted or compiled), or assembly code, code for setting up or controlling an ASIC (application specific integrated circuit) or FPGA (field programmable gate array), or code for a hardware description language such as Verilog (trademark) or VHDL (very high speed integrated circuit hardware description language).

[0045] The program code may be executed entirely on the user's computer, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer via any type of network. The code components may be embodied as procedures, methods, etc., and may include sub-components that can take the form of instructions or sequences of instructions at any level of abstraction, from direct machine instructions of a native instruction set to high-level compiled or interpreted language constructs.

[0046] It will also be apparent to those skilled in the art that all or part of the logical method according to a preferred embodiment of the present technique may be appropriately embodied in a logic device having logic elements for performing the steps of the method, and that such logic elements may comprise components such as programmable logic arrays or logic gates within application specific integrated circuits. Such a logical configuration may be further embodied, for example, using a virtual hardware descriptor language that can be stored and transmitted using a fixed or transmissible carrier medium, to enable elements for temporarily or permanently establishing a logical structure within such an array or circuit.

[0047] The examples and conditional language recited in this specification are intended to assist the reader in understanding the principles of the technology and are not intended to limit the scope thereof to such specifically recited examples and conditions. It will be understood by those skilled in the art that, although not explicitly described or illustrated herein, various configurations that embody the principles of the technology and are within the scope defined by the appended claims can be devised.

[0048] Furthermore, the above description may describe relatively simplified implementations of the technology for purposes of understanding. As will be understood by those skilled in the art, various implementations of the technology can be more complex.

[0049] In some cases, examples of useful modifications to the technology may also be described. This is merely for purposes of assisting understanding and is not intended to limit the scope of the technology or indicate its limitations. These examples of modifications are not an exhaustive list, and those skilled in the art can still make other modifications while remaining within the scope of the technology. Further, where examples of modifications are not described, it should not be construed that the modification is not possible and / or that what is described is the only way to implement that element of the technology.

[0050] Furthermore, all descriptions in this specification listing the principles, aspects, and implementations of the technology, as well as specific examples thereof, are intended to encompass both their structural equivalents and functional equivalents, whether currently known or developed in the future. Thus, for example, as will be understood by those skilled in the art, any block diagram in this specification represents a conceptual diagram of an exemplary circuit embodying the principles of the technology. Similarly, flowcharts, flow diagrams, state transition diagrams, pseudocode, etc. are substantially represented on a computer-readable medium and represent various processes that can be executed by a computer or processor, whether or not such a computer or processor is explicitly shown.

[0051] The functionality of the various elements shown in the figures, including any functional block labeled "processor", can be provided using dedicated hardware as well as hardware capable of executing software in association with appropriate software. When provided by a processor, the functionality may be provided by a single dedicated processor, by a single shared processor, or by a plurality of individual processors, some of which may be shared. Further, the explicit use of the terms "processor" or "controller" should not be construed as exclusively referring to hardware capable of executing software, and may implicitly include, but is not limited to, digital signal processor (DSP) hardware, network processors, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), read only memory (ROM) for storing software, random access memory (RAM), and non-volatile storage devices. Conventional and / or other custom hardware may also be included.

[0052] A software module, or a module that is implied to be simply software, may be represented herein as any combination of flowchart elements or other elements indicating the execution of a process step and / or a textual description. Such modules may be executed by hardware that is explicitly or implicitly shown.

[0053] It will be apparent to those skilled in the art that many improvements and changes can be made to the above exemplary embodiments without departing from the scope of the present technique.

Claims

1. A method for operating an energy storage system, wherein the energy storage system is configured to supply power to an electrical grid at time tb over a predetermined operating time window, the method comprising: determining a current state of charge, SoC, of the energy storage system at time t0; estimating a total energy usage by the energy storage system between the time t0 and the time tb; determining a predicted SoC of the energy storage system at the time tb based on the current SoC and the estimated total energy usage; inputting the predicted SoC, at least one operating constraint, and one or more system parameters into an optimization algorithm, wherein the at least one operating constraint is an operating condition to be satisfied by the energy storage system during the predetermined operating time window, and the one or more system parameters are parameters specific to the energy storage system; using the optimization algorithm to determine a plurality of power values each corresponding to a time step during the predetermined operating time window, each power value being decomposed into an integer component and a floating-point component; selecting one or more power values from the plurality of power values having a zero floating-point component to form an operating baseline for the energy storage system to operate during the predetermined operating time window A method comprising the steps of:

2. The method of claim 1, further comprising determining an average energy usage by the energy storage system during a period preceding the time t0.

3. The method of claim 2, wherein the total energy usage by the energy storage system between the time t0 and the time tb is estimated based on the average energy usage.

4. The method of claim 1, further comprising measuring an energy usage during a period preceding the time t0.

5. The method of claim 4, wherein the total energy usage by the energy storage system between the time t0 and the time tb is estimated based on the energy usage during the period preceding the time t0.

6. The period preceding the time t0 is the period immediately preceding the time t0 or any period preceding the time t0, and the period preceding the time t0 is 1 hour or a multiple of 1 hour, according to the method of claim 4 or 5.

7. The one or more system parameters include one or more of the storage capacity of the energy storage system, the minimum SoC, the maximum SoC, the minimum power, the maximum power, and the relationship between the SoC and power of the energy storage system, according to the method of any one of the preceding claims.

8. The minimum SoC is 5% and the maximum SoC is 95%, according to the method of claim 7.

9. The at least one operation constraint includes one or more of the target power at a predetermined time within the predetermined operation time window, the minimum power at the time tb, the maximum power at the time tb, the minimum power at the end time of the predetermined operation time window, and the maximum power at the end time of the predetermined operation time window, according to the method of any one of the preceding claims.

10. The one or more power values are selected from the plurality of power values based on the energy storage system operating under one or more criteria, according to the method of any one of the preceding claims.

11. The one or more criteria include satisfying the target energy amount supplied over the predetermined operation time window, satisfying the target energy amount received over the predetermined operation time window, operating below the maximum rate of change of power, and the power at which the energy storage system operates not changing from negative to positive or from positive to negative within a single time step, according to the method of claim 10.

12. The method further includes operating the energy storage system according to the operation baseline during the predetermined operation time window, according to the method of any one of the preceding claims.

13. The method further includes operating the energy storage system according to the operation baseline in addition to providing a frequency response service during the predetermined operation time window, according to the method of any one of the preceding claims.

14. The method according to any one of the preceding claims, wherein the predetermined operation time window includes a plurality of time steps, and each time step corresponds to 1 minute, 2 minutes, 3 minutes, 4 minutes, 5 minutes, or a multiple of 1 minute. **Claim 15** The method according to any one of the preceding claims, wherein the optimization algorithm is a mixed integer linear programming problem algorithm. **Claim 16** An apparatus for controlling the operation of an energy storage system, wherein the energy storage system is configured to supply power to a power grid at time tb over a predetermined operation time window, the apparatus comprising: a communication circuit; at least one processor; a non-transitory computer-readable medium storing software instructions that, when executed by the at least one processor, cause the apparatus to perform the method according to any one of the preceding claims An apparatus comprising.

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