Energy storage system dispatching control method and system

Abstract

The application provides a kind of energy storage system scheduling method and system, energy management system EMS and battery data center BDC realize data sharing, according to grid dispatching demand and each battery cluster battery parameter sent by BDC, to realize each battery cluster battery parameter equalization as control target generation local controller LC corresponding first instruction current, realize EMS level closed loop scheduling control.Power conversion unit according to second instruction current controls scheduling battery cluster, battery cluster management unit sends the battery parameter of battery cluster after scheduling control to BDC, realizes the closed loop scheduling control of power conversion unit level.The application improves the scheduling control precision of each battery cluster in energy storage system and the alignment degree of the battery parameter of each battery cluster through EMS level closed loop scheduling control and power conversion unit level closed loop scheduling control, thereby improves the overall constant power amplitude and duration of energy storage system.

Description

Technical Field

[0001] This invention relates to the field of power electronics technology, and more specifically, to a method and system for scheduling and controlling an energy storage system. Background Technology

[0002] With the development of photovoltaic and energy storage technologies, batteries are being used more and more widely in the energy sector.

[0003] During the operation of a large-scale energy storage system, various parameters of each battery cluster, such as SOC (super capacitor state of charge) and SOH (state of health), may become inconsistent, affecting the charging and discharging power of the energy storage system. Summary of the Invention

[0004] In view of this, the present invention provides an energy storage system scheduling and control method and system. Through closed-loop scheduling and control at the EMS level and the battery cluster management unit level, the scheduling and control accuracy of each battery cluster in the energy storage system and the alignment degree of battery parameters of each battery cluster are improved, thereby improving the overall constant power amplitude and duration of the energy storage system.

[0005] To achieve the above-mentioned objectives, the present invention provides the following specific technical solution:

[0006] A method for scheduling and controlling an energy storage system, comprising:

[0007] The Energy Management System (EMS) generates a first command current based on the grid dispatch requirements and the battery parameters of each battery cluster sent by the Battery Data Center (BDC) to achieve the balance of battery parameters of each battery cluster as the control objective, and sends the first command current to the local controller (LC).

[0008] The LC distributes current to the battery cluster through the power conversion unit according to the received first command current, and generates a second command current corresponding to the battery cluster.

[0009] The power conversion unit performs scheduling control on the battery clusters according to the second command current, and the battery cluster management unit sends the battery parameters of the scheduled battery clusters to the BDC.

[0010] Optionally, the power conversion unit performs scheduling control of the battery cluster according to the second command current, including:

[0011] The power conversion unit calculates the first state of charge (SOC) of the battery cluster using a battery model algorithm based on the cell voltage, actual temperature, and the second command current of the battery cluster, and uses the first SOC as the scheduling basis to schedule and control the battery cluster.

[0012] Optionally, the battery cluster management unit sends the battery parameters of the battery cluster after scheduling control to the BDC, including:

[0013] The battery cluster management unit calculates the second state of charge (SOC) of the battery cluster using a battery model algorithm based on the cell voltage, actual temperature, and actual current of the battery cluster.

[0014] The battery cluster management unit verifies whether the second state of charge (SOC) exceeds the theoretical value range based on the first state of charge (SOC), and sends the verification result, along with the first and second SOCs, to the BDC.

[0015] Optionally, the battery cluster management unit verifies whether the second state of charge (SOC) exceeds the theoretical range based on the first SOC, including:

[0016] When the second command current is greater than 0, the battery cluster management unit calculates the SOC fluctuation amplitude value according to the preset current fluctuation amplitude, takes the difference between the first state of charge SOC and the SOC fluctuation amplitude value as the lower limit of the theoretical value range, takes the sum of the first state of charge SOC and the SOC fluctuation amplitude value as the upper limit of the theoretical range, and determines whether the second state of charge SOC exceeds the theoretical value range.

[0017] Optionally, the power conversion unit includes an energy storage converter (PCS) and a DC / DC converter, and the battery cluster management unit verifies whether the second state of charge (SOC) exceeds the theoretical range based on the first SOC, including:

[0018] When the second command current is equal to 0, the DC switches on both sides of the DC / DC converter are closed, and the PCS is in a hot standby state, the battery cluster management unit calculates the SOC fluctuation amplitude value according to the preset current fluctuation amplitude, takes the sum of the first state of charge SOC and the SOC fluctuation amplitude value as the upper limit of the theoretical range, and determines whether the second state of charge SOC is less than the upper limit of the theoretical range taken as the sum of the first state of charge SOC and the SOC fluctuation amplitude value.

[0019] Optionally, the battery parameters sent by the BDC to each battery cluster of the EMS are the battery parameters after comprehensive correction.

[0020] Optionally, the method further includes:

[0021] The BDC acquires the cell voltage, actual temperature, actual current, first state of charge (SOC), and second state of charge (SOC) of each battery cluster sent by the battery cluster management unit.

[0022] The BDC calculates the third state of charge (SOC) of the battery cluster using a data-driven algorithm based on the cell voltage, actual temperature, and actual current of the battery cluster.

[0023] The BDC calculates a weighted average of the first state of charge (SOC), the second state of charge (SOC), and the third state of charge (SOC) of the battery cluster to obtain a fourth state of charge (SOC) after comprehensive verification. The weights of the second state of charge (SOC) and the third state of charge (SOC) are greater than the weight of the first state of charge (SOC).

[0024] Optionally, the power conversion unit includes an energy storage converter PCS and a DC / DC converter, or the power conversion unit is a DC / AC converter.

[0025] An energy storage system dispatch and control system includes: an energy management system (EMS), a cell data center (BDC), a local controller (LC), and at least one battery system;

[0026] The battery system includes a power conversion unit, a battery cluster management unit, and battery clusters;

[0027] The EMS is used to generate a first command current based on the grid dispatch requirements and the battery parameters of each battery cluster sent by the BDC, so as to achieve the battery parameter balance of each battery cluster as the control target, and sends the first command current to the LC.

[0028] The LC is used to distribute current to the battery cluster through the power conversion unit according to the received first command current, and generate a second command current corresponding to the battery cluster.

[0029] The power conversion unit performs scheduling control on the battery clusters according to the second command current, and the battery cluster management unit sends the battery parameters of the scheduled battery clusters to the BDC.

[0030] Optionally, the power conversion unit is specifically used to calculate the first state of charge (SOC) of the battery cluster based on the cell voltage, actual temperature, and the second command current of the battery cluster using a battery model algorithm, and to use the first SOC as a scheduling basis to schedule and control the battery cluster.

[0031] Optionally, the battery cluster management unit is specifically used to calculate the second state of charge (SOC) of the battery cluster using a battery model algorithm based on the cell voltage, actual temperature, and actual current of the battery cluster, and to verify whether the second state of charge (SOC) exceeds the theoretical value range based on the first state of charge (SOC), and to send the verification result, the first state of charge (SOC), and the second state of charge (SOC) to the BDC.

[0032] Optionally, the battery cluster management unit is specifically configured to, when the second command current is greater than 0, calculate the SOC fluctuation amplitude value according to the preset current fluctuation amplitude, take the difference between the first state of charge SOC and the SOC fluctuation amplitude value as the lower limit of the theoretical value range, take the sum of the first state of charge SOC and the SOC fluctuation amplitude value as the upper limit of the theoretical range, and determine whether the second state of charge SOC exceeds the theoretical value range.

[0033] Optionally, the power conversion unit includes an energy storage converter (PCS) and a DC / DC converter. Specifically, the battery cluster management unit is used to calculate the SOC fluctuation amplitude value based on a preset current fluctuation amplitude when the second command current is equal to 0, the DC switches on both sides of the DC / DC converter are closed, and the PCS is in a hot standby state. The sum of the first state of charge (SOC) and the SOC fluctuation amplitude value is used as the upper limit of the theoretical range, and it is determined whether the second state of charge (SOC) is less than the upper limit of the theoretical range using the sum of the first state of charge (SOC) and the SOC fluctuation amplitude value.

[0034] Optionally, the battery parameters sent by the BDC to each battery cluster of the EMS are the battery parameters after comprehensive correction.

[0035] Optionally, the BDC is also used for:

[0036] The battery cluster management unit sends the cell voltage, actual temperature, actual current, first state of charge (SOC) and second state of charge (SOC) of each battery cluster.

[0037] The third state of charge (SOC) of the battery cluster is calculated using a data-driven algorithm based on the cell voltage, actual temperature, and actual current of the battery cluster.

[0038] The first state of charge (SOC), the second state of charge (SOC), and the third state of charge (SOC) of the battery cluster are weighted and averaged to obtain a fourth state of charge (SOC) after comprehensive verification. The weights of the second state of charge (SOC) and the third state of charge (SOC) are greater than the weight of the first state of charge (SOC).

[0039] Optionally, the power conversion unit includes an energy storage converter PCS and a DC / DC converter, or the power conversion unit is a DC / AC converter.

[0040] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0041] This invention discloses a scheduling and control method for an energy storage system. The Energy Management System (EMS) and the Battery Data Center (BDC) share data. Based on grid scheduling requirements and battery parameters of each battery cluster sent by the BDC, a first command current corresponding to the local controller (LC) is generated with the goal of balancing the battery parameters of each battery cluster, achieving closed-loop scheduling and control at the EMS level. The power conversion unit (PCU) performs scheduling and control of the battery clusters based on the second command current. The battery cluster management unit sends the battery parameters of the scheduled and controlled battery clusters to the BDC, achieving closed-loop scheduling and control at the PCU level. This invention improves the scheduling and control accuracy of each battery cluster in the energy storage system and the alignment of battery parameters through closed-loop scheduling and control at both the EMS and PCU levels, thereby improving the overall constant power amplitude and duration of the energy storage system. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0043] Figure 1 This is a flowchart illustrating a scheduling and control method for an energy storage system disclosed in an embodiment of the present invention;

[0044] Figure 2 This is a schematic diagram of an energy storage system scheduling and control system disclosed in an embodiment of the present invention;

[0045] Figure 3 This is a schematic diagram of another energy storage system scheduling and control system disclosed in an embodiment of the present invention;

[0046] Figure 4 This is a schematic diagram illustrating the relationship between the actual current and the commanded current of the battery cluster under different operating conditions as disclosed in the embodiments of the present invention;

[0047] Figure 5 This is a schematic diagram of the structure of an energy storage system scheduling and control system disclosed in an embodiment of the present invention. Detailed Implementation

[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] This invention provides a scheduling and control method and system for an energy storage system. The energy management system (EMS) and the battery data center (BDC) share data to achieve the control objective of balancing the battery parameters of each battery cluster. Through closed-loop scheduling and control at the EMS level and the power conversion unit level, the scheduling and control accuracy of each battery cluster in the energy storage system and the alignment degree of the battery parameters of each battery cluster are improved, thereby improving the overall constant power amplitude and duration of the energy storage system.

[0050] For details, please refer to Figure 1 This invention discloses a scheduling and control method for an energy storage system, which specifically includes the following steps:

[0051] S101: The Energy Management System (EMS) generates a first command current based on the grid dispatch requirements and the battery parameters of each battery cluster sent by the Battery Data Center (BDC) to achieve the balance of battery parameters of each battery cluster as the control objective, and sends the first command current to the local controller (LC).

[0052] EMS achieves data sharing with BDC, and BDC provides data support to EMS. This enables EMS to predict the power state (SOP) and battery state of energy (SOE) of the energy storage system in the next cycle based on grid dispatch requirements and the battery parameters of each battery cluster sent by BDC. With the goal of balancing the battery parameters of each battery cluster, EMS performs power allocation on LC and generates the first command current corresponding to LC, thus realizing closed-loop dispatch control on a long time scale.

[0053] Preferably, in order to improve the scheduling and control accuracy of the EMS, the battery parameters of each battery cluster sent by the BDC to the EMS are the battery parameters after comprehensive correction.

[0054] S102: The LC distributes the current of the battery cluster through the power conversion unit according to the received first command current, and generates the second command current corresponding to the battery cluster.

[0055] In this embodiment, the power conversion unit can be implemented in various ways. The power conversion unit may include an energy storage converter PCS and a DC / DC converter. The power conversion unit may also be a DC / AC converter. This invention does not impose any specific limitations.

[0056] For example, a power conversion unit may include a PCS and a DC / DC converter. Please refer to [link to relevant documentation]. Figure 2 The schematic diagram of the energy storage system dispatch and control system shown indicates that one end of the PCS is connected to a transformer, and the other end is connected to a DC / DC converter. The cluster-level main circuit achieves DC-DC decoupling through the DC / DC converter and centrally completes the PCS conversion before grid connection. In this case, the LC performs a primary current distribution to the PCS based on the first command current, and the PCS then performs a secondary current distribution to the DC / DC converter to generate the second command current corresponding to the battery cluster.

[0057] Taking a DC / AC rate conversion unit as an example, please refer to [link / reference]. Figure 3 The schematic diagram of the energy storage system dispatch and control system shown depicts a DC / AC converter connected to a low-voltage combiner cabinet at one end and a battery cluster at the other. The cluster-level main circuit uses DC / DC converters for DC-DC decoupling, and each circuit completes its own DC / AC conversion before being centrally connected to the grid. In this case, the LC can perform a single current distribution to the DC / AC converter based on the first command current to generate the second command current corresponding to the battery cluster.

[0058] S103: The power conversion unit performs scheduling control on the battery clusters according to the second command current, and the battery cluster management unit sends the battery parameters of the scheduled battery clusters to the BDC.

[0059] The inventors discovered through research that the actual current of the battery cluster fluctuates within a certain range under certain operating conditions, while the State of Charge (SOC) obtained by integrating the command current in ampere-hours is relatively stable. In order to reduce the fluctuation of the actual current, the SOC obtained by integrating the command current in ampere-hours can be used as the basis for scheduling and controlling the battery cluster.

[0060] The power conversion unit calculates the first state of charge (SOC) of the battery cluster using a battery model algorithm based on the cell voltage, actual temperature, and second command current. The SOC is then used as the basis for scheduling control of the battery cluster. The battery model algorithm is a standard algorithm for calculating SOC and will not be elaborated upon here.

[0061] Specifically, the battery cluster management unit calculates the second state of charge (SOC) of the battery cluster using a battery model algorithm based on the cell voltage, actual temperature, and actual current of the battery cluster. To avoid deviations in SOC estimation and abnormal jumps, the battery cluster management unit or power conversion unit checks whether the second state of charge (SOC) exceeds the theoretical range based on the first SOC of the battery cluster. If the second SOC exceeds the theoretical range, an alarm is triggered. If the first SOC does not exceed the theoretical range, the power conversion unit predicts the second-level, minute-level, and hour-level SOP and SOE of the next cycle based on the consistency of battery parameters of each battery cluster, thereby scheduling and controlling the battery cluster.

[0062] The battery cluster management unit is used to control and manage the battery clusters. The battery cluster management unit is a cluster-level control unit.

[0063] Please see Figure 4 The actual current fluctuation of the battery pack varies under different operating conditions. When the second command current is greater than 0, the actual current will fluctuate around the second command current. When the second command current is equal to 0, the DC switches on both sides of the DC / DC converter are closed, and the PCS is in a hot standby state, the battery pack is in a closed DC circuit, which is equivalent to the battery pack being connected to a DC load, and the actual current will still fluctuate within a certain range. When the second command current is equal to 0, the DC switches on both sides of the DC / DC converter are open, and the PCS is in a cold standby state, the battery pack is in an open DC circuit, so the actual current is also 0, and there is no fluctuation.

[0064] Specifically, when the second command current is greater than 0, the battery cluster management unit calculates the SOC fluctuation amplitude value ΔSOC1 based on the preset current fluctuation amplitude. The difference between the first state of charge SOC (SOC1) and the SOC fluctuation amplitude value ΔSOC1 (SOC1-ΔSOC1) is taken as the lower limit of the theoretical value range, and the sum of the first state of charge SOC (SOC1) and the SOC fluctuation amplitude value ΔSOC1 (SOC1+ΔSOC1) is taken as the upper limit of the theoretical range. The unit then determines whether the second state of charge SOC exceeds the theoretical value range [SOC1-ΔSOC1, SOC1+ΔSOC1].

[0065] When the second command current is equal to 0, the DC switches on both sides of the DC / DC converter are closed, and the PCS is in a hot standby state, the battery cluster management unit calculates the SOC fluctuation amplitude value ΔSOC1 based on the preset current fluctuation amplitude. The sum of the first state of charge SOC (SOC1) and the SOC fluctuation amplitude value ΔSOC1 (SOC1+ΔSOC1) is taken as the upper limit of the theoretical range, and it is determined whether the second state of charge SOC is less than the upper limit of the theoretical range (SOC1+ΔSOC1) taken as the sum of the first state of charge SOC and the SOC fluctuation amplitude value.

[0066] Furthermore, the battery parameters of each battery cluster sent by BDC to EMS are the battery parameters after comprehensive correction. The comprehensive correction method is as follows:

[0067] BDC acquires the cell voltage, actual temperature, actual current, first state of charge (SOC), and second state of charge (SOC) of each battery cluster sent by the battery cluster management unit.

[0068] BDC calculates the third state of charge (SOC) of the battery cluster based on the cell voltage, actual temperature, and actual current of the battery cluster using a data-driven algorithm. The data-driven algorithm does not rely on the battery model or OCV curve, but instead uses BDC's powerful information processing capabilities to calculate the third state of charge (SOC) of the battery cluster through a self-learning method based on big data.

[0069] BDC calculates the weighted average of the first, second, and third states of charge (SOC) of the battery cluster to obtain the fourth SOC after comprehensive verification. The weights of the second and third SOCs are greater than the weight of the first SOC.

[0070] In other words, by comprehensively correcting the SOC calculated based on the command current and the SOC calculated using the data-driven algorithm against the SOC calculated using the conventional algorithm based on the actual current, the accuracy of the SOC is improved. This makes the SOP and SOE predicted based on the comprehensively corrected SOC more accurate, thereby improving the scheduling and control accuracy of the EMS.

[0071] As can be seen, the energy storage system scheduling and control method disclosed in this embodiment achieves data sharing between the energy management system (EMS) and the battery data center (BDC) to achieve battery parameter balancing among various battery clusters as the control objective. This is achieved through closed-loop scheduling and control at both the EMS and power conversion unit levels. Furthermore, battery parameters of battery clusters obtained using different algorithms on different controllers are cross-comprehensively corrected, and the corrected battery parameters are used as the basis for scheduling and control. This improves the scheduling and control accuracy of each battery cluster in the energy storage system and the alignment of battery parameters among the various battery clusters, thereby improving the overall constant power amplitude and duration of the energy storage system.

[0072] Based on the energy storage system scheduling and control method disclosed in the above embodiments, this embodiment correspondingly discloses an energy storage system scheduling and control system. Please refer to [link / reference needed]. Figure 5 The energy storage system dispatch and control system includes: an energy management system EMS100, a cell data center BDC200, a local controller LC300, and at least one battery system 400.

[0073] The battery system 400 includes a power conversion unit 401, a battery cluster management unit 402, and a battery cluster 403.

[0074] The EMS100 is used to generate a first command current based on the grid dispatch requirements and the battery parameters of each battery cluster 403 sent by the BDC200, so as to achieve the balance of battery parameters of each battery cluster 403 as the control target, and sends the first command current to the LC300.

[0075] The LC300 is used to distribute current to the battery cluster 403 through the power conversion unit 401 according to the received first command current, and generate a second command current corresponding to the battery cluster 403.

[0076] The power conversion unit 401 performs scheduling control on the battery cluster 403 according to the second command current, and the battery cluster management unit 402 sends the battery parameters of the scheduled and controlled battery cluster 403 to the BDC.

[0077] Optionally, the power conversion unit 401 is specifically used to calculate the first state of charge (SOC) of the battery cluster 403 based on the cell voltage, actual temperature, and the second command current of the battery cluster 403 using a battery model algorithm, and to use the first SOC as a scheduling basis to schedule and control the battery cluster 403.

[0078] Optionally, the battery cluster 403 management unit 402 is specifically used to calculate the second state of charge (SOC) of the battery cluster 403 using a battery model algorithm based on the cell voltage, actual temperature, and actual current of the battery cluster 403, and to verify whether the second state of charge (SOC) exceeds the theoretical value range based on the first state of charge (SOC), and to send the verification result, the first state of charge (SOC), and the second state of charge (SOC) to the BDC200.

[0079] Optionally, the battery cluster 403 management unit 402 is specifically used to calculate the SOC fluctuation amplitude value according to the preset current fluctuation amplitude when the second command current is greater than 0, take the difference between the first state of charge SOC and the SOC fluctuation amplitude value as the lower limit of the theoretical value range, take the sum of the first state of charge SOC and the SOC fluctuation amplitude value as the upper limit of the theoretical range, and determine whether the second state of charge SOC exceeds the theoretical value range.

[0080] Optionally, the power conversion unit 401 includes an energy storage converter PCS and a DC / DC converter. The battery cluster 403 management unit 402 is specifically used to calculate the SOC fluctuation amplitude value according to the preset current fluctuation amplitude when the second command current is equal to 0, the DC switches on both sides of the DC / DC converter are closed, and the PCS is in a hot standby state. The sum of the first state of charge SOC and the SOC fluctuation amplitude value is used as the upper limit of the theoretical range, and it is determined whether the second state of charge SOC is less than the upper limit of the theoretical range used as the sum of the first state of charge SOC and the SOC fluctuation amplitude value.

[0081] Optionally, the battery parameters sent by the BDC200 to each battery cluster 403 of the EMS100 are battery parameters that have been comprehensively corrected.

[0082] Optionally, the BDC200 is also used for:

[0083] The battery cluster 403 management unit 402 obtains the cell voltage, actual temperature, actual current, first state of charge (SOC) and second state of charge (SOC) of each battery cluster 403.

[0084] The third state of charge (SOC) of battery cluster 403 is calculated using a data-driven algorithm based on the cell voltage, actual temperature, and actual current of battery cluster 403.

[0085] The first state of charge (SOC), the second state of charge (SOC), and the third state of charge (SOC) of the battery cluster 403 are weighted and averaged to obtain a fourth state of charge (SOC) after comprehensive verification. The weights of the second state of charge (SOC) and the third state of charge (SOC) are greater than the weight of the first state of charge (SOC).

[0086] Optionally, the power conversion unit 401 includes an energy storage converter PCS and a DC / DC converter, or the power conversion unit 401 is a DC / AC converter.

[0087] This embodiment discloses a scheduling and control system for an energy storage system. The Energy Management System (EMS) and the Battery Data Center (BDC) share data. Based on grid scheduling requirements and the battery parameters of each battery module cluster sent by the BDC, a first command current corresponding to the local controller (LC) is generated with the goal of balancing the battery parameters of each battery module cluster, achieving closed-loop scheduling control at the EMS level. The power conversion unit performs scheduling control on the battery module clusters based on the second command current. The battery module control unit and battery cluster management unit send the scheduled battery parameters of the battery module clusters to the BDC, achieving closed-loop scheduling control at the power conversion unit level. This invention improves the scheduling and control accuracy of each battery module cluster in the energy storage system and the alignment of battery parameters through closed-loop scheduling control at both the EMS and power conversion unit levels, thereby improving the overall constant power amplitude and duration of the energy storage system.

[0088] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0089] It should also be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0090] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0091] The above embodiments can be combined arbitrarily. The descriptions of the disclosed embodiments and the features recorded in the embodiments of this specification can be substituted or combined with each other, so that those skilled in the art can implement or use this application.

[0092] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A scheduling and control method for an energy storage system, characterized in that, The energy management system EMS generates a first instruction current according to grid scheduling requirements and battery parameters of each battery cluster sent by a battery data center BDC, and sends the first instruction current to a local controller LC, wherein the battery parameters of each battery cluster sent by the BDC to the EMS are the state of charge after comprehensive correction. The LC generates a second instruction current corresponding to the battery cluster by current distribution of the battery cluster through a power conversion unit according to the received first instruction current. The power conversion unit performs scheduling control on the battery cluster according to the second instruction current, and a battery cluster management unit sends the battery parameters of the battery cluster after scheduling control to the BDC. The power conversion unit performs scheduling control on the battery cluster according to the second instruction current, including: The power conversion unit calculates the first state of charge SOC of the battery cluster according to the cell voltage, actual temperature and the second instruction current of the battery cluster by using a battery model algorithm, and performs scheduling control on the battery cluster according to the first state of charge SOC as the scheduling basis. The battery cluster management unit sends the battery parameters of the battery cluster after scheduling control to the BDC, including:

2. The method of claim 1, wherein, The battery cluster management unit calculates the second state of charge SOC of the battery cluster according to the cell voltage, actual temperature and actual current by using a battery model algorithm. The battery cluster management unit checks whether the second state of charge SOC exceeds the theoretical value range according to the first state of charge SOC, and sends the checking result and the first state of charge SOC and the second state of charge SOC to the BDC. The battery cluster management unit checks whether the second state of charge SOC exceeds the theoretical value range according to the first state of charge SOC, including:

3. The method of claim 2, wherein, In the case that the second instruction current is greater than 0, the battery cluster management unit calculates an SOC fluctuation amplitude value according to a pre-set current fluctuation amplitude, takes the difference between the first state of charge SOC and the SOC fluctuation amplitude value as the lower limit of the theoretical value range, takes the sum of the first state of charge SOC and the SOC fluctuation amplitude value as the upper limit of the theoretical value range, and determines whether the second state of charge SOC exceeds the theoretical value range. The power conversion unit includes a power conversion system PCS and a DC / DC, and the battery cluster management unit checks whether the second state of charge SOC exceeds the theoretical value range according to the first state of charge SOC, including:

4. The method of claim 2, wherein, In the case that the second instruction current is equal to 0, the DC / DC is closed on both sides, and the PCS is in a hot standby state, the battery cluster management unit calculates an SOC fluctuation amplitude value according to a pre-set current fluctuation amplitude, takes the sum of the first state of charge SOC and the SOC fluctuation amplitude value as the upper limit of the theoretical value range, and determines whether the second state of charge SOC is less than the upper limit of the theoretical value range. The method further includes:

5. The method of claim 2, wherein, ​ The BDC acquires the cell voltage, actual temperature, actual current, the first state of charge SOC and the second state of charge SOC of each battery cluster sent by the battery cluster management unit; The BDC calculates the third state of charge SOC of the battery cluster by using a data-driven algorithm according to the cell voltage, actual temperature and actual current of the battery cluster; The BDC performs weighted mean calculation on the first state of charge SOC, the second state of charge SOC and the third state of charge SOC of the battery cluster to obtain the fourth state of charge SOC after comprehensive correction, and the weights of the second state of charge SOC and the third state of charge SOC are greater than the weight of the first state of charge SOC.

6. The method of claim 1, wherein, The power conversion unit includes a power conversion system (PCS) and a DC / DC, or the power conversion unit is a DC / AC.

7. An energy storage system dispatch control system, comprising: It comprises: an energy management system (EMS), a battery cell data center (BDC), a local controller (LC) and at least one battery system; The battery system comprises a power conversion unit, a battery cluster management unit and a battery cluster; The EMS is configured to generate a first instruction current with the control target of balancing the battery parameters of each battery cluster according to the grid scheduling demand and the battery parameters of each battery cluster sent by the BDC, and send the first instruction current to the LC, wherein the battery parameters of each battery cluster sent by the BDC to the EMS are the state of charge after comprehensive correction. The LC is configured to perform current distribution on the battery cluster through the power conversion unit according to the received first instruction current to generate a second instruction current corresponding to the battery cluster. The power conversion unit performs scheduling control on the battery cluster according to the second instruction current, and the battery cluster management unit sends the battery parameters of the battery cluster after scheduling control to the BDC. The power conversion unit is specifically configured to calculate the first state of charge SOC of the battery cluster by using a battery model algorithm according to the cell voltage, actual temperature and second instruction current of the battery cluster, and use the first state of charge SOC as the scheduling basis for scheduling control on the battery cluster.

8. The system of claim 7, wherein, The battery cluster management unit is specifically configured to calculate the second state of charge SOC of the battery cluster by using a battery model algorithm according to the cell voltage, actual temperature and actual current of the battery cluster, and check whether the second state of charge SOC exceeds the theoretical value range according to the first state of charge SOC, and send the checking result, the first state of charge SOC and the second state of charge SOC to the BDC.

9. The system of claim 8, wherein, The battery cluster management unit is specifically configured to, in the case that the second instruction current is greater than 0, calculate an SOC fluctuation amplitude value according to a pre-set current fluctuation amplitude, take the difference between the first state of charge SOC and the SOC fluctuation amplitude value as the lower limit of the theoretical value range, take the sum of the first state of charge SOC and the SOC fluctuation amplitude value as the upper limit of the theoretical value range, and determine whether the second state of charge SOC exceeds the theoretical value range.

10. The system of claim 8, wherein, The power conversion unit comprises a power storage converter (PCS) and a DC / DC, and the battery cluster management unit is specifically configured to, in a case where the second instruction current is equal to 0, DC switches on both sides of the DC / DC are closed, and the PCS is in a hot standby state, calculate a SOC fluctuation amplitude value according to a pre-set current fluctuation amplitude, take a sum of the first state of charge (SOC) and the SOC fluctuation amplitude value as an upper limit of the theoretical value range, and determine whether the second state of charge (SOC) is less than the sum of the first state of charge (SOC) and the SOC fluctuation amplitude value as the upper limit of the theoretical value range.

11. The system of claim 8, wherein, The BDC is further configured to: acquire the cell voltage, actual temperature, actual current, the first state of charge (SOC) and the second state of charge (SOC) of each battery cluster sent by the battery cluster management unit; calculate a third state of charge (SOC) of the battery cluster according to the cell voltage, actual temperature and actual current of the battery cluster by using a data-driven algorithm; perform weighted mean calculation on the first state of charge (SOC), the second state of charge (SOC) and the third state of charge (SOC) of the battery cluster to obtain a fourth state of charge (SOC) after comprehensive verification, and the weights of the second state of charge (SOC) and the third state of charge (SOC) are greater than the weight of the first state of charge (SOC).

12. The system of claim 7, wherein, The power conversion unit comprises a power storage converter (PCS) and a DC / DC, or the power conversion unit is a DC / AC.

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