CN114583735A - Energy storage system scheduling control method and system - Google Patents
Energy storage system scheduling control method and system Download PDFInfo
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- CN114583735A CN114583735A CN202210268631.6A CN202210268631A CN114583735A CN 114583735 A CN114583735 A CN 114583735A CN 202210268631 A CN202210268631 A CN 202210268631A CN 114583735 A CN114583735 A CN 114583735A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0013—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries acting upon several batteries simultaneously or sequentially
- H02J7/0014—Circuits for equalisation of charge between batteries
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0047—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries with monitoring or indicating devices or circuits
- H02J7/0048—Detection of remaining charge capacity or state of charge [SOC]
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/22—The renewable source being solar energy
- H02J2300/24—The renewable source being solar energy of photovoltaic origin
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E70/00—Other energy conversion or management systems reducing GHG emissions
- Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin
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- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
The invention provides an energy storage system scheduling method and system, wherein an energy management system EMS and a battery core data center BDC realize data sharing, and according to power grid scheduling requirements and battery parameters of each battery cluster sent by the BDC, battery parameter balance of each battery cluster is realized to be a control target to generate a first instruction current corresponding to a local controller LC, so that closed-loop scheduling control of an EMS level is realized. And the power conversion unit carries out 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, so that closed-loop scheduling control of the power conversion unit level is realized. According to the invention, through closed-loop scheduling control of an EMS (energy management system) level and closed-loop scheduling control of a power conversion unit level, the scheduling control precision of each battery cluster in the energy storage system and the alignment degree of battery parameters of each battery cluster are improved, so that the integral constant power amplitude and the duration of the energy storage system are improved.
Description
Technical Field
The invention relates to the technical field of power electronics, in particular to a scheduling control method and system for an energy storage system.
Background
With the development of photovoltaic and energy storage technologies, batteries are increasingly widely applied in the field of energy.
In the operation process of a large-scale energy storage system, various parameters of each battery cluster, such as SOC (State of charge) and SOH (State of health), may be inconsistent, which affects the charging and discharging power of the energy storage system.
Disclosure of Invention
In view of this, the present invention provides a method and a system for scheduling and controlling an energy storage system, which improve the scheduling and controlling accuracy of each battery cluster in the energy storage system and the alignment degree of battery parameters of each battery cluster through closed-loop scheduling control at an EMS level and closed-loop scheduling control at a battery cluster management unit level, thereby improving the overall constant power amplitude and the duration of the energy storage system.
In order to achieve the above purpose, the invention provides the following specific technical scheme:
an energy storage system scheduling control method comprises the following steps:
the energy management system EMS generates a first instruction current for a control target by balancing the battery parameters of each battery cluster according to the power grid dispatching requirement and the battery parameters of each battery cluster transmitted by the battery core data center BDC, and transmits the first instruction current to the local controller LC;
the LC distributes current to 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;
and the power conversion unit carries out 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.
Optionally, the scheduling control of the battery cluster by the power conversion unit according to the second instruction current includes:
and the power conversion unit calculates a first state of charge (SOC) of the battery cluster by using a battery model algorithm according to the cell voltage, the actual temperature and the second instruction current of the battery cluster, and performs scheduling control on the battery cluster by using the first SOC as a scheduling basis.
Optionally, the sending, by the battery cluster management unit, the battery parameter of the battery cluster after scheduling control to the BDC includes:
the battery cluster management unit calculates a second state of charge (SOC) of the battery cluster by using a battery model algorithm according to the cell voltage, the actual temperature and the actual current of the battery cluster;
the battery cluster management unit verifies whether the second SOC exceeds a theoretical value range according to the first SOC, and sends a verification result, the first SOC and the second SOC to the BDC.
Optionally, the verifying, by the battery cluster management unit, whether the second state of charge SOC exceeds a theoretical value range according to the first state of charge SOC includes:
under the condition that the second instruction current is larger than 0, the battery cluster management unit calculates an SOC fluctuation amplitude value according to a preset current fluctuation amplitude value, takes the difference value of the first state of charge SOC and the SOC fluctuation amplitude value as the lower limit of the theoretical value range, takes the sum value 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.
Optionally, the power conversion unit includes an energy storage converter PCS and a DC/DC, and the battery cluster management unit verifies whether the second state of charge SOC exceeds a theoretical value range according to the first state of charge SOC, including:
when the second instruction current is equal to 0, the direct current switches on two sides of the DC/DC are closed, and the PCS is in a hot standby state, the battery cluster management unit calculates an SOC fluctuation amplitude value according to a preset current fluctuation amplitude value, 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 smaller than the sum of the first state of charge SOC and the SOC fluctuation amplitude value as the upper limit of the theoretical range.
Optionally, the battery parameters of each battery cluster sent by the BDC to the EMS are battery parameters after comprehensive correction.
Optionally, the method further includes:
the BDC acquires the cell voltage, the actual temperature, the actual current, the first SOC and the second SOC of each battery cluster, which are sent by the battery cluster management unit;
the BDC calculates a third state of charge (SOC) of the battery cluster by using a data driving algorithm according to the cell voltage, the actual temperature and the actual current of the battery cluster;
and the BDC carries out weighted mean calculation on the first SOC, the second SOC and the third SOC of the battery cluster to obtain a fourth SOC after comprehensive verification, and the weights of the second SOC and the third SOC are greater than that of the first SOC.
Optionally, the power conversion unit includes an energy storage converter PCS and a DC/DC, or the power conversion unit is a DC/AC.
An energy storage system dispatch control system, comprising: the system 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 used for generating a first instruction current for a control target according to the power grid dispatching requirement and the battery parameters of each battery cluster sent by the BDC so as to realize battery parameter balance of each battery cluster, and sending the first instruction current to the LC;
the LC is used for distributing current to 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;
and the power conversion unit carries out 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.
Optionally, the power conversion unit is specifically configured to calculate a first state of charge SOC of the battery cluster by using a battery model algorithm according to the cell voltage, the actual temperature, and the second instruction current of the battery cluster, and perform scheduling control on the battery cluster by using the first state of charge SOC as a scheduling basis.
Optionally, the battery cluster management unit is specifically configured to calculate a second state of charge SOC of the battery cluster by using a battery model algorithm according to the cell voltage, the actual temperature, and the actual current of the battery cluster, check whether the second state of charge SOC exceeds a theoretical value range according to the first state of charge SOC, and send a check result, the first state of charge SOC, and the second state of charge SOC to the BDC.
Optionally, the battery cluster management unit is specifically configured to, when the second instruction current is greater than 0, calculate an SOC fluctuation amplitude value according to a preset current fluctuation amplitude, use a difference value between the first state of charge SOC and the SOC fluctuation amplitude value as a lower limit of the theoretical value range, use a sum value between 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 exceeds the theoretical value range.
Optionally, the power conversion unit includes an energy storage converter PCS and a DC/DC, and the battery cluster management unit is specifically configured to calculate an SOC fluctuation amplitude value according to a preset current fluctuation amplitude when the second instruction current is equal to 0, the DC switches on both sides of the DC/DC are closed, and the PCS is in a hot standby state, take a sum of the first state of charge SOC and the SOC fluctuation amplitude value as an upper limit of the theoretical range, and determine whether the second state of charge SOC is smaller than or equal to a sum of the first state of charge SOC and the SOC fluctuation amplitude value as an upper limit of the theoretical range.
Optionally, the battery parameters of each battery cluster sent by the BDC to the EMS are battery parameters after comprehensive correction.
Optionally, the BDC is further configured to:
acquiring the cell voltage, the actual temperature, the actual current, the first state of charge SOC and the second state of charge SOC of each battery cluster, which are sent by the battery cluster management unit;
calculating a third state of charge (SOC) of the battery cluster by using a data driving algorithm according to the cell voltage, the actual temperature and the actual current of the battery cluster;
and performing 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, wherein 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.
Optionally, the power conversion unit includes an energy storage converter PCS and a DC/DC, or the power conversion unit is a DC/AC.
Compared with the prior art, the invention has the following beneficial effects:
the energy management system EMS and the battery core data center BDC realize data sharing, and according to the power grid dispatching requirement and the battery parameters of each battery cluster sent by the BDC, the battery parameter balance of each battery cluster is realized as a control target to generate a first instruction current corresponding to a local controller LC, so that closed-loop dispatching control of an EMS level is realized. And the power conversion unit carries out 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, so that closed-loop scheduling control of the power conversion unit level is realized. According to the invention, through closed-loop scheduling control of an EMS (energy management system) level and closed-loop scheduling control of a power conversion unit level, the scheduling control precision of each battery cluster in the energy storage system and the alignment degree of battery parameters of each battery cluster are improved, so that the integral constant power amplitude and the duration of the energy storage system are improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a schematic flowchart of a method for scheduling and controlling an energy storage system according to an embodiment of the present invention;
fig. 2 is a schematic diagram of an energy storage system scheduling control system according to an embodiment of the present invention;
fig. 3 is a schematic diagram of another energy storage system scheduling control system according to an embodiment of the disclosure;
FIG. 4 is a schematic diagram illustrating a relationship between an actual current and a command current of a battery cluster under different working conditions according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an energy storage system scheduling control system according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides an energy storage system scheduling control method and system, wherein an energy management system EMS and a battery core data center BDC realize data sharing to realize the balance of battery parameters of each battery cluster as a control target, and the scheduling control precision of each battery cluster in the energy storage system and the alignment degree of the battery parameters of each battery cluster are improved through closed-loop scheduling control of an EMS layer and closed-loop scheduling control of a power conversion unit layer, so that the integral constant power amplitude and the duration of the energy storage system are improved.
Specifically, referring to fig. 1, an embodiment of the present invention discloses a method for scheduling and controlling an energy storage system, which specifically includes the following steps:
s101: the energy management system EMS generates a first instruction current for a control target by balancing the battery parameters of each battery cluster according to the power grid dispatching requirement and the battery parameters of each battery cluster transmitted by the battery core data center BDC, and transmits the first instruction current to the local controller LC;
the EMS realizes data sharing with the BDC, and the BDC can provide data support for the EMS, so that the EMS can predict the Power State (State Of Power, SOP) and the battery electric quantity State (State Of energy, SOE) Of the energy storage system output in the second level, the minute level and the hour level Of the next period according to the Power grid scheduling requirement and the battery parameters Of each battery cluster sent by the BDC, and the Power distribution is carried out on the LC to generate a first instruction current corresponding to the LC and realize the closed-loop scheduling control Of a long time scale by taking the battery parameter balance Of each battery cluster as a control target.
Preferably, in order to improve the scheduling control accuracy of the EMS, the battery parameters of each battery cluster transmitted by the BDC to the EMS are battery parameters after comprehensive correction.
S102: the LC distributes current to 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;
in this embodiment, the power conversion unit may be implemented in various manners, the power conversion unit may include an energy storage converter PCS and a DC/DC, and the power conversion unit may also be a DC/AC, which is not limited in the invention.
For example, the power conversion unit may include a PCS and a DC/DC, please refer to the schematic diagram of the energy storage system scheduling control system shown in fig. 2, where one end of the PCS is connected to the transformer and the other end is connected to the DC/DC, the cluster main circuit implements DC decoupling by the DC/DC, and integrates the DC-DC conversion into a grid. In this case, the LC distributes primary current to the PCS according to the first instruction current, and the PCS distributes secondary current to the DC/DC to generate a second instruction current corresponding to the battery cluster.
Taking the rate conversion unit as DC/AC as an example, please refer to the schematic diagram of the energy storage system scheduling control system shown in fig. 3, one end of the DC/AC is connected to the low-voltage bus bar, the other end is connected to the battery cluster, the cluster main circuit realizes DC decoupling by DC/DC, and the DC/AC conversion is respectively completed before centralized grid connection. In this case, the LC may perform current distribution once to the DC/AC according to the first command current, and generate the second command current corresponding to the battery cluster.
S103: and the power conversion unit carries out 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 inventor finds out through research that: under some working conditions, the actual current of the battery cluster fluctuates in a certain range, the SOC obtained by ampere-hour integration of the command current is relatively stable, and in order to reduce the fluctuation of the actual current, the SOC obtained by ampere-hour integration of the command current can be used as the basis for scheduling control of the battery cluster.
The power conversion unit calculates a first state of charge (SOC) of the battery cluster by using a battery model algorithm according to the cell voltage, the actual temperature and the second instruction current of the battery cluster, and the first SOC is used as a scheduling basis to schedule and control the battery cluster. The battery model algorithm is a conventional algorithm for calculating the SOC, and is not described herein again.
Specifically, the battery cluster management unit calculates a second state of charge (SOC) of the battery cluster according to the cell voltage, the actual temperature and the actual current of the battery cluster by using a battery model algorithm, in order to avoid the problems of deviation of SOC estimation, abnormal jump and the like, the battery cluster management unit or the power conversion unit verifies whether the second SOC exceeds a theoretical value range according to the first SOC of the battery cluster, alarms when the second SOC exceeds the theoretical value range, and predicts the second-level SOP, the minute-level SOP and the SOE of the next period according to the consistency of battery parameters of each battery cluster when the first SOC does not exceed the theoretical value range, so as to schedule and control the battery cluster.
The battery cluster management unit is used for controlling and managing the battery cluster, and the battery cluster management unit is a cluster level control unit.
Referring to fig. 4, the actual current fluctuation conditions of the battery clusters under different working conditions are different. Under the condition that the second instruction current is larger than 0, the actual current fluctuates up and down the second instruction current; when the second instruction current is equal to 0, the direct current switches on the two sides of the DC/DC are closed, and the PCS is in a hot standby state, the battery cluster is in a closed direct current loop, namely the battery cluster is connected with a direct current load, and the actual current still fluctuates within a certain range; when the second instruction current is equal to 0, the direct current switches on the two sides of the DC/DC are all disconnected, and the PCS is in the cold standby state, the battery cluster is in the open direct current loop, so that the actual current is also 0, and no fluctuation exists.
Specifically, in the case where the second instruction current is greater than 0, the battery cluster management unit calculates an SOC fluctuation amplitude value Δ SOC1 from a current fluctuation amplitude set in advance, takes a difference (SOC1- Δ SOC1) between the first state of charge SOC (SOC1) and the SOC fluctuation amplitude value Δ SOC1 as a lower limit of a theoretical value range, takes a sum (SOC1+ Δ SOC1) of the first state of charge SOC (SOC1) and the SOC fluctuation amplitude value Δ SOC1 as an upper limit of the theoretical value range, and determines whether the second state of charge SOC exceeds the theoretical value range [ SOC1- Δ SOC1, SOC1+ Δ SOC1 ].
In the case where the second instruction current is equal to 0, the direct current switches on both sides of DC/DC are closed, and the PCS is in the warm standby state, the cluster management unit calculates an SOC fluctuation amplitude value Δ SOC1 from a preset current fluctuation amplitude, takes the sum of the first state of charge SOC (SOC1) and the SOC fluctuation amplitude value Δ SOC1 (SOC1+ Δ SOC1) as the upper limit of the theoretical range, and determines whether the second state of charge SOC is smaller than the upper limit of the theoretical range (SOC1+ Δ SOC1) that is the sum of the first state of charge SOC and the SOC fluctuation amplitude value.
Further, the battery parameters of each battery cluster sent by the BDC to the EMS are battery parameters after comprehensive correction, and the comprehensive correction method is as follows:
the BDC acquires the cell voltage, the actual temperature, the actual current, the first SOC and the second SOC of each battery cluster, which are sent by the battery cluster management unit;
the BDC calculates a third state of charge (SOC) of the battery cluster by using a data driving algorithm according to the cell voltage, the actual temperature and the actual current of the battery cluster, wherein the data driving algorithm does not depend on a battery model and an OCV curve, and the third SOC of the battery cluster is calculated by using strong information processing capacity of the BDC through a big data self-learning method;
and the BDC carries out weighted mean calculation on the first SOC, the second SOC and the third SOC of the battery cluster to obtain a fourth SOC after comprehensive verification, and the weights of the second SOC and the third SOC are greater than that of the first SOC.
That is, the SOC calculated according to the actual current by the conventional algorithm is comprehensively corrected by the SOC calculated according to the command current and the SOC calculated by the data driving algorithm, so that the precision of the SOC is improved, the SOP and the SOE predicted based on the SOC after comprehensive correction are more accurate, and the scheduling control precision of the EMS is improved.
As can be seen, in the energy storage system scheduling control method disclosed in this embodiment, the energy management system EMS and the cell data center BDC implement data sharing to achieve battery parameter balance of each battery cluster as a control target, and the closed-loop scheduling control at the EMS level and the closed-loop scheduling control at the power conversion unit level are implemented. And the battery parameters of the battery clusters obtained by different algorithms are subjected to cross comprehensive correction on different controllers, and the corrected battery parameters are used as a scheduling control basis, so that the scheduling control precision of each battery cluster in the energy storage system and the alignment degree of the battery parameters of each battery cluster are improved, and the integral constant power amplitude and the duration of the energy storage system are improved.
Based on the energy storage system scheduling control method disclosed in the foregoing embodiment, this embodiment correspondingly discloses an energy storage system scheduling control system, please refer to fig. 5, and the energy storage system scheduling control system includes: an energy management system EMS100, a cell data center BDC200, a local controller LC300, and at least one battery system 400;
the battery system 400 includes a power conversion unit 401, a battery cluster management unit 402, and a battery cluster 403;
the EMS100 is configured to generate a first instruction current for a control target according to a power grid scheduling requirement and the battery parameters of each battery cluster 403 sent by the BDC200 to achieve battery parameter balance of each battery cluster 403, and send the first instruction current to the LC 300;
the LC300 is configured to perform current distribution on the battery cluster 403 through the power conversion unit 401 according to the received first instruction current, and generate a second instruction current corresponding to the battery cluster 403;
the power conversion unit 401 performs scheduling control on the battery cluster 403 according to the second instruction current, and the battery cluster management unit 402 sends the battery parameters of the battery cluster 403 after the scheduling control to the BDC.
Optionally, the power conversion unit 401 is specifically configured to calculate a first state of charge SOC of the battery cluster 403 by using a battery model algorithm according to the cell voltage, the actual temperature, and the second instruction current of the battery cluster 403, and perform scheduling control on the battery cluster 403 by using the first state of charge SOC as a scheduling basis.
Optionally, the battery cluster 403 management unit 402 is specifically configured to calculate a second state of charge SOC of the battery cluster 403 by using a battery model algorithm according to the cell voltage, the actual temperature, and the actual current of the battery cluster 403, check whether the second state of charge SOC exceeds a theoretical value range according to the first state of charge SOC, and send a check result, the first state of charge SOC, and the second state of charge SOC to the BDC 200.
Optionally, the battery cluster 403 management unit 402 is specifically configured to, when the second instruction current is greater than 0, calculate an SOC fluctuation amplitude value according to a preset current fluctuation amplitude, use a difference between the first state of charge SOC and the SOC fluctuation amplitude value as a lower limit of the theoretical value range, use 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 exceeds the theoretical value range.
Optionally, the power conversion unit 401 includes an energy storage converter PCS and a DC/DC converter, and the battery cluster 403 management unit 402 is specifically configured to calculate an SOC fluctuation amplitude value according to a preset current fluctuation amplitude when the second instruction current is equal to 0, the direct current switches on both sides of the DC/DC converter are closed, and the PCS is in a hot standby state, take a sum of the first state of charge SOC and the SOC fluctuation amplitude value as an upper limit of the theoretical range, and determine whether the second state of charge SOC is smaller than or equal to a sum of the first state of charge SOC and the SOC fluctuation amplitude value as an upper limit of the theoretical range.
Optionally, the battery parameters sent by the BDC200 to each battery cluster 403 of the EMS100 are battery parameters after comprehensive correction.
Optionally, the BDC200 is further configured to:
acquiring the cell voltage, the actual temperature, the actual current, the first state of charge SOC, and the second state of charge SOC of each battery cluster 403 sent by the battery cluster 403 management unit 402;
calculating a third state of charge (SOC) of the battery cluster 403 by using a data driving algorithm according to the cell voltage, the actual temperature and the actual current of the battery cluster 403;
and performing 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 403 to obtain a fourth state of charge SOC after comprehensive verification, wherein 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.
Optionally, the power conversion unit 401 includes an energy storage converter PCS and a DC/DC, or the power conversion unit 401 is a DC/AC.
In the energy storage system scheduling control system disclosed in this embodiment, an energy management system EMS and a cell data center BDC implement data sharing, and according to a power grid scheduling requirement and battery parameters of each battery module battery cluster sent by the BDC, a first instruction current corresponding to a local controller LC is generated for a control target by implementing battery parameter balance of each battery module battery cluster, so as to implement closed-loop scheduling control at the EMS level. And the power conversion unit carries out scheduling control on the battery module battery cluster according to the second instruction current, and the battery module control unit battery cluster management unit sends the battery parameters of the battery module battery cluster after scheduling control to the BDC, so that closed-loop scheduling control of the power conversion unit level is realized. According to the invention, through closed-loop scheduling control of an EMS (energy management system) level and closed-loop scheduling control of a power conversion unit level, the scheduling control precision of each battery module battery cluster in the energy storage system and the alignment degree of battery parameters of each battery module battery cluster are improved, so that the integral constant power amplitude and the duration of the energy storage system are improved.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
It is further noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The above embodiments can be combined arbitrarily, and the features described in the embodiments in the present specification can be replaced or combined with each other in the above description of the disclosed embodiments, so that those skilled in the art can implement or use the present application.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended 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 (16)
1. An energy storage system scheduling control method is characterized by comprising the following steps:
the energy management system EMS generates a first instruction current for a control target by balancing the battery parameters of each battery cluster according to the power grid dispatching requirement and the battery parameters of each battery cluster transmitted by the battery core data center BDC, and transmits the first instruction current to the local controller LC;
the LC distributes current to 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;
and the power conversion unit carries out 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.
2. The method of claim 1, wherein the power conversion unit performs scheduling control on the battery cluster according to the second instruction current, and comprises:
and the power conversion unit calculates a first state of charge (SOC) of the battery cluster by using a battery model algorithm according to the cell voltage, the actual temperature and the second instruction current of the battery cluster, and performs scheduling control on the battery cluster by using the first SOC as a scheduling basis.
3. The method according to claim 2, wherein the battery cluster management unit transmits the battery parameters of the battery cluster after the scheduling control to the BDC, including:
the battery cluster management unit calculates a second state of charge (SOC) of the battery cluster by using a battery model algorithm according to the cell voltage, the actual temperature and the actual current of the battery cluster;
the battery cluster management unit verifies whether the second SOC exceeds a theoretical value range according to the first SOC, and sends a verification result, the first SOC and the second SOC to the BDC.
4. The method of claim 3, wherein the battery cluster management unit verifying whether the second state of charge SOC is outside of a theoretical range of values based on the first state of charge SOC comprises:
under the condition that the second instruction current is larger than 0, the battery cluster management unit calculates an SOC fluctuation amplitude value according to a preset current fluctuation amplitude value, takes the difference value of the first state of charge SOC and the SOC fluctuation amplitude value as the lower limit of the theoretical value range, takes the sum value 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.
5. The method of claim 3, wherein the power conversion unit comprises an energy storage converter (PCS) and a DC/DC converter, and the battery cluster management unit verifies whether the second state of charge (SOC) is out of a theoretical value range according to the first state of charge (SOC), and comprises:
when the second instruction current is equal to 0, the direct current switches on two sides of the DC/DC are closed, and the PCS is in a hot standby state, the battery cluster management unit calculates an SOC fluctuation amplitude value according to a preset current fluctuation amplitude value, 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 smaller than the sum of the first state of charge SOC and the SOC fluctuation amplitude value as the upper limit of the theoretical range.
6. The method of claim 1, wherein the battery parameters that the BDC sends to each battery cluster of the EMS are synthetically corrected battery parameters.
7. The method according to claims 3 and 6, characterized in that the method further comprises:
the BDC acquires the cell voltage, the actual temperature, the actual current, the first SOC and the second SOC of each battery cluster, which are sent by the battery cluster management unit;
the BDC calculates a third state of charge (SOC) of the battery cluster by using a data driving algorithm according to the cell voltage, the actual temperature and the actual current of the battery cluster;
and the BDC carries out weighted mean calculation on the first SOC, the second SOC and the third SOC of the battery cluster to obtain a fourth SOC after comprehensive verification, and the weights of the second SOC and the third SOC are greater than that of the first SOC.
8. The method of claim 1, wherein the power conversion unit comprises a power storage converter (PCS) and a DC/DC converter, or the power conversion unit is a DC/AC converter.
9. An energy storage system dispatch control system, comprising: the system 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 used for generating a first instruction current for a control target according to the power grid dispatching requirement and the battery parameters of each battery cluster sent by the BDC so as to realize battery parameter balance of each battery cluster, and sending the first instruction current to the LC;
the LC is used for distributing current to 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;
and the power conversion unit carries out 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.
10. The system according to claim 9, wherein the power conversion unit is specifically configured to calculate a first state of charge SOC of the battery cluster by using a battery model algorithm according to the cell voltage, the actual temperature, and the second instruction current of the battery cluster, and perform scheduling control on the battery cluster by using the first state of charge SOC as a scheduling basis.
11. The system according to claim 10, wherein the battery cluster management unit is specifically configured to calculate a second state of charge SOC of the battery cluster by using a battery model algorithm according to a cell voltage, an actual temperature, and an actual current of the battery cluster, check whether the second state of charge SOC exceeds a theoretical value range according to the first state of charge SOC, and send a check result, and the first state of charge SOC and the second state of charge SOC to the BDC.
12. The system according to claim 11, wherein the battery cluster management unit is specifically configured to, when the second command current is greater than 0, calculate an SOC fluctuation amplitude value according to a preset current fluctuation amplitude, use a difference value between the first state of charge SOC and the SOC fluctuation amplitude value as a lower limit of the theoretical value range, use a sum value between 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 exceeds the theoretical value range.
13. The system according to claim 11, wherein the power conversion unit includes an energy storage converter PCS and a DC/DC converter, and the battery cluster management unit is specifically configured to calculate an SOC fluctuation amplitude value according to a preset current fluctuation amplitude value 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, take a sum of the first state of charge SOC and the SOC fluctuation amplitude value as an upper limit of the theoretical range, and determine whether the second state of charge SOC is smaller than or equal to a sum of the first state of charge SOC and the SOC fluctuation amplitude value as an upper limit of the theoretical range.
14. The system of claim 9, wherein the battery parameters that the BDC sends to each battery cluster of the EMS are synthetically corrected battery parameters.
15. The system according to claims 11 and 14, wherein said BDC is further configured to:
acquiring the cell voltage, the actual temperature, the actual current, the first state of charge SOC and the second state of charge SOC of each battery cluster, which are sent by the battery cluster management unit;
calculating a third state of charge (SOC) of the battery cluster by using a data driving algorithm according to the cell voltage, the actual temperature and the actual current of the battery cluster;
and carrying out 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, wherein the weights of the second state of charge SOC and the third state of charge SOC are greater than that of the first state of charge SOC.
16. The system of claim 9, wherein the power conversion unit comprises a power storage converter (PCS) and DC/DC, or the power conversion unit is DC/AC.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115436833A (en) * | 2022-10-19 | 2022-12-06 | 阳光电源股份有限公司 | Energy storage system and SOC correction method thereof |
| CN115800416A (en) * | 2022-08-12 | 2023-03-14 | 宁德时代新能源科技股份有限公司 | Energy storage system, control method of energy storage system, computer device, and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115800416A (en) * | 2022-08-12 | 2023-03-14 | 宁德时代新能源科技股份有限公司 | Energy storage system, control method of energy storage system, computer device, and storage medium |
| CN115800416B (en) * | 2022-08-12 | 2023-11-14 | 宁德时代新能源科技股份有限公司 | Energy storage system, control method of energy storage system, computer device and storage medium |
| CN115436833A (en) * | 2022-10-19 | 2022-12-06 | 阳光电源股份有限公司 | Energy storage system and SOC correction method thereof |
| CN115436833B (en) * | 2022-10-19 | 2024-04-12 | 阳光电源股份有限公司 | Energy storage system and SOC correction method thereof |
| WO2024082604A1 (en) * | 2022-10-19 | 2024-04-25 | 阳光电源股份有限公司 | Energy storage system and soc correction method therefor |
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