A cluster-level control and balanced power distribution method for sodium ion energy storage power stations

Abstract

The present invention relates to a cluster-level control and balanced power distribution method applicable to sodium ion energy storage power stations. jc <1%, average active power is distributed to the PCS in normal operation; when the maximum extreme difference SOC jc When the active power is ≥1%, the active power of the PCS normally put into SOC balancing operation is allocated according to the current target active power of the battery compartment and the PCS that can be normally put into SOC balancing operation. This can accurately control the charging / discharging voltage range, remaining power and current to avoid overcharging and over-discharging, which can help improve the energy utilization efficiency of the battery, thereby extending the battery life to a certain extent, and solving the problem that sodium-ion energy storage power stations are difficult to achieve cluster-level precise power control and management of energy storage power stations.

Description

Technical Field

[0001] The present invention relates to a cluster-level control and balanced power distribution method applicable to a sodium ion energy storage power station. Background Art

[0002] In recent years, with the large-scale development of new energy sources, electrochemical energy storage has profoundly impacted the energy transition process due to its flexible resource control capabilities. It plays a crucial role in voltage frequency, power supply reliability, and grid energy economy. Lithium-ion batteries are considered one of the most promising energy storage technologies due to their high energy density, high cycle efficiency, and rapid power response. Compared to lithium, sodium is abundant and widely distributed in China. Furthermore, sodium-ion batteries have higher internal resistance than lithium-ion batteries and offer greater safety in the event of a short circuit, including lower instantaneous heat generation, lower temperature rise, and higher thermal runaway temperatures than lithium batteries. Therefore, sodium batteries offer specific advantages in low-temperature, safe, and fast-charging environments. Therefore, the large-scale application of new, high-capacity sodium-ion energy storage batteries (currently, Datang Qianjiang's 50MW / 100MWh sodium-ion new energy storage project has become the world's first 100MWh large-capacity sodium-ion new energy storage demonstration project) will alleviate the potential bottleneck of domestic lithium resource scarcity. Furthermore, the application of sodium-ion batteries in new energy storage will boost the development of the new energy industry, address various issues facing sodium-ion batteries, and accelerate the development of the entire domestic sodium-ion battery industry chain, encompassing production, storage, transportation, and utilization. Therefore, the development of sodium-ion batteries is essential to supporting the sustainable development of large-scale energy storage technology and safeguarding national energy security. Cluster-level control and management algorithms for energy storage power stations play a crucial role in maintaining power balance, managing energy, and ensuring the safe and efficient operation of energy storage facilities. Due to the limited capacity of individual power conversion systems (PCSs), which cannot meet grid dispatch requirements, large-scale energy storage systems typically consist of multiple PCSs to meet capacity and other requirements. During system operation, internal factors (such as manufacturing processes) and external factors (such as maintenance activities, expansion, or temperature changes) may lead to inconsistent state of health (SOH) between battery clusters, thereby seriously shortening the service life of the energy storage system. Therefore, it is necessary to study the balancing problem between battery clusters in the energy storage system.

[0003] With the large-scale application of sodium-ion batteries, the wide voltage characteristics of sodium-ion batteries will affect their lifespan, which depends on a variety of factors. To a certain extent, if the wide voltage characteristic can be properly managed and controlled, it may not have a significant adverse impact on battery lifespan. For example, by optimizing the battery management system to precisely control the voltage range and current of charge and discharge, and avoid overcharging and overdischarging, the wide voltage characteristic may even help improve the battery's energy utilization efficiency, thereby extending the battery's service life to a certain extent. However, if the wide voltage characteristic is not properly addressed, such as if the battery is frequently operated at excessively high or low voltages, it may lead to intensified chemical side reactions within the battery, accelerated damage and degradation of the electrode material structure, and thus shorten the battery's cycle life. In addition, factors such as the properties of the battery materials, the quality of the manufacturing process, and the temperature of the operating environment also interact with the wide voltage characteristic to jointly influence the lifespan of sodium-ion batteries. In summary, the wide voltage characteristic of sodium-ion batteries alone does not necessarily directly determine their lifespan. The key lies in how to effectively manage and control it, and comprehensively consider the influence of other relevant factors. Therefore, in terms of maintaining the power balance of sodium-ion energy storage power stations, managing energy, and ensuring the safe and efficient operation of energy storage facilities, how to achieve precise power control and management at the cluster level of energy storage power stations based on the wide voltage characteristics of sodium-ion batteries has become an urgent problem to be solved in the industry. Summary of the Invention

[0004] In view of the above situation, in order to overcome the shortcomings of the existing technology, the purpose of the present invention is to provide a cluster-level control and balanced power distribution method suitable for sodium ion energy storage power stations, which can effectively solve the problem that sodium ion energy storage power stations are difficult to achieve cluster-level precise power control and management of energy storage power stations.

[0005] The technical solution provided by the present invention is:

[0006] A cluster-level control and balanced power distribution method for a sodium ion energy storage power station includes the following steps:

[0007] S1: Confirm that the PCS corresponding to a battery compartment is communicating normally and has been started, the corresponding battery management system is communicating normally and operating normally, and that the collected voltage, current, and SOC parameters are normal;

[0008] S2: Send the target power setting value Ptar to the battery compartment;

[0009] S3: Selection of active power distribution method for battery cluster in battery compartment

[0010] (1) When the maximum extreme difference SOC jc When the percentage is less than 1% and the number of PCS units in normal operation is ≥ 2, the following allocation method is implemented:

[0011] Based on the current target active power of the battery compartment and the number of PCS units in normal operation, the active power is evenly distributed to the PCS units in normal operation. The active power distribution of the PCS units that cannot be put into normal operation is 0.

[0012] (2) When the maximum extreme difference SOC jc When the percentage is ≥1% and the number of PCS units in normal operation is ≥2, the following allocation method is implemented:

[0013] According to the current target active power of the battery compartment and the PCS that can be normally put into SOC balancing operation, the active power of the PCS normally put into SOC balancing is allocated, and the active power of the PCS that cannot be put into SOC balancing is allocated to 0.

[0014] The charge / discharge SOC balancing strategy issued to a certain battery compartment is as follows:

[0015] 1) When a battery compartment is ordered to discharge, the target active power P tar is a positive value;

[0016] Assuming that PCS 1 to PCS n can all be put into normal operation in a certain battery compartment to perform SOC balancing, the active power distribution method is as follows:

[0017] SOC sum =SOC1+SOC2+...+SOC n

[0018] in:

[0019] SOC1: SOC of battery cluster #1;

[0020] SOC2: SOC of battery cluster #2;

[0021] SOCn: SOC of battery cluster #n;

[0022] SOCsum: The sum of the SOCs of the battery clusters that can participate in SOC balancing. If the PCS corresponding to a battery cluster fails, the SOC value of that cluster is not included in the summation calculation.

[0023] SOC Fac :According to the current SOC maximum extreme difference value (SOC jc ) is obtained from the SOC balance adjustment coefficient selection principle.

[0024] P soc =P tar ×SOC Fac

[0025] P1=(Psoc×SOC1 / SOC sum )+(P tar -P soc ) / n

[0026] P2=(Psoc×SOC2 / SOC sum )+(P tart -P soc ) / n

[0027] P n =(Psoc×SOC n / SOC sum )+(P tart -P soc ) / n

[0028] in,

[0029] Psoc: Power used for SOC balanced distribution;

[0030] SOC Fac : is the SOC adjustment coefficient, which is used to control how much of the total target power is used for SOC balancing. The remaining power is evenly distributed to each PCS. The larger the adjustment coefficient, the greater the SOC balancing effect, and vice versa.

[0031] SOC Fac The value of follows the following principles:

[0032] When the maximum SOC range is 1% ≤ SOC jc <6%, 0≤SOC Fac <0.06;

[0033] When the maximum SOC range is 6% ≤ SOC jc <11%, 0.06≤SOC Fac <0.11;

[0034] When the maximum range of SOC is 11% ≤ SOC jc <16%, 0.11≤SOC Fac <0.16;

[0035] When the maximum range of SOC is 16% ≤ SOC jc <21%, 0.16≤SOC Fac <0.21;

[0036] …

[0037] And so on,

[0038] When the maximum range of SOC is 91% ≤ SOC jc <96%, 0.91≤SOC Fac <0.96;

[0039] When the maximum range of SOC is 96% ≤ SOCjc <99%, 0.96≤SOC Fac <0.99;

[0040] When the maximum SOC difference SOC jc =100%, SOC Fac =1.

[0041] In a certain battery compartment, assuming that PCSs 1 to n-1 can all be put into operation normally, the active power distribution method for SOC balancing is as follows. If PCS n fails and cannot be put into operation, then:

[0042] SOC sum =SOC1+SOC2+...+SOC n-1

[0043] P soc =P tar ×SOC Fac

[0044] P1=(Psoc×SOC1 / SOC sum )+(P tar -P soc ) / n-1

[0045] P2=(Psoc×SOC2 / SOC sum )+(P tar -P soc ) / n-1

[0046] P n-1 =(Psoc×SOCn-1 / SOC sum )+(P tar -P soc ) / n-1

[0047] P n =0

[0048] 2) When a battery compartment is ordered to be charged, the target active power P tar is a negative value;

[0049] Assuming that PCS 1 to PCS n can all be put into normal operation in a certain battery compartment to perform SOC balancing, the active power distribution method is as follows:

[0050] SOC sum =(100-SOC1)+(100-SOC2)+...+(100-SOC n )

[0051] P soc =P tar ×SOC Fac

[0052] P1=(Psoc×(100-SOC1) / SOC sum )+(P tar -P soc ) / n

[0053] P2=(Psoc×(100-SOC2) / SOC sum )+(P tar -P soc ) / n

[0054] P n =(Psoc×(100-SOC n ) / SOC sum )+(P tar -P soc ) / n

[0055] In a certain battery compartment, assuming that PCS 1 to PCS n-1 can all be put into operation normally, the active power distribution method for SOC balancing is as follows, and PCS n fails and cannot be put into operation;

[0056] SOC sum =(100-SOC1)+(100-SOC2)+...+(100-SOC n-1 )

[0057] P soc =P tar ×SOC Fac

[0058] P1=(Psoc×(100-SOC1) / SOC sum )+(P tar -P soc ) / n-1

[0059] P2=(Psoc×(100-SOC2) / SOC sum )+(P tar -P soc ) / n-1

[0060] P n-1 =(Psoc×(100-SOC n-1 ) / SOC sum )+(P tar -P soc ) / n-1

[0061] P n =0

[0062] The method of the present invention proposes a cluster-level control and balanced power distribution method suitable for sodium-ion energy storage power stations, which can accurately control the voltage range, remaining power and current of charging and discharging, avoid overcharging and over-discharging, and help improve the energy utilization efficiency of the battery, thereby extending the battery life to a certain extent, and solving the problem of sodium-ion energy storage power stations being difficult to achieve cluster-level precise power control and management of energy storage power stations. DETAILED DESCRIPTION

[0063] The specific embodiments of the present invention are further described in detail below with reference to the examples.

[0064] The present invention provides a cluster-level control and balanced power distribution method applicable to a sodium ion energy storage power station, comprising the following steps:

[0065] S1: Confirm that the PCS corresponding to a battery compartment is communicating normally and has been started, the corresponding battery management system (BMS) is communicating normally and operating normally, and that the collected voltage, current, and SOC parameters are normal;

[0066] S2: Send the target power setting value Ptar to the battery compartment;

[0067] S3: Selection of active power distribution method for battery cluster in battery compartment

[0068] (1) When the maximum extreme difference SOC jc <1% (when calculating the range, if a cluster's corresponding PCS cannot be put into normal operation, the SOC value of the cluster is not included in the range calculation) and the number of PCSs put into normal operation is ≥2, the following allocation method is implemented:

[0069] Based on the current target active power of the battery compartment and the number of PCS units in normal operation, the active power is evenly distributed to the PCS units in normal operation. The active power distribution of the PCS units that cannot be put into normal operation is 0.

[0070] Assuming that PCS 1 to PCS n can all be put into use in a certain battery compartment, the power distribution is as follows:

[0071] P1=P tar / n

[0072] P2=P tar / n

[0073] P n =P tar / n

[0074] in,

[0075] Ptar: target power setting value of a battery compartment;

[0076] P1: Active power setting value of PCS No. 1;

[0077] P2: active power setting value of PCS No. 2;

[0078] Pn: active power setting value of PCS No. n;

[0079] SOC jc : The maximum extreme difference value of SOC1, ..., SOCn, that is, the difference between the maximum SOC and the minimum SOC;

[0080] After the active power average distribution strategy is executed, the active power of the PCS of each battery cluster in a battery compartment is as follows:

[0081]

[0082] Assuming that PCSs 1 to n-1 are all operational in a battery compartment, and PCS n fails and cannot be put into operation, the power distribution is as follows:

[0083] P1=P tar / n-1

[0084] P2=P tar / n-1

[0085] P n-1 =P tar / n-1

[0086] P n =0

[0087] After the active power average distribution strategy is executed, the active power of the PCS of each battery cluster in a battery compartment is as follows:

[0088]

[0089] (2) When the maximum extreme difference SOC jc ≥1% (when calculating the range, if a cluster's corresponding PCS cannot be put into normal operation, the SOC value of the cluster is not included in the range calculation) and the number of PCSs put into normal operation is ≥2, the following allocation method is implemented:

[0090] According to the current target active power of the battery compartment and the PCS that can be normally put into SOC balancing operation, the active power of the PCS normally put into SOC balancing is allocated, and the active power of the PCS that cannot be put into SOC balancing is allocated to 0.

[0091] The charge / discharge SOC balancing strategy issued to a certain battery compartment is as follows:

[0092] 1) When a battery compartment is ordered to discharge, the target active power P tar is a positive value;

[0093] Assuming that PCS 1 to PCS n can all be put into normal operation in a certain battery compartment to perform SOC balancing, the active power distribution method is as follows:

[0094] SOC sum =SOC1+SOC2+...+SOC n

[0095] in:

[0096] SOC1: SOC of battery cluster #1;

[0097] SOC2: SOC of battery cluster #2;

[0098] SOCn: SOC of battery cluster #n;

[0099] SOCsum: The sum of the SOCs of the battery clusters that can participate in SOC balancing. If the PCS corresponding to a battery cluster fails, the SOC value of that cluster is not included in the summation calculation.

[0100] SOC Fac :According to the current SOC maximum extreme difference value (SOC jc ) is obtained from the SOC balance adjustment coefficient selection principle.

[0101] P soc =P tar ×SOC Fac

[0102] P1=(Psoc×SOC1 / SOC sum )+(P tar -P soc ) / n

[0103] P2=(Psoc×SOC2 / SOC sum )+(P tart -P soc ) / n

[0104] P n =(Psoc×SOC n / SOC sum )+(P tart -P soc ) / n

[0105] in,

[0106] Psoc: Power used for SOC balanced distribution;

[0107] SOC Fac: is the SOC adjustment coefficient, which is used to control how much of the total target power is used for SOC balancing. The remaining power is evenly distributed to each PCS. The larger the adjustment coefficient, the greater the SOC balancing effect, and vice versa.

[0108] SOC Fac The value of follows the following principles:

[0109] When the maximum SOC range is 1% ≤ SOC jc <6%, 0≤SOC Fac <0.06;

[0110] When the maximum SOC range is 6% ≤ SOC jc <11%, 0.06≤SOC Fac <0.11;

[0111] When the maximum range of SOC is 11% ≤ SOC jc <16%, 0.11≤SOC Fac <0.16;

[0112] When the maximum range of SOC is 16% ≤ SOC jc <21%, 0.16≤SOC Fac <0.21;

[0113] …

[0114] And so on,

[0115] When the maximum range of SOC is 91% ≤ SOC jc <96%, 0.91≤SOC Fac <0.96;

[0116] When the maximum range of SOC is 96% ≤ SOC jc <99%, 0.96≤SOC Fac <0.99;

[0117] When the maximum SOC difference SOC jc =100%, SOC Fac =1.

[0118] After the SOC balancing strategy is executed, the PCS active power of each battery cluster in a battery compartment is as follows:

[0119]

[0120] In a certain battery compartment, assuming that PCSs 1 to n-1 can all be put into operation normally, the active power distribution method for SOC balancing is as follows. If PCS n fails and cannot be put into operation, then:

[0121] SOC sum =SOC1+SOC2+...+SOC n-1

[0122] P soc =P tar ×SOC Fac

[0123] P1=(Psoc×SOC1 / SOC sum )+(P tar -P soc ) / n-1

[0124] P2=(Psoc×SOC2 / SOC sum )+(P tart -P soc ) / n-1

[0125] P n-1 =(Psoc×SOC n-1 / SOC sum )+(P tart -P soc ) / n-1

[0126] P n =0

[0127] After the SOC balancing strategy is executed, the PCS active power of each battery cluster in a battery compartment is as follows:

[0128]

[0129] 2) When a battery compartment is ordered to be charged, the target active power P tar is a negative value;

[0130] Assuming that PCS 1 to PCS n can all be put into normal operation in a certain battery compartment to perform SOC balancing, the active power distribution method is as follows:

[0131] SOC sum =(100-SOC1)+(100-SOC2)+...+(100-SOC n )

[0132] P soc =P tar ×SOC Fac

[0133] P1=(Psoc×(100-SOC1) / SOC sum )+(P tar -P soc ) / n

[0134] P2=(Psoc×(100-SOC2) / SOC sum )+(P tar -P soc ) / n

[0135] P n =(Psoc×(100-SOC n ) / SOC sum )+(P tar -P soc ) / n

[0136] After the SOC balancing strategy is executed, the PCS active power of each battery cluster in a battery compartment is as follows:

[0137]

[0138] In a certain battery compartment, assuming that PCS 1 to PCS n-1 can all be put into operation normally, the active power distribution method for SOC balancing is as follows, and PCS n fails and cannot be put into operation;

[0139] SOC sum =(100-SOC1)+(100-SOC2)+...+(100-SOC n-1 )

[0140] P soc =P tar ×SOC Fac

[0141] P1=(Psoc×(100-SOC1) / SOC sum )+(P tar -P soc ) / n-1

[0142] P2=(Psoc×(100-SOC2) / SOC sum )+(P tar -P soc ) / n-1

[0143] P n-1 =(Psoc×(100-SOC n-1 ) / SOC sum )+(P tar -P soc ) / n-1

[0144] P n =0

[0145] After the SOC balancing strategy is executed, the PCS active power of each battery cluster in a battery compartment is as follows:

[0146]

[0147] The present invention has achieved good technical effects through practical application. Taking the power distribution of battery clusters in the battery compartment of a 100-MWh sodium-ion energy storage power station as an example, the power station consists of 21 energy storage units, each unit consists of 2 battery compartments, totaling 42 battery compartments. Each battery compartment consists of 12 battery clusters (each with a rated active power of 100kW and a redundant configuration of 10kW). Based on cluster-level control and management, 12 PCSs (each with a rated active power of 125kW) are used. The following examples are listed:

[0148] S1: Taking battery compartment 1 as an example, confirm that the PCS communication corresponding to battery compartment 1 is normal and has been started, and the corresponding battery management system (BMS) communication is normal and running normally. Confirm that the collected voltage, current and SOC parameters are normal. The SOC conditions under different working conditions are as follows;

[0149] Working condition 1 SOC list

[0150]

[0151] Working condition 2 SOC list

[0152]

[0153] S2: Sends the target power setting value to the battery compartment: -1100kW during charging and 1100kW during discharging;

[0154] S3: Selection of active power distribution method for battery cluster in battery compartment

[0155] (1) Under working condition 1, the maximum extreme difference SOC of the 12 clusters in the battery compartment jc =(70.9-70.1)%=0.8%<1% and the number of PCS units in normal operation is 12≥2, the target power setting value Ptar of the battery compartment during the discharge process is 1100kW; the following distribution method is implemented:

[0156] According to the current target active power of the battery compartment and the number of PCSs in normal operation, the active power is evenly distributed to the PCSs in normal operation. The active power distribution of the PCSs that cannot be put into normal operation is 0.

[0157] If PCSs 1 to 12 corresponding to the battery cluster in battery compartment 1 can all be put into operation, the power distribution is as follows:

[0158] P1=P2......P 12＝ P tar / n=1100 / 12=91.67kW

[0159] After executing the active power average distribution strategy, the PCS of each battery cluster in battery compartment 1 executes the following discharge active power:

[0160]

[0161] PCSs 1 to 11 corresponding to the battery cluster in battery compartment 1 can all be put into operation. PCS 12 fails and cannot be put into operation. The power distribution is as follows:

[0162] P1=P2......P 11＝ P tar / n-1=1100 / 11=100kW,P 12 =0

[0163] After executing the active power average distribution strategy, the PCS discharge active power of each battery cluster in a battery compartment is as follows:

[0164]

[0165] On the contrary, during the charging process, after the active power average distribution strategy is executed, P1=P2......P 12 =-91.67kW; P1 = P2...P 11 =-100kW, P 12 =0kW

[0166] (2) Under working condition 2, the maximum extreme difference SOC of the 12 clusters in the battery compartment jc =(73.1-68.1)%=4%≥1% (When calculating the range, if a cluster's corresponding PCS cannot be put into normal operation, the SOC value of this cluster is not included in the range calculation) and the number of PCSs in normal operation is ≥2, the following allocation method is implemented:

[0167]

[0168] According to the current target active power of the battery compartment and the PCS that can be normally put into SOC balancing operation, the active power of the PCS normally put into SOC balancing is allocated, and the active power of the PCS that cannot be put into SOC balancing is allocated to 0.

[0169] The charge / discharge SOC balancing strategy for battery compartment 1 is as follows:

[0170] 1) When the No. 1 battery compartment is ordered to discharge, the target active power P tar It is a positive value of 1100kW;

[0171] PCSs 1 to 12 corresponding to the battery cluster in battery compartment 1 can all be put into normal operation to perform SOC balancing. The active power distribution method is as follows:

[0172] SOC Fac :According to the current SOC maximum extreme difference value (SOC jc ) is selected as 0.04 from the SOC balance adjustment coefficient selection principle (within the allowable range, the coefficient can be reasonably adjusted according to actual conditions).

[0173] SOC sum =SOC1+SOC2+...+SOC 12 =68.1+70.4+...+70.3=839.4

[0174] P soc =P tar ×SOC Fac =1100*0.04=44kW

[0175] P1=(Psoc×SOC1 / SOC sum )+(P tar -P soc ) / 12=(44*68.1 / 839.4)+(1100-44) / 12=91.57kW

[0176] P2=(Psoc×SOC2 / SOC sum )+(P tart -P soc ) / 12=(44*70.4 / 839.4)+(1100-44) / 12=91.69kW

[0177] P 12 =(Psoc×SOC 12 / SOC sum )+(P tart -P soc ) / 12=(44*70.3 / 839.4)+(1100-44) / 12=91.69kW

[0178] in,

[0179] Psoc: Power used for SOC balanced distribution;

[0180] SOC Fac : is the SOC adjustment coefficient, which is used to control how much of the total target power is used for SOC balancing. The remaining power is evenly distributed to each PCS. The larger the adjustment coefficient, the greater the SOC balancing effect, and vice versa.

[0181] SOC FacThe value of follows the following principles:

[0182] When the maximum SOC range is 1% ≤ SOC jc <6%, 0≤SOC Fac <0.06;

[0183] When the maximum SOC range is 6% ≤ SOC jc <11%, 0.06≤SOC Fac <0.11;

[0184] When the maximum range of SOC is 11% ≤ SOC jc <16%, 0.11≤SOC Fac <0.16;

[0185] When the maximum range of SOC is 16% ≤ SOC jc <21%, 0.16≤SOC Fac <0.21;

[0186] …

[0187] And so on,

[0188] When the maximum range of SOC is 91% ≤ SOC jc <96%, 0.91≤SOC Fac <0.96;

[0189] When the maximum range of SOC is 96% ≤ SOC jc <99%, 0.96≤SOC Fac <0.99;

[0190] When the maximum SOC difference SOC jc =100%, SOC Fac =1.

[0191] After the SOC balancing strategy is executed, the PCS active power of each battery cluster in battery compartment 1 is as follows:

[0192]

[0193] PCSs 1 to 11 corresponding to the battery cluster in battery compartment 1 can all be put into operation normally to perform SOC balancing. The active power distribution method is as follows. If PCS 12 fails and cannot be put into operation, then:

[0194] SOC Fac :According to the current SOC maximum extreme difference value (SOC jc ) is selected as 0.04 from the SOC balance adjustment coefficient selection principle (within the allowable range, the coefficient can be reasonably adjusted according to actual conditions).

[0195] SOC sum =SOC1+SOC2+...+SOC 11 =68.1+70.4+...+69.6=769.1

[0196] P soc =P tar ×SOC Fac =1100*0.4=44

[0197] P1=(Psoc×SOC1 / SOC sum )+(P tar -P soc ) / 11=(44*68.1 / 769.1)+(1100-44) / 11=99.90

[0198] P2=(Psoc×SOC2 / SOC sum )+(P tart -P soc ) / 11=(44*70.4 / 769.1)+(1100-44) / 11=110.3

[0199] P 11 =(Psoc×SOC n-1 / SOC sum )+(P tart -P soc ) / 11=(44*68.1 / 769.1)+(1100-44) / 11=99.98

[0200] P 12 =0

[0201] After the SOC balancing strategy is executed, the PCS active power of each battery cluster in battery compartment 1 is as follows:

[0202]

[0203]

[0204] 2) When the No. 1 battery compartment is ordered to charge, the target active power Ptar is a negative value of -1100kW;

[0205] PCSs 1 to 12 corresponding to the battery cluster in battery compartment 1 can all be put into normal operation to perform SOC balancing. The active power distribution method is as follows:

[0206] SOC Fac :According to the current SOC maximum extreme difference value (SOC jc) is selected as 0.04 from the SOC balance adjustment coefficient selection principle (within the allowable range, the coefficient can be reasonably adjusted according to actual conditions).

[0207] SOC sum =(100-SOC1)+(100-SOC2)+...+(100-SOC 12 )=31.9+29.6+...+27.9=360.6

[0208] P soc =P tar *SOC Fac =-1100*0.04=-44

[0209] SOC Fac :According to the current SOC maximum extreme difference value (SOC jc ) is selected as 0.04 from the SOC balance adjustment coefficient selection principle (within the allowable range, the coefficient can be reasonably adjusted according to actual conditions).

[0210] P1=[Psoc*(100-SOC1) / SOC sum ]+(P tar -P soc ) / 12=-[(44*31.9 / 360.6)+(1100-44) / 12]=-91.89

[0211] P2=[Psoc*(100-SOC2) / SOC sum ]+(P tar -P soc ) / 12=-[(44*29.6 / 360.6)+(1100-44) / 12]=-91.61

[0212] P 12 =[Psoc*(100-SOC 12 ) / SOC sum ]+(P tar -P soc ) / 12=-[(44*29.7 / 360.6)+(1100-44)]=-91.62

[0213] After the SOC balancing strategy is executed, the PCS active power of each battery cluster in battery compartment 1 is as follows:

[0214]

[0215] PCSs 1 to 11 corresponding to the battery cluster in battery compartment 1 can all be put into operation normally to perform SOC balancing and active power distribution as follows. PCS 12 fails and cannot be put into operation;

[0216] SOC sum =(100-SOC1)+(100-SOC2)+...+(100-SOC n-1 )=31.9+29.6+...+30.4=330.9

[0217] P soc =P tar ×SOC Fac =-1100*0.04=44

[0218] P1=[Psoc×(100-SOC1) / SOC sum ]+(P tar -P soc ) / 11=-[(44*31.9 / 360.6)+(1100-44) / 11]=-100.24

[0219] P2=[Psoc×(100-SOC2) / SOC sum ]+(P tar -P soc ) / 11=-[(44*29.6 / 360.6)+(1100-44) / 11]=-99.94

[0220] P 11 =[Psoc*(100-SOC2) / SOC sum ]+(P tar -P soc ) / 11=-[(44*29.6 / 360.6)+(1100-44) / 11]=-100.04

[0221] P 12 =0

[0222] After the SOC balancing strategy is executed, the PCS active power of each battery cluster in battery compartment 1 is as follows:

[0223]

[0224] During the charge / discharge process, if the maximum range difference (SOCjc) of the 12 clusters in battery compartment 1 is 4% or greater than 1%, the SOC balancing strategy is first used to reduce the maximum range difference (0.4%) to below 1% over a period of time. Then, charging / discharging is performed using an evenly distributed active power distribution method. For example, when charging changes from operating condition 2 to operating condition 3, the system switches from operating condition 2 to operating condition 3.

[0225] Before SOC balancing of 12 battery clusters in battery compartment 1

[0226]

[0227] After SOC balancing of the 12 battery clusters in battery compartment 1

[0228]

[0229] As can be seen from the above, the method of the present invention proposes a cluster-level control and balanced power distribution method suitable for sodium ion energy storage power stations. Through SOC balancing or average power distribution, the voltage range, remaining power and current of charging and discharging can be accurately controlled, thereby ensuring the consistency of SOC and voltage, avoiding overcharging and over-discharging, and at the same time helping to improve the energy utilization efficiency of the battery, thereby extending the service life of the battery to a certain extent, and solving the problem that the existing 100-megawatt-hour sodium ion energy storage power station is difficult to achieve cluster-level precise power control and management of the energy storage power station.

Claims

1. A cluster-level control and balanced power distribution method applicable to sodium ion energy storage power stations, characterized in that: The following steps are involved: S1: Confirm that the PCS corresponding to a battery compartment is communicating normally and has been started, the corresponding battery management system is communicating normally and operating normally, and that the collected voltage, current, and SOC parameters are normal; S2: Send the target power setting value Ptar to the battery compartment; S3: Selection of active power distribution method for battery cluster in battery compartment (1) When the maximum extreme difference SOC jc When the percentage is less than 1% and the number of PCS units in normal operation is ≥ 2, the following allocation method is implemented: Based on the current target active power of the battery compartment and the number of PCS units in normal operation, the active power is evenly distributed to the PCS units in normal operation. The active power distribution of the PCS units that cannot be put into normal operation is 0. (2) When the maximum extreme difference SOC jc ≥1% and the number of PCS units in normal operation is ≥2, the following allocation method is implemented: According to the current target active power of the battery compartment and the PCSs that can be put into SOC balancing operation normally, the active power of the PCSs that can be put into SOC balancing operation normally is allocated, and the active power of the PCSs that cannot be put into SOC balancing is allocated to 0; When a discharge command is issued to a battery compartment, the SOC balancing strategy is as follows: When a battery compartment is given a discharge command, the target active power P tar is a positive value; Assuming that PCS 1 to PCS n can all be put into normal operation in a certain battery compartment to perform SOC balancing, the active power distribution method is as follows: SOC sum = SOC1 + SOC2 + ... + SOC n in: SOC1: SOC of battery cluster #1; SOC2: SOC of battery cluster #2; ...... SOCn: SOC of battery cluster #n; SOCsum: The sum of the SOCs of the battery clusters that can participate in SOC balancing. If the PCS corresponding to a battery cluster fails, the SOC value of that cluster is not included in the summation calculation. SOC Fac :According to the current SOC maximum extreme difference value (SOC jc ) is obtained from the SOC balance adjustment coefficient selection principle; P soc = P tar ×SOC Fac P1 = (Psoc×SOC1 / SOC sum )+ (P tar - P soc ) / n P2 = (Psoc×SOC2 / SOC sum )+ (P tart - P soc ) / n ...... P n = (Psoc×SOC n / SOC sum )+ (P tart - P soc ) / n in, Psoc: Power used for SOC balanced distribution; SOC Fac : is the SOC adjustment coefficient, which is used to control how much of the total target power is used for SOC balancing. The remaining power is evenly distributed to each PCS. The larger the adjustment coefficient, the greater the SOC balancing effect, and vice versa. SOC Fac The value of follows the following principles: When the maximum SOC range is 1% ≤ SOC jc <6%, 0≤SOC Fac <0.06; When the maximum SOC range is 6% ≤ SOC jc <11%, 0.06≤SOC Fac <0.11; When the maximum SOC range is 11%≤SOC jc <16%, 0.11≤SOC Fac <0.16; When the maximum range of SOC is 16% ≤ SOC jc <21%, 0.16≤SOC Fac <0.21; …… And so on, When the maximum range of SOC is 91%≤SOC jc <96%, 0.91≤SOC Fac <0.96; When the maximum range of SOC is 96%≤SOC jc <99%, 0.96≤SOC Fac <0.99; When the maximum SOC difference SOC jc =100%, SOC Fac =1; In a certain battery compartment, assuming that PCSs 1 to n-1 can all be put into operation normally, the active power distribution method for SOC balancing is as follows. If PCS n fails and cannot be put into operation, then: SOC sum = SOC1 + SOC2 + ... + SOC n-1 P soc = P tar ×SOC Fac P1 = (Psoc×SOC1 / SOC sum )+ (P tar - P soc ) / n-1 P2 =(Psoc×SOC2 / SOC sum )+ (P tar - P soc ) / n-1 ...... P n-1 = (Psoc×SOCn-1 / SOC sum )+ (P tar - P soc ) / n-1 P n = 0。 2. The cluster-level control and balanced power distribution method applicable to a sodium ion energy storage power station according to claim 1 is characterized in that: When a charging command is issued to a battery compartment, the SOC balancing strategy is as follows: When a battery compartment is given a charging instruction, the target active power P tar is a negative value; Assuming that PCS 1 to PCS n can all be put into normal operation in a certain battery compartment to perform SOC balancing, the active power distribution method is as follows: SOC sum = (100 - SOC1) + (100 - SOC2) + ... + (100 - SOC n , P soc = P tar ×SOC Fac P1 = (Psoc×(100 - SOC1) / SOC sum )+ (P tar - P soc ) / n P2 = (Psoc×(100 - SOC2) / SOC sum )+ (P tar - P soc ) / n ...... P n = (Psoc×(100 - SOC n ) / SOC sum )+ (P tar - P soc ) / n In a certain battery compartment, assuming that PCS 1 to PCS n-1 can all be put into operation normally, the active power distribution method for SOC balancing is as follows, and PCS n fails and cannot be put into operation; SOC sum = (100 - SOC1) + (100 - SOC2) + ... + (100 - SOC n-1 , P soc = P tar ×SOC Fac P1 = (Psoc×(100 - SOC1) / SOC sum )+ (P tar - P soc ) / n-1 P2 = (Psoc×(100 - SOC2) / SOC sum )+ (P tar - P soc ) / n-1 ...... P n-1 = (Psoc×(100 - SOC n-1 ) / SOC sum )+ (P tar - P soc ) / n-1 P n = 0。

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