A method for parallel power control of an energy storage system

Abstract

This invention provides a method for parallel power control of an energy storage system. The method first defines an initial active power droop coefficient m. Then, it obtains an adjustment coefficient K1 based on the average SOC of the input batteries in each PCS and the average maximum SOC of the parallel system. It also obtains an adjustment coefficient K2 based on the average battery voltage of each PCS and the average maximum battery voltage of the parallel system. Furthermore, it calculates the number of battery clusters in each PCS to obtain an adjustment coefficient K3. Finally, it obtains an adjustment coefficient K4 based on the maximum allowable discharge power of the PCS batteries, the maximum allowable discharge power on the inverter side, and the load power percentage. The final droop coefficient M of the PCS is adjusted as M = m * K1 * K2 * K3 * K4. By adjusting the droop coefficient of each PCS in real time, the output power of the PCS is adjusted, enabling PCs with larger load capacities to output more power and PCs with smaller load capacities to output less power in the parallel system. This achieves long-term parallel operation with load, increasing the system's robustness.

Description

Technical Field

[0001] This invention relates to the fields of energy storage systems and new energy power generation systems, and specifically to a method for parallel power control of energy storage systems. Background Technology

[0002] Existing hybrid energy storage systems (HESS) typically consist of different types of energy storage devices and achieve energy management and power distribution through specific parallel topologies. For example... Figure 1 As shown, a typical parallel topology of a hybrid energy storage system in the prior art mainly includes: an energy storage converter PCS (101), a grid GRID (102), and a backup load LOAD (103). The grid and load of the parallel system are connected together through a common coupling point PCC (104). Each PCS can connect to one or two independent battery packs BATTx (105). Each battery pack consists of multiple PACKs connected in series, and each battery pack communicates with the PCS through a communication line (106). The PACK is a battery module or battery pack, which is composed of multiple battery cells connected in series or in parallel to provide the required voltage and capacity. During parallel operation, each PCS communicates in parallel through the parallel line (107). When the grid is normal, the GRID supplies power to the LOAD and charges the BATT at the same time, and the PCS operates in grid-connected mode. When the grid is abnormal, the system disconnects from the grid, and the BATT supplies power to the load through the PCS. At this time, the PCS operates in off-grid mode.

[0003] Existing parallel control methods commonly used in technology are mostly droop control methods, such as... Figure 2-3 As shown, the PCS adjusts the output frequency and voltage in real time according to the active and reactive power of the load. The frequency and active power have a linear relationship: F ​​= F0 - M(P - P0), where F is the current frequency, F0 is the rated frequency, M is the active power droop factor, P is the current active power, and P0 is the rated active power. The voltage and reactive power have a linear relationship: E = E0 - N(Q - Q0), where E is the current voltage amplitude, E0 is the rated voltage amplitude, N is the reactive power droop factor, Q is the current reactive power, and Q0 is the rated reactive power. By adjusting the output frequency and voltage, the load power is evenly distributed. However, in situations such as... Figure 1 In parallel systems with multiple battery inputs, due to differences in the State of Charge (SOC) of each battery cluster, the number of battery packs connected in series in each cluster, and the number of battery clusters connected to each PCS, if the goal is to achieve an absolute even distribution of load power, some PCS will first be tripped by overload protection, followed by the remaining PCS taking on the load alone and subsequently experiencing overload protection.

[0004] To address the aforementioned issues, this invention proposes a parallel power control method for an energy storage system. The PCS adjusts the output power of each PCS in real time based on the battery capacity of the connected BATT and the PCS's own load-carrying capacity, thereby enabling long-term parallel operation of the system and increasing its robustness. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of the aforementioned droop control methods by proposing a parallel power control method for energy storage systems.

[0006] The present invention adopts the following technical solution:

[0007] The parallel power control method for an energy storage system of the present invention is characterized by comprising the following steps:

[0008] S1: Define the initial active power droop coefficient m;

[0009] S2: The adjustment coefficient K1 is obtained based on the average SOC of the input battery of each PCS and the average maximum SOC of the parallel system;

[0010] S3: The adjustment coefficient K2 is obtained based on the average battery voltage of each PCS and the average maximum battery voltage of the parallel system;

[0011] S4: The adjustment factor K3 is obtained by calculating the number of battery clusters in each PCS;

[0012] S5: The adjustment coefficient K4 is obtained based on the maximum allowable discharge power of the PCS battery, the maximum allowable discharge power of the inverter side, and the load power percentage.

[0013] S6: Adjust the final droop coefficient of PCS M=m*K1*K2*K3*K4.

[0014] Optionally, the initial active power droop factor m is defined as follows: given that the allowable frequency drop under full load conditions of the PCS is f, then m = f / Pn, where Pn is the rated power of the PCS;

[0015] Optionally, the adjustment factor K1 is calculated as follows: the PCS obtains the average SOCx of the input battery; each PCS uploads its own SOCx to the host, the host obtains the maximum SOCx value as SOCmax, and sends SOCmax to each PCS, thus obtaining K1 = SOCmax / SOCx.

[0016] Optionally, the adjustment factor K2 is calculated as follows: the PCS obtains the average voltage Vbattx of the input battery; each PCS uploads its own Vbattx to the host, the host obtains the maximum Vbattx value as Vbattmax, and sends Vbattmax to each PCS, thus obtaining K2 = Vbattmax / Vbattx.

[0017] Optionally, the adjustment coefficient K3 is calculated as follows: The PCS obtains the number of battery clusters connected to the input battery. If it is determined that only one battery cluster is connected and running in the PCS, then K3=2; if it is determined that both battery clusters are connected and running in the PCS, then K3=1.

[0018] Optionally, the adjustment factor K4 is calculated as follows: Obtain the maximum allowable discharge current Ibatt of the battery; based on the aforementioned average battery voltage Vbattx, calculate the maximum allowable discharge power Pbattmax of the PCS battery: Pbattmax = Vbattx * Ibatt; calculate the maximum allowable discharge power Pinvmax of the PCS inverter side; obtain the minimum values ​​of Pbattmax and Pinvmax: Pmin = min(Pbattmax, Pinvmax); calculate the maximum phase load power percentage among the three-phase loads of the PCS: Psinglepercentmax = max(PpercentA, PpercentB, PpercentC); calculate the ratio of the maximum phase power percentage of the PCS load to Pinvmax: Psinglepercent = Psinglepercentmax * 3 / Pinvmax; calculate the total power percentage of the three-phase loads of the PCS: Psumload = sum(PpercentA, PpercentB, ... PpercentC); Calculate the ratio of Psumload to Pmin: Psumpercent = Psumload / Pmin; Get the maximum value between Psinglepercent and Psumpercent: Ploadpercent = max(Psinglepercent, Psumpercent), and get K4 = PI(Ploadpercent - 100%) + 1, where PI() is the integral proportional function.

[0019] Optionally, the integral proportional function PI(Err) is OUT=(Kp+Ki / s)*Err, where Kp is the proportional coefficient, Ki is the integral coefficient, and 1 / s is the integral operator.

[0020] The beneficial effects achieved by this invention are:

[0021] 1. The PCS of the present invention adjusts the droop coefficient of each PCS in real time according to the battery capacity of the connected BATT and the load capacity of the PCS itself, thereby adjusting the output power of the PCS. This enables the PCS with a large load capacity to output more power and the PCS with a small load capacity to output less power in the parallel system, thereby enabling the long-term parallel load operation of the system and increasing the robustness of the system.

[0022] 2. This invention dynamically adjusts the droop coefficient, enabling PCSs with strong load-carrying capacity to bear more power, avoiding over-limit operation of a single PCS. It solves the technical problem that traditional fixed droop coefficients may cause some PCSs to overload due to insufficient battery capacity or limited load-carrying capacity, leading to protection shutdown. This achieves overall system load balance and reduces the risk of accidental grid disconnection.

[0023] 3. This invention uses a dynamic droop coefficient to match the PCS response speed with the load capacity, quickly smoothing out fluctuations. It solves the technical problem in existing technologies where systems with fixed droop coefficients may experience voltage / frequency fluctuations due to uneven power distribution during sudden changes in the power grid or load. This achieves the technical effect of improving the system's robustness to transient disturbances and maintaining voltage / frequency stability.

[0024] 4. This invention dynamically adjusts the droop coefficient, enabling high-capacity battery packs to bear more energy loads while small-capacity batteries only provide auxiliary power support. This solves the technical problem that if a PCS with a smaller battery capacity is forced to continuously output high power, it may accelerate battery degradation. This achieves the technical effect of extending the life of low-capacity batteries and reducing system maintenance costs.

[0025] 6. This invention dynamically allocates power so that each PCS operates in its optimal efficiency range, solving the problem that if a PCS with low load capacity is forced to operate at high power, energy consumption may increase due to decreased efficiency (such as increased heat dissipation). This achieves the technical effect of reducing ineffective losses and improving the overall energy efficiency of the system.

[0026] 7. This invention avoids local overheating by dynamically adjusting power distribution, thus solving the problem that fixed power distribution may cause some PCS to operate at high load for a long time and have excessive temperature rise. This achieves the technical effect of reducing heat dissipation requirements and reducing cooling system energy consumption.

[0027] 8. This invention dynamically allocates power based on battery capacity and PCS load capacity by adjusting the droop coefficient of the PCS in real time. To a certain extent, it solves the problems of traditional parallel systems requiring strict consistency of PCS and battery parameters and poor flexibility in capacity expansion. It provides a technical possibility for mixed access of equipment with different capacities and models, reducing the cost of system upgrades and modifications.

[0028] 9. This invention provides technical support for adapting to high-dynamic scenarios such as fast charging of electric vehicles and peak shaving of microgrids by rapidly responding to load fluctuations through dynamic power allocation.

[0029] 10. This invention optimizes the power allocation strategy so that high-load-capacity PCS can bear more load, solving the problem that traditional solutions require configuring the capacity of all PCS according to the peak load, and achieving the technical effect of reducing initial investment costs.

[0030] 11. By balancing the load distribution among PCS, this invention solves the problem of some devices operating under high load for a long time due to fixed allocation, thereby achieving the technical effects of extending equipment life and reducing operation and maintenance costs, and thus comprehensively improving the system's flexibility, stability and economy.

[0031] To further understand the features and technical content of the present invention, please refer to the following detailed description and drawings of the present invention. However, the drawings provided are for reference and illustration only and are not intended to limit the present invention. Attached Figure Description

[0032] Figure 1 This is a parallel topology for existing hybrid energy storage systems;

[0033] Figure 2 The diagram shows the linear relationship between frequency and active power in the existing droop control method.

[0034] Figure 3 The diagram shows the linear relationship between voltage and reactive power in the existing droop control method.

[0035] Figure 4 This is a schematic diagram of the method flow of the present invention;

[0036] Figure 5 This is a schematic diagram of the method flow corresponding to Embodiment Six of the present invention.

[0037] Figure descriptions: 101: Energy storage converter PCS; 102: Grid GRID; 103: Backup load LOAD; 104: Point of common coupling PCC; 105: Battery pack BATTx; 106: Communication line; 107: Parallel line; PCS1: First energy storage converter; PCSx: xth energy storage converter; BMS-COM1: First communication module; BMS-COM2: Second communication module; PARA-COM: Parallel communication module. Detailed Implementation

[0038] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can understand the advantages and effects of the present invention from the content disclosed in this specification. The present invention can be implemented or applied through other different specific embodiments, and various details in this specification can also be modified and changed based on different viewpoints and applications without departing from the spirit of the present invention. Furthermore, the accompanying drawings of the present invention are for simple illustrative purposes only and are not depictions of actual dimensions; this is stated in advance. The following embodiments will further describe the relevant technical content of the present invention in detail, but the disclosed content is not intended to limit the scope of protection of the present invention.

[0039] Example 1: According to the attached diagram Figure 4 This embodiment provides a parallel power control method for an energy storage system according to the present invention, characterized by comprising the following steps:

[0040] S1: Define the initial active power droop coefficient m;

[0041] S2: The adjustment coefficient K1 is obtained based on the average SOC of the input battery of each PCS and the average maximum SOC of the parallel system;

[0042] S3: The adjustment coefficient K2 is obtained based on the average battery voltage of each PCS and the average maximum battery voltage of the parallel system;

[0043] S4: The adjustment factor K3 is obtained based on the number of battery clusters in each PCS;

[0044] S5: The adjustment coefficient K4 is obtained based on the maximum allowable discharge power of the PCS battery, the maximum allowable discharge power of the inverter side, and the load power percentage.

[0045] S6: Adjust the final droop coefficient of PCS M=m*K1*K2*K3*K4.

[0046] Existing energy storage systems often employ droop control during off-grid parallel operation. To ensure full-load operation, the droop coefficients of each PCS (Power Control System) are typically set to the same value, with each PCS sharing the load equally. However, for PCS with multiple battery input ports, since the configurations of each battery input are different, if the droop coefficients remain the same, some PCS in the parallel system will overload, leading to a phenomenon where all PCS in the system subsequently trigger overload protection, resulting in poor system robustness. In this embodiment, the PCS adjusts its droop coefficient in real time based on the battery capacity of the connected battery pack and the PCS's own load capacity, thereby adjusting the PCS's output power. This ensures that PCS with larger load capacity outputs more power and PCS with smaller load capacity output less power, enabling long-term parallel operation and increasing system robustness. By dynamically adjusting the droop coefficient, the high-capacity battery pack can bear more energy loads, while the small-capacity battery only provides auxiliary power support. This solves the technical problem that if the PCS with a small battery capacity is forced to continuously output high power, it may accelerate battery degradation. This achieves the technical effect of extending the life of low-capacity batteries and reducing system maintenance costs.

[0047] Example 2: This example should be understood as including all the features of any of the foregoing examples, and further improving upon them.

[0048] Optionally, the initial active power droop factor m is defined as follows: if the allowable frequency drop under full load condition of PCS is f, then m = f / Pn, where Pn is the rated power of PCS.

[0049] The initial setting of the droop factor based on rated power ensures that PCS of different capacities share the load proportionally during the initial grid connection phase, avoiding overload of small-capacity devices or underutilization of large-capacity devices. Simultaneously, this strategy provides a benchmark reference for subsequent dynamic adjustments, enabling the system to respond quickly to power fluctuations (such as microgrid frequency regulation) and smoothly transition to the optimal operating point through adaptive algorithms. This maximizes the overall system's load-carrying capacity and economy while ensuring the safe operation of each PCS device. This method of deeply coupling hardware capabilities with control strategies significantly improves the scalability and long-term robustness of hybrid energy storage systems.

[0050] Example 3: This example should be understood as including all the features of any of the foregoing examples, and further improving upon them.

[0051] Optionally, the adjustment coefficient K1 is calculated as follows: The PCS obtains the average SOCx of the input batteries. If it determines that only one battery cluster is connected and running in the PCS, the SOC of the currently running battery is assigned to SOCx. If it determines that both battery clusters are connected and running in the PCS, then SOCx = (SOC1 + SOC2) / 2. Each PCS uploads its own SOCx to the host. The host obtains the maximum SOCx value as SOCmax and sends SOCmax down to each PCS, resulting in K1 = SOCmax / SOCx.

[0052] Dynamically allocating power based on battery capacity and PCS load capacity solves to some extent the problems of traditional parallel systems requiring strict consistency of PCS and battery parameters and poor expansion flexibility. It provides a technical possibility for mixed access of equipment with different capacities and models, reducing system upgrade and transformation costs.

[0053] Optionally, the K1 limit range is 1 to 4.

[0054] Example 4: This example should be understood as including all the features of any of the foregoing examples, and further improving upon them.

[0055] Optionally, the adjustment factor K2 is calculated as follows: The PCS obtains the average voltage Vbattx of the input battery. When it is determined that only one battery cluster is connected and running in the PCS, the voltage of the running battery is assigned to Vbattx; when it is determined that both battery clusters are connected and running in the PCS, Vbattx = (Vbatt1 + Vbatt2) / 2. Each PCS uploads its own Vbattx to the host. The host obtains the maximum Vbattx value as Vbattmax and sends Vbattmax to each PCS, resulting in K2 = Vbattmax / Vbattx.

[0056] Optionally, the K2 limiting range is 1 to 4.

[0057] In this embodiment, the PCS adjusts the droop coefficient of each PCS in real time based on the battery capacity of the connected BATT and the load capacity of the PCS itself, thereby adjusting the output power of the PCS. This allows the PCS with a larger load capacity to output more power and the PCS with a smaller load capacity to output less power in the parallel system, thus enabling long-term parallel operation of the system and increasing the system's robustness.

[0058] Example 5: This example should be understood as including all the features of any of the foregoing examples, and further improving upon them.

[0059] Optionally, the adjustment coefficient K3 is calculated as follows: the PCS obtains the number of battery clusters connected to the input battery. When it is determined that the PCS has only one battery cluster connected and running, then K3=2; when it is determined that the PCS has two battery clusters connected and running, then K3=1; when it is determined that the PCS has three or more battery clusters connected and running, let the number of clusters be x, then K3=2 / x.

[0060] This invention enables PCS with strong load capacity to carry more power, avoids the over-limit operation of a single PCS, and solves the technical problem that the traditional fixed droop coefficient may cause some PCS to overload due to insufficient battery capacity or limited load capacity, triggering protection shutdown. It achieves the technical effect of overall system load balance and reduces the risk of accidental grid disconnection.

[0061] Example 6: This example should be understood as including all the features of any of the foregoing examples, and further improving upon them.

[0062] like Figure 5 As shown, the optional method for calculating the adjustment coefficient K4 is as follows: obtain the maximum allowable discharge current Ibatt of the battery; calculate the maximum allowable discharge power Pbattmax of the PCS battery based on the aforementioned average battery voltage Vbattx: Pbattmax = Vbattx * Ibatt; calculate the maximum allowable discharge power Pinvmax of the PCS inverter side based on the PCS rated power, over-temperature derating, and other comprehensive factors; obtain the minimum values ​​of Pbattmax and Pinvmax: Pmin = min(Pbattmax, Pinvmax); calculate the maximum phase load power percentage among the three-phase loads of the PCS Psinglepercentmax = max(PpercentA, PpercentB, PpercentC); calculate the ratio of the maximum phase power percentage of the PCS load to Pinvmax: Psinglepercent = Psinglepercentmax * 3 / Pinvmax. Calculate the percentage of total three-phase load power in the PCS: Psumload = sum(PpercentA, PpercentB, PpercentC); Calculate the percentage of Psumload to Pmin: Psumpercent = Psumload / Pmin. Obtain the maximum value between Psinglepercent and Psumpercent: Ploadpercent = max(Psinglepercent, Psumpercent), resulting in K4 = PI(Ploadpercent - 100%) + 1, where PI() is the integral proportional function.

[0063] This embodiment uses a dynamic droop coefficient to match the PCS response speed with the load capacity, quickly smoothing out fluctuations. It solves the technical problem in existing technologies where systems with fixed droop coefficients may experience voltage / frequency fluctuations due to uneven power distribution when the power grid or load changes abruptly. This achieves the technical effect of improving the system's robustness to transient disturbances and maintaining voltage / frequency stability.

[0064] The Ibatt value for each battery is not necessarily the same. The Ibatt value will be different in different states of the battery. The value may also be different due to different settings. The PCS obtains the maximum allowable discharge current based on the current state of the battery (such as temperature, SOC, health status, etc.).

[0065] Optionally, the K4 clipping range is 1 to 4.

[0066] Example 7: This example should be understood as including all the features of any of the foregoing examples, and further improving upon them.

[0067] Optionally, the transfer function of PI(Err) is OUT=(Kp+Ki / s)*Err, where Kp is the proportional coefficient, Ki is the integral coefficient, and 1 / s is the integral operator. That is, K4=(Kp+Ki / s)*(Ploadpercent-100%)+1.

[0068] Optionally, the limiting range of K1*K2*K3*K4 is 1~4, and the limiting range of M is 0.25~1.0.

[0069] This embodiment utilizes a PI function in PCS droop control to smoothly adjust power distribution, avoiding oscillation or residual problems caused by traditional pure proportional control. Furthermore, the adjustability of the PI parameters (such as adjusting the integral time constant) allows it to flexibly adapt to different operating conditions (such as high-inertia loads or high-frequency fluctuations), providing a robust and adaptive control basis for complex systems (such as hybrid energy storage and microgrids).

[0070] This invention addresses the problem of fixed power allocation failing to fully utilize the potential of PCS (Power Control System) by rapidly responding to load fluctuations through dynamic power allocation, providing technical support for adapting to highly dynamic scenarios such as fast charging of electric vehicles and peak shaving in microgrids. It enables PCSs with high load-carrying capacity to handle more power, preventing individual PCS from operating beyond their limits. This solves the technical problem that traditional fixed droop coefficients may cause some PCSs to overload due to insufficient battery capacity or limited load-carrying capacity, triggering protective shutdowns. This achieves overall system load balance and reduces the risk of unexpected grid disconnection. By dynamically allocating power, each PCS operates within its optimal efficiency range, solving the problem that forced high-power operation of low-load-carrying-capacity PCS may lead to increased energy consumption due to decreased efficiency (such as increased heat dissipation). This reduces ineffective losses and improves overall system energy efficiency. Furthermore, by dynamically adjusting power allocation, it avoids localized overheating, solving the problem that fixed power allocation may cause some PCSs to operate at high loads for extended periods, resulting in excessive temperature rise. This reduces heat dissipation requirements and lowers cooling system energy consumption.

[0071] The content disclosed above is only a preferred and feasible embodiment of the present invention, and is not intended to limit the scope of protection of the present invention. Therefore, all equivalent technical changes made based on the content of the present invention specification and drawings are included within the scope of protection of the present invention. Furthermore, the elements therein can be updated as technology develops.

Claims

1. A method for parallel power control of an energy storage system, characterized in that, Includes the following steps: S1: Define the initial active power droop coefficient m; S2: The adjustment coefficient K1 is obtained based on the average SOC of the input battery of each PCS and the average maximum SOC of the parallel system; S3: The adjustment coefficient K2 is obtained based on the average battery voltage of each PCS and the average maximum battery voltage of the parallel system; S4: The adjustment factor K3 is obtained by calculating the number of battery clusters in each PCS; S5: The adjustment coefficient K4 is obtained based on the maximum allowable discharge power of the PCS battery, the maximum allowable discharge power of the inverter side, and the load power percentage. S6: Adjust the final droop coefficient of PCS M=m*K1*K2*K3*K4; The adjustment factor K4 is calculated as follows: Obtain the maximum allowable discharge current Ibatt of the battery, and calculate the maximum allowable discharge power Pbattmax of the PCS battery based on the aforementioned average battery voltage Vbattx: Pbattmax = Vbattx * Ibatt; Calculate the maximum allowable discharge power Pinvmax of the PCS inverter side. To obtain the minimum values ​​of Pbattmax and Pinvmax: Pmin = min(Pbattmax, Pinvmax); Calculate the maximum phase load power percentage in the three-phase load of the PCS: Psinglepercentmax = max(PpercentA, PpercentB, PpercentC); Calculate the ratio of the maximum phase power percentage of the PCS load to Pinvmax: Psinglepercent = Psinglepercentmax * 3 / Pinvmax; Calculate the total power percentage of the three-phase load of the PCS: Psumload = sum(PpercentA, PpercentB, PpercentC); Calculate the ratio of Psumload to Pmin: Psumpercent = Psumload / Pmin; Obtain the maximum value between Psinglepercent and Psumpercent: Ploadpercent = max(Psinglepercent, Psumpercent), resulting in K4 = PI(Ploadpercent - 100%) + 1, where PI() is the integral proportional function.

2. The parallel power control method for an energy storage system as described in claim 1, characterized in that, The initial active power droop factor m is defined as follows: given that the allowable frequency drop under full load conditions of the PCS is f, then m = f / Pn, where Pn is the rated power of the PCS.

3. The parallel power control method for an energy storage system as described in claim 1, characterized in that, The adjustment factor K1 is calculated as follows: the PCS obtains the average SOCx of the input battery; each PCS uploads its own SOCx to the host, the host obtains the maximum SOCx value as SOCmax, and sends SOCmax down to each PCS, thus obtaining K1 = SOCmax / SOCx.

4. The parallel power control method for an energy storage system as described in claim 1, characterized in that, The adjustment factor K2 is calculated as follows: the PCS obtains the average voltage Vbattx of the input battery; each PCS uploads its own Vbattx to the host, the host obtains the maximum Vbattx value as Vbattmax, and sends Vbattmax to each PCS, thus obtaining K2 = Vbattmax / Vbattx.

5. The parallel power control method for an energy storage system as described in claim 1, characterized in that, The adjustment factor K3 is calculated as follows: The PCS obtains the number of battery clusters connected to the input battery. If it is determined that only one battery cluster is connected and running in the PCS, then K3=2; if it is determined that both battery clusters are connected and running in the PCS, then K3=1.

6. The parallel power control method for an energy storage system as described in claim 1, characterized in that, The integral proportional function PI(Err) is OUT=(Kp+Ki / s)*Err, where Kp is the proportional coefficient, Ki is the integral coefficient, and 1 / s is the integral operator.

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