Energy storage method, device, medium and equipment based on droop control

Abstract

The present invention discloses an energy storage method, device, medium and equipment based on droop control, including step S1, statistically analyzing all photovoltaic power generation powers P before the current date ev总 and the power P consumed by the load load总 ; step S2, predicting the photovoltaic power generation power and the load consumption power for the next day based on sample data; step S3, calculating the parameters a and b of the exponential droop control through the obtained photovoltaic power generation power P ev and the load consumption power P load ; step S4, inputting the obtained parameters a and b into the ESS controller, and the ESS controller makes a judgment to obtain the charging time t1 and the discharging time t2 of the energy storage system; step S5, controlling the energy storage system according to the charging time t1 and the discharging time t2. The present invention can effectively alleviate the overvoltage and possible congestion along the feeder.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic control, and particularly to an energy storage method, device, medium and equipment based on droop control. Background Art

[0002] In recent years, with the development of photovoltaic power generation, the promotion of clean energy power generation is advocated. It is expected that in the next few years, a large number of photovoltaic power generations connected to the power grid may be vigorously developed, thereby enhancing the reliable operation of the distribution system.

[0003] The large amount of active power of photovoltaic power generation injected into the power grid and the intermittent nature of photovoltaic power generation may pose several technical challenges to the distribution network. Distribution system operators may encounter protection problems, equipment overload and voltage control problems. During high production and low consumption periods, prosumer devices inject a large amount of electricity into the power grid, resulting in reverse power flow to the substation. Reverse power flow may cause congestion problems, and the voltage will exceed the operating limit, especially on low-voltage feeders with increasing photovoltaic penetration. The above problems have become the main obstacles to the further development of photovoltaic in active distribution feeders.

[0004] Existing linear droop control is linear, that is, the energy storage device may already be fully charged at the maximum power generation of photovoltaic power generation, and may be completely discharged at night when the load requires a large amount of electric energy, which may cause a large power exchange on the AC bus, failing to achieve the purpose of reducing the power mismatch problem of the energy storage device. At the same time, the existing linear droop control will cause a reduction in power after control, resulting in a very small mismatch, thus failing to achieve its actual operation purpose. Therefore, how to provide an energy storage method, device, medium and equipment based on droop control is an urgent problem to be solved by those skilled in the art. Summary of the Invention

[0005] An object of the present invention is to provide an energy storage method, device, medium and equipment based on droop control, which can effectively alleviate overvoltage and possible congestion along the feeder.

[0006] An energy storage method based on droop control according to an embodiment of the present invention includes:

[0007] Step S1: Statistically analyze all photovoltaic power generations P ev总 and the power P load总 consumed by the load before the current date to obtain sample data;

[0008] Step S2: Predict the photovoltaic power generation and the power consumed by the load for the next day based on the sample data to obtain the photovoltaic power generation P ev and the power P load consumed by the load;

[0009] Step S3: Calculate the parameters a and b of the exponential droop control based on the obtained photovoltaic power generation P ev and the load consumption power P load ;

[0010] Step S4: Input the obtained parameters a and b into the ESS controller, and the ESS controller determines the charging time t1 and the discharging time t2 of the energy storage system;

[0011] Step S5: Control the energy storage system according to the charging time t1 and the discharging time t2, and then fit the charge-discharge curve of the energy storage device to maximize the self-use of power without flowing to the AC bus, thereby alleviating the power mismatch.

[0012] In an alternative embodiment, the predicted photovoltaic power generation and load consumption power for the next day are determined based on the photovoltaic power generation and load consumption power data recorded in the same period of previous years in the sample data.

[0013] In an alternative embodiment, the formula for determining the exponential droop control of the energy storage system is:

[0014]

[0015] where the parameters a and b are variable constants, and the charge-discharge curves of the energy storage system are adjusted by adjusting the parameters a and b.

[0016] In an alternative embodiment, the control process of the energy storage system selects the charging mode or the discharging mode according to the value of P d :

[0017]

[0018] where is calculated from the above-mentioned photovoltaic power generation and load consumption power.

[0019] In an alternative embodiment, the control of the energy storage system in S5 is restricted by the maximum SoC and the minimum SoC of the battery. If the SoC value reaches one of the limits due to previous control actions, the ESS controller remains idle, that is, in a state of neither charging nor discharging. Otherwise, the control process continues to run to determine the value of P b (t), where the charging power is expressed as and the discharging power is expressed as

[0020] In an alternative embodiment, the obtained control of the energy storage system is combined with the photovoltaic power generation P ev and the load consumption power P load ; the control curve of the energy storage system power is divided into three different intervals, and control is performed separately on each interval.

[0021] In an alternative embodiment, an energy storage system is programmed within the ESS controller.

[0022] An energy storage device based on droop control, comprising:

[0023] A statistical module for statistically analyzing all photovoltaic power generation and power consumed by the load before the current date;

[0024] A prediction module for predicting the photovoltaic power generation and power consumed by the load for the next day based on the statistical module and calculating the parameters of exponential droop control;

[0025] A judgment module for inputting the calculated parameters of exponential droop control into the ESS controller for judgment to obtain the charging and discharging times;

[0026] A main control module for controlling the energy storage system based on the charging and discharging times.

[0027] A computer-readable storage medium, characterized in that it is used to store a computer program, wherein the computer program, when executed by a processor, implements the steps of an energy storage method based on droop control.

[0028] A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that the processor executes the steps of an energy storage method based on droop control.

[0029] The beneficial effects of the present invention are:

[0030] The distributed energy storage system of the present invention can effectively alleviate overvoltage and congestion in the distribution network. The ESS can locally store excess PV energy, thereby alleviating reverse power flow in this way, and thus alleviating overvoltage and possible congestion along the feeder. The ESS local control method does not require a communication system, providing a convenient and readily available solution for the control of integrated PV and ESS. Description of the Drawings

[0031] In the drawings:

[0032] Figure 1 is the overall control schematic diagram of the energy storage method based on droop control proposed by the present invention;

[0033] Figure 2 is the overall method flow chart of the energy storage method based on droop control proposed by the present invention;

[0034] Figure 3 is the energy storage system control flow chart of the energy storage method based on droop control proposed by the present invention;

[0035] Figure 4 The curve graph of the relationship between the AC bus voltage and time under two control modes of the energy storage method based on droop control proposed by the present invention;

[0036] Figure 5 The curve graph of the relationship between the voltage and time of the existing droop control and the droop control of the present invention of the energy storage method based on droop control proposed by the present invention. Detailed implementation manners

[0037] The following description and the accompanying drawings fully illustrate the specific implementation manners herein. Refer to Figures 1-3 , an energy storage method based on droop control, including:

[0038] Step S1, statistically analyze all the photovoltaic power generation P ev总 and the power P consumed by the load load总 before the current date to obtain sample data;

[0039] Step S2, predict the photovoltaic power generation and the power consumed by the load for the next day based on the sample data to obtain the photovoltaic power generation P ev and the power P consumed by the load load ;

[0040] Step S3, calculate the parameters a and b of the exponential droop control through the obtained photovoltaic power generation P ev and the power P consumed by the load load ;

[0041] Step S4, input the obtained parameters a and b into the ESS controller (Energy Storage Systems controller, energy storage system controller), and the ESS controller makes a judgment to obtain the charging time t1 and the discharging time t2 of the energy storage system;

[0042] Step S, control the energy storage system according to the charging time t1 and the discharging time t2, and then fit the charge and discharge curves of the energy storage device to maximize the self - use of power without flowing to the AC bus, thereby alleviating the power mismatch.

[0043] In an optional implementation manner, the prediction of the photovoltaic power generation and the power consumed by the load for the next day is determined according to the photovoltaic power generation and the power consumed by the load data recorded in the same period of previous years in the sample data.

[0044] In an optional implementation manner, the formula for determining the exponential droop control of the energy storage system is:

[0045]

[0046] Among them, the parameters a and b are variable constants, and the charge and discharge curves of the energy storage system are adjusted by adjusting the parameters a and b.

[0047] In this embodiment, the control process of the energy storage system selects a charging mode or a discharging mode according to the value of P d :

[0048]

[0049] wherein, it is calculated from the power generation power of the photovoltaic and the power consumption power of the load through the above formula..

[0050] In an alternative embodiment, the control of the energy storage system in S5 is restricted by the maximum SoC (System on Chip) and the minimum SoC of the battery. If the SoC value reaches one of the limits due to previous control actions, the ESS controller remains idle, that is, in a state of neither charging nor discharging. Otherwise, the control process continues to run to determine the value of P b (t), wherein the charging power is expressed as The discharging power is expressed as

[0051] Reference Figure 3 As shown, in this embodiment, the remaining part of the control process is also applicable to both the charging mode and the discharging mode to calculate the value of P exp (t).

[0052] If this value is lower than the maximum allowable ESS power P b max and P d (t), then the ESS charges or discharges at P exp (t). Otherwise, the ESS power is limited to the minimum value between P b max and P d (t). As long as the power of the ESS is defined, the control process terminates.

[0053] In this embodiment, the control of the obtained energy storage system is combined with the photovoltaic power generation power P ev and the load consumption power P load to divide the control curve of the energy storage system power into three different intervals, and control them separately on each partition. Among them, the exponential droop control proposed by the present invention is one of the intervals. When the charging or discharging power of the energy storage system is greater than the minimum SoC of the battery manufacturer and less than the power generation power of the photovoltaic minus the load consumption power, that is, P d, the control method of the energy storage system at this time is exponential droop control. The purpose of exponential droop control is to better ensure that when the photovoltaic power generation reaches the maximum power, the energy storage device is not fully charged. At this time, the excess energy after the load consumption of the photovoltaic power generation is stored in the energy storage device, and the energy storage device can release sufficient electric energy for the load to use when the load is large at night. The ultimate goal of such control is to minimize the power mismatch between the common power grid side and the bus shared by the energy storage device and the load on the AC bus, and reduce the impact on the power grid.

[0054] The main principle of the droop control proposed by the present invention is that as P d (t) increases, the ESS power increases exponentially. Specifically, during periods of low photovoltaic power surplus, the ESS charges at a lower rate, thus maintaining the availability of the ESS capacity to absorb higher photovoltaic excess power during increased solar irradiation times. Similarly, when the load demand is limited, the ESS discharge power is set at a lower rate, thus maintaining sufficient energy to cover peak load power, such as in the evening. In this way, the proposed control device reduces the high power mismatch between generation and demand and smooths the power distribution between the AC bus and the power grid. Following this strategy, the stress imposed by prosumers on the network is reduced, thus improving the voltage profile of the feeder.

[0055] Considering the charging and discharging limitations of the ESS, such as the rated charging and discharging power, the power of the energy storage system can be described as a distribution function:

[0056]

[0057] In the formula, P b (t) is the power absorbed or generated by the ESS at each moment t in the time period T on the AC side of the device, is the maximum charging or discharging power of the ESS, and the control method is divided into three regions.

[0058] 1) When P exp (t) ≤ |P d (t)| and At this time, the relationship between P d (t) and P b (t) in the control strategy is an exponential relationship.

[0059] 2) When P exp (t) > |P d (t)| and At this time, the curve of P b (t) in the control strategy is a linear straight line.

[0060] 3) When and |P d (t)| > P bmax , where the P of the control strategy at this time b (t) curve is a horizontal line of P b max .

[0061] The development function of the ESS operation strategy can be used to control the charging and discharging processes. In the former, it injects lower power into the grid during several hours when the PV production increases, while in the latter, it can prevent the load demand from reaching the peak.

[0062] In this embodiment, during actual operation, first, the control coefficients a and b are calculated on a 24-hour basis through an optimization process, based on the predicted PV power generation and load demand of the previous day. Once these coefficients are determined, they are forwarded to the ESS controller and used in the real-time ESS control of the next day.

[0063] The proposed ESS control strategy alleviates the peak of the AC bus power distribution by reducing the high-power mismatch between consumption and PV production, while ensuring an increase in self-consumption. However, to maximize self-consumption, the control coefficients a and b should be fine-tuned according to the individual characteristics of each prosumer, namely the PV system and load power curves, as well as the ESS capacity and operation limits. Therefore, an optimization problem can be formulated to fine-tune the a and b coefficients in the best way every day. The control coefficients of the charging and discharging operations are updated every 24 hours, based on the advance prediction of PV power generation and consumption.

[0064] Maximizing self-consumption can be achieved by minimizing the energy exchange between the prosumer and the public power grid within a 24-hour interval. This can be mathematically expressed by minimizing the active power (P grid (t)) of the AC bus at all moments during the inspection period.

[0065] The optimization problem is shown in (4)-(19). The objective function of minimizing the sum of the power exchanged with the grid at the AC bus at each moment, P grid (t), is described by (). The absolute value is used because P grid (t) may obtain positive and negative values when injecting power into the grid or absorbing power from the grid, respectively.

[0066]

[0067] P grid (t) = P d (t) - P b ch (t)s(t) + P b dch (t)(1 - s(t)) (5)

[0068] In the above formula, P grid (t) represents the power balance on the AC grid side, and P d (t) is the difference between the photovoltaic power generation and the load consumption power. represents the charging power of the energy storage system, represents the discharging power of the energy storage system.

[0069]

[0070] The s(t) in the above formula is an auxiliary binary parameter used to represent different battery operating modes.

[0071]

[0072]

[0073]

[0074] In formulas (7) and (8), P exp (t) represents the exponential part of the control function. The equality constraints form the mathematical expression of the proposed ESS control method. Binary variables k1(t), k2(t), k3(t) are introduced as constraint variables in the formula, which ensures that only one item in formula (3) is enabled each time.

[0075]

[0076] Formula (10) is used to calculate the value of the next time step of SoC, where a ch , b ch are the coefficients for the charging mode, and a dch , b dch are the coefficients for the discharging mode.

[0077]

[0078] k1(t)P exp (t) ≤ k1(t)|P d (t)| (Equation 12)

[0079] k1(t)P exp (t) ≤ k1(t)P b max (t) (Equation 13)

[0080] k2(t)|P d (t)| < k2(t)P exp (t) + m (Equation 14)

[0081] k2(t)|P d (t)| ≤ k2(t)P bmax (t) (15)

[0082]

[0083]

[0084] Equations (12)-(17) constrain the boundary conditions of the control function. η ch and η dch are the charging and discharging efficiencies of the ESS, respectively. A small positive quantity m is added to Equation (14) to ensure the validity of the equation when k2(t) = 0. The functions of Equations (16) and (17) are the same.

[0085] SoC max ≥SoC(t + 1) (18)

[0086] SoC min ≥SoC(t + 1) (19)

[0087] Equations (18) and (19) limit the SoC of the ESS, where SoC max , SoC min represent the maximum and minimum SoC of the ESS.

[0088] In the above embodiments, referring to Figure 5 , as shown in the experimental graphs obtained by comparing the traditional droop control with the improved droop control, where the vertical axis represents the AC bus voltage and the horizontal axis is the time of a day. According to the experimental graphs, it can be seen that the AC bus voltage of the improved droop control is significantly lower than that of the traditional droop control for most of the time. Therefore, it can effectively reduce the bus voltage and form self-consumption to a greater extent.

[0089] In this embodiment, the ESS controller is programmed with an energy storage system.

[0090] An energy storage device based on droop control, comprising:

[0091] A statistical module for statistically analyzing all the photovoltaic power generation and the power consumed by the load before the current date;

[0092] A prediction module for predicting the photovoltaic power generation and the power consumed by the load in the next day according to the statistical module and calculating the parameters of the exponential droop control;

[0093] A judgment module for inputting the calculated parameters of the exponential droop control into the ESS controller for judgment to obtain the charging and discharging times;

[0094] A main control module for controlling the energy storage system based on the charging and discharging times.

[0095] A computer-readable storage medium, characterized in that it is used to store a computer program, wherein when the computer program is executed by a processor, it implements the steps of an energy storage method based on droop control.

[0096] A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that the processor executes the steps of an energy storage method based on droop control.

[0097] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structural diagram may be as Figure 1 shown. The computer device includes a processor, a memory, and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store static information and dynamic information data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements the steps in the above method embodiments.

[0098] Those skilled in the art can understand that Figure 1 the structure shown in

[0099] is only a block diagram of some structures related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout.

[0100] In this embodiment, the most perfect ESS local operation strategy is the self-consumption maximization control scheme. The scope of this scheme is to minimize the energy exchange between the prosumer and the public power grid by eliminating the power exchange of the AC bus at each moment t. It has a power P at moment tb (t) Charges or discharges the ESS, and the difference between the photovoltaic power generation and the load consumption power is P d (t). To avoid early charging or discharging of the storage system, a new ESS control method introduced by the present invention defines the ESS power as a function of P d (t). Its purpose is to create a droop control to improve the voltage distribution of the network. For this purpose, a mathematical function is needed to determine the low ESS power when low residual power is observed on the AC bus, and when the remaining power becomes high, it greatly increases the ESS power. Among several studied mathematical functions, the exponential droop is selected due to its superior results.

[0101] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memories.

[0102] A new control strategy relying on local measurements is introduced in the present invention to effectively manage the ESS controller. The goal of the proposed control is twofold; it aims to improve the voltage distribution of the distribution feeder by reducing the peaks in the net power distribution at the prosumer's AC bus, while maximizing the prosumer's self-consumption. To reduce the peaks in the net power curve, a new exponential droop control is invented.

[0103] Reference Figures 4-5 , in this embodiment, specifically, the proposed control charges the ESS controller at a higher rate during high photovoltaic power generation and discharges the ESS controller at a higher rate when peak load demand occurs. To maximize the producer's self-consumption, an optimization method is proposed to fine-tune the droop control parameters. The efficiency of the developed strategy is evaluated on two low-voltage distribution networks with increasing photovoltaic penetration and compared with two other mature local ESS controller control schemes. Based on the simulation results, it can be concluded that the proposed exponential droop control scheme optimizes the utilization of the ESS controller by reducing the bus voltage while maximizing the prosumer's self-consumption. Therefore, it is superior to traditional methods and constitutes a reliable alternative solution for managing distributed ESS controllers. In addition, the experimental results prove the applicability of the proposed control strategy. It is obtained through experiments that the proposed control can be easily applied using a traditional ESS controller.

[0104] The distributed energy storage system of the present invention can effectively alleviate overvoltage and congestion in the distribution network. The ESS can locally store excess PV energy, alleviating reverse power flow in this way, thereby alleviating overvoltage and possible congestion along the feeder. The ESS local control method does not require a communication system, providing a convenient and readily available solution for the control of integrated PV and ESS.

Claims

1. A energy storage method based on droop control, characterized in that, Including: Step S1. Statistically analyze all photovoltaic power generations P before the current date ev总 and the power P consumed by the load load总 to obtain sample data; Step S2: Predict the photovoltaic power generation and load consumption power for the next day based on the sample data, and obtain the photovoltaic power generation P ev and the load consumption power P load ; Step S3: Calculate the parameters a and b of the exponential droop control based on the obtained photovoltaic power generation P ev and the load consumption power P load ​ Step S4: Input the obtained parameters a and b into the ESS controller, and the ESS controller judges to obtain the charging time t1 and discharging time t2 of the energy storage system; Step S5: Control the energy storage system according to the charging time t1 and discharging time t2; Determine the exponential droop control of the energy storage system, and its formula is: Wherein, the parameters a and b are variable constants, and the charging and discharging curves of the energy storage system are adjusted by adjusting the parameters a and b; The control process of the energy storage system selects a charging mode or a discharging mode according to the value of P d : Wherein, it is calculated from the photovoltaic power generation power and load consumption power through the above formula; The control of the energy storage system in S5 is through the maximum and minimum SoC limits of the battery. If the SoC value reaches one of the limits due to previous control actions, the ESS controller remains idle, i.e., in a state of neither charging nor discharging. Otherwise, the control process continues to run to determine the value of P b (t), where the charging power is expressed as The discharging power is expressed as 2. The energy storage method based on droop control according to claim 1, wherein, The predicted photovoltaic power generation power and load consumption power for the next day are determined according to the photovoltaic power generation power and load consumption power data recorded in the same period of previous years in the sample data.

3. The energy storage method based on droop control according to claim 1, wherein Combine the control of the obtained energy storage system with the photovoltaic power generation P ev and the load consumption power P load Combine them. Divide the control curve of the energy storage system power into three different intervals and conduct control separately on each interval.

4. The energy storage method based on droop control according to claim 1, wherein A preset energy storage system is programmed in the ESS controller.

5. A energy storage device based on droop control, characterized in that, Including: A statistics module for statistically analyzing all photovoltaic power generation powers and load consumption powers before the current date; A prediction module for predicting the photovoltaic power generation power and load consumption power for the next day according to the statistics module, and calculating the parameters of the exponential droop control by applying the energy storage method based on droop control according to any one of claims 1-4; A judgment module for inputting the calculated parameters of the exponential droop control into the ESS controller for judgment by applying the energy storage method based on droop control according to any one of claims 1-4 to obtain the charging and discharging times; A main control module for controlling the energy storage system through the charging and discharging times.

6. A computer-readable storage medium, characterized in that, For storing a computer program, wherein when the computer program is executed by a processor, the steps of the energy storage method based on droop control according to any one of claims 1-4 are implemented.

7. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the energy storage method based on droop control according to any one of claims 1-4 are implemented.

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