A method for 5G base station battery energy storage to participate in power system auxiliary frequency regulation control

Abstract

This invention relates to a method for 5G base station battery energy storage to participate in power system auxiliary frequency regulation control. The method includes: establishing a power system aggregation model incorporating battery energy storage; obtaining frequency deviation by setting disturbance parameters; dividing the frequency deviation range into an unregulated zone, a normal regulated zone, and an emergency regulated zone based on the needs of 5G base station battery energy storage participation in frequency response; establishing a low-pass filter model to divide the system frequency deviation signal into low-frequency and high-frequency parts, used for the frequency regulation signal of thermal power units and the frequency regulation signal of 5G base station battery energy storage, respectively; obtaining the real-time frequency deviation signal and the state of charge (SOC) of the energy storage battery; and adjusting the battery energy storage charging and discharging power in real time, using the energy storage battery SOC as the independent variable, according to the discharge rules of different regions, thereby optimizing the efficiency of battery energy storage participation in frequency response. This invention improves the effect of 5G base station battery energy storage participating in load frequency response, enhances system frequency stability, reduces energy storage battery lifespan loss, and improves the utilization efficiency of energy storage batteries.

Description

Technical Field

[0001] This invention relates to the field of power system frequency control, and more specifically to a method for 5G base station battery energy storage to participate in power system auxiliary frequency regulation control. Background Technology

[0002] In a free-market electricity sector, the vertically integrated market structure comprises three market players: power generation groups, transmission companies, and distribution companies. These three players participate autonomously in electricity trading, impacting the Localized Power Flow (LFC) of regional interconnected grids, which directly manifests in the frequency deviation of the power system. Frequency, as one of the three key indicators of power quality, reflects the relationship between electricity consumption and supply, serving as a crucial indicator of grid supply-demand balance. When the amount of electricity transmitted to the grid exceeds the amount consumed by the load, the system frequency increases; conversely, it decreases. Since the power system frequency is closely related to users' lives, continuous frequency fluctuations negatively impact users, power plants, and the power system itself. Therefore, effectively simulating the impact of emerging market players on the power system and maintaining a constant grid frequency within a certain range is crucial.

[0003] Furthermore, the power grid is constantly developing towards higher energy levels and greater intelligence, and the power system structure is becoming increasingly complex. In order to ensure the safe and economical operation of the power grid and improve the quality of the power supplied by the grid, the requirements for frequency regulation units are becoming increasingly stringent. Currently, the units used to maintain frequency stability are still traditional large-scale hydropower and thermal power units, which respond to system frequency changes by continuously adjusting the frequency regulation output. However, due to the insufficient frequency regulation characteristics of traditional units, the existing frequency regulation methods cannot meet the system's rapid response requirements when facing sudden shocks and disturbances. Therefore, new frequency regulation methods are urgently needed to maintain the stability of the power grid frequency.

[0004] Compared to traditional thermal power units, battery energy storage systems offer advantages such as rapid response and precise tracking. Advanced energy storage technologies can improve the utilization rate of renewable energy, effectively mitigating the curtailment of solar and wind power. Simultaneously, the stability and controllability of new energy grid-connected systems will be further improved. Battery energy storage technology is considered by domestic and international experts to be a key technological link in achieving large-scale grid connection of renewable energy sources such as photovoltaics and wind power. However, current research on energy storage batteries and related technologies still has some shortcomings, especially regarding frequency response, which poses greater challenges to the capacity and power control of energy storage batteries. Furthermore, the output of energy storage batteries is affected by factors such as State of Charge (SOC). Therefore, energy storage batteries cannot completely replace conventional frequency regulation power supplies. Existing research uses energy storage batteries as an auxiliary means to participate in load frequency regulation response, aiming to improve the frequency regulation effect of the power system.

[0005] Current research on energy storage participation in frequency regulation, both domestically and internationally, mainly focuses on the primary frequency regulation stage. This involves providing inertia support to the system through methods such as droop control and virtual inertia control to mitigate the impact of numerous low-inertia generators on the power system. However, there is a relative lack of in-depth discussion on control strategies for secondary frequency regulation. Therefore, this paper focuses on how to incorporate the limitations of energy storage participation in frequency regulation, such as the influence of state of charge (SOC) on output, into frequency response control methods. Summary of the Invention

[0006] The purpose of this invention is to provide a method for 5G base station battery energy storage to participate in power system auxiliary frequency regulation control. Based on the power market contract trading mechanism, a power system aggregation model incorporating battery energy storage is established. Disturbance parameters are set, and the system frequency deviation f is obtained. By combining the frequency deviation signal with the state of charge (SOC) of the energy storage battery, a frequency response control method considering both the energy storage frequency regulation characteristics and the SOC is proposed. Furthermore, the output of the energy storage battery is adjusted according to the discharge rules of different discharge regions to achieve the goal of balancing the lifespan loss of the energy storage battery and rapidly responding to system frequency deviation.

[0007] To achieve the above objectives, the technical solution of the present invention is: a method for 5G base station battery energy storage to participate in power system auxiliary frequency regulation control, comprising the following steps:

[0008] Step 1: Based on the mathematical model of 5G base station battery energy storage and its operating characteristics, establish a corresponding model for 5G base station battery energy storage aggregation to participate in power system auxiliary frequency regulation.

[0009] Step 2: Establish a 5G base station battery energy storage participation in power system load frequency response model based on the electricity market contract trading mechanism. By setting disturbance parameters, obtain the frequency deviation f, and then apply different set values ​​of f. n f w Each zone is designated as a non-frequency tuning zone, a normal frequency tuning zone, and a frequency tuning emergency zone.

[0010] Step 3: Construct a low-pass filter model and obtain the high-frequency and low-frequency components of the frequency deviation f, where the high-frequency component is denoted as f. high The low-frequency part is calculated as f low Low frequency part f low Used for frequency regulation signals in thermal power units, high-frequency component f high Frequency regulation signal used for 5G base station battery energy storage;

[0011] Step 4: Establish a real-time SOC partitioning model for 5G base station battery energy storage, and in conjunction with frequency partitioning, establish an energy storage output constraint model with 5G base station battery energy storage SOC as the variable.

[0012] Step 5: Based on the frequency regulation characteristics of 5G base station battery energy storage, and combined with the high-frequency part of the frequency deviation f, design a coordinated frequency regulation scheme that considers the 5G base station battery energy storage SOC and the frequency deviation f, and combine the energy storage output constraint model to control the charging, discharging and standby behavior of the energy storage battery.

[0013] In one embodiment of the present invention, step one is specifically implemented as follows:

[0014] The mathematical model for power injection into battery storage in a single 5G base station is as follows:

[0015]

[0016] In the formula: P bess The discharge power of 5G base station battery energy storage; r bess The participation factor for battery energy storage in 5G base stations; Rated discharge power for 5G base station battery energy storage;

[0017] The State of Charge (SOC) of a single 5G base station's battery energy storage varies as follows:

[0018]

[0019] In the formula: h is the step size selected during calculation; soc(k) is the SOC of the battery energy storage at time k; soc(k+1) is the SOC of the battery energy storage at time k+1; C bess Indicates the rated capacity of the battery energy storage for 5G base stations; η bess This represents the charge / discharge participation factor of the 5G base station battery energy storage.

[0020] For idle 5G base station battery energy storage resources, it is necessary to participate in the auxiliary frequency regulation of the power system through aggregation and control. The transfer function and SOC change function of the 5G base station battery energy storage aggregation participation in the auxiliary frequency regulation of the power system are expressed as follows:

[0021]

[0022]

[0023] In the formula, T e The time constant of the energy storage battery for 5G base stations; SOC e0 ΔP represents the initial state of charge (SOC) of the 5G base station's energy storage battery. e S represents the output value of the energy storage battery for a 5G base station at time t. e s represents the rated capacity of the energy storage battery for 5G base stations, and s represents the complex frequency.

[0024] In one embodiment of the present invention, in step two, the frequency deviation f is obtained by the ACE control method, as follows:

[0025] Under ACE control mode, the ACE control signal obtains the real-time frequency of the power grid through the power grid dispatch center. Based on the 5G base station battery energy storage aggregation participation power system auxiliary frequency regulation model and the power grid frequency regulation model based on regional control deviation, the 5G base station energy storage battery transfer function G is obtained. e (s) and thermal power unit transfer function G s (s) are as follows:

[0026]

[0027]

[0028] In the formula, T e T represents the time constant of the energy storage battery for 5G base stations. rh F is the reheater time constant. hp For reheater gain, T n T is the governor constant of a conventional unit. ch Let s be the turbine time constant, and s be the complex frequency;

[0029] In the context of the electricity market, a distribution participation matrix is ​​established, specifically as follows:

[0030]

[0031] In the formula: A dmp For the distribution participation matrix, ε cpf,ij For contract participation factors; in this matrix, i and j represent the row and column of the matrix, respectively, for example, ε cpf,12 This represents the participation factor in the first row and second column. In practice, it is expressed as the normalized scalar value of the electrical energy purchased by distribution company j in the contract between power generation company i and power distribution company j.

[0032] The switching power on the interconnection line of the two-area interconnection system is expressed as follows:

[0033]

[0034] In the formula, ΔP t,s The power deviation on the tie line; ΔP b2-1 Electricity purchased by Region 2 from Region 1; ΔP b1-2 Electricity purchased by Region 1 from Region 2;

[0035] Calculate the output ΔP1(s) of the thermal power unit under primary frequency regulation, the output ΔP2(s) of the thermal power unit under secondary frequency regulation, and the output ΔP of the energy storage battery of the 5G base station under ACE control mode. e (s):

[0036] ΔP1(s)=-K s ·G n (s)·Δf(s)

[0037] ΔP2(s)=λ(1-η)·(K P +K i / s)·G n (s)·Δf(s)

[0038] ΔP e (s)=λ·η·G e (s)·Δf(s)

[0039] In the formula, Gn(s) is the transfer function of the thermal power unit, K s λ is the unit regulating power of the thermal power unit; λ is the frequency deviation coefficient of the system PI controller; K p K is the proportional gain of the PI controller. i Here, η is the integral coefficient of the PI controller; η is the weighting coefficient of the 5G base station energy storage battery participating in frequency regulation; (1-η) is the weighting factor of the thermal power unit participating in frequency regulation; Δf(s) is the frequency domain signal of the frequency deviation; the transfer function Δf(s) of the system frequency deviation frequency domain signal is calculated as follows:

[0040]

[0041] According to different setting values ​​f n f w The following are defined: a non-frequency modulation zone, a normal frequency modulation zone, and a frequency modulation emergency zone.

[0042] Unmodulated region: 0≤f t ≤f n ;

[0043] Normal frequency modulation range: f n ≤f t ≤f w ;

[0044] FM emergency zone: f w ≤f t ;

[0045] In the formula, f t For real-time frequency; f n The minimum value to cross the unmodulated region; f w This represents the minimum frequency for emergency response.

[0046] In one embodiment of the present invention, step three involves constructing a low-pass filter model, specifically implemented as follows:

[0047] Based on the frequency regulation characteristics of thermal power plants and 5G base station energy storage batteries, a first-order low-pass filter model is constructed to decompose the frequency deviation obtained in step two into a high-frequency component f. high Low-frequency part f lowThe details are as follows:

[0048]

[0049] In the formula, T m The time constant of the first-order low-pass filter;

[0050] f, obtained by passing the frequency deviation through a low-pass filter high f low They are as follows:

[0051] f low =G m (s)·Δf(s)

[0052] f high =1-G m (s)·Δf(s)

[0053] In the formula, G m (s) is the transfer function model of a first-order low-pass filter, f high For the high-frequency component of the frequency deviation, f low Δf(s) represents the low-frequency component of the frequency deviation; Δf(s) represents the frequency domain signal of the frequency deviation.

[0054] In one embodiment of the present invention, in step four, when the system frequency is in the unmodulated region, the established energy storage output constraint model with the 5G base station battery energy storage SOC as the variable is as follows:

[0055]

[0056]

[0057] In the formula: P dmax The adaptive maximum discharge power is based on real-time SOC correction; P cmax For adaptive maximum charging power based on real-time SOC correction; SOC t Real-time SOC value for 5G base station energy storage batteries; SOC min Minimum frequency modulation dead zone threshold for 5G base station energy storage batteries; SOC low For 5G base station energy storage batteries participating in frequency modulation, the low-level SOC value; SOC high For 5G base station energy storage batteries to participate in frequency modulation, the SOC (State of Charge) is at a high level; max This represents the maximum value of the frequency modulation dead zone threshold for 5G base station energy storage batteries.

[0058] In one embodiment of the present invention, in step four, when the system frequency is in the normal frequency modulation zone, the energy storage output constraint model with the 5G base station battery energy storage SOC as the variable is as follows:

[0059]

[0060]

[0061] In the formula: P dmax The adaptive maximum discharge power is based on real-time SOC correction; P cmax For adaptive maximum charging power based on real-time SOC correction; p r Rated charge and discharge power for 5G base station battery energy storage; p c For reference only; n c Adaptive coefficients for charging and discharging 5G base station battery energy storage; SOC t Real-time SOC value for 5G base station energy storage batteries; SOC min Minimum frequency modulation dead zone threshold for 5G base station energy storage batteries; SOC low For 5G base station energy storage batteries participating in frequency modulation, the low-level SOC value; SOC high For 5G base station energy storage batteries to participate in frequency modulation, the SOC (State of Charge) is at a high level; max This represents the maximum value of the frequency modulation dead zone threshold for 5G base station energy storage batteries.

[0062] In one embodiment of the present invention, in step four, when the system frequency is in the frequency regulation emergency zone, the power grid is subjected to significant disturbances. The primary goal is to quickly reduce the system frequency deviation and restore the system frequency to the normal frequency regulation zone. To this end, energy storage still needs to leverage its fast response speed to provide rapid support to the system. Furthermore, energy storage SOC recovery is no longer performed in the frequency regulation emergency zone; it is only necessary to ensure that the SOC is within the normal operating range. Therefore, the energy storage output constraint model with the 5G base station battery energy storage SOC as the variable is as follows:

[0063]

[0064] In the formula: P c Power for charging 5G base station battery energy storage; P d Power for charging 5G base station battery energy storage; Maximum charging power for 5G base station battery energy storage; Maximum charging power for 5G base station battery energy storage; SOC t Real-time SOC value for 5G base station battery energy storage; SOC min Minimum dead zone threshold for frequency modulation of 5G base station battery energy storage; SOC max This represents the maximum value of the frequency modulation dead zone threshold for 5G base station battery energy storage.

[0065] In one embodiment of the present invention, the coordinated frequency modulation scheme considering the 5G base station battery energy storage SOC and frequency deviation f in step five is as follows:

[0066] 1) Determine |f t |<fn When |f t |<f n At the time of its establishment, the energy storage system was in a penalty standby state.

[0067] 2) Determine |f t |<f n When |f t |<f n If not true, continue to evaluate |f t |>f w ,|f t |>f w If it is established, continue to determine f. t >f w f t >f w Upon establishment, continue to determine the SOC. t ≤SOC max When SOC t ≤SOC max When established, the energy storage is in a penalty standby state; when SOC... t ≤SOC max If this condition is not met, the energy storage is in a charging state;

[0068] 3) Determine |f t |<f n When |f t |<f n If not true, continue to evaluate |f t |>f w ,|f t |>f w If it is established, continue to determine f. t >f w f t >f w If not, continue to determine SOC. t ≤SOC min When SOC t ≤SOC min When established, the energy storage is in a penalty standby state; when SOC... t ≤SOC min If this condition is not met, the energy storage will be in a discharging state.

[0069] 4) Determine |f t |<f n When |f t |<f n If not true, continue to evaluate |f t |>f w ,|f t |>f w If not, continue to determine SOC. low<SOC t <SOC high SOC low <SOC t <SOC high At the time of its establishment, the energy storage system was in a penalty standby state.

[0070] 5) Determine |f t |<f n When |f t |<f n If not true; continue judging |f t |>f w ,|f t |>f w If not, continue to determine SOC. low <SOC t <SOC high SOC low <SOC t <SOC high If not, continue to determine SOC. high <SOC t <SOC max SOC high <SOC t <SOC max If this condition is not met, the energy storage is in a charging state; otherwise, the energy storage is in a discharging state.

[0071] In the formula, f t f is the real-time value of the frequency deviation; n The minimum value to cross the unmodulated region; f w This represents the minimum frequency for emergency response; SOC t Real-time SOC value for 5G base station battery energy storage; SOC min Minimum dead zone threshold for frequency modulation of 5G base station battery energy storage; SOC low For 5G base station battery energy storage to participate in frequency modulation, the low SOC value; SOC high High SOC value for 5G base station battery energy storage to participate in frequency modulation; SOC max This represents the maximum value of the frequency modulation dead zone threshold for 5G base station battery energy storage.

[0072] The present invention also provides a 5G base station battery energy storage participation power system auxiliary frequency regulation control system, including a memory, a processor, and computer program instructions stored in the memory and executable by the processor. When the processor executes the computer program instructions, it can implement the steps described above.

[0073] The present invention also provides a computer-readable storage medium having stored thereon computer program instructions that can be executed by a processor, wherein when the processor executes the computer program instructions, it can implement the steps of the method described above.

[0074] Compared with the prior art, the present invention has the following beneficial effects:

[0075] 1) After adopting the above scheme, the obtained frequency deviation signal is divided into high-frequency part and low-frequency part by a first-order low-pass filter, so that the frequency deviation signal can better adapt to the frequency regulation characteristics of traditional thermal power units and energy storage battery packs. This allows the thermal power units and energy storage batteries to give full play to their respective frequency regulation advantages after receiving disturbances, and the frequency deviation can be quickly restored to the rated value.

[0076] 2) This invention combines frequency deviation value with 5G base station battery energy storage SOC, and divides the frequency deviation into three regions according to a given partitioning method: frequency modulation dead zone, normal frequency modulation zone, and emergency frequency modulation zone. By properly planning the relationship between the two, the operating state of the energy storage battery can be more in line with the actual needs within the allowable range of system deviation. At the same time, the control method of this invention greatly reduces the life loss of the energy storage battery.

[0077] 3) By combining the charge and discharge constraint function and taking SOC as the independent variable, the power output under various modes is controlled in a time-varying manner, which optimizes the depth of discharge of the energy storage battery and reduces the life loss of the energy storage battery. Attached Figure Description

[0078] Figure 1 This is a flowchart illustrating the structure of the present invention.

[0079] Figure 2 This is a regional system structure diagram within the context of the electricity market. Detailed Implementation

[0080] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0081] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0082] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0083] like Figure 1 As shown in the figure, this embodiment provides a method for 5G base station battery energy storage to participate in power system auxiliary frequency regulation control, including the following steps:

[0084] Step 1: Based on the mathematical model of 5G base station battery energy storage and its operating characteristics, establish a corresponding model for 5G base station battery energy storage aggregation to participate in power system auxiliary frequency regulation.

[0085] Step 2: Establish a 5G base station battery energy storage participation in power system load frequency response model based on the electricity market contract trading mechanism. By setting disturbance parameters, obtain the frequency deviation f, and then apply different set values ​​of f. n f w Each zone is designated as a non-frequency tuning zone, a normal frequency tuning zone, and a frequency tuning emergency zone.

[0086] Step 3: Construct a low-pass filter model and obtain the high-frequency and low-frequency components of the frequency deviation f, where the high-frequency component is denoted as f. high The low-frequency part is calculated as f low Low frequency part f low Used for frequency regulation signals in thermal power units, high-frequency component f high Frequency regulation signal used for 5G base station battery energy storage;

[0087] Step 4: Establish a real-time SOC partitioning model for 5G base station battery energy storage, and in conjunction with frequency partitioning, establish an energy storage output constraint model with 5G base station battery energy storage SOC as the variable.

[0088] Step 5: Based on the frequency regulation characteristics of 5G base station battery energy storage, and combined with the high-frequency part of the frequency deviation f, design a coordinated frequency regulation scheme that considers the 5G base station battery energy storage SOC and the frequency deviation f, and combine the energy storage output constraint model to control the charging, discharging and standby behavior of the energy storage battery.

[0089] The following is a detailed implementation process of the present invention.

[0090] like Figure 1As shown, the present invention provides a method for 5G base station battery energy storage to participate in power system auxiliary frequency regulation control, which can be mainly divided into three modules: Module 1 is the frequency deviation signal partitioning and allocation part after disturbance; Module 2 is the frequency deviation signal and energy storage battery SOC coordinated frequency regulation control method part; Module 3 is the 5G base station battery energy storage adaptive adjustment charging and discharging output constraint part.

[0091] Module one, namely the frequency deviation signal partitioning and allocation section, is implemented as follows:

[0092] A convergent frequency modulation model considering contract transaction mechanisms is constructed. Under the applied disturbance, the frequency deviation f value is obtained under ACE control as follows:

[0093] Under ACE control mode, the ACE control signal obtains the real-time frequency of the power grid through the power grid dispatch center. Based on the power grid frequency regulation model of 5G base station battery energy storage operation characteristics and regional control deviation, the battery energy storage transfer function G is obtained. e (s) and the transfer function G of conventional thermal power units s (s):

[0094]

[0095]

[0096] In the formula, T e The time constant of the energy storage battery; SOC e0 ΔP represents the initial state of charge (SOC) of the 5G base station's energy storage battery. e S represents the output value of the energy storage battery for a 5G base station at time t. e Rated capacity of energy storage batteries for 5G base stations; T rh F is the reheater time constant; hp For reheater gain; T n The time constant of the governor in a conventional unit; T ch s is the turbine time constant; s is the complex frequency;

[0097] Based on the electricity market context, the specific structural diagram of the participating system frequency response is attached. Figure 2 As shown, a distribution participation matrix is ​​established, specifically as follows:

[0098]

[0099] In the formula: A dmp For the distribution participation matrix, ε cpf,ij For contract participation factors; in this matrix, i and j represent the row and column of the matrix, respectively, for example, ε cpf,12This represents the participation factor in the first row and second column. In practice, it is expressed as the normalized scalar value of the electrical energy purchased by distribution company j in the contract between power generation company i and power distribution company j.

[0100] The switching power on the interconnection line of the two-area interconnection system can be expressed as follows:

[0101]

[0102] In the formula, ΔP t,s The power deviation on the tie line; ΔP b2-1 Electricity purchased by Region 2 from Region 1; ΔP b1-2 Electricity purchased by Region 1 from Region 2;

[0103] Calculate the output ΔP1(s) of a conventional thermal power unit under primary frequency regulation, the output ΔP2(s) of a conventional thermal power unit under secondary frequency regulation, and the output ΔP of the battery energy storage system under ACE control. e (s):

[0104] ΔP1(s)=-K s ·G n (s)·Δf(s)

[0105] ΔP2(s)=λ(1-η)·(K P +K i / s)·G n (s)·Δf(s)

[0106] ΔP e (s)=λ·η·G e (s)·Δf(s)

[0107] In the formula, Gn(s) is the transfer function of the thermal power unit, K s λ is the unit regulating power of the thermal power unit; λ is the frequency deviation coefficient of the system PI controller; K p K is the proportional gain of the PI controller. i Here, η is the integral coefficient of the PI controller; η is the weighting coefficient of the 5G base station energy storage battery participating in frequency regulation; (1-η) is the weighting factor of the thermal power unit participating in frequency regulation; Δf(s) is the frequency domain signal of the frequency deviation; the transfer function Δf(s) of the system frequency deviation frequency domain signal is calculated as follows:

[0108]

[0109] In the formula, M is the power grid inertia time constant; D is the load damping coefficient; further derivation based on the above formula yields the relationship between system frequency offset and load disturbance as follows:

[0110]

[0111] In the formula, ΔP l (s) is a complex function of the load disturbance; λ, K p K i The parameters , η, (1-η) are illustrated above.

[0112] According to different setting values ​​f n f w The following are defined: a non-frequency modulation zone, a normal frequency modulation zone, and a frequency modulation emergency zone.

[0113] Unmodulated region: 0≤f t ≤f n ;

[0114] Normal frequency modulation range: f n ≤f t ≤f w ;

[0115] FM emergency zone: f w ≤f t ;

[0116] In the formula, f t For real-time frequency; f n The minimum value to cross the unmodulated region; f w This represents the minimum frequency for emergency response.

[0117] Based on the frequency regulation characteristics of traditional thermal power and energy storage batteries, a first-order low-pass filter model is constructed to decompose the frequency deviation signal obtained in step one into a high-frequency component f. high The low-frequency component is calculated as f. low Its specific model G m (s) are as follows:

[0118]

[0119] In the formula, T m is the time constant of the first-order low-pass filter.

[0120] The frequency deviation signal is passed through a low-pass filter to obtain f high f low They are as follows:

[0121] f low =G m (s)·Δf(s)

[0122] f high =1-G m (s)·Δf(s)

[0123] In the formula, G m (s) is the transfer function model of a first-order low-pass filter, f highf represents the high-frequency component of the obtained frequency deviation signal. low This refers to the low-frequency component of the obtained frequency deviation signal.

[0124] After completing the frequency deviation signal partitioning and allocation process described above, a coordinated frequency deviation signal and energy storage battery SOC frequency modulation control method is established, with the following specific steps:

[0125] 1) Determine |f t |<f n When the above relationship holds, energy storage is in a penalized standby state;

[0126] 2) Determine |f t |<f n If the above relationship does not hold, continue to judge |f t |>f w If the relationship is established, continue to determine f. t >f w If the relationship is established, continue to determine the SOC. t ≤SOC max When this relationship is true, the energy storage is in a penalty standby state; when the relationship is false, the energy storage is in a charging state.

[0127] 3) Determine |f t |<f n If the above relationship does not hold, continue to judge |f t |>f w If the relationship is established, continue to determine f. t >f w If the relationship is not established, continue to determine the SOC. t ≤SOC min When this relationship holds, the energy storage is in a penalty standby state; when the relationship does not hold, the energy storage is in a discharge state.

[0128] 4) Determine |f t |<f n If the above relationship does not hold, continue to judge |f t |>f w If the relationship is not established, continue to determine the SOC. low <SOC t <SOC high When this relationship is established, energy storage is in a penalized standby state.

[0129] 5) Determine |f t |<f n When the above relationship does not hold, continue to judge |f t |>f w If the relationship is not established, continue to determine the SOC. low<SOC t <SOC high If the relationship is not established, continue to determine the SOC. high <SOC t <SOC max If this relationship does not hold, the energy storage is in a charging state; otherwise, the energy storage is in a discharging state.

[0130] In the formula, f t f is the real-time value of the frequency deviation; n The minimum value to cross the unmodulated region; f w This represents the minimum frequency for emergency response; SOC t Real-time SOC value of energy storage battery; SOC min This represents the minimum dead-zone threshold for frequency regulation of the energy storage battery; SOC low For energy storage batteries participating in frequency regulation, the SOC (State of Charge) is at a low level; SOC high For energy storage batteries participating in frequency regulation, the SOC (State of Charge) is at a high level; max This represents the maximum value of the frequency regulation dead zone threshold for energy storage batteries.

[0131] Based on the aforementioned frequency deviation signal and the SOC-coordinated frequency modulation control model for energy storage batteries, an adaptive adjustment module for charging and discharging output constraints of 5G base station energy storage batteries is established, and the implementation plan is as follows:

[0132] When the system frequency is in the aforementioned untuned frequency range, the established output constraint model is as follows:

[0133]

[0134]

[0135] In the formula: P dmax The adaptive maximum discharge power is based on real-time SOC correction; P cmax For adaptive maximum charging power based on real-time SOC correction; SOC t Real-time SOC value of energy storage battery; SOC min This represents the minimum dead-zone threshold for frequency regulation of the energy storage battery; SOC low For energy storage batteries participating in frequency regulation, the SOC (State of Charge) is at a low level; SOC high For energy storage batteries participating in frequency regulation, the SOC (State of Charge) is at a high level; max This represents the maximum value of the frequency regulation dead zone threshold for energy storage batteries.

[0136] When the system is in the normal frequency regulation range, the output constraint model is as follows:

[0137]

[0138]

[0139] In the formula: P dmax The adaptive maximum discharge power is based on real-time SOC correction; P cmax For adaptive maximum charging power based on real-time SOC correction; p r The rated charge and discharge power of the energy storage; p c For reference only; n c For adaptive coefficients of energy storage charge and discharge; SOC t Real-time SOC value of energy storage battery; SOC min This represents the minimum dead-zone threshold for frequency regulation of the energy storage battery; SOC low For energy storage batteries participating in frequency regulation, the SOC (State of Charge) is at a low level; SOC high For energy storage batteries participating in frequency regulation, the SOC (State of Charge) is at a high level; max This represents the maximum value of the frequency regulation dead zone threshold for energy storage batteries.

[0140] When the system is in the emergency regulation zone, the grid experiences significant disturbances. The primary objective is to quickly reduce the system frequency deviation and restore it to the normal regulation zone. Therefore, energy storage still needs to leverage its fast response speed to provide rapid support to the system. Furthermore, in the emergency regulation zone, energy storage SOC recovery is no longer performed; it is only necessary to ensure that the SOC remains within the normal operating range. Therefore, the frequency regulation output constraint strategy is as follows:

[0141]

[0142] In the formula: P c The charging power of the energy storage battery for 5G base stations; P d The charging power for the energy storage batteries of 5G base stations; This represents the maximum charging power of the energy storage device. This represents the maximum charging power of the energy storage; SOC t Real-time SOC value of energy storage battery; SOC min This represents the minimum dead-zone threshold for frequency regulation of the energy storage battery; SOC max This represents the maximum value of the frequency regulation dead zone threshold for energy storage batteries.

[0143] Based on the above-mentioned frequency regulation control method of thermal power unit and energy storage battery, the goal of balancing battery energy storage life and system frequency stability can be achieved.

[0144] The present invention also provides a 5G base station battery energy storage participation power system auxiliary frequency regulation control system, including a memory, a processor, and computer program instructions stored in the memory and executable by the processor. When the processor executes the computer program instructions, it can implement the steps described above.

[0145] The present invention also provides a computer-readable storage medium having stored thereon computer program instructions that can be executed by a processor, wherein when the processor executes the computer program instructions, it can implement the steps of the method described above.

[0146] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0147] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0148] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0149] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0150] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for 5G base station battery energy storage to participate in power system auxiliary frequency regulation control, characterized in that, Includes the following steps: Step 1: Based on the mathematical model of 5G base station battery energy storage and its operating characteristics, establish a corresponding model for 5G base station battery energy storage aggregation to participate in power system auxiliary frequency regulation. Step 2: Establish a 5G base station battery energy storage participation in power system load frequency response model based on the electricity market contract trading mechanism. By setting disturbance parameters, obtain the frequency deviation f, and then apply different set values ​​of f. n f w Each zone is designated as a non-frequency tuning zone, a normal frequency tuning zone, and a frequency tuning emergency zone. Step 3: Construct a low-pass filter model and obtain the high-frequency and low-frequency components of the frequency deviation f, where the high-frequency component is denoted as f. high The low-frequency part is calculated as f low Low frequency part f low Used for frequency regulation signals in thermal power units, high-frequency component f high Frequency regulation signal used for 5G base station battery energy storage; Step 4: Establish a real-time SOC partitioning model for 5G base station battery energy storage, and in conjunction with frequency partitioning, establish an energy storage output constraint model with 5G base station battery energy storage SOC as the variable. Step 5: Based on the frequency regulation characteristics of 5G base station battery energy storage, and combined with the high-frequency part of the frequency deviation f, design a coordinated frequency regulation scheme that considers the 5G base station battery energy storage SOC and the frequency deviation f, and combine the energy storage output constraint model to control the charging, discharging and standby behavior of the energy storage battery. Step one is implemented as follows: The mathematical model for power injection into battery storage in a single 5G base station is as follows: In the formula: P bess The discharge power of 5G base station battery energy storage; r bess The participation factor for battery energy storage in 5G base stations; Rated discharge power for 5G base station battery energy storage; The State of Charge (SOC) of a single 5G base station's battery energy storage varies as follows: In the formula: h is the step size selected during calculation; soc(k) is the SOC of the battery energy storage at time k; soc(k+1) is the SOC of the battery energy storage at time k+1; C bess This indicates the rated capacity of the battery energy storage for 5G base stations; η bess This represents the charge / discharge participation factor of the 5G base station battery energy storage. For idle 5G base station battery energy storage resources, it is necessary to participate in the auxiliary frequency regulation of the power system through aggregation and control. The transfer function and SOC change function of the 5G base station battery energy storage aggregation participation in the auxiliary frequency regulation of the power system are expressed as follows: In the formula, T e The time constant of the energy storage battery for 5G base stations; SOC e0 ΔP represents the initial state of charge (SOC) of the 5G base station's energy storage battery. e S represents the output value of the energy storage battery for a 5G base station at time t. e s represents the rated capacity of the energy storage battery for 5G base stations, and s represents the complex frequency. In step five, the designed coordinated frequency modulation scheme considering the 5G base station battery energy storage SOC and frequency deviation f is as follows: 1) Determine |f t |<f n When |f t |<f n At the time of its establishment, the energy storage system was in a penalty standby state. 2) Determine |f t |<f n When |f t |<f n If not true, continue to evaluate |f t |>f w ,|f t |>f w If it is established, continue to determine f. t >f w f t >f w Upon establishment, continue to determine the SOC. t ≤SOC max When SOC t ≤SOC max When established, the energy storage is in a penalty standby state; when SOC... t ≤SOC max If this condition is not met, the energy storage is in a charging state; 3) Determine |f t |<f n When |f t |<f n If not true, continue to evaluate |f t |>f w ,|f t |>f w If it is established, continue to determine f. t >f w f t >f w If not, continue to determine SOC. t ≤SOC min When SOC t ≤SOC min When established, the energy storage is in a penalty standby state; when SOC... t ≤SOC min If this condition is not met, the energy storage will be in a discharging state. 4) Determine |f t |<f n When |f t |<f n If not true, continue to evaluate |f t |>f w ,|f t |>f w If not, continue to determine SOC. low <SOC t <SOC high SOC low <SOC t <SOC high At the time of its establishment, the energy storage system was in a penalty standby state. 5) Determine |f t |<f n When |f t |<f n If not true; continue judging |f t |>f w ,|f t |>f w If not, continue to determine SOC. low <SOC t <SOC high SOC low <SOC t <SOC high If not, continue to determine SOC. high <SOC t <SOC max SOC high <SOC t <SOC max If this condition is not met, the energy storage is in a charging state; otherwise, the energy storage is in a discharging state. In the formula, f t f is the real-time value of the frequency deviation; n The minimum value to cross the unmodulated region; f w This represents the minimum frequency for emergency response; SOC t Real-time SOC value for 5G base station battery energy storage; SOC min Minimum dead zone threshold for frequency modulation of 5G base station battery energy storage; SOC low For 5G base station battery energy storage to participate in frequency modulation, the low SOC value; SOC high High SOC value for 5G base station battery energy storage to participate in frequency modulation; SOC max This represents the maximum value of the frequency modulation dead zone threshold for 5G base station battery energy storage.

2. The method for 5G base station battery energy storage to participate in power system auxiliary frequency regulation control according to claim 1, characterized in that, In step two, the frequency deviation f is obtained using the ACE control method, as detailed below: Under ACE control mode, the ACE control signal obtains the real-time frequency of the power grid through the power grid dispatch center. Based on the 5G base station battery energy storage aggregation participation power system auxiliary frequency regulation model and the power grid frequency regulation model based on regional control deviation, the 5G base station energy storage battery transfer function G is obtained. e (s) and thermal power unit transfer function G s (s) are as follows: In the formula, T e T represents the time constant of the energy storage battery for 5G base stations. rh F is the reheater time constant. hp For reheater gain, T n T is the governor constant of a conventional unit. ch Let s be the turbine time constant, and s be the complex frequency; In the context of the electricity market, a distribution participation matrix is ​​established, specifically as follows: In the formula: A dmp For the distribution participation matrix, ε cpf,ij As a contract participation factor; In this matrix, i and j represent the row and column of the matrix, respectively, and are actually expressed as the normalized scalar of the electrical energy purchased by power distribution company j in the contract signed between power generation company i; The switching power on the interconnection line of the two-area interconnection system is expressed as follows: In the formula, ΔP t,s The power deviation on the tie line; ΔP b2-1 Electricity purchased by Region 2 from Region 1; ΔP b1-2 Electricity purchased by Region 1 from Region 2; Calculate the output ΔP1(s) of the thermal power unit under primary frequency regulation, the output ΔP2(s) of the thermal power unit under secondary frequency regulation, and the output ΔP of the energy storage battery of the 5G base station under ACE control mode. e (s): ΔP1(s)=-K s ·G n (s)·Δf(s) ΔP2(s)=λ(1-η)·(K P +K i / s)·G n (s)·Δf(s) ΔP e (s)=λ·η·G e (s)·Δf(s) In the formula, G n (s) is the transfer function of the thermal power unit, K s λ is the unit regulating power of the thermal power unit; λ is the frequency deviation coefficient of the system PI controller; K p K is the proportional gain of the PI controller. i Here, η is the integral coefficient of the PI controller; η is the weighting coefficient of the 5G base station energy storage battery participating in frequency regulation; (1-η) is the weighting factor of the thermal power unit participating in frequency regulation; Δf(s) is the frequency domain signal of the frequency deviation; the transfer function Δf(s) of the system frequency deviation frequency domain signal is calculated as follows: According to different setting values ​​f n f w The following are defined: a non-frequency modulation zone, a normal frequency modulation zone, and a frequency modulation emergency zone. Unmodulated region: 0≤f t ≤f n ; Normal frequency modulation range: f n ≤f t ≤f w ; FM emergency zone: f w ≤f t ; In the formula, f t For real-time frequency; f n The minimum value to cross the unmodulated region; f w This represents the minimum frequency for emergency response.

3. A method for 5G base station battery energy storage to participate in power system auxiliary frequency regulation control according to claim 1, characterized in that, In step three, a low-pass filter model is constructed, and the specific implementation is as follows: Based on the frequency regulation characteristics of thermal power plants and 5G base station energy storage batteries, a first-order low-pass filter model is constructed to decompose the frequency deviation obtained in step two into a high-frequency component f. high Low-frequency part f low The details are as follows: In the formula, T m The time constant of the first-order low-pass filter; f, obtained by passing the frequency deviation through a low-pass filter high f low They are as follows: f low =G m (s)·Δf(s) f high =1-G m (s)·Δf(s) In the formula, G m (s) is the transfer function model of a first-order low-pass filter, f high For the high-frequency component of the frequency deviation, f low Δf(s) represents the low-frequency component of the frequency deviation; Δf(s) represents the frequency domain signal of the frequency deviation.

4. A method for 5G base station battery energy storage to participate in power system auxiliary frequency regulation control according to claim 1, characterized in that, In step four, when the system frequency is in the un-tuned region, the energy storage output constraint model with the 5G base station battery energy storage SOC as the variable is as follows: In the formula: P dmax The adaptive maximum discharge power is based on real-time SOC correction; P cmax For adaptive maximum charging power based on real-time SOC correction; SOC t Real-time SOC value for 5G base station energy storage batteries; SOC min Minimum frequency modulation dead zone threshold for 5G base station energy storage batteries; SOC low For 5G base station energy storage batteries participating in frequency modulation, the low-level SOC value; SOC high For 5G base station energy storage batteries to participate in frequency modulation, the SOC (State of Charge) is at a high level; max This represents the maximum value of the frequency modulation dead zone threshold for 5G base station energy storage batteries.

5. A method for 5G base station battery energy storage to participate in power system auxiliary frequency regulation control according to claim 1, characterized in that, In step four, when the system frequency is in the normal frequency modulation range, the energy storage output constraint model with the 5G base station battery energy storage SOC as the variable is as follows: In the formula: P dmax The adaptive maximum discharge power is based on real-time SOC correction; P cmax For adaptive maximum charging power based on real-time SOC correction; p r Rated charge and discharge power for 5G base station battery energy storage; p c For reference only; n c Adaptive coefficients for charging and discharging 5G base station battery energy storage; SOC t Real-time SOC value for 5G base station energy storage batteries; SOC min Minimum frequency modulation dead zone threshold for 5G base station energy storage batteries; SOC low For 5G base station energy storage batteries participating in frequency modulation, the low-level SOC value; SOC high For 5G base station energy storage batteries to participate in frequency modulation, the SOC (State of Charge) is at a high level; max This represents the maximum value of the frequency modulation dead zone threshold for 5G base station energy storage batteries.

6. A method for 5G base station battery energy storage to participate in power system auxiliary frequency regulation control according to claim 1, characterized in that, In step four, when the system frequency is in the frequency regulation emergency zone, the power grid is subjected to significant disturbances. The primary goal is to quickly reduce the system frequency deviation and restore the system frequency to the normal frequency regulation zone. Therefore, energy storage still needs to leverage its fast response speed to provide rapid support to the system. Furthermore, energy storage SOC recovery is no longer performed in the frequency regulation emergency zone; it is only necessary to ensure that the SOC remains within the normal operating range. Therefore, the energy storage output constraint model with the 5G base station battery energy storage SOC as the variable is established as follows: In the formula: P c Power for charging 5G base station battery energy storage; P d Power for charging 5G base station battery energy storage; Maximum charging power for 5G base station battery energy storage; Maximum charging power for 5G base station battery energy storage; SOC t Real-time SOC value for 5G base station battery energy storage; SOC min Minimum dead zone threshold for frequency modulation of 5G base station battery energy storage; SOC max This represents the maximum value of the frequency modulation dead zone threshold for 5G base station battery energy storage.

7. A control system for 5G base station battery energy storage participating in power system auxiliary frequency regulation, characterized in that, It includes a memory, a processor, and computer program instructions stored in the memory and executable by the processor, which, when executed by the processor, enable the implementation of the steps of the method as described in any one of claims 1-6.

8. A computer-readable storage medium having stored thereon computer program instructions executable by a processor, wherein when the processor executes the computer program instructions, it is able to implement the steps of the method as described in any one of claims 1-6.

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