Space-time adaptive voltage coordination control method, device, equipment, medium and product

Abstract

The invention discloses a space-time adaptive voltage coordination control method, device and equipment, a medium and a product, and relates to the field of voltage coordination control, and the method comprises the steps: determining a voltage quality risk-approaching coefficient of a functional region according to the current state of the n-phase voltage of any functional region; according to the voltage quality risk approaching coefficient of each functional area, whether each functional area needs to enter second-level distributed BESS coordinated output is judged; if yes, a distributed BESS coordinated output strategy is selected according to the voltage quality risk approaching coefficient; the distributed BESS coordinated output strategy comprises a functional area EVs-based coordinated control strategy, a vine model threshold band strategy and a coordinated control strategy combining the functional area EVs-based coordinated control strategy and the vine model threshold band strategy; according to the method, the voltage quality of the power distribution network is improved, the BESS voltage regulation economy is improved, and meanwhile, the workload during voltage coordination control is reduced.

Description

Technical Field

[0001] The present application relates to the field of voltage coordinated control, and in particular to a time-space adaptive voltage coordinated control method, device, equipment, medium and product. Background Art

[0002] As the global energy structure accelerates its transition toward a low-carbon economy, the large-scale integration of renewable energy has become a hallmark of modern power system development. Photovoltaic power generation, thanks to its clean, environmentally friendly, and distributed deployment advantages, has seen its penetration rate in distribution networks continue to increase. However, the reverse flow triggered by high-penetration PV grid integration can cause voltage overshoots in distribution networks. Furthermore, PV output is random and intermittent, influenced by factors such as light intensity and temperature. This can cause voltage fluctuations in distribution networks and, in severe cases, even short-term voltage flicker, posing a threat to the stable operation of power systems. Traditionally, mechanical voltage regulation devices such as on-load tap changers (OLTCs) and step voltage regulators (SVRs) are used to control voltage overshoots in distribution networks caused by load fluctuations. However, in distribution networks with high PV penetration, the randomness and uncertainty of PV output can lead to rapid voltage overshoots and fluctuations.

[0003] Traditional voltage regulation equipment is discrete, with drawbacks such as low regulation accuracy and slow response speed. It cannot operate continuously in a short period of time, and frequent operation will reduce its service life, making it difficult to meet the distribution network's demand for fast, continuous, and accurate voltage control. In this context, battery energy storage systems (BESS) can achieve rapid switching between charge and discharge states due to their rapid response capabilities and flexible regulation characteristics. At the same time, with the explosive growth in the number of electric vehicles (EVs), their role in the distribution network is undergoing profound changes. EVs are no longer simply loads; they can now participate in the distribution network's voltage regulation through vehicle-to-grid (V2G) technology.

[0004] As the penetration rate of distributed photovoltaic (PV) and EVs in distribution networks continues to rise, strong random disturbances on both the source and load sides can cause problems such as voltage exceeding the limit and voltage fluctuation in the distribution network. Although BESS, EVs, OLTC, and SVR can achieve precise control of distribution network voltage by coordinating at different time scales, the continuous use of coordinated control of distribution network voltage, the collection of real-time data of the entire distribution network, and the voltage regulation process will inevitably bring a heavy workload. Summary of the Invention

[0005] The purpose of this application is to provide a spatio-temporal adaptive voltage coordination control method, device, equipment, medium and product to solve the problem of large workload in voltage coordination control.

[0006] To achieve the above object, this application provides the following solutions:

[0007] In the first aspect, this application provides a spatio-temporal adaptive voltage coordination control method, including:

[0008] Determine the voltage quality risk coefficient of the functional area according to the current voltage state of phase n in any functional area; the voltage quality risk coefficient includes the voltage amplitude risk coefficient and the voltage fluctuation risk coefficient;

[0009] Judge whether each functional area needs to enter the second-level distributed BESS coordinated output according to the voltage quality risk coefficient of the functional area;

[0010] If so, select a distributed BESS coordinated output strategy according to the voltage quality risk coefficient; the distributed BESS coordinated output strategy includes a coordinated control strategy based on functional area EVs, a vine model threshold band strategy, and a coordinated control strategy combining the coordinated control strategy based on functional area EVs and the vine model threshold band strategy;

[0011] If not, use a minute-level control strategy for voltage control.

[0012] In the second aspect, this application provides a spatio-temporal adaptive voltage coordination control device, including:

[0013] A voltage quality risk coefficient determination module, configured to determine the voltage quality risk coefficient of the functional area according to the current voltage state of phase n in any functional area; the voltage quality risk coefficient includes the voltage amplitude risk coefficient and the voltage fluctuation risk coefficient;

[0014] A judgment module, configured to judge whether each functional area needs to enter the second-level distributed BESS coordinated output according to the voltage quality risk coefficient;

[0015] An output strategy selection module, configured to select a distributed BESS coordinated output strategy according to the voltage quality risk coefficient; the distributed BESS coordinated output strategy includes a coordinated control strategy based on functional area EVs, a vine model threshold band strategy, and a coordinated control strategy combining the coordinated control strategy based on functional area EVs and the vine model threshold band strategy;

[0016] A voltage control module, configured to use a minute-level control strategy for voltage control.

[0017] In a third aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the spatio-temporal adaptive voltage coordination control method described in any one of the above.

[0018] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the spatio-temporal adaptive voltage coordination control method described in any one of the above.

[0019] In a fifth aspect, the present application provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the spatio-temporal adaptive voltage coordination control method described in any one of the above.

[0020] According to the specific embodiments provided by the present application, the following technical effects are disclosed by the present application:

[0021] By calculating the voltage quality risk coefficient, the present application determines whether to enter the second-level distributed BESS coordinated output, and selects voltage regulation methods at different time scales, which include the second level and the minute level, avoiding the continuous coordinated control of voltage by BESS, EVs, OLTC, and SVR, reducing the workload in the voltage regulation process. Moreover, if entering the second-level distributed BESS coordinated output, the present application selects different coordinated output strategies according to the voltage quality risk coefficient, so as to be able to collect real-time data in the distribution network specifically, and then more quickly coordinate the control of voltage, further reducing the workload during voltage coordinated control. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0023] Figure 1 It is a flowchart of the spatio-temporal adaptive voltage coordination control method provided by the present application;

[0024] Figure 2 It is a schematic diagram of the strategy architecture of the spatio-temporal adaptive voltage coordination control method provided by the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0025] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts shall fall within the protection scope of the present application.

[0026] To make the above objects, features, and advantages of the present application more obvious and understandable, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0027] The embodiment of the present application provides a spatio-temporal adaptive voltage coordination control method, which is executed by a computer device. Specifically, it can be executed independently by a computer device such as a terminal or a server, or jointly executed by a terminal and a server. In the embodiment of the present application, as Figure 1 shown, the method includes the following steps.

[0028] S1: Determine the voltage quality risk coefficient of the functional area according to the current voltage state of the n-phase of any functional area; the voltage quality risk coefficient includes the voltage amplitude risk coefficient and the voltage fluctuation risk coefficient.

[0029] S2: According to the voltage quality risk coefficient, judge whether each functional area needs to enter the second-level distributed BESS coordinated output. If so, execute S3; if not, execute S4.

[0030] S3: Select a distributed BESS coordinated output strategy according to the voltage quality risk coefficient; the distributed BESS coordinated output strategy includes a coordinated control strategy based on EVs in the functional area, a vine model threshold band strategy, and a coordinated control strategy combining the coordinated control strategy based on EVs in the functional area and the vine model threshold band strategy.

[0031] S4: Use a minute-level control strategy for voltage control.

[0032] In an exemplary embodiment, the present application is based on a dynamic partition control strategy of the Voltage Quality Risk Prognostication Coefficient (VQRPC). This VQRPC dynamic partition control strategy calculates the voltage quality risk coefficient of each functional area at the next moment respectively, and judges the time scale of voltage control in each functional area at the next moment according to the voltage quality risk coefficient of each functional area, that is, whether to perform OLTC and SVR operations only at the minute level, or to jointly perform voltage control by second-level BESS, EVs coordinated with minute-level OLTC and SVR.

[0033] By flexibly applying the VQRPC dynamic partition control strategy, while alleviating the heavy data sampling workload brought by real-time control to the distribution network, and ensuring good voltage quality, S1 can be replaced by the following steps.

[0034] S11: Use the autoregressive integrated moving average model to fit the voltages at multiple sampling points within a time period, and determine the voltage amplitude risk coefficient of any phase within the functional area at the next moment.

[0035] S12: During the photovoltaic power output stage, determine the voltage fluctuation risk coefficient according to the maximum predicted voltage fluctuation of any phase within the functional area at the next moment.

[0036] In practical applications, the voltage quality risk coefficient consists of two parts: namely, the voltage amplitude risk coefficient (Voltage Amplitude Risk Prognostication Coefficient, VARPC) used to measure the voltage deviation degree of the functional area and the voltage fluctuation risk coefficient (Voltage Fluctuation Risk Prognostication Coefficient, VFRPC) used to measure the voltage fluctuation intensity of the functional area.

[0037] The calculation process of the voltage amplitude risk coefficient is as follows:

[0038] The voltage amplitude risk coefficient of the nth phase of the functional area z at time t + 1 Defined as shown in formula (1), to predict the risk of voltage over-limit in the functional area at the next moment, this application uses the autoregressive integrated moving average model (ARIMA) for short-term prediction, and fits the voltages of ο sampling points from t - ο to t as the input of ARIMA for prediction And take the maximum voltage deviation within the time period from t - ο to t as the prediction error margin at time t + 1

[0039]

[0040] Among them, are respectively the maximum and minimum values of the predicted voltage of the nth phase in the functional area z at time t + 1; is the voltage value of the nth phase of node i in the functional area z at time t - ι, and both ι and are variables V between the predicted sampling points 0 and ο nom is the nominal voltage.

[0041] The calculation process of the voltage fluctuation risk coefficient is as follows:

[0042] During the photovoltaic output period, due to the randomness of photovoltaic output, the voltage in the distribution network fluctuates frequently, which has an adverse impact on the stable operation of the distribution network. The voltage fluctuation risk coefficient of phase n in functional area z at time t+1 is shown by formula (5).

[0043]

[0044] where, T st and T ed represent the start and end times of photovoltaic output respectively; is the maximum predicted voltage fluctuation of phase n in functional area z at time t+1; is the voltage fluctuation threshold of phase n; is the voltage of phase n at node i at time

[0045] The voltage quality risk coefficient VQRPC of functional area z at time t+1 z (t+1) is represented by formula (8).

[0046] The voltage quality risk coefficient

[0047]

[0048] where, is the sum of the voltage amplitude risk coefficient and the voltage fluctuation risk coefficient at time t+1; represents the set including phase ab, phase bc and phase ca.

[0049] In an exemplary embodiment, S2 can be replaced by the following steps.

[0050] S21: Determine whether both the voltage amplitude risk coefficient and the voltage fluctuation risk coefficient are equal to 0. If so, execute S22; if not, execute S23.

[0051] S22: Perform voltage control using a minute-level control strategy.

[0052] S23: Determine that it is necessary to enter the second-level coordinated output of distributed BESS.

[0053] In an exemplary embodiment, S3 can be replaced by the following steps.

[0054] S31: When the voltage amplitude risk coefficient is equal to 1 and the voltage fluctuation risk coefficient is equal to 0, select a coordinated control strategy based on EVs in the functional area for voltage regulation, and determine the optimal output of each distributed BESS in the functional area under voltage control.

[0055] S32: When the voltage fluctuation danger coefficient is equal to 1 and the voltage amplitude danger coefficient is equal to 0, select the vine model threshold band strategy for voltage regulation, and determine the output of each distributed BESS in the functional area under voltage fluctuation regulation.

[0056] S33: When both the voltage fluctuation danger coefficient and the voltage amplitude danger coefficient are equal to 1, select a coordinated control strategy that combines the coordinated control strategy based on EVs in the functional area and the vine model threshold band strategy, and determine the output of each distributed BESS in the functional area under voltage control and voltage fluctuation regulation.

[0057] In an exemplary embodiment, for the problem of the coordinated output accuracy of distributed BESSs in the functional area. Use BKA to optimize the output of distributed BESSs in the functional area, and S31 can be replaced by the following steps.

[0058] S311: According to the over-limit index of any phase voltage in the functional area at the current moment, calculate the voltage to be adjusted and the adjustable amount of EVs voltage.

[0059] S312: Calculate the voltage of the adjusted functional area according to the voltage to be adjusted and the adjustable amount of EVs voltage.

[0060] S313: Determine the optimal output of each distributed BESS in the functional area under voltage control according to the voltage of the adjusted functional area.

[0061] In practical applications, the present application provides a coordinated control strategy based on EVs in the functional area. By scheduling EVs in the functional area to participate in the voltage regulation of the distribution network, the coordinated output with distributed BESSs is realized. Effectively reduce the capacity demand of distributed BESSs. In particular, to achieve the accuracy of voltage regulation of distributed BESSs in the functional area, the present application uses the recently proposed Black Kite Algorithm (BKA) to optimize the output of BESSs. This algorithm simulates the dynamic encirclement strategy of the black kite in predatory attacks and the highly adaptable and intelligent behavior shown during migration. It has the characteristics of strong adaptability, few adjustable parameters, and high convergence accuracy. The specific implementation steps are as follows:

[0062] Step 1: Judge the voltage in functional area z Whether it is over-limit. If it is over-limit, calculate the voltage to be adjusted according to formula (10)

[0063]

[0064] is the over-limit index of the n-phase voltage in functional area z at time t.

[0065] Step 2: Calculate the adjustable amount of EVs voltage in functional area z at time t according to formula (12) If the formula (15) is satisfied, the voltage regulation ends at time t, and only the EVs in the functional area z are used for voltage regulation. Otherwise, step 3 is executed for the coordinated control of BESS and EVs.

[0066]

[0067]

[0068] Among them, are the charging and discharging powers of the nth phase of the schedulable EVs in the functional area z at time t; L z (t), Y z (t) are the numbers of fast and slow charging of the schedulable EVs in the functional area z at time t respectively;

[0069] Step 3: Calculate the voltage of the functional area z after the adjustment of EVs at time t according to formula (16)

[0070]

[0071] Replace in formula (10) with Calculate the voltage required for the coordinated control of BESS in the functional area

[0072] Step 4: Determine the number o(t) of distributed BESSs participating in voltage regulation in the functional area z at time t according to formula (17). If ο(t) is 1, it represents economic voltage regulation, and only the distributed BESS with the highest power-capacity availability in the functional area z needs to participate in voltage regulation. Otherwise, it is emergency coordinated voltage regulation, and all distributed BESSs in the functional area z coordinate to control the voltage.

[0073]

[0074] Among them, is the threshold value of economic voltage regulation in the functional area z; is the maximum output of the bth distributed BESS in the functional area z; B z is the number of distributed BESSs in the functional area z.

[0075] Step 5: Determine the BKA variable dimension ξ z (t), and set the upper and lower boundaries, the number of iterations and the population parameters, and randomly initialize the position of the black-winged kite.

[0076]

[0077] Among them, is the number of outputs of the distributed BESS in the functional area z at time t;

[0078] Step 6: Calculate the fitness value f of the black-winged kite according to formula (21) bka , and select the individual with the best fitness value as the leader.

[0079]

[0080] where are respectively the maximum and minimum values of the voltage in the functional area z after substituting the position of the black-winged kite.

[0081] If the voltage after substituting the position of the black-winged kite is still out of limit, then update f according to formula (22) bka .

[0082] f bka = f bka + k pen (22)

[0083] where k pen is the penalty value.

[0084] Step 7: Update the position of the black-winged kite according to the unique attack and migration behaviors of the black-winged kite.

[0085] Step 8: Repeat Step 6 - Step 7 until the maximum number of iterations is reached, and output the best position of the black-winged kite, that is, the optimal output P b,bka (t) of each distributed BESS under voltage control.

[0086] In an exemplary embodiment, the present application provides a novel vine model threshold band strategy to improve the frequent voltage fluctuations caused by the randomness of photovoltaic output. S32 can be replaced by the following steps.

[0087] S321: Determine the amount of adjustment required to suppress voltage fluctuations at the current moment according to the difference between any phase voltage in the functional area and the upper and lower limits of the vine model threshold band at the current moment.

[0088] S322: Calculate the adjustable amount of EVs in the functional area according to the amount of adjustment required to suppress voltage fluctuations at the current moment;

[0089] S323: Suppress voltage fluctuations according to the adjustable amount of EVs in the functional area, and calculate the output of EVs.

[0090] S324: Based on the output of the EVs, calculate the value of the adjustment required for the BESS to suppress voltage fluctuations according to the adjustable amount of EVs in the functional area, and determine the output of each BESS.

[0091] In practical applications, the present application provides a vine model threshold band to achieve the suppression of voltage fluctuations in the functional area. The vine model threshold band is defined as follows.

[0092]

[0093]

[0094] Among them, are respectively the upper and lower limits of the vine model threshold band; is the predicted voltage value of n - phase ARMIA in the functional area z at time t + 1; is the voltage fluctuation safety margin in the functional area z at time t + 1; is the average value of n - phase voltage fluctuations at node i in the functional area z from time t to t - ο; α1 and α2 represent weights.

[0095] If the vine model threshold band exceeds the voltage safety threshold, the vine model threshold band is updated according to formula (28).

[0096]

[0097] The specific steps are as follows:

[0098] Step 1: Calculate the regulation amount required to suppress voltage fluctuations at time t according to formula (29)

[0099]

[0100] Among them, are respectively the differences between the n - phase voltage in the functional area z at time t and the upper and lower limits of the vine model threshold band.

[0101] Step 2: Calculate the adjustable amount of EVs in the functional area z at time t according to formula (32)

[0102]

[0103] Step 3: If formula (33) is satisfied, go to Step 4 to only use EVs to suppress voltage fluctuations, otherwise go to Step 5, where BESS coordinates with EVs to suppress voltage fluctuations.

[0104]

[0105] Step 4: Calculate the output of EVs according to formula (34)

[0106]

[0107] Step 5: Calculate the value of voltage fluctuation suppression that BESS needs to coordinate according to formula (35) And according to the deviation degree of the distributed BSSS in the functional area z at time t Through formulas (36) and (37), ψ b(t) becomes the weight Γ of the output of each BESS in the functional area z at time t b (t), and finally, the output of each BESS is given by formula (38).

[0108]

[0109] Verification whether it satisfies formula (39), if not, adjust according to formula (40)

[0110]

[0111] In practical applications, the coordinated control strategy combining the coordinated control strategy based on functional area EVs and the vine model threshold band strategy is to replace the upper and lower limits of the vine model threshold band in the vine model threshold band strategy with V max and V min in formula (21) of the coordinated control strategy based on functional area EVs, and obtain the optimal output of each distributed BESS based on the modified coordinated control strategy based on functional area EVs.

[0112] The strategy framework of the spatio-temporal adaptive voltage coordinated control method provided by this application is as Figure 2 shown. In day-ahead scheduling, photovoltaic prediction data is obtained using a photovoltaic prediction model, and day-ahead scheduling plans for OLTC and SVR are formulated. In intraday minute-level optimization, the day-ahead OLTC and SVR scheduling plans are optimized. In real-time adaptive control, the VQRPC dynamic partitioning control strategy is adopted. When the VQRPC of functional area z exceeds the threshold, functional area z enters real-time control, and BESS and EV respond quickly for precise adjustment. Through this flexible voltage adjustment strategy, while improving voltage quality, the workload of real-time data acquisition is effectively reduced.

[0113] This application proposes a VQRPC dynamic perception mechanism based on partition decision-making, which intelligently screens functional areas based on 0-1 risk indicators, reducing the workload of data sampling while improving voltage quality. The results show that the voltage is controlled within the safety threshold throughout the day. Compared with full real-time control, the data acquisition workload in the entertainment area, office area, and residential area has decreased by 83.3%, 52.97%, and 67.2% respectively.

[0114] And through the proposed VMTB strategy, the voltage volatility χ z,vf in the entertainment area, office area, and residential area has decreased by 29.21%, 40.53%, and 39.75% respectively. A power-capacity availability index is proposed to achieve the uniform control of SOC within the functional area. The results show that the maximum SOC deviation of distributed BESS in the working area is only 1.17%, and the maximum SOC deviation of distributed BESS in the residential area is only 4.82%.

[0115] In the VMTB, a deviation management strategy is introduced to alleviate the deep charge / discharge of the BESS and optimize the available capacity of the BESS. The results show that the maximum SOC of BESS3 in the working area decreases by 3.85%, and the available capacity increases by 6.42%. The maximum SOC of BESS4 decreases by 3.11%, and the available capacity increases by 5.18%.

[0116] In addition, to relieve the pressure on BESS capacity configuration, EVs are used to coordinate the output of the BESS. The results show that the BESS capacity in the office area can be reduced by 29.91% and 20.81%; the BESS capacity in the residential area can be reduced by 25.15% and 33.61%.

[0117] Based on the same inventive concept, an embodiment of the present application further provides a spatio-temporal adaptive voltage coordination control device for implementing the spatio-temporal adaptive voltage coordination control method involved above. The implementation solutions provided by this device to solve problems are similar to the implementation solutions recorded in the above method. Therefore, the specific limitations in one or more embodiments of the spatio-temporal adaptive voltage coordination control device provided below can refer to the limitations on the spatio-temporal adaptive voltage coordination control method in the above text, and will not be repeated here.

[0118] In an exemplary embodiment, a spatio-temporal adaptive voltage coordination control device is provided, including:

[0119] A voltage quality crisis coefficient determination module, configured to determine the voltage quality crisis coefficient of a functional area according to the current voltage state of the n-phase of any functional area; the voltage quality crisis coefficient includes a voltage amplitude crisis coefficient and a voltage fluctuation crisis coefficient.

[0120] A judgment module, configured to judge whether each functional area needs to enter the second-level distributed BESS coordinated output according to the voltage quality crisis coefficient.

[0121] An output strategy selection module, configured to select a distributed BESS coordinated output strategy according to the voltage quality crisis coefficient; the distributed BESS coordinated output strategy includes a coordinated control strategy based on EVs in the functional area, a vine model threshold band strategy, and a coordinated control strategy combining the coordinated control strategy based on EVs in the functional area and the vine model threshold band strategy.

[0122] A voltage control module, configured to perform voltage control using a minute-level control strategy.

[0123] In an exemplary embodiment, a computer device is provided, which may be a server or a terminal. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. 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 spatio-temporal adaptive voltage coordination control data. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication 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, a spatio-temporal adaptive voltage coordination control method is implemented.

[0124] In an exemplary embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the above method is implemented.

[0125] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the above method is implemented.

[0126] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the above method is implemented.

[0127] 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. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the various embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include Read-Only Memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0128] In this application, all actions of obtaining signals, information, or data are carried out on the premise of complying with the corresponding data protection regulations and policies of the country where it is located and obtaining authorization from the owner of the corresponding device.

[0129] The databases involved in the various embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the various embodiments provided in the present application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0130] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0131] In this application, specific examples are used to illustrate the principles and implementation manners of the application. The description of the above embodiments is only used to help understand the method and its core idea of the application; at the same time, for those of ordinary skill in the art, according to the idea of the application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the application.

Claims

1. A spatio-temporal adaptive voltage coordination control method, characterized in that The spatio-temporal adaptive voltage coordination control method includes: Determining the voltage quality risk coefficient of a functional area according to the current voltage state of any n-phase in the functional area; the voltage quality risk coefficient includes a voltage amplitude risk coefficient and a voltage fluctuation risk coefficient; Judging whether each functional area needs to enter the second-level distributed BESS coordinated output according to the voltage quality risk coefficient; If so, selecting a distributed BESS coordinated output strategy according to the voltage quality risk coefficient; the distributed BESS coordinated output strategy includes a coordinated control strategy based on EVs in the functional area, a vine model threshold band strategy, and a coordinated control strategy combining the coordinated control strategy based on EVs in the functional area and the vine model threshold band strategy; If not, using a minute-level control strategy for voltage control.

2. The spatio-temporal adaptive voltage coordination control method according to claim 1, wherein Determining the voltage quality risk coefficient of a functional area according to the current voltage state of any n-phase in the functional area, specifically including: Adopting an autoregressive integrated moving average model to fit the voltages of multiple sampling points within a time period, and determining the voltage amplitude risk coefficient of any phase in the functional area at the next moment; During the photovoltaic output stage, determining the voltage fluctuation risk coefficient according to the maximum voltage fluctuation predicted for any phase in the functional area at the next moment.

3. The spatio-temporal adaptive voltage coordination control method according to claim 1, wherein Judging whether each functional area needs to enter the second-level distributed BESS coordinated output according to the voltage quality risk coefficient, specifically including: Judging that both the voltage amplitude risk coefficient and the voltage fluctuation risk coefficient are equal to 0; If so, using a minute-level control strategy for voltage control; If not, determining that it is necessary to enter the second-level distributed BESS coordinated output.

4. The spatio-temporal adaptive voltage coordination control method according to claim 1, wherein Selecting a distributed BESS coordinated output strategy according to the voltage quality risk coefficient, specifically including: When the voltage amplitude risk coefficient is equal to 1 and the voltage fluctuation risk coefficient is equal to 0, selecting a coordinated control strategy based on EVs in the functional area for voltage regulation, and determining the optimal output of each distributed BESS in the functional area under voltage control; When the voltage fluctuation risk coefficient is equal to 1 and the voltage amplitude risk coefficient is equal to 0, selecting a vine model threshold band strategy for voltage regulation, and determining the output of each distributed BESS in the functional area under voltage fluctuation regulation; When both the voltage fluctuation risk coefficient and the voltage amplitude risk coefficient are equal to 1, selecting a coordinated control strategy combining the coordinated control strategy based on EVs in the functional area and the vine model threshold band strategy, and determining the output of each distributed BESS in the functional area under voltage control and voltage fluctuation regulation.

5. The spatio-temporal adaptive voltage coordination control method according to claim 4, characterized in that Selecting a coordinated control strategy based on EVs in the functional area for voltage regulation, and determining the optimal output of each distributed BESS in the functional area under voltage control, specifically including: Calculating the voltage to be adjusted and the adjustable amount of the EV voltage according to the voltage over-limit index of any phase in the functional area at the current moment; Calculating the voltage of the adjusted functional area according to the voltage to be adjusted and the adjustable amount of the EV voltage; Determining the optimal output of each distributed BESS in the functional area under voltage control according to the voltage of the adjusted functional area.

6. The spatio-temporal adaptive voltage coordination control method according to claim 5, wherein Select the vine model threshold band strategy for voltage regulation, and determine the output of each distributed BESS in the functional area under voltage fluctuation regulation, specifically including: Determine the amount of regulation required to suppress voltage fluctuations at the current moment according to the difference between the voltage of any phase in the functional area at the current moment and the upper and lower limits of the vine model threshold band; Calculate the adjustable amount of EVs in the functional area according to the amount of regulation required to suppress voltage fluctuations at the current moment; Suppress voltage fluctuations according to the adjustable amount of EVs in the functional area, and calculate the output of EVs; Based on the output of the EVs, calculate the value of the voltage fluctuation suppression required to be adjusted by the BESS according to the adjustable amount of EVs in the functional area, and determine the output of each BESS.

7. A spatio-temporal adaptive voltage coordination control device, characterized in that, The spatio-temporal adaptive voltage coordination control device includes: A voltage quality risk coefficient determination module for determining the voltage quality risk coefficient of the functional area according to the current voltage state of any phase n in the functional area; the voltage quality risk coefficient includes a voltage amplitude risk coefficient and a voltage fluctuation risk coefficient; A judgment module for judging whether each functional area needs to enter the second-level distributed BESS coordinated output according to the voltage quality risk coefficient; An output strategy selection module for selecting a distributed BESS coordinated output strategy according to the voltage quality risk coefficient; the distributed BESS coordinated output strategy includes a coordinated control strategy based on EVs in the functional area, a vine model threshold band strategy, and a coordinated control strategy combining the coordinated control strategy based on EVs in the functional area and the vine model threshold band strategy; A voltage control module for performing voltage control using a minute-level control strategy.

8. A computer device, comprising: A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the spatio-temporal adaptive voltage coordination control method according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the spatio-temporal adaptive voltage coordination control method according to any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the spatio-temporal adaptive voltage coordination control method according to any one of claims 1-6.

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