Multi-dimensional multi-resource comprehensive voltage regulation and control optimization method for multi-voltage-class bipolar direct-current power distribution network

Abstract

The invention discloses a multi-dimensional multi-resource comprehensive voltage regulation and control optimization method for a multi-voltage-class bipolar direct-current power distribution network. The method comprises the following steps: 1, establishing control models of a bipolar direct-current transformer DCT, an electric vehicle, energy storage equipment and a power flow controller; 2, establishing a multi-dimension multi-resource coordination control model of the multi-voltage-level bipolar direct current power distribution network; 3, establishing a comprehensive voltage regulation and control optimization model of the multi-voltage-level bipolar direct-current power distribution network; 4, establishing a linearization and relaxation model constrained by the bipolar direct-current power distribution network comprehensive voltage regulation and control model; and 5, obtaining a comprehensive voltage regulation and control optimization strategy of the bipolar direct-current power distribution system by solving the multi-voltage-level bipolar direct-current power distribution network. According to the method, the load demand and the distributed energy fluctuation can be quickly responded, the stability of the voltage at the low-voltage side is ensured, the problems of voltage unbalance degree and out-of-limit between the positive electrode and the negative electrode are effectively controlled, and the stability of the system voltage is improved.

Description

Technical Field

[0001] The present invention proposes a multi-dimensional and multi-resource integrated voltage control optimization method for a multi-voltage level bipolar DC distribution network. Background Art

[0002] As a new power system architecture, bipolar DC distribution networks, with their bipolar structure (positive and negative) and neutral line design, offer significant advantages in power supply reliability and transmission efficiency. In recent years, they have become a key approach to addressing future energy system needs. Compared to traditional AC distribution networks, bipolar DC distribution networks not only reduce losses in the energy conversion process but also better accommodate the integration of new sources and loads, such as distributed photovoltaics, electric vehicles, and energy storage systems. However, with the increasing number of renewable energy sources and load types, complex voltage issues have emerged in system operation, which urgently require in-depth research and solutions.

[0003] In bipolar DC distribution networks, voltage problems primarily manifest as inter-pole voltage imbalance, voltage fluctuations, and node voltage over-limits. Inter-pole voltage imbalance is typically caused by asymmetric power distribution between the positive and negative poles. For example, when the load on one pole is significantly greater than the other, the voltage difference between the positive and negative poles increases significantly. This imbalance not only reduces power supply reliability but also exacerbates power losses in transmission lines, impacting overall system efficiency. Furthermore, due to the volatility of distributed photovoltaic power generation and the random nature of electric vehicle charging and discharging, node voltages may experience significant fluctuations or even over-limits. For example, in scenarios with high PV penetration, PV power generation may significantly exceed load demand during low-load periods, leading to excessive voltage. During peak load periods, node voltages may rapidly drop below the safe operating range, seriously threatening equipment safety and system stability. Voltage problems not only impact the power supply quality and safety of bipolar DC distribution networks but also restrict their ability to integrate high proportions of renewable energy and complex loads. Inter-pole voltage imbalance weakens the system's adaptability to load fluctuations, while node voltage over-limits and fluctuations reduce grid reliability. As the proportion of DC sources and loads such as distributed photovoltaics, electric vehicles and energy storage continues to increase, the scope and complexity of voltage problems will increase significantly. Summary of the Invention

[0004] In order to address the shortcomings of the above-mentioned existing technologies, the present invention proposes a multi-dimensional and multi-resource integrated voltage control optimization method for a multi-voltage-level bipolar DC distribution network, so as to achieve rapid response to load demand and distributed energy fluctuations, ensure the stability of the low-voltage side voltage, and effectively solve the voltage imbalance and over-limit problems between the positive and negative poles, thereby improving the voltage control capability of the bipolar DC distribution network, ensuring the safe operation of the system and supporting future energy transformation.

[0005] In order to achieve the above-mentioned object, the present invention adopts the following technical solutions:

[0006] The multi-dimensional and multi-resource integrated voltage control optimization method for a bipolar DC distribution network under multiple voltage levels of the present invention is characterized in that it includes the following steps:

[0007] S1: Establish control models for bipolar DC transformer (DCT), electric vehicle (EV), energy storage device (ESS), and unipolar power flow controller (PFC);

[0008] S2: Construct a multi-voltage distribution network power flow model including DC transformers (DCTs);

[0009] S3: Establish a comprehensive voltage regulation optimization model for multi-voltage level bipolar DC distribution networks;

[0010] S4: transforming the comprehensive voltage regulation optimization model of the multi-voltage level bipolar DC distribution network to obtain a transformed comprehensive voltage regulation optimization model;

[0011] S5: Use the solver to solve the converted comprehensive voltage control optimization model to obtain the comprehensive voltage control optimization strategy of the bipolar DC distribution system, including: the control strategy and power transmission strategy of the bipolar DC transformer DCT, the charging and discharging strategy of the electric vehicle, the charging and discharging strategy of the energy storage device, and the control strategy and power transmission strategy of the power flow controller.

[0012] The multi-dimensional and multi-resource integrated voltage control optimization method for a bipolar DC distribution network under multiple voltage levels described in the present invention is also characterized in that S1 includes the following steps:

[0013] S1-1: Establish a control model for a bipolar DC transformer DCT:

[0014] S1-1-1: Use equation (1) to construct a model of the relationship between the output power and the voltage on both sides of any single-pole DC transformer DCT:

[0015] (1)

[0016] In formula (1), Connect the polarity of different terminals of the unipolar DC transformer DCT, and ; p represents positive electrode, n represents negative electrode, b represents bipolar, The port polarity is The turns ratio of the unipolar DC transformer DCT; Indicates the port polarity is Compared with the equivalent shift of the unipolar DC transformer DCT, is the switching frequency of the unipolar DC transformer DCT; is the equivalent inductance of the unipolar DC transformer DCT; The port polarity is The terminal voltage of the unipolar DC transformer DCT on the high voltage side; The terminal polarity of the unipolar DC transformer DCT The port voltage on the low voltage side; The port polarity is The unipolar DC transformer DCT Output power at the moment; The port polarity is The deviation coefficient is caused by the inconsistency between the actual voltage ratio of the unipolar DC transformer DCT and the turns ratio of the high-frequency isolation transformer;

[0017] S1-1-2: Use formula (2) to construct the port polarity The power transfer relationship between the input and output sides of the unipolar DC transformer DCT is:

[0018] (2)

[0019] In formula (2), The port polarity is The unipolar DC transformer DCT The input power at the moment, The port polarity is The intermediate circuit of the unipolar DC transformer DCT is Power loss generated at any moment;

[0020] S1-1-3: Use equations (3) to (5) to construct mathematical models of the unipolar DC transformer DCT in constant ratio control mode, constant power control mode, and constant voltage control mode:

[0021] (3)

[0022] (4)

[0023] (5)

[0024] In formula (3) to formula (5), In the constant ratio control mode, the port polarity is The turns ratio of the unipolar DC transformer DCT; Indicates that the port polarity is in constant power control mode. The unipolar DC transformer DCT Output power at the moment; Indicates the voltage level of the unipolar DC transformer DCT port in constant voltage control mode. Down The voltage at the moment, Indicates the voltage level of the unipolar DC transformer DCT port in constant voltage control mode. Down Voltage at the moment; , Indicates high pressure, Indicates medium pressure, Indicates low pressure;

[0025] S1-2: Use equations (6) to (8) to establish a charging and discharging model for electric vehicles (EV):

[0026] (6)

[0027] (7)

[0028] (8)

[0029] In formula (6) to formula (8), and They are Time Node The charging power and discharging power of the electric vehicle EV at the location; for Time Node The equivalent power of electric vehicle (EV) charging at the location; Represents nodes respectively The connection time and disconnection time of the electric vehicle EV and the charging equipment at the location; and are the exchange efficiencies of charging power and discharging power, respectively; for Time Node The state of charge of the electric vehicle EV at the location, for Time Node The state of charge of the electric vehicle EV at the location; For nodes Battery capacity of the electric vehicle EV at the location; and Node The maximum charging power and maximum discharging power of the electric vehicle EV at the location; and is a node The lower and upper bounds of the state of charge of the electric vehicle EV at the location; and Node The initial state of charge and the desired state of charge of the electric vehicle EV at the location; for Time Node The charging and discharging status of the electric vehicle EV at the location =0 means Time Node The electric car at position is in discharge state. =1 means Time Node The electric vehicle EV at the location is in charging state; represents the set of all nodes, Indicates the time period when the electric vehicle EV is connected to the charging station. Indicates a time interval;

[0030] S1-3: Use equations (9) to (14) to establish a mathematical model of the energy storage device ESS:

[0031] (9)

[0032] (10)

[0033] (11)

[0034] (12)

[0035] (13)

[0036] (14)

[0037] In formula (9) to formula (14), 、 Node The maximum value of the charging power and discharging power of the energy storage device ESS at the location; and Node The energy storage device ESS at the location is at time Charging power and discharging power; For nodes When the energy storage device ESS is charging, the auxiliary variable set at the position =1, when discharging, let =0; 、 、 Node The minimum, maximum, and initial values of the state of charge of the energy storage device ESS at the location; 、 Node The total capacity of the energy storage equipment ESS at the location and capacity of the moment; For nodes Where The energy storage device ESS connected to the pole The equivalent load at the moment, if the energy storage device ESS is not connected to the node Where Extreme time, =0; The polarity of the port connected to the energy storage device ESS is Auxiliary variables of the line, if the polarity of the energy storage device ESS connection port is When the line =1, otherwise, let =0;

[0038] S1-4: Use equations (15) and (16) to construct the port polarity: The mathematical model of the transmission power of the single-pole power flow controller PFC is:

[0039] (15)

[0040] In formula (15), Indicates the port polarity is The turns ratio of the single-pole power flow controller PFC; Indicates the port polarity is Compared with the equivalent shift of the single-pole power flow controller PFC, is the switching frequency of the unipolar power flow controller PFC; is the equivalent inductance value of the single-pole power flow controller PFC; 、 The port polarity is The single-pole power flow controller PFC connects the nodes on both sides ,node The interelectrode voltage value; is the equivalent inductance value of the single-pole power flow controller PFC;

[0041] Using formula (16), the maximum transmission power of the single-pole power flow controller PFC under the shift control is obtained as follows: :

[0042] (16)

[0043] In formula (16), is the turns ratio of the single-pole power flow controller PFC; 、 The nodes on both sides connected by the single-pole power flow controller PFC ,node The positive terminal voltage value.

[0044] Furthermore, in S2, equations (17) to (20) are used to construct a multi-voltage level distribution network power flow model containing a DC transformer DCT;

[0045] (17)

[0046] (18)

[0047] (19)

[0048] (20)

[0049] In formula (17) to formula (20), It is a collection of lines without DC transformers in a multi-voltage bipolar DC distribution network; It is a collection of lines containing DC transformers in a multi-voltage bipolar DC distribution network; Indicates the port polarity is No. DC transformer DCT m The input side is The transmission power of the connected line at any moment; Indicates the port polarity is No. DC transformer DCT m The output side of The transmission power of the connected line at any moment; For voltage level Download slave node Flow Node Between lines Where Extreme Transmission power at the moment; For voltage level Down Polar Line resistance; For voltage level Downline Where Extreme The current flowing at any moment; For voltage level Next node Where Extreme Active power injected at all times; For voltage level Download slave node Flow Node Lines between Where Extreme Transmission power at the moment; For voltage level Next node Where Extreme Voltage at the moment; For voltage level Next node Where Extreme Voltage at the moment; For voltage level Next node Where The distributed power generation DG connected to the pole Active power output at all times; For voltage level Next node Where The pole-connected energy storage system ESS Active power charged at all times; For voltage level Next node Where Extremely connected electric vehicles (EVs) Active power charged at all times; For voltage level Next node Where Active power consumed by the pole-connected load L; ; Indicates the positive electrode, Indicates the negative electrode, Indicates the center line.

[0050] Furthermore, S3 includes the following steps:

[0051] S3-1 Use equations (21) and (22) to establish the objective function of the comprehensive voltage regulation optimization model of multi-voltage level bipolar DC distribution network :

[0052] (twenty one)

[0053] (twenty two)

[0054] In formula (21)-formula (22), The losses generated by the operation of multi-voltage bipolar DC distribution networks are Indicates the penalty caused by voltage exceeding the limit in multi-voltage level bipolar DC distribution network. and They are the unit operating loss coefficient of the multi-voltage level bipolar DC distribution network and the unit load failure coefficient caused by voltage exceeding the limit; is the total number of optimization time periods; Indicates voltage level Next node Where Extreme The penalty caused by the voltage exceeding the limit at the moment, Indicates the voltage level of the bipolar DC distribution system Next node Where The load L connected to the pole is Active power consumed at all times; Indicates voltage level Next node Where The balance coefficient of the pole; For voltage level Next node Where Extreme The over-limit penalty coefficient at the moment, when the voltage level Next node Where The pole voltage value is in the optimized range Within the time, ; When the voltage level Next node Where The extreme voltage value is in the safe range Outside, , Indicates voltage level The minimum value of the lower voltage optimization interval, Indicates voltage level The maximum value of the lower voltage optimization interval, Indicates voltage level The minimum value of the safe voltage allowed by the lower line voltage, Indicates voltage level The maximum value of the safe voltage allowed by the lower line voltage, and:

[0055] (twenty three)

[0056] S3-2: Use equations (24) and (25) to construct basic safety constraints:

[0057] (twenty four)

[0058] (25)

[0059] In formula (24)-formula (25), For multi-voltage level bipolar DC distribution network The voltage of the reference node ref connected to the pole, and Voltage levels The multi-voltage level bipolar DC distribution network is located in The upper and lower voltage limits of the nodes connected to the poles; and Voltage levels The multi-voltage level bipolar DC distribution network is located in Pole-connected lines The upper and lower current limits; For multi-voltage level bipolar DC distribution network The reference standard voltage of the initial node st of the pole connection, For multi-voltage level bipolar DC distribution network The voltage of the initial node st where the poles are connected;

[0060] S3-3: Use equation (26) to construct the inter-pole unbalance voltage constraint:

[0061] (26)

[0062] In formula (26), and For voltage level Next node The positive and negative voltages at is the maximum value of voltage unbalance; Voltage level Next node The degree of voltage imbalance between electrodes at ;

[0063] S3-4: Equations (17) to (20), (24) to (26), (1) to (5), (6) to (8), and (9) to (16) are used as the comprehensive voltage regulation optimization model for multi-voltage level bipolar DC distribution networks.

[0064] Furthermore, S4 includes the following steps:

[0065] S4-1: Linearization of square terms:

[0066] Current variables and voltage variables After replacing the square terms of current and voltage in equations (17) to (18), we can obtain equations (27) to (28):

[0067] (27)

[0068] (28)

[0069] In formula (27)-formula (28): For voltage level Downline Where Extreme The square of the current flowing at any moment; For voltage level Next node Where Extreme The square of the voltage at that moment; For voltage level Next node Where Extreme The square of the voltage at that moment;

[0070] The relationship between node voltage and inter-electrode voltage is constructed using formula (29):

[0071] (29)

[0072] In formula (29), Representation node The voltage at the positive terminal, Representation node The voltage at the negative terminal, Representation node The voltage at the bipolar port, Representation node At positive voltage, Representation node At negative voltage, Representation node The neutral voltage;

[0073] Convert equation (5) and equation (7) into equation (30)-(31);

[0074] (30)

[0075] (31)

[0076] In formula (30)-formula (31), The port polarity is The square of the voltage at the high-voltage side port of the DC transformer DCT; The port polarity is The square of the voltage at the low-voltage side port of the DC transformer DCT; Indicates voltage level Multi-voltage level bipolar DC distribution network The square of the voltage at that moment, Indicates voltage level Multi-voltage level bipolar DC distribution network The square of the voltage at that moment;

[0077] The unbalanced voltage constraint of equation (26) is transformed into equation (34):

[0078] (32)

[0079] In formula (30), Representation node The square of the positive voltage; Representation node The square of the neutral voltage at ; Representation node The square of the negative voltage; Representation node Auxiliary variable at positive pole, Representation node Auxiliary variable at negative pole, Representation node Auxiliary variables at the bipolar position, with:

[0080] (33)

[0081] S4-2: Linearization of the objective function:

[0082] Assumptions , then Linearized into equations (34)-(36):

[0083] (34)

[0084] (35)

[0085] (36)

[0086] In formula (34) to formula (36), For voltage level Next node Where Extreme The degree to which the actual voltage at any moment deviates from the voltage optimization range;

[0087] S4-3: Linearize the flexible device using the large M method and obtain (37):

[0088] (37)

[0089] In formula (37), M is a positive number; The energy storage system ESS is located Extreme The state variables accessed at the moment =1, the energy storage system ESS is located Extreme Power of the moment Constrained to ,when =0, the energy storage system ESS is located Extreme Power at all times Constrained to ; Nodes without ESS Where The energy storage device ESS connected to the pole Charging power at the moment, Nodes connected to energy storage devices (ESS) Where The energy storage device ESS connected to the pole Charging power at the moment; and Node Where The energy storage device ESS connected to the pole Charging power and discharging power at each moment;

[0090] S4-4: Relaxation of bilinear terms, including:

[0091] Introducing the port polarity in formula (1) is Node Premises connected to load Auxiliary variables , and have , we get formula (38):

[0092] (38)

[0093] In formula (38), Indicates the port polarity is Node Premises connected to load Power; Indicates the port polarity is Node The coupling coefficient at ; Indicates the positive line node after decoupling Premises connected to load Power; Indicates the negative line node after decoupling Premises connected to load Power, Indicates the center line node after decoupling Premises connected to load Power, Representation node Auxiliary variable for positive power decoupling, Representation node Auxiliary variable for negative power decoupling, Representation node Auxiliary variables for bipolar power decoupling at

[0094] S4-5: Second-order cone relaxation:

[0095] Using the second-order cone relaxation method to relax Equation (19), we get Equation (39):

[0096] (39)

[0097] In formula (39), represents the two-norm;

[0098] Converting Equation (33) into the standard second-order cone form yields Equation (40):

[0099] (40)

[0100] S4-6: Relaxation of hyperbolic terms, including:

[0101] The method of combining second-order cone relaxation and approximation is used to transform the 、 、 The relaxation is equation (41)-equation (42):

[0102] (41)

[0103] (42)

[0104] In formula (41)-formula (42), and They represent the maximum and minimum values of the positive coefficient under voltage level g respectively; and They represent the maximum and minimum values of the neutral coefficient under voltage level g respectively; and They represent the maximum and minimum values of the negative pole coefficient under voltage level g, Representation node The auxiliary variable introduced by the relaxation of the positive hyperbolic term at Representation node The auxiliary variable introduced by the negative hyperbolic relaxation term is Representation node Auxiliary variables introduced by the bipolar hyperbolic relaxation at .

[0105] The electronic device of the present invention includes a memory and a processor, and is characterized in that the memory is used to store a program that supports the processor to execute the multi-dimensional and multi-resource integrated voltage control optimization method, and the processor is configured to execute the program stored in the memory.

[0106] The present invention provides a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium. The computer program is characterized in that when the computer program is executed by a processor, the steps of the multi-dimensional and multi-resource integrated voltage control optimization method are executed.

[0107] Compared with the prior art, the present invention has the following beneficial effects:

[0108] 1. This invention achieves comprehensive management of multi-target voltage issues. Existing technologies typically focus on single voltage issues, such as inter-electrode voltage imbalance or node voltage over-limit, but lack the ability to comprehensively manage multiple voltage issues. Through global modeling and coordinated multi-resource control, this strategy simultaneously addresses inter-electrode voltage imbalance, voltage fluctuation, and voltage over-limit, significantly improving the system's voltage quality and stability.

[0109] 2. This invention adapts to the complexity of multi-voltage systems. This strategy addresses the unique characteristics of multi-voltage bipolar DC distribution networks and constructs an optimal power flow model based on power injection. This effectively addresses the coupling issues between subsystems at different voltage levels, optimizes voltage and power distribution, and ensures coordinated operation across all voltage levels. Compared to traditional technologies, this technology better adapts to the complex characteristics of multi-voltage systems.

[0110] 3. This invention enhances dynamic control capabilities. The strategy of this invention combines real-time optimization technology to flexibly adjust the control parameters of the energy storage system, power flow controller, and DC transformer based on the dynamic changes in distributed photovoltaic power generation and load fluctuations. This significantly improves the adaptability and flexibility of the system in high-penetration scenarios. Existing technologies have limited control capabilities in dynamic scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0111] Figure 1 This is a structural diagram of a three-voltage-level bipolar DC power distribution test system;

[0112] Figure 2 It is the load consumption and photovoltaic output diagram of positive and negative electrodes under different voltage levels;

[0113] Figure 3This is a diagram of the positive and negative voltage fluctuations under three cases;

[0114] Figure 4 This is a comparison of the positive and negative voltage distribution ranges under three cases;

[0115] Figure 5 This is a comparison chart of inter-electrode voltage imbalance under three cases;

[0116] Figure 6 This is an analysis diagram of the impact of photovoltaic loading on system voltage quality;

[0117] Figure 7 It is a flow chart of a multi-dimensional and multi-resource integrated voltage control optimization method for a multi-voltage-level bipolar DC distribution network. DETAILED DESCRIPTION

[0118] The present invention will be further described below with reference to the accompanying drawings.

[0119] Reference Figures 1 to 6 A multi-dimensional and multi-resource integrated voltage control optimization method for multi-voltage level bipolar DC distribution network is established. Specifically, the implementation flow chart is as follows Figure 7 As shown, the method includes the following steps:

[0120] S1: Establish control models for bipolar DC transformer (DCT), electric vehicle (EV), energy storage device (ESS), and unipolar power flow controller (PFC);

[0121] S1-1: Establish a control model for a bipolar DC transformer DCT:

[0122] S1-1-1: Use equation (1) to construct a model of the relationship between the output power and the voltage on both sides of any single-pole DC transformer DCT:

[0123] (1)

[0124] In formula (1), Connect the polarity of different terminals of the unipolar DC transformer DCT, and ; p represents the positive port, n represents the negative port, b represents the bipolar port, The port polarity is The turns ratio of the unipolar DC transformer DCT; Indicates the port polarity is Compared with the equivalent shift of the unipolar DC transformer DCT, is the switching frequency of the unipolar DC transformer DCT; is the equivalent inductance of the unipolar DC transformer DCT; The port polarity is The terminal voltage of the unipolar DC transformer DCT on the high voltage side; The terminal polarity of the unipolar DC transformer DCT The port voltage on the low voltage side; The port polarity is The unipolar DC transformer DCT Output power at the moment; The port polarity is The deviation coefficient is caused by the inconsistency between the actual voltage transformation ratio of the unipolar DC transformer DCT and the turns ratio of the high-frequency isolation transformer.

[0125] S1-1-2: Use formula (2) to construct the port polarity The power transfer relationship between the input and output sides of the unipolar DC transformer DCT is:

[0126] (2)

[0127] In formula (2), The port polarity is The unipolar DC transformer DCT The input power at the moment, The port polarity is The intermediate circuit of the unipolar DC transformer DCT is The power loss generated at any time.

[0128] S1-1-3: Use equations (3) to (5) to construct mathematical models of the unipolar DC transformer DCT in constant ratio control mode, constant power control mode, and constant voltage control mode:

[0129] (3)

[0130] (4)

[0131] (5)

[0132] In formula (3) to formula (5), In the constant ratio control mode, the port polarity is The turns ratio of the unipolar DC transformer DCT; Indicates that the port polarity is in constant power control mode. The unipolar DC transformer DCT Output power at the moment; Indicates the voltage level of the unipolar DC transformer DCT port in constant voltage control mode. Down The voltage at the moment, Indicates the voltage level of the unipolar DC transformer DCT port in constant voltage control mode. Down Voltage at the moment; , Indicates high pressure, Indicates medium pressure, Indicates low pressure.

[0133] S1-2: Use equations (6) to (8) to establish a charging and discharging model for electric vehicles (EV):

[0134] (6)

[0135] (7)

[0136] (8)

[0137] In formula (6) to formula (8), and They are Time Node The charging power and discharging power of the electric vehicle EV at the location; for Time Node The equivalent power of electric vehicle (EV) charging at the location; Represents nodes respectively The connection time and disconnection time of the electric vehicle EV and the charging equipment at the location; and are the exchange efficiencies of charging power and discharging power, respectively; for Time Node The state of charge of the electric vehicle EV at the location, for Time Node The state of charge of the electric vehicle EV at the location; For nodes Battery capacity of the electric vehicle EV at the location; and Node The maximum charging power and maximum discharging power of the electric vehicle EV at the location; and is a node The lower and upper bounds of the state of charge of the electric vehicle EV at the location; and Node The initial state of charge and the desired state of charge of the electric vehicle EV at the location; for Time Node The charging and discharging status of the electric vehicle EV at the location =0 means Time Node The electric car at position is in discharge state. =1 means Time Node The electric vehicle EV at the location is in charging state; represents the set of all nodes, Indicates the time period when the electric vehicle EV is connected to the charging station. Indicates a time interval.

[0138] S1-3: Use equations (9) to (14) to establish a mathematical model of the energy storage device ESS:

[0139] (9)

[0140] (10)

[0141] (11)

[0142] (12)

[0143] (13)

[0144] (14)

[0145] In formula (9) to formula (14), 、 Node The maximum value of the charging power and discharging power of the energy storage device ESS at the location; and Node The energy storage device ESS at the location is at time Charging power and discharging power; For nodes When the energy storage device ESS is charging, the auxiliary variable set at the position =1, when discharging, let =0; 、 、 Node The minimum, maximum, and initial values of the state of charge of the energy storage device ESS at the location; 、 Node The total capacity of the energy storage equipment ESS at the location and capacity of the moment; For nodes Where The energy storage device ESS connected to the pole The equivalent load at the moment, if the energy storage device ESS is not connected to the node Where Extreme time, =0; The polarity of the port connected to the energy storage device ESS is Auxiliary variables of the line, if the polarity of the energy storage device ESS connection port is When the line =1, otherwise, let =0;

[0146] S1-4: Use equations (15) and (16) to construct the port polarity: The mathematical model of the transmission power of the single-pole power flow controller PFC is:

[0147] (15)

[0148] In formula (15), Indicates the port polarity is The turns ratio of the single-pole power flow controller PFC; Indicates the port polarity is Compared with the equivalent shift of the single-pole power flow controller PFC, is the switching frequency of the unipolar power flow controller PFC; is the equivalent inductance value of the single-pole power flow controller PFC; 、 The port polarity is The single-pole power flow controller PFC connects the nodes on both sides 、 The interelectrode voltage value; is the equivalent inductance value of the single-pole power flow controller PFC.

[0149] Using formula (16), the maximum transmission power of the single-pole power flow controller PFC under the shift control is obtained as follows: :

[0150] (16)

[0151] In formula (16), is the turns ratio of the single-pole power flow controller PFC; 、 The nodes on both sides connected by the single-pole power flow controller PFC 、 The positive terminal voltage value.

[0152] S2: To achieve comprehensive control of multiple voltage levels, DC transformers are used to interconnect subsystems of different voltage levels to achieve the flow of power between different subsystems. The bipolar DC distribution network consists of three conductors. After decoupling, they are positive, neutral, and negative, represented by the symbols +, o, and -, respectively. The power, node voltage, and current between different poles no longer have a coupling relationship with other poles. The power flow model of the multi-voltage distribution network containing DC transformers DCT is constructed using Equations (17) to (20):

[0153] (17)

[0154] (18)

[0155] (19)

[0156] (20)

[0157] In formula (17) to formula (20), It is a collection of lines without DC transformers in a multi-voltage bipolar DC distribution network; It is a collection of lines containing DC transformers in a multi-voltage bipolar DC distribution network; Indicates the port polarity is No. DC transformer DCT m The input side is The transmission power of the connected line at any moment; Indicates the port polarity is No. DC transformer DCT m The output side of The transmission power of the connected line at any moment; For voltage level Download slave node Flow Node Between lines Where Extreme Transmission power at the moment; For voltage level Down Polar Line resistance; For voltage level Downline Where Extreme The current flowing at any moment; For voltage level Next node Where Extreme Active power injected at all times; For voltage level Download slave node Flow Node Lines between Where Extreme Transmission power at the moment; For voltage level Next node Where Extreme Voltage at the moment; For voltage level Next node Where Extreme Voltage at the moment; For voltage level Next node Where The distributed power generation DG connected to the pole Active power output at all times; For voltage level Next node Where The pole-connected energy storage system ESS Active power charged at all times; For voltage level Next node Where Extremely connected electric vehicles (EVs) Active power charged at all times; For voltage level Next node Where Active power consumed by the pole-connected load L; ; Indicates the positive line, Indicates the negative line, Indicates the neutral line.

[0158] S3: Establish a comprehensive voltage regulation optimization model for a multi-voltage level bipolar DC distribution network:

[0159] S3-1 Use equations (21) and (22) to establish the objective function of the comprehensive voltage regulation optimization model of multi-voltage level bipolar DC distribution network :

[0160] (twenty one)

[0161] (twenty two)

[0162] In formula (21)-formula (22), The losses generated by the operation of multi-voltage bipolar DC distribution networks are Indicates the penalty caused by voltage exceeding the limit in multi-voltage level bipolar DC distribution network. and They are the unit operating loss coefficient of the multi-voltage level bipolar DC distribution network and the unit load failure coefficient caused by voltage exceeding the limit; is the total number of optimization time periods; Indicates voltage level Next node Where Extreme The penalty caused by the voltage exceeding the limit at the moment, Indicates the voltage level of the bipolar DC distribution system Next node Where The load L connected to the pole is Active power consumed at all times; Indicates voltage level Next node Where The balance coefficient of the pole; For voltage level Next node Where Extreme The over-limit penalty coefficient at the moment, when the voltage level Next node Where The pole voltage value is in the optimized range Within the time, ; When the voltage level Next node Where The extreme voltage value is in the safe range Outside, , Indicates voltage level The minimum value of the lower voltage optimization interval, Indicates voltage level The maximum value of the lower voltage optimization interval, Indicates voltage level The minimum value of the safe voltage allowed by the lower line voltage, Indicates voltage level The maximum value of the safe voltage allowed by the lower line voltage, and:

[0163] (twenty three)

[0164] S3-2: Use equations (24) and (25) to construct basic safety constraints:

[0165] (twenty four)

[0166] (25)

[0167] In formula (24)-formula (25), For multi-voltage level bipolar DC distribution network The voltage of the reference node ref connected to the pole, and Voltage levels The multi-voltage level bipolar DC distribution network is located in The upper and lower voltage limits of the nodes connected to the poles; and Voltage levels The multi-voltage level bipolar DC distribution network is located in Pole-connected lines The upper and lower current limits; For multi-voltage level bipolar DC distribution network The initial node st of the pole connection is the reference standard voltage, For multi-voltage level bipolar DC distribution network The voltage of the initial node st connected to the pole.

[0168] S3-3: Use equation (26) to construct the inter-pole unbalance voltage constraint:

[0169] (26)

[0170] In formula (26), and For voltage level Next node The positive and negative voltages at is the maximum value of voltage unbalance; Voltage level Next node The degree of voltage imbalance between electrodes at ;

[0171] S3-4: Equations (17) to (20), (24) to (26), (1) to (5), (6) to (8), and (9) to (16) are used as the comprehensive voltage regulation optimization model for multi-voltage level bipolar DC distribution networks.

[0172] S4: transforming the comprehensive voltage regulation optimization model of the multi-voltage level bipolar DC distribution network to obtain a transformed comprehensive voltage regulation optimization model;

[0173] S4-1: Linearization of square terms:

[0174] Current variables and voltage variables After replacing the square terms of current and voltage in equations (17) to (18), we can obtain equations (27) to (28):

[0175] (27)

[0176] (28)

[0177] In formula (27)-formula (28): For voltage level Downline Where Extreme The square of the current flowing at any moment; For voltage level Next node Where Extreme The square of the voltage at that moment; For voltage level Next node Where Extreme The square of the voltage at that moment.

[0178] The relationship between node voltage and inter-electrode voltage is constructed using formula (29):

[0179] (29)

[0180] In formula (29), Representation node The voltage at the positive terminal, Representation node The voltage at the negative terminal, Representation node The voltage at the bipolar port, Representation node At positive voltage, Representation node At negative voltage, Representation node At neutral voltage.

[0181] Convert equation (5) and equation (7) into equation (30)-(31);

[0182] (30)

[0183] (31)

[0184] In formula (30)-formula (31), The port polarity is The square of the voltage at the high-voltage side port of the DC transformer DCT; The port polarity is The square of the voltage at the low-voltage side port of the DC transformer DCT; Indicates voltage level Multi-voltage level bipolar DC distribution network The square of the voltage at that moment, Indicates voltage level Multi-voltage level bipolar DC distribution network The square of the voltage at that moment.

[0185] The unbalanced voltage constraint of equation (26) is transformed into equation (34):

[0186] (32)

[0187] In formula (30), Representation node The square of the positive voltage; Representation node The square of the neutral voltage at ; Representation node The square of the negative voltage; Representation node Auxiliary variable at positive pole, Representation node Auxiliary variable at negative pole, Representation node Auxiliary variables at the bipolar position, with:

[0188] (33)

[0189] S4-2: Linearization of the objective function:

[0190] Assumptions , then Linearized into equations (34)-(36):

[0191] (34)

[0192] (35)

[0193] (36)

[0194] In formula (34) to formula (36), For voltage level Next node Where Extreme The degree to which the actual voltage at a given moment deviates from the voltage optimization range.

[0195] S4-3: Linearize the flexible device using the large M method and obtain (37):

[0196] (37)

[0197] In formula (37), M is a positive number; The energy storage system ESS is located Extreme The state variables accessed at the moment =1, the energy storage system ESS is located Extreme Power of the moment Constrained to ,when =0, the energy storage system ESS is located Extreme Power at all times Constrained to ; Nodes without ESS Where The energy storage device ESS connected to the pole Charging power at the moment, Nodes connected to energy storage devices (ESS) Where The energy storage device ESS connected to the pole Charging power at the moment; and Node Where The energy storage device ESS connected to the pole The charging power and discharging power at each moment.

[0198] S4-4: Relaxation of bilinear terms, including:

[0199] Introducing the port polarity in formula (1) is Node Premises connected to load Auxiliary variables , and have , we get formula (38):

[0200] (38)

[0201] In formula (38), Indicates the port polarity is Node Premises connected to load Power; Indicates the port polarity is Node The coupling coefficient at ; Indicates the positive line node after decoupling Premises connected to load Power; Indicates the negative line node after decoupling Premises connected to load Power, Indicates the center line node after decoupling Premises connected to load Power, Representation node Auxiliary variable for positive power decoupling, Representation node Auxiliary variable for negative power decoupling, Representation node Auxiliary variable for bipolar power decoupling at .

[0202] S4-5: Second-order cone relaxation:

[0203] Using the second-order cone relaxation method to relax Equation (19), we get Equation (39):

[0204] (39)

[0205] In formula (39), represents the two-norm;

[0206] Converting Equation (33) into the standard second-order cone form yields Equation (40):

[0207] (40)

[0208] S4-6: Relaxation of hyperbolic terms, including:

[0209] The method of combining second-order cone relaxation and approximation is used to transform the 、 、 The relaxation is equation (41)-equation (42):

[0210] (41)

[0211] (42)

[0212] In formula (41)-formula (42), and They represent the maximum and minimum values of the positive coefficient under voltage level g respectively; and They represent the maximum and minimum values of the neutral coefficient under voltage level g respectively; and They represent the maximum and minimum values of the negative pole coefficient under voltage level g, Representation node The auxiliary variable introduced by the relaxation of the positive hyperbolic term at Representation node The auxiliary variable introduced by the negative hyperbolic relaxation term is Representation node Auxiliary variables introduced by the bipolar hyperbolic relaxation at .

[0213] S5: Use the solver to solve the converted integrated voltage control optimization model to obtain the integrated voltage control optimization strategy of the bipolar DC distribution system, including: the selection of the control mode of the bipolar DC transformer DCT and the power transmission Control strategies for electric vehicle charging and discharging power and Control strategy, energy storage device charging and discharging power and The control strategy and control parameters of the power flow controller Control strategy and transmission power control strategy.

[0214] In this embodiment, an electronic device includes a memory and a processor, wherein the memory is used to store a program that supports the processor to execute the above method, and the processor is configured to execute the program stored in the memory.

[0215] In this embodiment, a computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method are executed.

[0216] To help those skilled in the art better understand the present invention, the example analysis includes the following components:

[0217] 1) Network model and parameter setting: In order to verify the effectiveness of the proposed method, the present invention Figure 1The three-voltage level bipolar DC distribution system shown in the figure is simulated, tested and numerically analyzed. In the system, the reference voltage on the high-voltage side is ±10kV, which is connected to the data center through a dedicated transformer. A large-capacity DC photovoltaic power supply is built inside the center. The computing equipment is generally powered by 240V DC, showing the characteristics of high-power load at a single location throughout the entire period. During the planning process, problems caused by inter-pole imbalance will be avoided as much as possible. The reference voltage on the medium-voltage side is ±375V, which supplies power to higher-power equipment, including electric vehicles, energy storage, distributed photovoltaics, and household high-power loads. The reference voltage on the low-voltage side is ±48V, which is usually used to supply constant-power loads such as 5G base stations. It has high requirements for voltage levels and hardly changes with grid voltage changes. It is only related to load usage; the constant-power loads at nodes 15 to 18 are set to 2kW, 1kW, and 2kW, respectively. The sequential photovoltaic output and load consumption on ports of different polarity at high voltage levels, low voltage levels and in data centers are shown as follows. Figure 2 The four photovoltaic generators are connected to the bipolar DC distribution network, and their basic installation parameters are shown in Table 1:

[0218] Table 1 PV installation location and parameters

[0219]

[0220] Nodes 8 and 14 each have a DC charging station. Node 8 has four charging piles and is located in the work area parking lot. During work hours, multiple vehicles take turns charging, divided into two groups: one group charges upon arriving at the office in the morning and finishes during lunch break, and the other group charges upon arriving in the afternoon and leaves at the end of the evening. Node 14 has eight charging piles and is located in a residential parking lot. Its charging characteristics begin upon arriving home in the evening and end before work the next day. During this time, electric vehicles can freely charge and discharge as energy storage. The desired SOC for both electric vehicles is 1.0. Table 2 shows some parameters for the energy storage device and electric vehicle. The energy storage installed at node 32 is a switchable type with positive and negative electrodes.

[0221] Table 2 Energy storage and electric vehicle parameters

[0222]

[0223] The power flow controller adopts the DC / DC converter type. The parameter settings of the power flow controller and DC transformer are shown in Table 3. Other parameters in the simulation are shown in Table 4.

[0224] Table 3 Parameters of power flow controller and DC transformer

[0225]

[0226] Table 4 Other parameters in simulation

[0227]

[0228] In order to better verify the advantages of the proposed method in voltage regulation and operation optimization, we further compared three typical cases:

[0229] Case 1: Multi-voltage bipolar DC distribution network without optimization measures;

[0230] Case 2: Based on Case 1, the objective function of the traditional solution is adopted, a DC power flow controller is added to the model, and comprehensive voltage control is not considered for multiple voltage levels and multiple voltage issues;

[0231] Case 3: The comprehensive voltage regulation model proposed in this invention.

[0232] 2) Analysis of the overall voltage situation: Figure 3 From left to right, the positive and negative node voltages for three typical cases are shown. The figure clearly shows that without optimization measures, the positive system experienced a significant power shortage due to the high positive load and low power supply. Voltage levels were generally low, and many nodes experienced downward voltage limits. The opposite was true for the negative system. Power redundancy caused some nodes to exceed the limits, leading to severe voltage imbalance between the positive and negative poles. While Option 2 optimized some nodes, the single objective function and optimization approach did not fully address inter-pole imbalance and voltage limits. Figure 4 From left to right, the operating ranges of the positive and negative electrode voltages under different schemes are shown. Figure 4 It can be seen that the optimization measures of the present invention can maintain the voltage within the safe operating range of [0.97, 1.03]. The operating range of the voltage has been effectively improved. Compared with the traditional solution, it can achieve comprehensive optimization of the entire voltage system with fewer optimization resources. By interconnecting the low-voltage side with the high-voltage side, the redundant power of the high-voltage side is used to improve the power shortage of the line between the low-voltage side node 8 and the node 15, which significantly reduces the voltage limit of the line. The inter-pole switchable energy storage transfers the load of the positive pole to the negative pole, achieving balanced operation of the positive and negative poles, thereby Figure 3-4 It can be clearly seen that in Scheme 3, the voltage at nodes 30-33 has been optimized from extreme imbalance and partial over-limit to partial imbalance and voltage within a safe allowable range.

[0233] 3) System Operation Optimization Comparison: Table 5 shows the system losses and load failure rates for the three typical schemes. While Scheme 2 improves both system losses and voltage overshoot rates, the voltage overshoot rate and load failure rates remain high. This is due to the single optimization objective function. Under the constraints of unbalanced voltage, in order to achieve balance between the positive and negative voltages, Scheme 2 reduces the positive voltage overshoot rate while not significantly improving the negative voltage overshoot rate. While voltage balance improves, it significantly limits the potential for optimizing negative voltage quality.

[0234] Under the optimization measures of this invention, compared to the unoptimized distribution system, system losses were reduced by 20.15%, load failures were reduced by 99.54%, and positive and negative voltage over-limit rates were reduced by 99.23% and 67.89%, respectively. Compared to the traditional optimization scheme, load failures and voltage over-limit rates were significantly improved compared to the second scheme of the traditional optimization strategy, both falling within the safe operating range.

[0235] Table 5 Comparison of system operation optimization data of three solutions

[0236]

[0237] Since the ±48V low-voltage side is a constant power load, its voltage fluctuation is small and there are fewer unbalanced nodes on the low-voltage side. This paper mainly studies the voltage imbalance on the high-voltage side. Figure 5 The voltage imbalance of two typical nodes, 12 nodes and 32 nodes, under three cases is shown. Option 2 can reduce voltage imbalance to a certain extent, but it cannot achieve overall optimization of the entire system. Taking 32 nodes as an example, the voltage imbalance of Option 2 is not effectively improved compared to the unoptimized case. Combined with the average voltage imbalance of the three options in the table, the optimization strategy of the present invention can achieve overall comprehensive optimization, and has significantly enhanced the optimization of voltage imbalance compared to Option 2. Compared with Option 1, it is optimized by 56.49%, and compared with the traditional optimization strategy, Option 2 is optimized by 43.00%.

[0238] 4) Comparative analysis of system photovoltaic carrying capacity: This paper tests the impact of different penetration rates of photovoltaic access on the voltage regulation performance of the proposed method by changing the access capacity of distributed photovoltaics. To this end, the following two typical scenarios are selected for comparative analysis. Scenario 1: Flow calculation without integrated voltage regulation in a multi-voltage level bipolar DC distribution network; Scenario 2: The photovoltaic access capacity of the integrated voltage regulation model proposed in the present invention is increased from 1.0 times the standard capacity in intervals of 0.05 times to 1.8 times. Figure 6The results of inter-pole voltage imbalance and voltage over-limit rate under different photovoltaic access capacities are shown. . It can be seen from the results that the proposed scheme can significantly improve the system voltage quality and the carrying capacity of distributed photovoltaics when a large number of distributed photovoltaics are connected and cause voltage problems. Compared with the traditional model, the model proposed in this invention improves the photovoltaic access capacity by 15.79% under the premise that the system maintains stable voltage operation. In addition, the model effectively controls the voltage imbalance in the scenario of high photovoltaic access ratio, maintaining it at around 0.5%, which is more than 30.23% lower than that without regulation, significantly enhancing the system's ability to adapt to high photovoltaic penetration scenarios.

[0239] In summary, the multi-resource collaborative control method proposed in this multi-dimensional, multi-resource integrated voltage control optimization method for a multi-voltage-level bipolar DC distribution network enhances the flexible deployment of heterogeneous resources and demonstrates significant advantages in improving the voltage performance and power flow distribution capabilities of bipolar DC distribution systems. Compared with traditional optimization methods, this strategy significantly reduces overall system losses in multi-voltage-level scenarios, effectively controls voltage imbalance and over-limit issues between the positive and negative poles, and improves system voltage stability. Furthermore, the proposed model significantly improves the accessibility of distributed photovoltaics and enhances the system's adaptability to high-penetration photovoltaic access.

[0240] In the description of this specification, the schematic description of the present invention does not necessarily refer to the same embodiment or example. Those skilled in the art may combine and combine the different embodiments or examples described in this specification. In addition, the additional content described in the embodiments of this specification is merely an enumeration of the implementation forms of the inventive concept. The scope of protection of the present invention should not be considered limited to the specific forms described in the implementation cases. The scope of protection of the present invention also includes equivalent technical means that can be conceived by those skilled in the art based on the inventive concept.

[0241] In the description of this specification, the schematic description of the present invention does not necessarily refer to the same embodiment or example. Those skilled in the art may combine and combine the different embodiments or examples described in this specification. In addition, the additional content described in the embodiments of this specification is merely an enumeration of the implementation forms of the inventive concept. The scope of protection of the present invention should not be considered limited to the specific forms described in the implementation cases. The scope of protection of the present invention also includes equivalent technical means that can be conceived by those skilled in the art based on the inventive concept.

Claims

1. A multi-dimensional and multi-resource integrated voltage control optimization method for a bipolar DC distribution network under multiple voltage levels, characterized in that: The following steps are involved: S1: Establish control models for bipolar DC transformer (DCT), electric vehicle (EV), energy storage device (ESS), and unipolar power flow controller (PFC); S2: Construct a multi-voltage distribution network power flow model including DC transformers (DCTs); S3: Establish a comprehensive voltage regulation optimization model for multi-voltage level bipolar DC distribution networks; S4: transforming the comprehensive voltage regulation optimization model of the multi-voltage level bipolar DC distribution network to obtain a transformed comprehensive voltage regulation optimization model; S5: Use the solver to solve the converted comprehensive voltage control optimization model to obtain the comprehensive voltage control optimization strategy of the bipolar DC distribution system, including: the control strategy and power transmission strategy of the bipolar DC transformer DCT, the charging and discharging strategy of the electric vehicle, the charging and discharging strategy of the energy storage device, and the control strategy and power transmission strategy of the power flow controller.

2. The multi-dimensional and multi-resource integrated voltage control optimization method for a bipolar DC distribution network under multiple voltage levels according to claim 1 is characterized in that: S1 includes the following steps: S1-1: Establish a control model for a bipolar DC transformer DCT: S1-1-1: Use equation (1) to construct a model of the relationship between the output power and the voltage on both sides of any single-pole DC transformer DCT: (1) In formula (1), Connect the polarity of different terminals of the unipolar DC transformer DCT, and ; p represents positive electrode, n represents negative electrode, b represents bipolar, The port polarity is The turns ratio of the unipolar DC transformer DCT; Indicates the port polarity is Compared with the equivalent shift of the unipolar DC transformer DCT, is the switching frequency of the unipolar DC transformer DCT; is the equivalent inductance of the unipolar DC transformer DCT; The port polarity is The terminal voltage of the unipolar DC transformer DCT on the high voltage side; The terminal polarity of the unipolar DC transformer DCT The port voltage on the low voltage side; The port polarity is The unipolar DC transformer DCT Output power at the moment; The port polarity is The deviation coefficient is caused by the inconsistency between the actual voltage ratio of the unipolar DC transformer DCT and the turns ratio of the high-frequency isolation transformer; S1-1-2: Use formula (2) to construct the port polarity The power transfer relationship between the input and output sides of the unipolar DC transformer DCT is: (2) In formula (2), The port polarity is The unipolar DC transformer DCT The input power at the moment, The port polarity is The intermediate circuit of the unipolar DC transformer DCT is Power loss generated at any moment; S1-1-3: Use equations (3) to (5) to construct mathematical models of the unipolar DC transformer DCT in constant ratio control mode, constant power control mode, and constant voltage control mode: (3) (4) (5) In formula (3) to formula (5), In the constant ratio control mode, the port polarity is The turns ratio of the unipolar DC transformer DCT; Indicates that the port polarity is in constant power control mode. The unipolar DC transformer DCT Output power at the moment; Indicates the voltage level of the unipolar DC transformer DCT port in constant voltage control mode. Down The voltage at the moment, Indicates the voltage level of the unipolar DC transformer DCT port in constant voltage control mode. Down Voltage at the moment; , Indicates high pressure, Indicates medium pressure, Indicates low pressure; S1-2: Use equations (6) to (8) to establish a charging and discharging model for electric vehicles (EV): (6) (7) (8) In formula (6) to formula (8), and They are Time Node The charging power and discharging power of the electric vehicle EV at the location; for Time Node The equivalent power of electric vehicle (EV) charging at the location; Represents nodes respectively The connection time and disconnection time of the electric vehicle EV and the charging equipment at the location; and are the exchange efficiencies of charging power and discharging power, respectively; for Time Node The state of charge of the electric vehicle EV at the location, for Time Node The state of charge of the electric vehicle EV at the location; For nodes Battery capacity of the electric vehicle EV at the location; and Node The maximum charging power and maximum discharging power of the electric vehicle EV at the location; and is a node The lower and upper bounds of the state of charge of the electric vehicle EV at the location; and Node The initial state of charge and the desired state of charge of the electric vehicle EV at the location; for Time Node The charging and discharging status of the electric vehicle EV at the location =0 means Time Node The electric car at position is in discharge state. =1 means Time Node The electric vehicle EV at the location is in charging state; represents the set of all nodes, Indicates the time period when the electric vehicle EV is connected to the charging station. Indicates a time interval; S1-3: Use equations (9) to (14) to establish a mathematical model of the energy storage device ESS: (9) (10) (11) (12) (13) (14) In formula (9) to formula (14), 、 Node The maximum value of the charging power and discharging power of the energy storage device ESS at the location; and Node The energy storage device ESS at the location is at time Charging power and discharging power; For nodes When the energy storage device ESS is charging, the auxiliary variable set at the position =1, when discharging, let =0; 、 、 Node The minimum, maximum, and initial values of the state of charge of the energy storage device ESS at the location; 、 Node The total capacity of the energy storage equipment ESS at the location and capacity of the moment; For nodes Where The energy storage device ESS connected to the pole The equivalent load at the moment, if the energy storage device ESS is not connected to the node Where Extreme time, =0; The polarity of the port connected to the energy storage device ESS is Auxiliary variables of the line, if the polarity of the energy storage device ESS connection port is When the line =1, otherwise, let =0; S1-4: Use equations (15) and (16) to construct the port polarity: The mathematical model of the transmission power of the single-pole power flow controller PFC is: (15) In formula (15), Indicates the port polarity is The turns ratio of the single-pole power flow controller PFC; Indicates the port polarity is Compared with the equivalent shift of the single-pole power flow controller PFC, is the switching frequency of the unipolar power flow controller PFC; is the equivalent inductance value of the single-pole power flow controller PFC; 、 The port polarity is The single-pole power flow controller PFC connects the nodes on both sides ,node The interelectrode voltage value; is the equivalent inductance value of the single-pole power flow controller PFC; Using formula (16), the maximum transmission power of the single-pole power flow controller PFC under the shift control is obtained as follows: : (16) In formula (16), is the turns ratio of the single-pole power flow controller PFC; 、 The nodes on both sides connected by the single-pole power flow controller PFC ,node The positive terminal voltage value.

3. The multi-dimensional and multi-resource integrated voltage control optimization method for a bipolar DC distribution network under multiple voltage levels according to claim 2 is characterized in that: In S2, equations (17) to (20) are used to construct a multi-voltage distribution network power flow model containing a DC transformer DCT; (17) (18) (19) (20) In formula (17) to formula (20), It is a collection of lines without DC transformers in a multi-voltage bipolar DC distribution network; It is a collection of lines containing DC transformers in a multi-voltage bipolar DC distribution network; Indicates the port polarity is No. DC transformer DCT m The input side is The transmission power of the connected line at any moment; Indicates the port polarity is No. DC transformer DCT m The output side of The transmission power of the connected line at any moment; For voltage level Download slave node Flow Node Between lines Where Extreme Transmission power at the moment; For voltage level Down Polar Line resistance; For voltage level Downline Where Extreme The current flowing at any moment; For voltage level Next node Where Extreme Active power injected at all times; For voltage level Download slave node Flow Node Lines between Where Extreme Transmission power at the moment; For voltage level Next node Where Extreme Voltage at the moment; For voltage level Next node Where Extreme Voltage at the moment; For voltage level Next node Where The distributed power generation DG connected to the pole Active power output at all times; For voltage level Next node Where The pole-connected energy storage system ESS Active power charged at all times; For voltage level Next node Where Extremely connected electric vehicles (EVs) Active power charged at all times; For voltage level Next node Where Active power consumed by the pole-connected load L; ; Indicates the positive electrode, Indicates the negative electrode, Indicates the center line.

4. The multi-dimensional and multi-resource integrated voltage control optimization method for a bipolar DC distribution network under multiple voltage levels according to claim 3 is characterized in that: S3 includes the following steps: S3-1 Use equations (21) and (22) to establish the objective function of the comprehensive voltage regulation optimization model of multi-voltage level bipolar DC distribution network : (21) (22) In formula (21)-formula (22), The losses generated by the operation of multi-voltage bipolar DC distribution networks are Indicates the penalty caused by voltage exceeding the limit in multi-voltage level bipolar DC distribution network. and They are the unit operating loss coefficient of the multi-voltage level bipolar DC distribution network and the unit load failure coefficient caused by voltage exceeding the limit; is the total number of optimization time periods; Indicates voltage level Next node Where Extreme The penalty caused by the voltage exceeding the limit at the moment, Indicates the voltage level of the bipolar DC distribution system Next node Where The load L connected to the pole is Active power consumed at all times; Indicates voltage level Next node Where The balance coefficient of the pole; For voltage level Next node Where Extreme The over-limit penalty coefficient at the moment, when the voltage level Next node Where The pole voltage value is in the optimized range Within the time, ; When the voltage level Next node Where The extreme voltage value is in the safe range Outside, , Indicates voltage level The minimum value of the lower voltage optimization interval, Indicates voltage level The maximum value of the lower voltage optimization interval, Indicates voltage level The minimum value of the safe voltage allowed by the lower line voltage, Indicates voltage level The maximum value of the safe voltage allowed by the lower line voltage, and: (23) S3-2: Use equations (24) and (25) to construct basic safety constraints: (24) (25) In formula (24)-formula (25), For multi-voltage level bipolar DC distribution network The voltage of the reference node ref connected to the pole, and Voltage levels The multi-voltage level bipolar DC distribution network is located in The upper and lower voltage limits of the nodes connected to the poles; and Voltage levels The multi-voltage level bipolar DC distribution network is located in Pole-connected lines The upper and lower current limits; For multi-voltage level bipolar DC distribution network The reference standard voltage of the initial node st of the pole connection, For multi-voltage level bipolar DC distribution network The voltage of the initial node st where the poles are connected; S3-3: Use equation (26) to construct the inter-pole unbalance voltage constraint: (26) In formula (26), and For voltage level Next node The positive and negative voltages at is the maximum value of voltage unbalance; Voltage level Next node The degree of voltage imbalance between electrodes at ; S3-4: Equations (17) to (20), (24) to (26), (1) to (5), (6) to (8), and (9) to (16) are used as the comprehensive voltage regulation optimization model for multi-voltage level bipolar DC distribution networks.

5. The multi-dimensional and multi-resource integrated voltage control optimization method for a bipolar DC distribution network under multiple voltage levels according to claim 4 is characterized in that: S4 includes the following steps: S4-1: Linearization of square terms: Current variables and voltage variables After replacing the square terms of current and voltage in equations (17) to (18), we can obtain equations (27) to (28): (27) (28) In formula (27)-formula (28): For voltage level Downline Where Extreme The square of the current flowing at any moment; For voltage level Next node Where Extreme The square of the voltage at that moment; For voltage level Next node Where Extreme The square of the voltage at that moment; The relationship between node voltage and inter-electrode voltage is constructed using formula (29): (29) In formula (29), Representation node The voltage at the positive terminal, Representation node The voltage at the negative terminal, Representation node The voltage at the bipolar port, Representation node At positive voltage, Representation node At negative voltage, Representation node The neutral voltage; Convert equation (5) and equation (7) into equation (30)-(31); (30) (31) In formula (30)-formula (31), The port polarity is The square of the voltage at the high-voltage side port of the DC transformer DCT; The port polarity is The square of the voltage at the low-voltage side port of the DC transformer DCT; Indicates voltage level Multi-voltage level bipolar DC distribution network The square of the voltage at that moment, Indicates voltage level Multi-voltage level bipolar DC distribution network The square of the voltage at that moment; The unbalanced voltage constraint of equation (26) is transformed into equation (34): (32) In formula (30), Representation node The square of the positive voltage; Representation node The square of the neutral voltage at ; Representation node The square of the negative voltage; Representation node Auxiliary variable at positive pole, Representation node Auxiliary variable at negative pole, Representation node Auxiliary variables at the bipolar position, with: (33) S4-2: Linearization of the objective function: Assumptions , then Linearized into equations (34)-(36): (34) (35) (36) In formula (34) to formula (36), For voltage level Next node Where Extreme The degree to which the actual voltage at any moment deviates from the voltage optimization range; S4-3: Linearize the flexible device using the large M method and obtain (37): (37) In formula (37), M is a positive number; The energy storage system ESS is located Extreme The state variables accessed at the moment =1, the energy storage system ESS is located Extreme Power at all times Constrained to ,when =0, the energy storage system ESS is located Extreme Power at all times Constrained to ; Nodes without ESS Where The energy storage device ESS connected to the pole Charging power at the moment, Nodes connected to energy storage devices (ESS) Where The energy storage device ESS connected to the pole Charging power at the moment; and Node Where The energy storage device ESS connected to the pole Charging power and discharging power at each moment; S4-4: Relaxation of bilinear terms, including: Introducing the port polarity in formula (1) is Node Premises connected to load Auxiliary variables , and have , we get formula (38): (38) In formula (38), Indicates the port polarity is Node Premises connected to load Power; Indicates the port polarity is Node The coupling coefficient at ; Indicates the positive line node after decoupling Premises connected to load Power; Indicates the negative line node after decoupling Premises connected to load Power, Indicates the center line node after decoupling Premises connected to load Power, Representation node Auxiliary variable for positive power decoupling, Representation node Auxiliary variable for negative power decoupling, Representation node Auxiliary variables for bipolar power decoupling at S4-5: Second-order cone relaxation: Using the second-order cone relaxation method to relax Equation (19), we get Equation (39): (39) In formula (39), represents the two-norm; Converting Equation (33) into the standard second-order cone form yields Equation (40): (40) S4-6: Relaxation of hyperbolic terms, including: The method of combining second-order cone relaxation and approximation is used to transform the 、 、 The relaxation is equation (41)-equation (42): (41) (42) In formula (41)-formula (42), and They represent the maximum and minimum values of the positive coefficient under voltage level g respectively; and They represent the maximum and minimum values of the neutral coefficient under voltage level g respectively; and They represent the maximum and minimum values of the negative pole coefficient under voltage level g, Representation node The auxiliary variable introduced by the relaxation of the positive hyperbolic term at Representation node The auxiliary variable introduced by the negative hyperbolic relaxation term is Representation node Auxiliary variables introduced by the bipolar hyperbolic relaxation at .

6. An electronic device comprising a memory and a processor, characterized in that: The memory is used to store a program that supports the processor to execute the multi-dimensional and multi-resource integrated voltage control optimization method according to any one of claims 1 to 5, and the processor is configured to execute the program stored in the memory.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the multi-dimensional and multi-resource integrated voltage control optimization method according to any one of claims 1 to 5 are executed.

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