A power system network control method and apparatus

Abstract

The application discloses a power system network control method and device, and the method comprises the following steps: establishing a charging current control model and a discharging current control model of distributed energy storage according to a power system network to be controlled; establishing a distributed photovoltaic and energy storage collaborative voltage control model according to the charging current control model and the discharging current control model; performing voltage control simulation according to the distributed photovoltaic and energy storage collaborative voltage control model, and generating a simulation result; and controlling the power system network to be controlled according to the simulation result. The embodiment of the application realizes collaborative voltage coordination control of the distributed photovoltaic and energy storage, thereby improving the safety of the power system.

Description

Technical Field

[0001] This invention relates to the field of control system technology, and in particular to a power system network control method and apparatus. Background Technology

[0002] With the continuous expansion of modern power grids and the increasing investment in new energy power generation, modern power systems have exhibited some new characteristics. Existing electromechanical transient and long-process analysis software uses quasi-steady-state models to simulate power electronic equipment, failing to reflect its rapid transient characteristics and waveform distortions caused by nonlinear components. However, by interfacing electromagnetic transient simulation with electromechanical transient simulation, hybrid simulation of these two technologies can be achieved. This allows for the simulation of both large-scale power systems and local networks' electromagnetic transients in a single simulation, accurately reflecting the transient stability and dynamic characteristics of the power system.

[0003] In recent years, with rapid economic development, environmental pollution and energy depletion have become increasingly serious problems, leading to a gradual increase in the penetration rate of distributed photovoltaic (PV) power. However, the integration of distributed PV can adversely affect grid voltage. Distributed energy storage, on the other hand, can effectively regulate the voltage of grids containing distributed PV. Both power regulation using PV inverters and energy management using distributed energy storage can achieve voltage control. However, when both distributed PV and distributed energy storage exist in the grid simultaneously, a coordination problem arises between these two control methods. Currently, hybrid simulations of electromagnetic and electromechanical transients have not yet established control models for the coordinated voltage regulation of distributed PV and energy storage, making it impossible to achieve coordinated control analysis between the two, thus resulting in low power system security. Summary of the Invention

[0004] This invention provides a power system network control method and apparatus that realizes coordinated voltage control of distributed photovoltaic and energy storage, thereby improving the security of the power system.

[0005] The first aspect of this application provides a power system network control method, including:

[0006] Based on the power system network to be controlled, a charging current control model and a discharging current control model for distributed energy storage are established. Specifically, when the terminal node voltage is less than the upper limit of the reference voltage, the distributed energy storage in the power system network to be controlled is charged to generate the charging current control model; wherein, the charging current of the distributed energy storage is adjusted by the state of charge and a first calculation formula; when the terminal node voltage is less than the lower limit of the reference voltage, the distributed energy storage is controlled to discharge to generate the discharging current control model; wherein, the first calculation formula is specifically:

[0007] ;

[0008] in, I DES,i1 It is a node i The charging current for distributed energy storage, P sur,i It is a node i The remaining power, P sur,i = P DG,i - P L,i , P L,i It is a node i Load power, P DG,i It is a node i Power generation capacity, V DES_C It is the charging voltage for distributed energy storage. P PV_R It is the rated capacity of the photovoltaic system. λ C,i It is a node i The charging current coefficient, SOC i It is a node i The state of charge;

[0009] A distributed photovoltaic (PV) and energy storage collaborative voltage control model is established based on the charging current control model and the discharging current control model. Specifically, when the PV inverter capacity in the power system network to be controlled is sufficient and the terminal node voltage does not exceed the limit, the PV inverter controls the distributed PV in the power system network to adjust the terminal node voltage according to the utilization index and the consensus algorithm; when the PV inverter capacity in the power system network to be controlled is insufficient and the terminal node voltage exceeds the limit, the distributed energy storage is controlled to adjust the terminal node voltage through the charging current control model and the discharging current control model; thus generating the distributed PV and energy storage collaborative voltage control model.

[0010] Voltage control simulation is performed based on a distributed photovoltaic and energy storage coordinated voltage control model, and simulation results are generated.

[0011] The power system network to be controlled is controlled based on the simulation results.

[0012] In one possible implementation of the first aspect, the discharge current of the distributed energy storage is expressed by the following formula:

[0013] ;

[0014] in, I DES,i2 It is a nodei The discharge current of distributed energy storage P DES_Max This is the maximum discharge power of distributed energy storage. V DES_D It is the discharge voltage of distributed energy storage. λ D,i It is a node i The control coefficient for the discharge current, where k represents the time.

[0015] In one possible implementation of the first aspect, the utilization rate metric is represented by the following formula:

[0016] ;

[0017] Among them, u pv,i Q represents the utilization rate indicator; pv,i This represents the reactive power output of inverter i. This indicates the upper limit of reactive power output by inverter i, which is the reactive capacity of the inverter.

[0018] One possible implementation of the first aspect also includes:

[0019] The system containing power electronic devices in the power system network to be controlled is defined as an electromagnetic transient subsystem;

[0020] The external AC power network in the controlled power system network is defined as the electromechanical transient subsystem;

[0021] The bus used to connect the electromagnetic transient subsystem and the electromechanical transient subsystem is defined as the interface bus for hybrid simulation, so that the electromagnetic transient subsystem and the electromechanical transient subsystem can synchronize the two simulations and exchange data through the interface bus.

[0022] In one possible implementation of the first aspect, the electromagnetic transient subsystem and the electromechanical transient subsystem interact with each other via an interface bus, specifically:

[0023] The electromechanical transient subsystem is subjected to positive, negative, and zero three-sequence Thevenin equivalent processing using the compensation method to generate the first equivalent processing result, which is then transmitted to the electromagnetic transient subsystem through the interface bus.

[0024] The electromagnetic transient subsystem converts the first equivalent processing result into an admittance array and power supply adapted to the electromagnetic transient simulation, performs electromagnetic transient simulation based on the admittance array and power supply, generates fundamental positive, negative, and zero three-sequence currents, and transmits the fundamental positive, negative, and zero three-sequence currents to the electromechanical transient subsystem through the interface bus.

[0025] In one possible implementation of the first aspect, the external AC power network includes:

[0026] Equivalent models of fundamental positive sequence, negative sequence, and zero sequence.

[0027] A second aspect of this application provides a power system network control device for performing the steps of a power system network control method of the present invention, comprising: a first establishment module, a second establishment module, a simulation module, and a control module;

[0028] The first establishing module is used to establish a charging current control model and a discharging current control model for distributed energy storage based on the power system network to be controlled. Specifically, when the terminal node voltage is less than the upper limit of the reference voltage, the distributed energy storage in the power system network to be controlled is charged to generate the charging current control model; wherein, the charging current of the distributed energy storage is adjusted by the state of charge and a first calculation formula; when the terminal node voltage is less than the lower limit of the reference voltage, the distributed energy storage is controlled to discharge to generate the discharging current control model; wherein, the first calculation formula is specifically:

[0029] ;

[0030] in, I DES,i1 It is a node i The charging current for distributed energy storage, P sur,i It is a node i The remaining power, P sur,i = P DG,i - P L,i , P L,i It is a node i Load power, P DG,i It is a node i Power generation capacity, V DES_C It is the charging voltage for distributed energy storage. P PV_R It is the rated capacity of the photovoltaic system. λ C,i It is a node i The charging current coefficient, SOC i It is a node i The state of charge;

[0031] The second module is used to establish a distributed photovoltaic and energy storage coordinated voltage control model based on the charging current control model and the discharging current control model. Specifically, when the photovoltaic inverter capacity in the power system network to be controlled is sufficient and the terminal node voltage does not exceed the limit, the photovoltaic inverter controls the distributed photovoltaic in the power system network to adjust the terminal node voltage according to the utilization index and the consensus algorithm; when the photovoltaic inverter capacity in the power system network to be controlled is insufficient and the terminal node voltage exceeds the limit, the distributed energy storage is controlled to adjust the terminal node voltage through the charging current control model and the discharging current control model; thus generating the distributed photovoltaic and energy storage coordinated voltage control model.

[0032] The simulation module is used to perform voltage control simulation based on the distributed photovoltaic and energy storage coordinated voltage control model and generate simulation results;

[0033] The control module is used to control the power system network to be controlled based on the simulation results.

[0034] Compared to existing technologies, this invention provides a power system network control method and apparatus. The method includes: establishing a charging current control model and a discharging current control model for distributed energy storage based on the power system network to be controlled; establishing a distributed photovoltaic and energy storage coordinated voltage control model based on the charging current control model and the discharging current control model; performing voltage control simulation based on the distributed photovoltaic and energy storage coordinated voltage control model to generate simulation results; and controlling the power system network to be controlled based on the simulation results.

[0035] Its beneficial effects are as follows: After establishing a distributed photovoltaic and energy storage coordinated voltage control model based on the charging current control model and the discharging current control model, the embodiments of the present invention perform voltage control simulation based on the distributed photovoltaic and energy storage coordinated voltage control model, generate simulation results, realize coordinated simulation analysis when distributed photovoltaic and energy storage regulate voltage, make full use of voltage control means to control voltage, provide technical support for solving the voltage problem of grids with high photovoltaic penetration, and finally control the power system network to be controlled based on the simulation results, realize coordinated voltage control of distributed photovoltaic and energy storage, improve control accuracy, and thus improve the safety of the power system. Attached Figure Description

[0036] Figure 1 This is a flowchart illustrating a power system network control method according to an embodiment of the present invention;

[0037] Figure 2 This is a flowchart illustrating a hybrid simulation method for voltage regulation of distributed photovoltaic and energy storage provided in an embodiment of the present invention.

[0038] Figure 3 This is a schematic diagram of a system for coordinated voltage regulation of distributed photovoltaic and energy storage provided in an embodiment of the present invention;

[0039] Figure 4 This is a schematic diagram of a simulation model of a photovoltaic power generation system with distributed energy storage provided in an embodiment of the present invention;

[0040] Figure 5 This is a schematic diagram of the voltage curve of bus 13 without any control provided in an embodiment of the present invention;

[0041] Figure 6 This is a schematic diagram of the voltage curve of bus 13 controlled by a photovoltaic inverter according to an embodiment of the present invention;

[0042] Figure 7 This is a schematic diagram of the voltage curve of bus 13 after setting parameters according to an embodiment of the present invention;

[0043] Figure 8 This is a schematic diagram of the output current of distributed energy storage provided in an embodiment of the present invention;

[0044] Figure 9 This is a schematic diagram of the structure of a power system network control device provided in an embodiment of the present invention. Detailed Implementation

[0045] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] Reference Figure 1 , Figure 1 This is a flowchart illustrating a power system network control method according to an embodiment of the present invention, including steps S101-S104:

[0047] S101: Establish charging current control model and discharging current control model for distributed energy storage based on the power system network to be controlled.

[0048] In this embodiment, the establishment of a charging current control model and a discharging current control model for distributed energy storage based on the power system network to be controlled specifically includes:

[0049] When the voltage at the terminal node is less than the upper limit of the reference voltage, the distributed energy storage in the power system network to be controlled is charged to generate the charging current control model; wherein, the charging current of the distributed energy storage is adjusted by the state of charge and the first calculation formula;

[0050] When the voltage at the terminal node is lower than the lower limit of the reference voltage, the distributed energy storage is controlled to discharge, thereby generating the discharge current control model.

[0051] In one specific embodiment, the first calculation formula is as follows:

[0052] ;

[0053] in, I DES,i1 It is a node i The charging current for distributed energy storage, P sur,i It is a node i The remaining power, P sur,i = P DG,i - P L,i , P L,i It is a node i Load power, P DG,i It is a node i Power generation capacity, V DES_C It is the charging voltage for distributed energy storage. P PV_R It is the rated capacity of the photovoltaic system. λ C,i It is a node i The charging current coefficient, SOC i It is a node i The state of charge.

[0054] In one specific embodiment, the discharge current of the distributed energy storage is expressed by the following formula:

[0055] ;

[0056] in, I DES,i2 It is a node i The discharge current of distributed energy storage P DES_Max This is the maximum discharge power of distributed energy storage. V DES_D It is the discharge voltage of distributed energy storage. λ D,i It is a node i The control coefficient for the discharge current, where k represents the time.

[0057] S102: Establish a distributed photovoltaic and energy storage coordinated voltage control model based on the charging current control model and the discharging current control model.

[0058] In this embodiment, the establishment of a distributed photovoltaic and energy storage coordinated voltage control model based on the charging current control model and the discharging current control model specifically involves:

[0059] When the photovoltaic inverter capacity in the power system network to be controlled is sufficient and the voltage of the terminal node does not exceed the limit, the photovoltaic inverter controls the distributed photovoltaic in the power system network to be controlled to adjust the voltage of the terminal node according to the utilization index and the consensus algorithm.

[0060] When the capacity of the photovoltaic inverter in the power system network to be controlled is insufficient and the voltage of the terminal node exceeds the limit, the distributed energy storage is controlled to adjust the voltage of the terminal node through the charging current control model and the discharging current control model.

[0061] Generate the distributed photovoltaic and energy storage coordinated voltage control model.

[0062] In one specific embodiment, the utilization rate index is represented by the following formula:

[0063] ;

[0064] Among them, u pv,i Q represents the utilization rate indicator; pv,i This represents the reactive power output of inverter i. This indicates the upper limit of reactive power output by inverter i, which is the reactive capacity of the inverter.

[0065] S103: Perform voltage control simulation based on the distributed photovoltaic and energy storage coordinated voltage control model, and generate simulation results.

[0066] S104: Control the power system network to be controlled based on the simulation results.

[0067] In one specific embodiment, it further includes:

[0068] The system containing power electronic devices in the power system network to be controlled is defined as an electromagnetic transient subsystem;

[0069] The external AC power network in the controlled power system network is defined as an electromechanical transient subsystem;

[0070] The bus used to connect the electromagnetic transient subsystem and the electromechanical transient subsystem is defined as the interface bus for hybrid simulation, so that the electromagnetic transient subsystem and the electromechanical transient subsystem can synchronize the two simulations and interact with data through the interface bus.

[0071] In one specific embodiment, the electromagnetic transient subsystem and the electromechanical transient subsystem interact with each other via the interface bus, specifically as follows:

[0072] The electromechanical transient subsystem is subjected to positive, negative, and zero three-sequence Thevenin equivalent processing using a compensation method to generate a first equivalent processing result, which is then transmitted to the electromagnetic transient subsystem via the interface bus.

[0073] The electromagnetic transient subsystem converts the first equivalent processing result into an admittance array and a power supply adapted to the electromagnetic transient simulation, performs electromagnetic transient simulation based on the admittance array and the power supply, generates a fundamental positive, negative, and zero three-sequence current, and transmits the fundamental positive, negative, and zero three-sequence current to the electromechanical transient subsystem through the interface bus.

[0074] In one specific embodiment, the external AC power network includes:

[0075] Equivalent models of fundamental positive sequence, negative sequence, and zero sequence.

[0076] To better illustrate a power system network control method, please refer to... Figure 2 , Figure 2 This is a flowchart illustrating a hybrid simulation method for voltage regulation considering distributed photovoltaic and energy storage coordination, provided in an embodiment of the present invention, including S201-S204:

[0077] S201: Equivalent network and data interaction method for electromagnetic-electromechanical hybrid simulation of power system.

[0078] The electromagnetic-electromechanical hybrid simulation power system network equivalence and data interaction methods include: power system network decomposition method, electromechanical transient subsystem equivalent to electromagnetic transient subsystem, electromagnetic transient subsystem equivalent to electromechanical transient subsystem, and data exchange method when electromagnetic transient subsystem and electromechanical transient subsystem interface with each other.

[0079] Power system network decomposition method: The power system network is decomposed into three parts: electromagnetic transient subsystem, electromechanical transient subsystem, and interface bus. The detailed system containing power electronic devices is defined as the electromagnetic transient subsystem, and detailed simulation is performed using an electromagnetic transient program. The traditional external AC power network is defined as the electromechanical transient subsystem, and simulation is performed using an electromechanical transient program. The bus used to connect the electromagnetic transient subsystem and the electromechanical transient subsystem is defined as the interface bus for hybrid simulation. The electromagnetic transient subsystem and the electromechanical transient subsystem synchronize and exchange data through the interface bus.

[0080] Equivalent method of electromechanical transient subsystem to electromagnetic transient subsystem: To facilitate the use of existing electromechanical transient stability programs and data, a three-sequence equivalent model of fundamental positive sequence, negative sequence, and zero sequence is adopted for the external AC power network. The external electromechanical transient subsystem is equivalent to the electromagnetic transient subsystem as a Norton circuit.

[0081] The equivalent method for the electromagnetic transient subsystem to the electromechanical transient subsystem: The electromagnetic transient subsystem is equivalent to the electromechanical transient subsystem as a fundamental frequency load or fundamental frequency current source. Since the electromechanical transient subsystem is a slowly changing system relative to the electromagnetic transient subsystem, a constant power load within one electromechanical transient simulation step is used as the equivalent of the electromagnetic transient subsystem for the electromechanical transient subsystem simulation.

[0082] Data exchange method when electromagnetic transient subsystem and electromechanical transient subsystem interface with each other: Select the converter terminal bus as the interface bus for electromechanical-electromagnetic transient hybrid simulation. The electromagnetic transient subsystem only includes the DC system (converter, converter transformer, reactive power compensation, filter, smoothing reactor, DC line, control system, etc.) and does not include the AC system. The advantages of this network decomposition method are that the detailed system scope is small, the hybrid simulation efficiency is high, and the mutual equivalence between the electromagnetic transient subsystem and the electromechanical transient system is relatively simple.

[0083] The data interaction process is as follows: the electromechanical transient subsystem is subjected to positive, negative, and zero three-sequence Thevenin equivalent processing using the compensation method to generate a first equivalent processing result, and the first equivalent processing result is transmitted to the electromagnetic transient subsystem through the interface bus.

[0084] The electromagnetic transient subsystem converts the first equivalent processing result into an admittance array and a power supply adapted to the electromagnetic transient simulation, performs electromagnetic transient simulation based on the admittance array and the power supply, generates a fundamental positive, negative, and zero three-sequence current, and transmits the fundamental positive, negative, and zero three-sequence current to the electromechanical transient subsystem through the interface bus.

[0085] S202: Method for establishing a control model for distributed energy storage.

[0086] The method for establishing a control model for distributed energy storage includes a charging current control method and a discharging current control method for distributed energy storage.

[0087] Among them, the charging current control method for distributed energy storage is as follows:

[0088] Distributed energy storage connected to the power system is used to control the grid connection point voltage. When the terminal node voltage is lower than the upper limit of the reference voltage, charging is performed based on the distributed energy storage in the power system network to be controlled, generating a charging current control model. The charging current of the distributed energy storage is adjusted by the state of charge and a first calculation formula, which can be expressed as follows:

[0089] ;

[0090] in, I DES,i1 It is a node i The charging current for distributed energy storage, P sur,i It is a node i The remaining power, P sur,i = P DG,i - P L,i , P L,i It is a node i Load power, P DG,i It is a node i Power generation capacity, V DES_C It is the charging voltage for distributed energy storage. P PV_R It is the rated capacity of the photovoltaic system. λ C,i It is a node i The charging current coefficient, SOC i It is a node i The state of charge.

[0091] λ C,i It is a non-negative integer. λ C,i The default value is zero. λ C,i Calculated using the following formula:

[0092] ;

[0093] When the terminal node voltage V end ≥ V UL , P sur,i When >0, λ C,i Increase the charging power of distributed energy storage. V end It is the terminal node voltage. V UL This is the upper limit of the reference voltage. When P sur,i When <0, λ C,i Reduce the charging power of distributed energy storage. When V end< V UL hour, λ C,i =0.

[0094] Distributed energy storage utilizes surplus power for charging and suppresses voltage rise at the end nodes. To prevent battery degradation in distributed energy storage, the State of Charge (SOC) is capped at 80%. When SOC < 60%, the charging current increases to rapidly charge the distributed energy storage. When 70 ≤ SOC ≤ 85%, the charging current gradually decreases according to the SOC. As a result, even if SOC > 85% and charging stops, the node voltage will not increase rapidly.

[0095] The discharge current control of distributed energy storage is as follows: Discharge of distributed energy storage is used to suppress voltage drop and maintain the voltage within a specified range, when the terminal node voltage... V end < V LL At that time, it will discharge, among which, V LL This is the lower limit of the reference voltage. The discharge current of distributed energy storage is expressed by the following formula:

[0096] ;

[0097] in, I DES,i2 It is a node i The discharge current of distributed energy storage P DES_Max This is the maximum discharge power of distributed energy storage. V DES_D It is the discharge voltage of distributed energy storage. λ D,i It is a node i The control coefficient for the discharge current, where k represents the time.

[0098] When distributed energy storage discharges, the current of the distributed energy storage is negative.

[0099] λ D,i It is a non-negative integer, with a default value of 0. λ D,i Calculated using the following formula:

[0100] ;

[0101] when V end < V LL , P L,i - P DES_D >P DES_Thr1 hour, λ D,i Increase the discharge power of distributed energy storage. P DES_D It is the discharge power of distributed energy storage. P DES_Thr1 This is the first threshold value of the discharge power. When V end > V LL hour, λ D,i Reduce the discharge power of distributed energy storage.

[0102] In addition, the discharge power of distributed energy storage is adjusted according to the State of Charge (SOC). When SOC i > SOC Thr , P L,i - P DES_D > P DES_Thr2 hour, λ D,i Increase, among which, P DES_Thr2 It is the second threshold of discharge power. SOC Thr This is the threshold of SOC. At this point, P DES_Thr1 > P DES_Thr2 On the other hand, when SOC i < SOC Thr , P L,i - P DES_D < P DES_Thr2 hour, λ D,i Decrease.

[0103] S203: Method for establishing a voltage control model for distributed photovoltaic and energy storage collaboration.

[0104] The method for establishing a voltage control model for distributed photovoltaic and energy storage includes a consistency control method for photovoltaic inverters and a consistency coordination control method for distributed energy storage.

[0105] Among them, the consistency control method of photovoltaic inverters uses the power regulation control voltage of photovoltaic inverters. It is necessary to ensure that all grid-connected distributed photovoltaics participate in voltage adjustment in a fair manner. An inverter utilization rate index is defined, and a collaborative control method with inverter utilization rate as the consistency target is adopted to ensure that distributed photovoltaics of different capacities fully participate in voltage adjustment. If the voltage is still not within the safe range (i.e., when the voltage of the terminal node exceeds the limit), then distributed energy storage is used to participate in voltage control, that is, the consistency coordination control method of distributed energy storage is used.

[0106] The consistency coordination control method for distributed energy storage also requires that all distributed energy storage participating in voltage control participate in voltage adjustment in a fair manner. It defines the utilization rate index of distributed energy storage and adopts a coordinated control method with the utilization rate of distributed energy storage as the consistency target to ensure that all distributed energy storage willing to participate in voltage control fully participate in voltage adjustment. If the voltage is too low, the distributed energy storage enters the discharge current control mode to increase the voltage level; if the voltage is too high, the distributed energy storage enters the charging current control mode to decrease the voltage level.

[0107] Consistency Control of Photovoltaic Inverters: When the capacity of photovoltaic inverters in the power system network to be controlled is sufficient and the voltage of the terminal nodes does not exceed the limit, the photovoltaic inverters control the distributed photovoltaic adjustment of the terminal node voltage in the power system network to be controlled according to the utilization index and consensus algorithm. For all photovoltaic inverters in the power network, it is crucial to control them fairly to participate in the voltage regulation process. To control the inverters to fairly absorb / generate reactive power using limited communication links between inverters, a distributed inverter control based on a consensus algorithm is proposed. Furthermore, to ensure that inverters of different capacities are fully utilized, this paper selects the inverter utilization index u. pv,i For the consistency objective, it is expressed as:

[0108] ;

[0109] Among them, u pv,i Q represents the utilization rate indicator; pv,i This represents the reactive power output of inverter i. This indicates the upper limit of reactive power output by inverter i, which is the reactive capacity of the inverter.

[0110] During peak photovoltaic power generation and peak load, for any bus voltage V i In the feeder, the proposed consensus algorithm will satisfy the conditions given by the following formula:

[0111] ;

[0112] Among them, V min The lower limit of voltage, Vmax V is the upper limit of voltage. i Let i be the voltage of bus i.

[0113] The goal of consensus algorithms is to correct the state variables of all nodes by exchanging information with neighboring nodes, so that the state variables of all nodes tend to the same stable state. G =( V , E ), V =[1, 2, … N [] represents the set of nodes in a photovoltaic-storage system; E Denotes the edge set, if ( j , i If )∈E, then it represents a node. i With nodes j Adjacent and receiving nodes j Information. Assume the... i The state of the bus at time t is represented as: x i ( t The sampling time interval is T s Then a discretized consensus algorithm can be expressed as:

[0114] ;

[0115] in, a ij The coefficients of the state transition matrix are represented by:

[0116] ;

[0117] in, N This indicates that it is possible to send data to nodes. i The number of nodes sending information.

[0118] For radially distributed feeders with multiple buses, the last bus is the critical bus, exhibiting the highest / lowest voltage in the system. Therefore, the last bus is selected as the dominant node to initiate voltage control. The utilization rate of the dominant node is determined by measuring the voltage of the last bus. Then, through the communication link... Shared with available inverters to achieve the required voltage regulation target, and Update according to the following formula:

[0119] ;

[0120] in, α 1 and α 2 represents the control gain, which affects the convergence speed and control accuracy of distributed control.PV,N V represents the utilization rate of the photovoltaic system inverter at the Nth node. N Let t represent the voltage at the Nth node, and t represent time.

[0121] Assume the photovoltaic system can only communicate with adjacent units. i Inverter utilization rate of a photovoltaic system u PV,i Updated to:

[0122] ;

[0123] Where a ij These are the coefficients of the state transition matrix between node i and node j, a iN The coefficients of the state transition matrix between node i and node N, u j No. j Inverter utilization rate per node.

[0124] Then the first i The reactive power required to be output by each inverter is:

[0125] ;

[0126] ;

[0127] The constraint for distributed control of inverters is the reactive power capacity of each inverter. :

[0128] ;

[0129] Consistent Coordination Control of Distributed Energy Storage: When the capacity of photovoltaic inverters in the power system network to be controlled is insufficient and the voltage of the terminal nodes exceeds the limit, the distributed energy storage is controlled to adjust the voltage of the terminal nodes through charging current control models and discharging current control models. The primary objective is to coordinate the battery energy of the distributed energy storage used for voltage regulation. Similar to the distributed control of inverters, the utilization rate of distributed energy storage is considered. u DES,i For consistency goals. Utilization. u DES,i Calculated using the following formula:

[0130] ;

[0131] in, β 1 and β 2 is the control gain. It is the utilization rate of the dominant node. u DES,N V is the inverter utilization rate indicator for the Nth node. N Let t represent the voltage at the Nth node, and t represent time.

[0132] No. i Utilization rate of distributed energy storage u DES,i Updated to:

[0133] ;

[0134] Among them, a ij These are the coefficients of the state transition matrix between node i and node j, a iN The coefficients of the state transition matrix between node i and node N, u j No. j Inverter utilization rate per node.

[0135] The aforementioned distributed control will regulate the feeder voltage and determine the utilization rate of each distributed energy storage unit. However, since the SOC of distributed energy storage units varies and is unpredictable, they may be fully charged / discharged when needed. The second objective is to effectively utilize the available distributed energy storage capacity in the network for voltage regulation. Therefore, for each distributed energy storage unit, localized control will be implemented based on local SOC information to adjust the charging / discharging rate.

[0136] The proposed localized SOC control adjusts the SOC of each distributed energy storage unit within the expected range of its predefined reference SOC. This is achieved through estimated state of charge (SOC). SOC ( t (and reference state of charge) SOC ref ( t Compare and determine availability. ε . SOC ref ( t This represents the expected State of Charge (SOC) of distributed energy storage during daily operation. ε Defined by the following formula:

[0137] ;

[0138] in, k 1 and k 2 is the threshold for SOC control, used to define the allowable deviation range between SOC and reference SOC. β 3 = 1 / ( k 2- k 1).

[0139] Taking charging as an example, the discharging process is similar. When SOC ( t )≥ SOC ref ( t )+ k 2. Distributed energy storage does not perform charging; when SOC( t )≥ SOC ref ( t )+ k 1. Distributed energy storage is fully charged; SOC ( t )exist[ SOC ref ( t )+ k 1, SOC ref ( t )+ k Within the range of 2], the charging of distributed energy storage will be slowed down.

[0140] Combining the proposed distributed and local control methods, the output of distributed energy storage... It can be represented as:

[0141] ;

[0142] ;

[0143] The constraints for distributed-local coordinated control of distributed energy storage are the power and energy constraints of each distributed energy storage unit:

[0144] ;

[0145] ;

[0146] in, It is the rated discharge power of distributed energy storage, SOC. min and SOC max These are the upper and lower limits of the State of Charge (SOC), respectively. It is the distributed energy storage availability of the i-th node.

[0147] S204: Parallel processing method for electromagnetic-electromechanical hybrid simulation.

[0148] A parallel processing method for electromagnetic-electromechanical hybrid simulation, including a method for constructing multi-machine, multi-core parallel simulation calculations, and a method for result analysis and presentation. Among these:

[0149] Multi-machine, multi-core parallel simulation computing construction method: Construct multi-machine, multi-core parallel simulation computing function, rely on server clusters to realize the parallelization of simulation computing services, and improve the simulation computing speed under multiple modes and multiple fault sets computing conditions.

[0150] (1) Model and abstract the process for electromagnetic-electromechanical hybrid simulation business functions, and establish a parallel computing working mode based on file transfer mode; (2) According to the hardware environment, effectively decompose and reasonably assign simulation computing task sets, fault sets and other tasks, realize the concurrent allocation of multi-user computing tasks to computing nodes, and realize multi-machine distributed parallel computing on computing nodes through machine clusters. The work of multiple tasks should be balanced among computing servers. When multiple tasks work in parallel, there should be no obvious workload imbalance between servers; (3) Within a single computing node, perform multi-core decomposition and parallel computing analysis of computing tasks according to CPU configuration, and realize electromechanical transient, electromagnetic-electromechanical hybrid simulation, and medium- and long-term large-scale parallel computing scanning functions. For users, time-consuming power calculations can be transferred from the local machine to the server, which can greatly improve the efficiency of users' calculation, result viewing, statistics and analysis.

[0151] Results Analysis and Presentation Methods: Data analysis is performed on the simulation calculation results to obtain corresponding index results. The simulation calculation results and data analysis results are presented using various visualization methods such as tables and curves.

[0152] (1) Implement the classification and statistical analysis of power flow simulation calculation results; implement the field-based report display of power flow calculation results for easy access by users; (2) Implement the multi-terminal shared display of output result curves of transient stability simulation, medium- and long-term stability simulation, and electromagnetic-electromechanical hybrid simulation calculation results.

[0153] Accordingly, one embodiment of the present invention describes a system for coordinated voltage regulation of distributed photovoltaic and energy storage, please refer to... Figure 3 , Figure 3 This is a schematic diagram of a system for voltage regulation of distributed photovoltaic and energy storage in accordance with an embodiment of the present invention, including: an electromagnetic-electromechanical hybrid simulation power system network equivalent and data interaction unit 301, a distributed energy storage control model unit 302, a distributed photovoltaic and energy storage coordinated voltage control model unit 303, and an electromagnetic-electromechanical hybrid simulation parallel processing unit 304.

[0154] The electromagnetic-electromechanical hybrid simulation power system network equivalent and data interaction unit 301 includes: a power system network decomposition unit, an equivalent unit of the electromechanical transient subsystem to the electromagnetic transient subsystem, an equivalent unit of the electromagnetic transient subsystem to the electromechanical transient subsystem, and a data exchange unit when the electromagnetic transient subsystem and the electromechanical transient subsystem interface with each other.

[0155] The control model unit 302 for distributed energy storage includes: a charging current control unit for distributed energy storage and a discharging current control unit for distributed energy storage.

[0156] The distributed photovoltaic and energy storage coordinated voltage control model unit 303 includes: a consistency control unit for the photovoltaic inverter and a consistency coordination control unit for the distributed energy storage.

[0157] The electromagnetic-electromechanical hybrid simulation parallel processing unit 304 includes: a multi-machine multi-core parallel simulation calculation construction unit and a result analysis and display unit.

[0158] To further illustrate the voltage control model for distributed photovoltaic and energy storage collaboration, please refer to... Figure 4 , Figure 4 This is a schematic diagram of a simulation model of a photovoltaic power generation system with distributed energy storage provided in an embodiment of the present invention.

[0159] The simulation system has a base voltage of 6.6kV and consists of 13 buses, with buses 1, 3, 5, 7, 10, 12, and 13 connected to 100 distributed energy storage units. Simulation parameter settings: safe voltage range [0.95 pu, 1.05 pu]; allowable SOC variation range for EVs [20%, 80%]; sampling interval time of 5 minutes; distance between adjacent buses of 500m; line impedance of 0.647 + j0.463Ω / km; rated photovoltaic power of 9kW; distributed energy storage capacity of 90kW; maximum distributed charging and discharging power of 18kW.

[0160] Furthermore, selecting the node where bus 13 is located as the dominant node, the voltage curve of bus 13 without any control is as follows: Figure 5 As shown, Figure 5 This is a schematic diagram of the voltage curve of bus 13 without any control provided in an embodiment of the present invention.

[0161] When only a photovoltaic inverter is used to regulate the voltage, the voltage curve of bus 13 is as follows: Figure 6 As shown, Figure 6 This is a schematic diagram of the voltage curve of a bus 13 controlled by a photovoltaic inverter according to an embodiment of the present invention, wherein, Figure 6 The horizontal axis represents time, and the vertical axis represents voltage. Figure 6 It can be seen that when photovoltaic inverters are used for control, the situation of voltage exceeding the upper limit can be effectively improved, but the situation of voltage exceeding the lower limit is not improved because the photovoltaic storage capacity is insufficient at night and voltage regulation cannot be performed. Therefore, distributed photovoltaic voltage regulation is required.

[0162] against Figure 6 To address the insufficient control performance, adjust the photovoltaic inverter consistency control parameters. α 1 = 0.001 α 2 = 0.001; EV consistency control parameter β 1 = 0.001 β2 = 0.001, Distributed energy storage charging parameters β 3 = 20 k 1=0, k 2=0.05; Distributed energy storage discharge parameters β 3 = -20 k 1=0, k 2 = -0.05. This is to make the voltage curve of bus 13 as shown... Figure 7 As shown, Figure 7 This is a schematic diagram of the voltage curve of bus 13 after setting parameters according to an embodiment of the present invention, wherein, Figure 7 The horizontal axis represents time, and the vertical axis represents voltage. Furthermore, the current output by distributed energy storage is as follows: Figure 8 As shown, Figure 8 This is a schematic diagram of the output current of distributed energy storage according to an embodiment of the present invention, wherein, Figure 8 The horizontal axis represents time, and the vertical axis represents current.

[0163] from Figure 7 and Figure 8 It can be seen that by performing voltage control simulation based on the distributed photovoltaic and energy storage coordinated voltage control model, and generating simulation results, controlling the power system network to be controlled based on the simulation results can keep the voltage of all nodes within the specified voltage range. Distributed energy storage discharges in the early morning to suppress voltage drops, utilizes the remaining power of the photovoltaic system for charging, and during the day, the photovoltaic inverters primarily regulate the voltage. At night, distributed energy storage discharges to ensure the voltage does not fall below the lower limit of the range. This achieves coordinated voltage control of distributed photovoltaic and energy storage, improves control accuracy, and thus enhances the safety of the power system.

[0164] For further explanation of power system network control devices, please refer to... Figure 9 , Figure 9 This is a schematic diagram of the structure of a power system network control device according to an embodiment of the present invention, including: a first establishment module 901, a second establishment module 902, a simulation module 903, and a control module 904;

[0165] The first establishment module 901 is used to establish a charging current control model and a discharging current control model for distributed energy storage based on the power system network to be controlled.

[0166] The second establishment module 902 is used to establish a distributed photovoltaic and energy storage coordinated voltage control model based on the charging current control model and the discharging current control model;

[0167] The simulation module 903 is used to perform voltage control simulation based on the distributed photovoltaic and energy storage coordinated voltage control model and generate simulation results.

[0168] The control module 904 is used to control the power system network to be controlled based on the simulation results.

[0169] In this embodiment of the invention, a first establishment module establishes a charging current control model and a discharging current control model for distributed energy storage based on the power system network to be controlled; a second establishment module establishes a distributed photovoltaic and energy storage coordinated voltage control model based on the charging current control model and the discharging current control model; a simulation module performs voltage control simulation based on the distributed photovoltaic and energy storage coordinated voltage control model and generates simulation results; and a control module controls the power system network to be controlled based on the simulation results.

[0170] In this embodiment of the invention, after establishing a distributed photovoltaic and energy storage coordinated voltage control model based on the charging current control model and the discharging current control model, voltage control simulation is performed based on the distributed photovoltaic and energy storage coordinated voltage control model to generate simulation results. This realizes the coordinated simulation analysis of distributed photovoltaic and energy storage regulating voltage, making full use of voltage control methods to control voltage, providing technical support for solving the voltage problem of power grids with high photovoltaic penetration. Finally, the power system network to be controlled is controlled based on the simulation results, realizing the coordinated voltage control of distributed photovoltaic and energy storage, improving control accuracy, and thus improving the safety of the power system.

[0171] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A power system network control method, characterized in that, include: Based on the power system network to be controlled, a charging current control model and a discharging current control model for distributed energy storage are established. Specifically, when the terminal node voltage is less than the upper limit of the reference voltage, the distributed energy storage in the power system network to be controlled is charged to generate the charging current control model; wherein, the charging current of the distributed energy storage is adjusted by the state of charge and a first calculation formula; when the terminal node voltage is less than the lower limit of the reference voltage, the distributed energy storage is controlled to discharge to generate the discharging current control model; wherein, the first calculation formula is specifically: ； in, I DES,i1 It is a node i The charging current for distributed energy storage, P sur,i It is a node i The remaining power, P sur,i = P DG,i - P L,i , P L,i It is a node i Load power, P DG,i It is a node i Power generation capacity, V DES_C It is the charging voltage for distributed energy storage. P PV_R It is the rated capacity of the photovoltaic system. λ C,i It is a node i The charging current coefficient, SOC i It is a node i The state of charge; A distributed photovoltaic (PV) and energy storage coordinated voltage control model is established based on the charging current control model and the discharging current control model. Specifically, when the PV inverter capacity in the power system network to be controlled is sufficient and the terminal node voltage does not exceed the limit, the PV inverter controls the distributed PV in the power system network to adjust the terminal node voltage according to the utilization index and consensus algorithm; when the PV inverter capacity in the power system network to be controlled is insufficient and the terminal node voltage exceeds the limit, the distributed energy storage is controlled to adjust the terminal node voltage through the charging current control model and the discharging current control model; thus generating the distributed PV and energy storage coordinated voltage control model. Voltage control simulation is performed based on the distributed photovoltaic and energy storage coordinated voltage control model, and simulation results are generated. The power system network to be controlled is controlled based on the simulation results.

2. The power system network control method according to claim 1, characterized in that, The discharge current of the distributed energy storage is expressed by the following formula: ； in, I DES,i2 It is a node i The discharge current of distributed energy storage P DES_Max It is the maximum discharge power of distributed energy storage. V DES_D It is the discharge voltage of distributed energy storage. λ D,i It is a node i The control coefficient for the discharge current, where k represents the time.

3. The power system network control method according to claim 2, characterized in that, The utilization rate index is expressed by the following formula: ； Among them, u pv,i Q represents the utilization rate indicator; pv,i This represents the reactive power output of inverter i. This indicates the upper limit of reactive power output by inverter i, which is the reactive capacity of the inverter.

4. The power system network control method according to claim 3, characterized in that, Also includes: The system containing power electronic devices in the power system network to be controlled is defined as an electromagnetic transient subsystem; The external AC power network in the controlled power system network is defined as an electromechanical transient subsystem; The bus used to connect the electromagnetic transient subsystem and the electromechanical transient subsystem is defined as the interface bus for hybrid simulation, so that the electromagnetic transient subsystem and the electromechanical transient subsystem can synchronize the two simulations and interact with data through the interface bus.

5. A power system network control method according to claim 4, characterized in that, The electromagnetic transient subsystem and the electromechanical transient subsystem interact with each other through the interface bus, specifically as follows: The electromechanical transient subsystem is subjected to positive, negative, and zero three-sequence Thevenin equivalent processing using a compensation method to generate a first equivalent processing result, which is then transmitted to the electromagnetic transient subsystem via the interface bus. The electromagnetic transient subsystem converts the first equivalent processing result into an admittance array and a power supply adapted to the electromagnetic transient simulation, performs electromagnetic transient simulation based on the admittance array and the power supply, generates a fundamental positive, negative, and zero three-sequence current, and transmits the fundamental positive, negative, and zero three-sequence current to the electromechanical transient subsystem through the interface bus.

6. A power system network control method according to claim 5, characterized in that, The external AC power network includes: Equivalent models of fundamental positive sequence, negative sequence, and zero sequence.

7. A power system network control device, used to execute a power system network control method as described in any one of claims 1-6, characterized in that, include: The system consists of a first setup module, a second setup module, a simulation module, and a control module. The first establishing module is used to establish a charging current control model and a discharging current control model for distributed energy storage based on the power system network to be controlled. Specifically, when the terminal node voltage is less than the upper limit of the reference voltage, the distributed energy storage in the power system network to be controlled is charged to generate the charging current control model; wherein the charging current of the distributed energy storage is adjusted by the state of charge and a first calculation formula; when the terminal node voltage is less than the lower limit of the reference voltage, the distributed energy storage is controlled to discharge to generate the discharging current control model; wherein the first calculation formula is specifically: ； in, I DES,i1 It is a node i The charging current for distributed energy storage, P sur,i It is a node i The remaining power, P sur,i = P DG,i - P L,i , P L,i It is a node i Load power, P DG,i It is a node i Power generation capacity, V DES_C It is the charging voltage for distributed energy storage. P PV_R It is the rated capacity of the photovoltaic system. λ C,i It is a node i The charging current coefficient, SOC i It is a node i The state of charge; The second establishment module is used to establish a distributed photovoltaic and energy storage coordinated voltage control model based on the charging current control model and the discharging current control model. Specifically, when the photovoltaic inverter capacity in the power system network to be controlled is sufficient and the terminal node voltage does not exceed the limit, the photovoltaic inverter controls the distributed photovoltaic in the power system network to adjust the terminal node voltage according to the utilization index and the consensus algorithm; when the photovoltaic inverter capacity in the power system network to be controlled is insufficient and the terminal node voltage exceeds the limit, the distributed energy storage is controlled to adjust the terminal node voltage through the charging current control model and the discharging current control model; thus generating the distributed photovoltaic and energy storage coordinated voltage control model. The simulation module is used to perform voltage control simulation based on the distributed photovoltaic and energy storage coordinated voltage control model and generate simulation results. The control module is used to control the power system network to be controlled based on the simulation results.

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