Multi-port hybrid distribution transformer power collaborative hierarchical control method and system

Abstract

This invention discloses a multi-port hybrid distribution transformer power coordination hierarchical control method and system, relating to the field of power equipment control technology, including the following steps: S1, the central system control layer establishes a system optimization objective function based on the control objective and distribution system operation data and sets constraints; S2, the central system control layer linearizes the system optimization objective function in combination with the constraints to obtain active power reference values ​​and reactive power reference values ​​for each port and generates power reference commands; S3, the power coordination optimization layer collects real-time operating parameters of each port, constructs a multi-port power coordination control model, and uses a model predictive control algorithm to dynamically correct the power reference commands in real time, obtaining the optimal correction amount and generating power correction commands; S4, the port execution layer generates the final power commands for each port based on the power reference commands and power correction commands, and uses the final power commands for each port to control the corresponding ports.

Description

Technical Field

[0001] This invention relates to the field of power equipment control technology, and more specifically to a multi-port hybrid distribution transformer power collaborative hierarchical control method and system. Background Technology

[0002] The construction of new power distribution networks is currently facing a transformation in form towards an "active" two-way interactive system. Traditional power distribution networks suffer from uneven development of power sources and loads, with problems such as the large-scale integration of photovoltaic power leading to overload of distribution transformers and 10kV lines, the long-term occupation of a large amount of distribution transformer capacity by tidal loads such as charging piles, and the fact that the line / transformer load rate is generally below 30%, resulting in the unreleased power supply potential of the power distribution network.

[0003] Multi-port hybrid flexible intelligent distribution transformer is a new type of power equipment. It has multiple ports on both AC and DC sides, enabling flexible energy conversion and power control between AC and DC. It can also improve the power quality and flexible operation of microgrids, and provide reliable technical support for the large-scale integration of renewable energy.

[0004] To ensure the operational reliability and stability of multi-port hybrid distribution transformer systems, and to reduce losses and improve operating efficiency, in-depth research is needed on their modulation, control, and protection strategies. Therefore, a control method and system for multi-port hybrid distribution transformers is urgently required. Summary of the Invention

[0005] To overcome the shortcomings of the prior art, this invention discloses a power collaborative hierarchical control method and system for multi-port hybrid distribution transformers, which adopts a three-layer power collaborative control strategy for the input / output power of multiple ports in a multi-port hybrid distribution transformer.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: In a first aspect, the present invention provides a multi-port hybrid distribution transformer power coordinated hierarchical control method, comprising the following steps: S1. The data acquisition module collects real-time power distribution system operation data. The central system control layer establishes a system optimization objective function and sets constraints based on the control objectives and power distribution system operation data. Preferably, in step S1, the system optimization objective function is:

[0007] in, Optimize the objective function for the system; For coefficients; These are the photovoltaic output power, energy storage device output power, grid output power, and total load power on the load side, respectively. Output reactive power to each port; This refers to the system's operating frequency. This refers to the grid-side voltage. These are the instantaneous output power and the maximum output power of the photovoltaic system, respectively.

[0008] Preferably, in step S1, the control objectives include system active power balance, system frequency stability, and bus voltage stability. Each control objective is assigned a corresponding weight coefficient, and the adjustment formula for the weight coefficient is as follows:

[0009] in, for Weighting coefficients at each time point; These are the initial weights; for Time of the first The amount of deviation change of each target; The goal is to optimize the system.

[0010] Preferably, in step S1, the constraints include: Power constraints for each port: , ; Voltage and current constraints at each port: , ; Energy storage system charge constraints: ; System operating frequency constraints: ; in, For the first Active power of each port; , The first Minimum and maximum active power of each port; For the first reactive power of each port; , The first Minimum and maximum reactive power of each port; For the first Port voltage; , The first Minimum and maximum values ​​of the port voltage; For the first Current at each port; For the first The maximum value of the port current; State of charge of the energy storage system; , These are the minimum and maximum values ​​of the state of charge of the energy storage system, respectively. This refers to the system's operating frequency.

[0011] S2. Based on the sequential linear programming algorithm, the central system control layer linearizes the system optimization objective function in combination with the constraints to obtain the active power reference value and reactive power reference value of each port and generate power reference command. Preferably, step S2 includes: S21. Set the initial value for iteration. ;

[0012] in, For the first Initial values ​​of active power at each port; For the first Initial values ​​of reactive power at each port; ; S22, at any iteration point At this point, the system optimization objective function Linearization yields the linearized objective function. :

[0013] in, For the objective function in The gradient vector at that point; S23. Based on the linearized objective function Based on the constraints in step S1, find the optimal solution for the current iteration. ; S24. Based on iteration error Alternatively, the iteration may be terminated after a certain number of iterations. During the iteration process, the iteration compensation is adjusted using the following formula: ;in, Iterative compensation for the N+1 iteration point, Iterative compensation for N iteration points; S25. By iteratively solving, the final active power reference values ​​and reactive power reference values ​​for each port are obtained:

[0014] in, For the first Reference values ​​for active power at each port; For the first Reference values ​​for reactive power at each port; ; S26. Generate a power reference command based on the active power reference value and reactive power reference value of each port, and send the power reference command to the power coordination optimization layer and the port execution layer.

[0015] In step S2, the central system control layer globally allocates the total active power and total reactive power of the multi-port hybrid distribution transformer to obtain the active power reference value and reactive power reference value for each port. During the allocation process, the following principles are followed: priority is given to photovoltaic system power supply. When the energy required by the load side is less and the photovoltaic output is excessive, the active power is stored through the energy storage port first. When the photovoltaic output is insufficient, the energy storage device is given priority to supplement the active power required by the load side. For reactive power allocation, it is first achieved through parallel converters.

[0016] S3: The power coordination optimization layer collects real-time operating parameters of each port, constructs a multi-port power coordination control model, and uses a model predictive control algorithm to dynamically correct the power reference command in real time, obtain the optimal correction amount, and generate a power correction command. Preferably, step S3 includes: Construct a multi-port power coordination control model; Based on the multi-port power coordination control model, a model prediction optimization objective function, as well as correction values ​​and constraints for each port, are established. Based on the multi-port power coordination control model, the model prediction optimization objective function, the correction amount and the constraints of each port, the optimal correction amount is solved, and the power correction command is generated using the optimal correction amount and sent to the port execution layer.

[0017] Preferably, the multi-port power coordination control model in step S3 includes state equations and output equations, including: The state equation is:

[0018] The output equation is:

[0019] in, State vector The derivative of , i.e., the rate of change of state; It is a state vector; The input vector; This is the interference vector; This is the output vector; , , , , For parameter matrices; in: The state vector is:

[0020] ,

[0021] In the formula, The active power adjustment deviation of port 1 is the difference between the instantaneous active power reference value and the actual value. For the first Ports Real-time active power reference value; For the first Ports Real-time active power; The reactive power adjustment deviation of port 1 is the difference between the instantaneous reactive power reference value and the actual value. For the first Ports Real-time reactive power reference value; For the first Ports Actual reactive power at any given moment; The input vector is:

[0022] ,

[0023] In the formula, For port The correction amount for the active power reference value; For the first Ports Real-time active power reference value; For the first Ports Real-time active power; For port The correction amount for the reactive power reference value; For the first Ports Real-time reactive power reference value; For the first Ports Actual reactive power at any given moment; ; The interference vector is:

[0024] In the formula, For port Coupled interference signal, ; The output vector is:

[0025] in, For port The actual output active power; For port The actual output reactive power; .

[0026] Preferably, in step S3, the objective function for model prediction optimization is:

[0027] in, To optimize the objective function; To predict the total number of steps; This is the output vector; For time; This represents the current prediction step number; The prediction step size for this model is set to 50ms here; This is a reference value for power prediction; The input vector; This is the weight matrix.

[0028] Preferably, in step S3, the correction amount and the constraints of each port include: Correction constraint: , ; Port power constraints: , ; Converter output power constraints: ; in, For the first Correction amount for active power at each port; , For the first Minimum and maximum values ​​of the correction amount for the active power of each port; For the first Correction amount for reactive power at each port; , For the first Minimum and maximum values ​​of the correction amount for reactive power at each port; For the first Reference values ​​for active power at each port; , For the first Minimum and maximum active power of each port; For the first Reference values ​​for reactive power at each port; , For the first Minimum and maximum reactive power of each port; The rated apparent power of the converter.

[0029] Preferably, in step S3, the optimal correction amount is:

[0030] in, For the first Optimal correction amount for active power at each port; For the first Optimal correction amount for reactive power at each port; .

[0031] In step S3, the power coordination and optimization layer modifies the power reference command based on the power reference command and optimizes the power allocation of each port. When an abnormal operating condition is detected in a port, the power allocation ratio of that port and related ports is adjusted to prioritize the stable operation of the system.

[0032] S4. The port execution layer generates the final power command for each port based on the power reference command and the power correction command, and uses the final power command for each port to control the corresponding port, thereby realizing the coordinated control of active and reactive power of each port.

[0033] Preferably, in step S4, the final power command for each port is:

[0034] in, For the first Reference values ​​for active power at each port; For the first Optimal correction amount for active power at each port; For the first Reference values ​​for reactive power at each port; For the first Optimal correction amount for reactive power at each port; .

[0035] Secondly, this invention provides a multi-port hybrid power cooperative hierarchical control system for distribution transformers, comprising a power main circuit system and a control main circuit system, wherein: The power main circuit system includes: Energy harvesting converters are used to extract energy from the distribution network to establish and maintain DC bus voltage; A regulating converter is used to stabilize the voltage and current on the load side and maintain the power balance of the system according to the system control requirements. Distribution transformers are used for voltage transformation, energy extraction, and electrical isolation. The main control circuit system includes: The data acquisition module is used to collect real-time operating data of the power distribution system; The power hierarchical control module includes a central system control layer, a power coordination and optimization layer, and a port execution layer. The central system control layer, power coordination and optimization layer, and port execution layer adopt a power collaborative hierarchical control method for power hierarchical control. The communication module is used to enable communication and data exchange between various units / modules in the system, facilitating system control. Relay protection modules are used to monitor the operating status of the protected unit / device / module. When a fault occurs in the equipment, the module can promptly locate the fault type and location, generate a fault signal, and isolate the fault, thereby protecting the equipment and maintaining system stability.

[0036] Preferably, the multi-port hybrid distribution transformer has a multi-port structure, including an AC bus input port, a DC bus port, a photovoltaic access port, an energy storage device access port, and a load access port.

[0037] Preferably, the distribution transformer is connected to the power distribution network on one side and to the energy harvesting converter on the other side; The DC side of both the energy harvesting converter and the regulating converter is connected to the DC bus port. The DC bus port has an external port for connecting photovoltaic devices and energy storage devices. The photovoltaic device is connected to the DC bus port via a step-up / buck converter, which uses maximum power point tracking modulation (MPPT). The energy storage device is connected to the DC bus port through a bidirectional DC / DC converter; the bidirectional DC / DC converter is used to maintain the stability of the DC bus and to regulate the charge and discharge of the difference between the power required by the DC bus and the output power of the photovoltaic system.

[0038] Preferably, the control strategy of the energy harvesting converter includes: a DC voltage outer loop control combined with a current inner loop control method, which draws energy from the grid and maintains the DC bus voltage stability by controlling the output current; The detailed control process of the energy harvesting converter includes: sampling and acquiring the three-phase output AC voltage and AC current of the energy harvesting converter; performing synchronous rotating coordinate transformation on the AC voltage and AC current to obtain the d-axis and q-axis components of the AC voltage and AC current; and achieving independent control of the d-axis and q-axis components of the control quantity by introducing feedforward decoupling control and PI controller, and then obtaining the modulation voltage through dq inverse transformation.

[0039] Preferably, the active power P1 and reactive power Q1 absorbed by the energy harvesting converter from the grid are controlled by adjusting the d-axis component I of the output current. 1dand q-axis component I 1q They are controlled independently, and P1 and Q1 are represented as follows:

[0040] in, These are the d-axis and q-axis components of the three-phase input voltage of the energy harvesting converter in the synchronous rotating coordinate system, respectively. These are the d-axis and q-axis components of the three-phase input current of the energy harvester in the synchronous rotating coordinate system, respectively.

[0041] Preferably, the modulation voltage U output by the energy harvesting converter 2d U 2q By comparing with a carrier wave, a modulated wave is generated, thereby causing the energy harvester converter to generate a corresponding modulated voltage; the modulated voltage U 2d U 2q With output current I 1d I 1q Represented as:

[0042] Introducing feedforward decoupling control and PI control, the above equation can be further rewritten as:

[0043] in, , These are the d-axis and q-axis modulated voltages output from the energy harvester converter, respectively. This is the resistance value; For the domain s; This is the inductance value; The system angular frequency; , These are the d-axis and q-axis components of the three-phase input current of the energy harvester in the synchronous rotating coordinate system, respectively. , These are the d-axis and q-axis components of the three-phase input voltage of the energy harvesting converter in the synchronous rotating coordinate system, respectively. Pass functions to the PI controller; , They are currents , The target value.

[0044] Preferably, the current , target value , Represented as:

[0045]

[0046] in, The proportional gain of the PI controller; The integral coefficient of the PI controller; These are the actual and target values ​​of the DC bus voltage, respectively.

[0047] Preferably, the regulating converter changes its modulation voltage according to the voltage command value output by the upper-level control strategy, thereby compensating for the load voltage at the load end and maintaining the stability of the load-side voltage.

[0048] The beneficial effects of this invention are: Currently, most existing control modes adopt centralized control or single-level control modes. In the centralized control mode, all port control commands are issued uniformly by the central controller, resulting in slow response speed, difficulty in responding to rapid fluctuations in distributed energy and load power, and high dependence on the stability of the central controller, leading to low system reliability. In the single-level control mode, it is impossible to balance global power balance and the control accuracy of each port, which can easily lead to problems such as power conflicts between ports and control redundancy.

[0049] The proposed "multi-port" hybrid distribution transformer system structure can simultaneously handle power flows from multiple power sources (such as distribution networks, renewable energy sources such as photovoltaics, energy storage devices such as supercapacitors, and batteries) and loads. It can flexibly connect to AC loads, DC loads, distributed energy sources, and energy storage systems, has strong versatility, and possesses efficient energy dispatch and flexible voltage regulation capabilities, enabling it to cope with diverse needs and complex operating conditions.

[0050] This invention proposes a power-coordinated hierarchical control strategy for multi-port hybrid distribution transformers. Through hierarchical control architecture design and power coordination mechanism optimization, precise allocation of active and reactive power across multiple ports is achieved through global control, coordinated control, and local control. This reduces the system control complexity under centralized control mode, improves system response speed, and enhances system reliability based on multi-layer control mode, thus avoiding system paralysis caused by a single fault under centralized control mode. Attached Figure Description

[0051] Figure 1 This is a schematic diagram of the multi-port hybrid power distribution transformer power collaborative hierarchical control system of the present invention; Figure 2 This is a schematic diagram of the wiring ports and typical wiring of the multi-port hybrid distribution transformer of the present invention; Figure 3 This is a schematic diagram of the internal structure of the multi-port hybrid distribution transformer of the present invention; Figure 4 This is a schematic diagram of the energy harvesting converter control strategy of the present invention; Figure 5This is a schematic diagram of the converter control strategy of the present invention. Detailed Implementation

[0052] The following will provide a clear and complete description of the concept, specific structure, and technical effects of the present invention in conjunction with the embodiments and accompanying drawings, so as to fully understand the purpose, features, and effects of the present invention.

[0053] like Figure 1 As shown, a multi-port hybrid distribution transformer system includes a power main circuit system and a control main circuit system; The power main circuit system mainly refers to the circuit of the multi-port hybrid distribution transformer used for voltage and current transformation and main power flow; The main power circuit unit mainly includes an energy harvesting converter, a regulating converter, and a distribution transformer; The main control circuit system includes a data acquisition module, a power hierarchical control module, a communication module, and a relay protection module.

[0054] The multi-port hybrid distribution transformer system has a multi-port structure; like Figure 2 As shown, the multi-port includes an AC bus input port, a DC bus port, a distributed energy access port (mainly a photovoltaic access port), an energy storage device access port, and a load access port.

[0055] The internal structure of the multi-port hybrid distribution transformer is as follows: Figure 3 As shown: The multi-port hybrid distribution transformer has a turns ratio of 10kVA / 220V. One side of the distribution transformer is connected to a 10kVA distribution network, and the other side is connected to an energy harvesting converter. The DC side of both the energy harvesting converter and the regulating converter is connected to the DC bus port.

[0056] The DC bus port has an external port for connecting photovoltaic and energy storage devices. The photovoltaic system is connected to the DC bus port via a step-up / buck converter. The photovoltaic boost / buck converter uses MPPT (maximum power point tracking modulation) to ensure that the photovoltaic system always outputs maximum power.

[0057] The energy storage device is connected to the DC bus port via a bidirectional DC / DC converter. The bidirectional DC / DC converter is used to maintain the stability of the DC bus and to regulate the difference between the power required by the DC bus and the output power of the photovoltaic system by charging and discharging.

[0058] The multi-port hybrid distribution transformer employs a three-layer power collaborative control strategy for the input / output power of multiple ports; The control technology adopts a three-layer hierarchical control architecture, namely, the central system control layer, the power coordination and optimization layer, and the port execution layer; The control strategy is as follows: (1) The central system control layer collects the power distribution system operation data through the data acquisition unit, including but not limited to the voltage and current data of the power distribution network side, the power of the load side, the state of charge of the energy storage system and the power of each port, etc. Based on the collected relevant data, it coordinates and sets control targets such as power / voltage / frequency of each port in a unified manner to achieve active power balance, reactive power balance, system frequency stability, etc. (2) The central system control layer uses relevant algorithms to globally allocate the total active power and total reactive power of the multi-port hybrid distribution transformer, and obtain the active power reference value and reactive power reference value of each port. In the allocation process, the following principles are followed: ① Priority photovoltaic system power supply principle. When the energy required by the load side is less and the photovoltaic output is excessive, the active power is stored through the energy storage port first; when the photovoltaic output is insufficient, the energy storage device is given priority to output power to supplement the active power required by the load side; for reactive power allocation, in order to ensure rapid adjustment of reactive power, it is given priority to achieve it through parallel converters.

[0059] (3) The power coordination optimization layer uses the corresponding algorithm to further modify the power command based on the power command of the central system control layer and optimize the power allocation of each port. When an abnormal working condition such as power overload or voltage overload is detected in a port, the power allocation ratio of the port and related ports will be automatically adjusted to ensure the stable operation of the system. (4) The port execution layer receives power commands from the central system control layer and coordination optimization layer, controls the corresponding ports, and finally realizes the coordinated control of active and reactive power of multiple ports.

[0060] The detailed control strategy is as follows: (1) Step 1 The central system control layer collects key data in real time through the data acquisition unit, including but not limited to the distribution network side voltage U. grid Current I gird Load-side power P L Distributed photovoltaic energy output power P DG The state of charge (SOC) of the energy storage system and the power P at each port. i Q i wait; With the control objectives of system active power balance, system frequency stability, and bus voltage stability, and based on real-time data acquisition by the data acquisition unit, a system optimization objective function G is established, the expression of which is as follows:

[0061] in, Optimize the objective function for the system; For coefficients; These are the photovoltaic output power, energy storage device output power, grid output power, and total load power on the load side, respectively. Output reactive power to each port; This refers to the system's operating frequency. This refers to the grid-side voltage. These are the instantaneous output power and the maximum output power of the photovoltaic system, respectively.

[0062] Set the weight coefficient k for each control objective. G The formula for adjusting the weighting coefficients is as follows:

[0063] In the formula, As the initial weights, Let be the change in deviation of the g-th target at time t; The constraints on the system parameters are as follows: ① Power constraints at each port: ,

[0064] ②Voltage and current constraints at each port: ,

[0065] ③ Charge constraints of energy storage systems:

[0066] ④ System operating frequency constraints:

[0067] (2) Step 2 Based on the sequential linear programming algorithm, the system optimization objective function G is linearized. The detailed steps are as follows: ① Initialization, setting initial values ​​for iteration:

[0068] ② At any iteration point X N At this point, the linearization objective function G(X) is:

[0069] In the formula For the objective function in X N The gradient vector at that point; ③ Based on the linearized objective function G(X) described above, and combined with the constraints in step 1, the optimal solution X for the current iteration can be obtained. N+1 ; ④ Based on iteration error Alternatively, the iteration can be terminated by determining the number of iterations, and the iteration compensation can be adjusted during the iteration process. The compensation adjustment formula is as follows: ; ⑤ By iteratively solving, the final reference values ​​of active and reactive power at each port are obtained:

[0070] (3) Step 3 The coordination and optimization layer receives active power reference values ​​for each port from the central system control layer. and reactive power reference value Meanwhile, real-time operating parameters of each port are collected to construct a multi-port power coordination control model. A model predictive control algorithm is used to dynamically correct the power command values ​​issued by the central system control layer in real time.

[0071] The process is as follows: ① Construct a multi-port power coordinated control model, and construct the state equation and output equation as follows: Equations of state:

[0072] Output equation:

[0073] in: —The state vector is: ; ,

[0074] —Input vector:

[0075] ,

[0076] —Interference vector:

[0077] —Output vector:

[0078] —A, B, C, D, and E are parameter matrices.

[0079] ② Based on the above system optimization control model, establish the model prediction optimization objective function and constraints:

[0080] In the formula: for The reference value for power prediction at time step, where Q and R are weight matrices.

[0081] The correction amount and the constraints for each port are as follows: A. Correction amount constraint: ,

[0082] B. Power constraints at the port: ,

[0083] C. Converter output power constraint:

[0084] ③ Based on the above optimization control model, objective function, and constraints, solve for the optimal correction amount:

[0085] In summary, the final power command for each port is:

[0086] (4) The port execution layer receives power commands from the central system control layer and coordination optimization layer, controls the corresponding converters, and realizes coordinated control of active and reactive power at each port.

[0087] For example Figure 3 The multi-port hybrid distribution transformer shown: The multi-port hybrid distribution transformer body involves energy harvesting converter control and regulating converter control.

[0088] The control strategy of the energy-harvesting converter is a combination of DC voltage outer loop control and current inner loop control. It draws energy from the grid and maintains the DC bus voltage stability by controlling the output current. The detailed control process of the energy harvesting converter is as follows: the three-phase output AC voltage and AC current of the energy harvesting converter are sampled and acquired; synchronous rotating coordinate transformation is performed on the AC voltage and AC current to obtain the d-axis and q-axis components of the AC voltage and AC current; by introducing feedforward decoupling control and PI controller, the d-axis and q-axis components of the control quantity are independently controlled, and then the modulation voltage is obtained through dq inverse transformation.

[0089] The active power absorbed by the power grid by the energy harvesting converter is P1, and the reactive power absorbed is Q1. This can be controlled by adjusting the d-axis component I of the output current. 1d and q-axis component I 1q If controlled independently, P1 and Q1 can be represented as:

[0090] In the formula: These are the d-axis and q-axis components of the three-phase input voltage and three-phase input current of the energy harvester in the synchronous rotating coordinate system, respectively. The modulation voltage U output by the energy harvesting converter 2d U 2q By comparing with a carrier wave, a modulated wave is generated, thereby causing the energy harvesting converter to produce a corresponding modulated voltage. The modulated voltage U... 2d U 2q With output current I 1d I 1q It can be represented as:

[0091] Introducing feedforward decoupling control and PI control, the above equation can be further rewritten as:

[0092] In the formula: Pass functions to the PI controller; The output current I is respectively 1d、 I 1q The target value; The output current I 1d、 I 1q target value It can be represented as:

[0093]

[0094] In the formula, These are the actual and target values ​​of the DC bus voltage, respectively. The control block diagram of the energy harvesting converter is as follows: Figure 4 As shown.

[0095] The regulating converter changes its modulation voltage according to the voltage command value output by the upper-level control strategy, thereby compensating for the load voltage at the load end and maintaining load-side voltage stability. Its control strategy is as follows: Figure 5 As shown.

[0096] The embodiments of the present invention have been described in detail above, but the present invention is not limited to the described embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention, and these equivalents or substitutions are all included within the scope defined by the claims of the present invention.

Claims

1. A multi-port hybrid distribution transformer power collaborative hierarchical control method, characterized in that, Includes the following steps: S1. The data acquisition module collects real-time power distribution system operation data. The central system control layer establishes a system optimization objective function and sets constraints based on the control objectives and power distribution system operation data. S2. Based on the sequential linear programming algorithm, the central system control layer linearizes the system optimization objective function in combination with the constraints to obtain the active power reference value and reactive power reference value of each port and generate power reference command. S3: The power coordination optimization layer collects real-time operating parameters of each port, constructs a multi-port power coordination control model, and uses a model predictive control algorithm to dynamically correct the power reference command in real time, obtain the optimal correction amount, and generate a power correction command. S4. The port execution layer generates the final power command for each port based on the power reference command and the power correction command, and uses the final power command for each port to control the corresponding port, thereby realizing the coordinated control of active and reactive power of each port.

2. The multi-port hybrid distribution transformer power collaborative hierarchical control method as described in claim 1, characterized in that, In step S1, the system optimization objective function is: in, Optimize the objective function for the system; For coefficients; These are the photovoltaic output power, energy storage device output power, grid output power, and total load power on the load side, respectively. Output reactive power to each port; This refers to the system's operating frequency. This refers to the grid-side voltage. These are the instantaneous output power and the maximum output power of the photovoltaic system, respectively.

3. The multi-port hybrid distribution transformer power collaborative hierarchical control method as described in claim 1, characterized in that, In step S1, each control target is assigned a corresponding weight coefficient, and the adjustment formula for the weight coefficient is as follows: in, for Weighting coefficients at different times; These are the initial weights; for Time of the first The amount of deviation change of each target; The goal is to optimize the system.

4. The multi-port hybrid distribution transformer power collaborative hierarchical control method as described in claim 1, characterized in that, Step S2 includes: S21. Set the initial value for iteration. ; in, For the first Initial values ​​of active power at each port; For the first Initial values ​​of reactive power at each port; ; S22, at any iteration point At this point, the system optimization objective function Linearization yields the linearized objective function. : in, For the objective function in The gradient vector at that point; S23. Based on the linearized objective function Based on the constraints in step S1, find the optimal solution for the current iteration. ; S24. Based on iteration error Alternatively, the iteration may be terminated after a certain number of iterations. During the iteration process, the iteration compensation is adjusted using the following formula: ;in, Iterative compensation for the N+1 iteration point, Iterative compensation for N iteration points; S25. Solve iteratively to obtain the final active power reference values ​​and reactive power reference values ​​for each port: in, For the first Reference values ​​for active power at each port; For the first Reference values ​​for reactive power at each port; ; S26. Generate a power reference command based on the active power reference value and reactive power reference value of each port, and send the power reference command to the power coordination optimization layer and the port execution layer.

5. The multi-port hybrid distribution transformer power collaborative hierarchical control method as described in claim 1, characterized in that, Step S3 includes: Construct a multi-port power coordination control model; Based on the multi-port power coordination control model, a model prediction optimization objective function, as well as correction values ​​and constraints for each port, are established. Based on the multi-port power coordination control model, the model prediction optimization objective function, the correction amount and the constraints of each port, the optimal correction amount is solved, and the power correction command is generated using the optimal correction amount and sent to the port execution layer.

6. The multi-port hybrid distribution transformer power collaborative hierarchical control method as described in claim 5, characterized in that, The multi-port power coordination control model in step S3 includes state equations and output equations, including: The state equation is: The output equation is: in, State vector The derivative of , i.e., the rate of change of state; It is a state vector; The input vector; This is the interference vector; This is the output vector; , , , , For parameter matrices; in: The state vector is: ， In the formula, The active power adjustment deviation of port 1 is the difference between the instantaneous active power reference value and the actual value. For the first Ports Real-time active power reference value; For the first Ports Real-time active power; The reactive power adjustment deviation of port 1 is the difference between the instantaneous reactive power reference value and the actual value. For the first Ports Real-time reactive power reference value; For the first Ports Actual reactive power at any given moment; The input vector is: ， In the formula, For port The correction amount for the active power reference value; For the first Ports Real-time active power reference value; For the first Ports Real-time active power; For port The correction amount for the reactive power reference value; For the first Ports Real-time reactive power reference value; For the first Ports Actual reactive power at any given moment; ; The interference vector is: In the formula, For port Coupled interference signal, ; The output vector is: in, For port The actual output active power; For port The actual output reactive power; .

7. The multi-port hybrid distribution transformer power collaborative hierarchical control method as described in claim 5, characterized in that, In step S3, the objective function for model prediction optimization is: in, To optimize the objective function; To predict the total number of steps; This is the output vector; For time; This represents the current prediction step number; The prediction step size for this model is set to 50ms here; This is a reference value for power prediction; The input vector; This is the weight matrix.

8. The multi-port hybrid distribution transformer power collaborative hierarchical control method as described in claim 1, characterized in that, In step S4, the final power command for each port is: in, For the first Reference values ​​for active power at each port; For the first Optimal correction amount for active power at each port; For the first Reference values ​​for reactive power at each port; For the first Optimal correction amount for reactive power at each port; .

9. A multi-port hybrid power distribution transformer power collaborative hierarchical control system, characterized in that, It includes the power main circuit system and the control main circuit system, wherein: The power main circuit system includes: Energy harvesting converters are used to extract energy from the distribution network to establish and maintain DC bus voltage; A regulating converter is used to stabilize the voltage and current on the load side and maintain the power balance of the system according to the system control requirements. Distribution transformers are used for voltage transformation, energy extraction, and electrical isolation. The main control circuit system includes: The data acquisition module is used to collect real-time operating data of the power distribution system; The power hierarchical control module includes a central system control layer, a power coordination optimization layer, and a port execution layer. The central system control layer, power coordination optimization layer, and port execution layer use the power collaborative hierarchical control method of any one of claims 1-8 to perform power hierarchical control. The communication module is used to enable communication and data exchange between various units / modules in the system; The relay protection module is used to monitor the operating status of the protected unit / device / module. When a fault occurs in the equipment, it can promptly locate the fault type and location, generate a fault signal, and isolate the fault.

10. The multi-port hybrid distribution transformer power collaborative hierarchical control system as described in claim 9, characterized in that, The control strategy of the energy harvesting converter includes: DC voltage outer loop control combined with current inner loop control, energy is harvested from the grid, and the DC bus voltage is maintained stable by controlling the output current. The detailed control process of the energy harvesting converter includes: sampling and acquiring the three-phase output AC voltage and AC current of the energy harvesting converter; performing synchronous rotating coordinate transformation on the AC voltage and AC current to obtain the d-axis and q-axis components of the AC voltage and AC current; and achieving independent control of the d-axis and q-axis components of the control quantity by introducing feedforward decoupling control and PI controller, and then obtaining the modulation voltage through dq inverse transformation.

Images