Flexible resource coordination control method for power distribution network

Abstract

The invention discloses a power distribution network-oriented flexibility resource coordination control method, which comprises the following steps of: performing preliminary site selection on access nodes of flexibility resources in a power distribution network, and calculating a power-voltage sensitivity matrix of the power distribution network under different flexibility resource access schemes through a Jacobian matrix of a Newton-Raphson iterative power flow algorithm; the power-voltage sensitivity matrix is combined with the active power variable quantity of the access node when the flexibility resource is accessed to correct the variable quantity of the voltage module value of the node in the power distribution network; and carrying out statistics on variable quantities of voltage module values of the nodes under different flexible resource access schemes, and selecting the flexible resource access scheme with the minimum total variable quantity of the voltage module values of all the nodes as a flexible resource coordination control scheme. And the problem of voltage out-of-limit of each node of the power distribution network is solved by optimizing and controlling the grid-connected power of the access node in real time, adjusting the active and reactive power output of multiple flexible resources of the power distribution network and coordinating and configuring the locating and sizing scheme of the intelligent remote control switch of the power distribution network.

Description

Technical Field

[0001] This invention relates to the field of power distribution network technology, and more specifically, to a method for coordinated control of flexible resources in power distribution networks. Background Technology

[0002] To address major issues such as energy shortages and environmental pollution, and to actively promote the construction of new power systems, large-scale renewable energy generation is continuously replacing the previously dominant fossil fuel power generation. Load characteristics are also gradually shifting from rigid, consumption-driven to flexible, production-driven. The randomness, intermittency, and volatility of new energy generation, along with the unavoidable prediction errors of flexible loads, have led to a series of challenges for traditional distribution networks, including uneven power flow distribution, increased operational complexity, and decreased voltage quality.

[0003] The new distribution network under the energy system transformation is characterized by the integration of multiple distributed and flexible resources. However, with the increasing penetration of various flexible resources such as energy storage devices, distributed photovoltaics, and wind turbines, the power flow in the distribution network exhibits multidirectional changes, leading to increasingly prominent problems such as voltage exceeding limits and increased network losses, seriously affecting the safe and stable operation of the power system. Therefore, how to rationally optimize the allocation of different types of flexible resources to enable them to synergistically improve the safety, stability, and economy of the distribution network is a crucial issue that urgently needs to be addressed after the integration of multiple flexible resources.

[0004] Therefore, the coordinated control of various flexible resources within new distribution networks plays a crucial role. Effective control strategies for these resources can fully leverage their active and reactive power regulation capabilities, addressing issues such as voltage exceeding limits, increased network losses, and wind and solar power curtailment caused by large-scale distributed generation. Simultaneously improving the operational safety and economy of active distribution networks while scientifically and dynamically regulating various flexible resources within them has become a shared concern for both academia and industry. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention provides a flexible resource coordination control method for distribution networks. Based on correcting the changes in voltage magnitude at nodes in the distribution network, it realizes the location, capacity setting, and optimization control of multiple flexible resources in the distribution network. This solves the voltage over-limit problem of each node in the distribution network under multiple flexible resources connected to the grid, and optimizes the voltage deviation of each node. It can effectively improve the voltage quality of the distribution network under multiple flexible resources connected to the grid, thereby improving its operational safety and power supply reliability.

[0006] To achieve the above technical objectives, the present invention adopts the following technical solution:

[0007] A method for coordinated control of flexibility resources in distribution networks includes the following steps: Step S1: Perform preliminary site selection for the access nodes of flexible resources in the distribution network, and calculate the power-voltage sensitivity matrix of the distribution network under different flexible resource access schemes using the Jacobian matrix of the Newton-Raphson iterative power flow algorithm. Step S2: Combine the power-voltage sensitivity matrix with the change in active power of the access node when accessing flexible resources to correct the change in voltage magnitude of the node in the distribution network; Step S3: Calculate the change in voltage magnitude of nodes under different flexible resource access schemes, and select the flexible resource access scheme with the smallest total change in voltage magnitude of all nodes as the flexible resource coordination and control scheme.

[0008] Furthermore, the correction process for the change in voltage magnitude at nodes in the distribution network is as follows:

[0009] in, Represents nodes in a distribution network The change in voltage magnitude at that point This indicates the number of flexible resource access schemes. express index, This represents the number of nodes accessing flexible resources in the distribution network. express index, Indicating flexible resource access solutions At the access node Changes in active power cause node Sensitivity to changes in voltage magnitude Indicating flexible resource access solutions At the access node The change in active power over time.

[0010] Furthermore, it also includes: adjusting the grid-connected power of the access node based on the change in the voltage magnitude of the node under the flexible resource coordination control scheme, so as to avoid the voltage of the access node exceeding the limit.

[0011] Furthermore, the adjustment process for the grid-connected power of the access node is as follows:

[0012] in, This indicates the access node under the flexible resource coordination and control scheme. The amount of grid-connected power adjustment, Indicates the number of nodes in the distribution network. express index, Represents nodes in a distribution network Voltage magnitude at that point Represents nodes in a distribution network The change in voltage magnitude at that point Represents nodes in a distribution network The maximum allowable voltage magnitude at that location The matrix elements represent the inverted power-voltage sensitivity matrix of the distribution network under the flexible resource coordination control scheme.

[0013] Furthermore, it also includes: i: Construct a fitness function based on the voltage changes at each node of the distribution network and the output power of flexible resources; ii: Identify the node with the largest change in voltage magnitude under the flexible resource coordination control scheme as the power control node, randomly initialize the injected power of the flexible resources at the power control node as the individual particles of the particle swarm algorithm, and set the size of the individual particles. iii: Check whether each individual particle satisfies the distribution network constraints. If so, calculate the fitness function value of each individual particle and retain the individual particle with the smallest fitness function value. Update the remaining individual particles through crossover and mutation. Otherwise, update the individual particles using the boundary values ​​of the distribution network constraints. iv: Repeat step iii for the updated particle, retaining the particle with the smallest fitness function value; v: Repeat steps iii-iv until the absolute error between the fitness function value of the retained particle and the fitness function value of the previously retained particle is less than the threshold. The finally retained particle is taken as the optimal solution for injecting power into the flexibility resources at the power control node.

[0014] Furthermore, the construction process of the fitness function is as follows:

[0015] in, This represents the normalized value of the node voltage offset in the distribution network. , Indicates the number of nodes in the distribution network. express index, Indicates time h Next node k voltage magnitude, Represents a node k The rated voltage value, express Weighting coefficients; This represents the normalized error between the actual active power output and the predicted active power of flexible resources in the distribution network. , This indicates the number of access nodes under the flexible resource coordination and control scheme. express index, Indicates time h Downstream access node The flexibility of resources actually outputs active power. Indicates time h Downstream access node The flexibility of resource forecasting active power, Weighting coefficients; This represents the normalized error between the actual reactive power output and the predicted reactive power of flexible resources in the distribution network. , Indicates time h Downstream access node The actual reactive power output of the flexible resources. Indicates access node The rated capacity of flexible resources, express Weighting coefficients; .

[0016] Furthermore, the distribution network constraints include: distribution network power flow balance constraints, node voltage variation constraints, energy storage device charging and discharging constraints, distributed photovoltaic power generation operation constraints, on-load tap-changing transformer operation constraints, parallel capacitor constraints, and static var compensator constraints.

[0017] Furthermore, it also includes: i: Set the maximum allowable number of smart remote control switches to be installed in the distribution network, and construct the annual overall operating cost objective function for smart remote control switches; ii: Arrange the changes in node voltage magnitude under the flexible resource coordination control scheme in descending order, and select the node with the largest change in node voltage magnitude as the installation location of the intelligent remote control switch. The number of selected nodes is the same as the maximum allowable number of installations. iii: Optimize the installation capacity of smart remote control switches with the objective function of minimizing the overall annual operating cost of smart remote control switches; iv: Under the optimal installation capacity of the intelligent remote control switch, determine whether the operating status of the distribution network meets the constraints of the distribution network. If so, use the installation location and optimal installation capacity of the intelligent remote control switch as the site selection and capacity setting scheme for the intelligent remote control switch; otherwise, proceed to step v. v: Reduce the maximum allowed number of smart remote control switches one by one, repeating steps ii-iv.

[0018] Furthermore, the process of constructing the annual overall operating cost objective function of the intelligent remote control switch is as follows:

[0019] in, This indicates the overall annual operating cost of the smart remote control switch. This indicates the total investment cost of the smart remote control switch within one year. , This represents the set of installation nodes for a smart remote control switch. All indicate index, Indicates the installation node of the smart remote control switch and The actual capacity of the intelligent remote control switch. This indicates the unit capacity investment cost of the smart remote control switch. Indicates the specified service life of the smart remote control switch; This indicates the total maintenance cost of a smart remote control switch over one year. , This represents the maintenance cost coefficient of a smart remote control switch within one year. This indicates the total electricity cost of a smart remote control switch over one year. , This represents the annual power consumption cost coefficient of a smart remote control switch. Indicates time period Installation nodes of the smart remote control switch and The active power loss caused by installing intelligent remote control switches.

[0020] Furthermore, the constraints include: power flow balance constraints of the distribution network, node voltage variation constraints, energy storage device charging and discharging constraints, distributed photovoltaic power generation operation constraints, on-load tap-changing transformer operation constraints, parallel capacitor constraints, static var compensator constraints, active power constraints, reactive power constraints, and capacity constraints.

[0021] Compared with the prior art, the present invention has the following beneficial effects: (1) The flexible resource coordination control method of the present invention for distribution networks determines the access scheme of flexible resources of distribution networks based on the change of voltage magnitude of nodes in the distribution network, fully considers the nonlinear change characteristics of voltage sensitivity of distribution network nodes under multiple flexible resources access, improves the traditional voltage sensitivity calculation method, and evaluates the advantages and disadvantages of flexible resource access schemes of distribution networks. (2) The flexible resource coordination control method of the present invention for distribution networks adjusts the grid-connected power of the access node under the access scheme of the flexible resources of the power grid, effectively preventing the node voltage over-limit problem in the steady-state operation of the distribution network after accessing the flexible resources; (3) The flexible resource coordination control method of the present invention for distribution networks optimizes and adjusts the injected power of flexible resources at the power control node by constructing a fitness function based on the voltage change of each node in the distribution network and the output power of flexible resources. This helps to suppress voltage instability and power flow fluctuation caused by the grid connection of multiple flexible resources, achieve their friendly access, and improve the safety and economy of distribution network operation. (4) The flexible resource coordination control method of the present invention for distribution networks optimizes the scheme of intelligent remote control switch location and capacity setting by constructing an annual overall operating cost objective function for intelligent remote control switches. This can effectively save the overall operating cost of distribution networks and improve system voltage, which is conducive to improving the economy and reliability of distribution network operation.

[0022] In summary, this invention solves the voltage over-limit problem of each node in the distribution network by optimizing the grid-connected power of the access node in real time, adjusting the active and reactive power output of the multiple flexible resources of the distribution network, and coordinating the configuration of the intelligent remote control switch location and capacity setting scheme of the distribution network. This optimizes the voltage deviation and over-limit of each node in the distribution network, and overall achieves a dual improvement in the safety of distribution network operation and the reliability of power supply. Attached Figure Description

[0023] Figure 1 This is a flowchart of the flexible resource coordination control method for power distribution networks according to the present invention. Figure 2 A flowchart illustrating the optimization of injection power for flexibility resources using this invention; Figure 3 This is a flowchart illustrating the application of this invention for intelligent remote control switch addressing and capacity determination. Detailed Implementation

[0024] The technical solution of the present invention will be further explained and described below with reference to the accompanying drawings.

[0025] like Figure 1 This is a flowchart of the flexible resource coordination control method for distribution networks according to the present invention. The flexible resource coordination control method includes the following steps: Step S1: Preliminary site selection is performed for the access nodes of flexible resources in the distribution network. These flexible resources include energy storage devices, distributed photovoltaic systems, and wind turbines. The power-voltage sensitivity matrix of the distribution network under different flexible resource access schemes is calculated using the Jacobian matrix of the Newton-Raphson iterative power flow algorithm. Specifically: Under the polar coordinate Newton-Raphson power flow algorithm, the Jacobian matrix for power flow calculation in a distribution network is:

[0026] Among them, △ P , △ Q , △ δ , △ U These are column vector matrices representing the active power, reactive power, voltage phase angle, and voltage amplitude changes at each node in the distribution network. H Pδ , N PU , J Qδ , L QU These are submatrices of the Jacobian matrix, which are divided into blocks according to four relationships: active power-voltage phase angle, active power-voltage magnitude, reactive power-voltage phase angle, and reactive power-voltage magnitude.

[0027] Inverting the Jacobian matrix above yields the power-voltage sensitivity matrix of the node:

[0028] in, S Pδ , S PU , S Qδ , S QU These represent the sensitivity matrices for active power-voltage phase angle, active power-voltage magnitude, reactive power-voltage phase angle, and reactive power-voltage magnitude, respectively.

[0029] In new power systems, the resistance and reactance of distribution network lines are similar, meaning that changes in the node voltage magnitude are related to changes in both active and reactive power at the nodes. Therefore, considering the actual operation of typical flexibility resources at each node in the distribution network, energy storage devices generally prioritize adjusting the injected active power to maintain node voltage stability. Distributed photovoltaic systems typically operate in unity power factor mode, so the impact of reactive power changes on the node voltage magnitude can be ignored, and Δ... Q =0, further combining with the Jacobian matrix, we have:

[0030] Solution:

[0031] Expand the active power-voltage magnitude sensitivity matrix S PU We can obtain:

[0032] in, s ij Indicates due to node j Changes in active power cause node i Sensitivity to changes in voltage magnitude.

[0033] Step S2: Combine the power-voltage sensitivity matrix with the change in active power of the access node when accessing flexibility resources to correct the change in voltage magnitude of the nodes in the distribution network. Specifically: for any node in the distribution network k The change in voltage magnitude can be expressed by the following formula:

[0034] Obviously, nodes k The voltage change at a given point is influenced by the combined effects of changes in active power at all nodes in the distribution network. However, when selecting a node flexibility resource access scheme, since the differences between different access capacity values ​​are relatively small, the node can be considered as... k The voltage change at a given point is the result of the successive superposition of small active power disturbances caused by different grid connection capacities when selecting flexibility resources at each node, thus yielding a correction value for the change in the voltage magnitude at each node in the distribution network:

[0035] in, Represents nodes in a distribution network The change in voltage magnitude at that point This indicates the number of flexible resource access schemes. express index, This represents the number of nodes accessing flexible resources in the distribution network. express index, Indicating flexible resource access solutions At the access node Changes in active power cause node Sensitivity to changes in voltage magnitude Indicating flexible resource access solutions At the access node The change in active power over time.

[0036] Step S3: Statistically analyze the changes in the voltage magnitude of nodes under different flexible resource access schemes, select the flexible resource access scheme with the smallest total change in the voltage magnitude of all nodes as the flexible resource coordination control scheme, fully consider the nonlinear variation characteristics of the voltage sensitivity of distribution network nodes under multiple flexible resource access, improve the traditional voltage sensitivity calculation method, and evaluate the advantages and disadvantages of the flexible resource access schemes of the distribution network.

[0037] In one technical solution of the present invention, in order to avoid voltage over-limit at each node in the distribution network, the grid-connected power of the access node is adjusted according to the change in the voltage modulus of the node under the flexible resource coordination control scheme, so that the voltage of each node in the distribution network will not exceed the limit under this access scheme.

[0038] The process of adjusting the grid-connected power of the access node is as follows:

[0039] in, This indicates the access node under the flexible resource coordination and control scheme. The amount of grid-connected power adjustment, Indicates the number of nodes in the distribution network. express index, Represents nodes in a distribution network The voltage limit is exceeded after the flexible access resources are connected. This indicates the nodes in the distribution network after the flexible resources are connected. Voltage magnitude at that point Represents nodes in a distribution network Voltage magnitude at that point Represents nodes in a distribution network The change in voltage magnitude at that point Represents nodes in a distribution network The maximum allowable voltage magnitude at that location The matrix elements represent the inverted power-voltage sensitivity matrix of the distribution network under the flexible resource coordination control scheme.

[0040] In one technical solution of this invention, to achieve real-time voltage regulation of each node in a distribution network after the integration of various flexible resources, the problem of voltage exceeding limits at each node in the network is solved by the coordinated control of various flexible resources in the distribution network. This helps to suppress voltage instability and power flow fluctuations caused by the integration of multiple flexible resources, achieves friendly access, and improves the safety and economy of distribution network operation. Figure 2 ,include: i: Construct a fitness function based on the voltage changes of each node in the distribution network and the output power of flexible resources, in order to minimize the voltage deviation of the distribution network nodes from the rated value, minimize the active power loss during steady-state operation, and maximize the output power of the access flexible resources.

[0041] fitness function The construction process is as follows:

[0042] in, This represents the normalized value of the node voltage offset in the distribution network. , Indicates the number of nodes in the distribution network. express index, Indicates time h Next node k voltage magnitude, Represents a node k The rated voltage value, express Weighting coefficients; This represents the normalized error between the actual active power output and the predicted active power of flexible resources in the distribution network. , This indicates the number of access nodes under the flexible resource coordination and control scheme. express index, Indicates time h Downstream access node The flexibility of resources actually outputs active power. Indicates time h Downstream access node The flexibility of resource forecasting active power, Weighting coefficients; This represents the normalized error between the actual reactive power output and the predicted reactive power of flexible resources in the distribution network. , Indicates time h Downstream access node The actual reactive power output of the flexible resources. Indicates access node The rated capacity of flexible resources, express Weighting coefficients; .

[0043] ii: Identify the node with the largest change in voltage magnitude under the flexible resource coordination control scheme as the power control node, randomly initialize the injected power of the flexible resources at the power control node as the individual particles of the particle swarm algorithm, and set the size of the individual particles. iii: Check whether each individual particle satisfies the distribution network constraints. If so, calculate the fitness function value of each individual particle and retain the individual particle with the smallest fitness function value. Update the remaining individual particles through crossover and mutation. Otherwise, update the individual particles using the boundary values ​​of the distribution network constraints. iv: Repeat step iii for the updated particle, retaining the particle with the smallest fitness function value; v: Repeat steps iii-iv until the absolute error between the fitness function value of the retained particle and the fitness function value of the previously retained particle is less than the threshold. The finally retained particle is taken as the optimal solution for injecting power into the flexibility resources at the power control node.

[0044] In one technical solution of the present invention, the distribution network constraints include: distribution network power flow balance constraints, node voltage change constraints, energy storage device charging and discharging constraints, distributed photovoltaic power generation operation constraints, on-load tap-changing transformer operation constraints, parallel capacitor constraints, and static var compensator constraints.

[0045] Power flow balance constraints in distribution networks:

[0046] in, , They are time points h Next node k Active power and reactive power at the location, For a moment h Next node Voltage magnitude at that point G ki , B ki They are nodes With nodes The conductivity and susceptance between them δ ki For nodes With nodes The phase angle difference between the voltages.

[0047] Node voltage variation constraints:

[0048] in, , They are nodes kThe minimum and maximum allowable values ​​of the voltage at the location.

[0049] Energy storage device charge and discharge constraints:

[0050] in, For a moment Downstream access node The active power output of the energy storage device connected to the location. , Representing access nodes The minimum and maximum charging and discharging power of the energy storage device connected to the location. For a moment h Downstream access node The state of charge of the energy storage device connected to the site. , Representing access nodes The lower and upper limits of the state of charge of the energy storage device connected to the site.

[0051] Operating constraints of distributed photovoltaic power generation:

[0052] in, , Representing time respectively h Downstream access node The active and reactive power outputs of the distributed photovoltaic system connected to the grid via inverters are measured. For access nodes The maximum apparent power that the inverter can provide is... For a moment h Downstream access node The power factor angle of the distributed photovoltaic grid-connected output.

[0053] On-load tap-changing transformer (OLTC) operating constraints:

[0054] in, Indicates time h Next node k With nodes p The actual gear ratios of the OLTC. Indicates time h Next node k With nodes p The gear position of OLTC. Represents a node k With nodes p Adjustment step size of OLTC , They are nodesk With nodes p The lower and upper limits of the OLTC gear range.

[0055] Parallel capacitor constraints:

[0056] in, Indicates time h Next node k The operational capacity of the parallel capacitor reactive power compensation system. Represents a node k The reactive power compensation for each stage of the parallel capacitor. For nodes k The initial operating capacity of the parallel capacitors under original compensation. , The time is obtained by forming a binary code. h Next node k The position of the parallel capacitor. This represents the exponent, which can take the value of 0 or 1.

[0057] Static Var Compensator (SVC) Constraints:

[0058] in, Indicates time h Next node k The operational capacity of SVC reactive power compensation , They are nodes k The lower and upper limits of the permissible operational capacity when the SVC continuously performs reactive power compensation.

[0059] In one technical solution of this invention, among the various flexible resources connected to the distribution network, a Smart Remote Control Switch (SRCS) can replace a traditional tie switch, enabling real-time control of the active and reactive power between two adjacent feeders at its installation location. To further improve the voltage deviation of each node in the distribution network, the corrected voltage sensitivity values ​​of all nodes are sorted from largest to smallest to obtain the corresponding node locations for priority installation of the Smart Remote Control Switch. The problem of determining the installation capacity of the Smart Remote Control Switch is transformed into a second-order cone programming problem through cone relaxation, allowing the site selection and capacity determination of the Smart Remote Control Switch to reduce its overall cost while optimizing the voltage quality of the distribution network, thereby improving the operational economy of the distribution network. Simultaneously, since the power regulation capability and overall operating cost of the Smart Remote Control Switch are directly related to its installation capacity, after determining suitable installation nodes by combining the required number of Smart Remote Control Switches and the corrected voltage sensitivity values ​​of each node in the distribution network, it is necessary to optimize the installation capacity of the switch. Figure 3 ,include: i: Set the maximum allowable number of smart remote control switches to be installed in the distribution network, and construct the annual overall operating cost objective function for smart remote control switches: The process of constructing the annual overall operating cost objective function for intelligent remote control switches is as follows:

[0060] in, This indicates the overall annual operating cost of the smart remote control switch. This indicates the total investment cost of the smart remote control switch within one year. , This represents the set of installation nodes for a smart remote control switch. All indicate index, Indicates the installation node of the smart remote control switch and The actual capacity of the intelligent remote control switch. This indicates the unit capacity investment cost of the smart remote control switch. Indicates the specified service life of the smart remote control switch; This indicates the total maintenance cost of a smart remote control switch over one year. , This represents the maintenance cost coefficient of a smart remote control switch within one year. This indicates the total electricity cost of a smart remote control switch over one year. , This represents the annual power consumption cost coefficient of a smart remote control switch. Indicates time period Installation nodes of the smart remote control switch and The active power loss caused by installing intelligent remote control switches.

[0061] ii: Arrange the changes in node voltage magnitude under the flexible resource coordination control scheme in descending order, and select the node with the largest change in node voltage magnitude as the installation location of the intelligent remote control switch. The number of selected nodes is the same as the maximum allowable number of installations. iii: Optimize the installation capacity of smart remote control switches with the objective function of minimizing the overall annual operating cost of smart remote control switches; iv: Under the optimal installation capacity of the intelligent remote control switch, determine whether the operating status of the distribution network meets the constraints of the distribution network. If so, use the installation location and optimal installation capacity of the intelligent remote control switch as the site selection and capacity setting scheme for the intelligent remote control switch; otherwise, proceed to step v. v: Reduce the maximum allowed number of smart remote control switches one by one, repeating steps ii-iv.

[0062] In one technical solution of the present invention, the constraints include: power flow balance constraints of distribution network, node voltage change constraints, energy storage device charging and discharging constraints, distributed photovoltaic power generation operation constraints, on-load tap-changing transformer operation constraints, parallel capacitor constraints, static var compensator constraints, active power constraints, reactive power constraints, and capacity constraints.

[0063] Active power constraint:

[0064] Reactive power constraint:

[0065] Capacity constraints:

[0066] in, , They represent time periods respectively. Installation nodes for smart remote control switches p The active power and loss of the power grid are considered. , They represent time periods respectively. Installation nodes for smart remote control switches q The active power and loss of the power grid are considered. , These represent the installation nodes of the smart remote control switch. p、 q Active power loss coefficient at the location; , They represent time periods respectively. Installation nodes for smart remote control switches p, q The reactive power of the injection network, , and , These represent the installation nodes of the smart remote control switch. p、 q The lower and upper limits of reactive power in the power grid; , They represent time periods respectively. Installation nodes for smart remote control switches p, q Grid connection capacity at the location.

[0067] This invention solves the voltage over-limit problem of each node in the distribution network by optimizing the grid-connected power of the access node in real time, adjusting the active and reactive power output of the multiple flexible resources of the distribution network, and coordinating the configuration of the intelligent remote control switch location and capacity setting scheme of the distribution network. It optimizes the voltage deviation and over-limit of each node in the distribution network, and overall achieves a two-way improvement in the safety of distribution network operation and the reliability of power supply.

[0068] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A flexible resource coordination control method for distribution networks, characterized in that, Includes the following steps: Step S1: Perform preliminary site selection for the access nodes of flexible resources in the distribution network, and calculate the power-voltage sensitivity matrix of the distribution network under different flexible resource access schemes using the Jacobian matrix of the Newton-Raphson iterative power flow algorithm. Step S2: Combine the power-voltage sensitivity matrix with the change in active power of the access node when accessing flexible resources to correct the change in voltage magnitude of the node in the distribution network; Step S3: Calculate the change in voltage magnitude of nodes under different flexible resource access schemes, and select the flexible resource access scheme with the smallest total change in voltage magnitude of all nodes as the flexible resource coordination and control scheme.

2. The flexible resource coordination control method for distribution networks according to claim 1, characterized in that, The correction process for the change in voltage magnitude at nodes in a distribution network is as follows: in, Represents nodes in a distribution network The change in voltage magnitude at that point This indicates the number of flexible resource access schemes. express index, This represents the number of nodes accessing flexible resources in the distribution network. express index, Indicating flexible resource access solutions At the access node Changes in active power cause node Sensitivity to changes in voltage magnitude Indicating flexible resource access solutions At the access node The change in active power over time.

3. The flexible resource coordination control method for distribution networks according to claim 1, characterized in that, Also includes: The grid-connected power of the access node is adjusted based on the change in the voltage magnitude of the node under the flexible resource coordination control scheme to prevent the voltage of the access node from exceeding the limit.

4. The flexible resource coordination control method for distribution networks according to claim 3, characterized in that, The process for adjusting the grid connection power of the access node is as follows: in, This indicates the access node under the flexible resource coordination and control scheme. The amount of grid-connected power adjustment, Indicates the number of nodes in the distribution network. express index, Represents nodes in a distribution network Voltage magnitude at that point Represents nodes in a distribution network The change in voltage magnitude at that point Represents nodes in a distribution network The maximum allowable voltage magnitude at that location The matrix elements represent the inverted power-voltage sensitivity matrix of the distribution network under the flexible resource coordination control scheme.

5. A flexible resource coordination control method for distribution networks according to claim 1, characterized in that, Also includes: i: Construct a fitness function based on the voltage changes at each node of the distribution network and the output power of flexible resources; ii: Identify the node with the largest change in voltage magnitude under the flexible resource coordination control scheme as the power control node, randomly initialize the injected power of the flexible resources at the power control node as the individual particles of the particle swarm algorithm, and set the size of the individual particles. iii: Check whether each individual particle satisfies the distribution network constraints. If so, calculate the fitness function value of each individual particle and retain the individual particle with the smallest fitness function value. Update the remaining individual particles through crossover and mutation. Otherwise, update the individual particles using the boundary values ​​of the distribution network constraints. iv: Repeat step iii for the updated particle, retaining the particle with the smallest fitness function value; v: Repeat steps iii-iv until the absolute error between the fitness function value of the retained particle and the fitness function value of the previously retained particle is less than the threshold. The finally retained particle is taken as the optimal solution for injecting power into the flexibility resources at the power control node.

6. A flexible resource coordination control method for distribution networks according to claim 5, characterized in that, The process of constructing the fitness function is as follows: in, This represents the normalized value of the node voltage offset in the distribution network. , Indicates the number of nodes in the distribution network. express index, Indicates time h Next node k voltage magnitude, Represents a node k The rated voltage value, express Weighting coefficients; This represents the normalized error between the actual active power output and the predicted active power of flexible resources in the distribution network. , This indicates the number of access nodes under the flexible resource coordination and control scheme. express index, Indicates time h Downstream access node The flexibility of resources actually outputs active power. Indicates time h Downstream access node The flexibility of resource forecasting active power, express Weighting coefficients; This represents the normalized error between the actual reactive power output and the predicted reactive power of flexible resources in the distribution network. , Indicates time h Downstream access node The actual reactive power output of the flexible resources. Indicates access node The rated capacity of flexible resources, express Weighting coefficients; .

7. A flexible resource coordination control method for distribution networks according to claim 5, characterized in that, The distribution network constraints include: distribution network power flow balance constraints, node voltage variation constraints, energy storage device charging and discharging constraints, distributed photovoltaic power generation operation constraints, on-load tap-changing transformer operation constraints, parallel capacitor constraints, and static var compensator constraints.

8. A flexible resource coordination control method for distribution networks according to claim 1, characterized in that, Also includes: i: Set the maximum allowable number of smart remote control switches to be installed in the distribution network, and construct the annual overall operating cost objective function for smart remote control switches; ii: Arrange the changes in node voltage magnitude under the flexible resource coordination control scheme in descending order, and select the node with the largest change in node voltage magnitude as the installation location of the intelligent remote control switch. The number of selected nodes is the same as the maximum allowable number of installations. iii: Optimize the installation capacity of smart remote control switches with the objective function of minimizing the overall annual operating cost of smart remote control switches; iv: Under the optimal installation capacity of the intelligent remote control switch, determine whether the operating status of the distribution network meets the constraints of the distribution network. If so, use the installation location and optimal installation capacity of the intelligent remote control switch as the site selection and capacity setting scheme for the intelligent remote control switch; otherwise, proceed to step v. v: Reduce the maximum allowed number of smart remote control switches one by one, repeating steps ii-iv.

9. A flexible resource coordination control method for distribution networks according to claim 8, characterized in that, The process of constructing the annual overall operating cost objective function of the intelligent remote control switch is as follows: in, This indicates the overall annual operating cost of the smart remote control switch. This indicates the total investment cost of the smart remote control switch within one year. , This represents the set of installation nodes for a smart remote control switch. All indicate index, Indicates the installation node of the smart remote control switch and The actual capacity of the intelligent remote control switch. This indicates the unit capacity investment cost of the smart remote control switch. Indicates the specified service life of the smart remote control switch; This indicates the total maintenance cost of a smart remote control switch over one year. , This represents the maintenance cost coefficient of a smart remote control switch within one year. This indicates the total electricity cost of a smart remote control switch over one year. , This represents the annual power consumption cost coefficient of a smart remote control switch. Indicates time period Installation nodes of the smart remote control switch and The active power loss caused by installing intelligent remote control switches.

10. A method for coordinated control of flexible resources in a distribution network according to claim 8, characterized in that, The constraints include: power flow balance constraints of distribution network, node voltage variation constraints, energy storage device charging and discharging constraints, distributed photovoltaic power generation operation constraints, on-load tap-changing transformer operation constraints, parallel capacitor constraints, static var compensator constraints, active power constraints, reactive power constraints, and capacity constraints.

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