Flexible interconnection system cooperative control method based on dynamic line loss optimization

Abstract

The invention discloses a flexible interconnection system cooperative control method based on dynamic line loss optimization. According to the method, the influence of power adjustment on line loss is quantified in real time through dynamic line loss sensitivity analysis, a cooperative control strategy with line loss minimization as the core is constructed, and global line loss optimization of the flexible interconnection system is achieved. The method improves the energy efficiency of the power distribution network, and adapts to the real-time fluctuation of distributed energy and load.

Description

Technical Field

[0001] This invention belongs to the field of power system optimization control technology, and in particular relates to a collaborative control method for flexible interconnected systems based on dynamic line loss optimization. Background Technology

[0002] With the large-scale integration of distributed energy sources such as photovoltaics and wind power, the power distribution network has evolved from a traditional radial network into a complex system with multiple power sources and multiple loads. Flexible interconnection technology (such as flexible interconnection switches and distributed converters) has become a key means to improve system flexibility because it can flexibly adjust the power exchange between nodes.

[0003] However, in existing technologies, the control strategies of flexible interconnected systems mostly focus on voltage stability, power distribution, or renewable energy consumption, with line loss optimization usually treated as a secondary objective. A systematic approach centered on minimizing line loss has not yet been developed. Firstly, the control strategies are based on static line loss models, failing to consider real-time fluctuations in load and distributed energy output, leading to a decline in line loss optimization effectiveness over time. Secondly, decentralized control is frequently employed, with each flexible device adjusting independently, lacking global coordination; local optima may result in increased overall line loss. Thirdly, the power regulation potential of flexible interconnected systems has not been fully explored, resulting in insufficient depth and real-time performance in line loss optimization.

[0004] In summary, it is necessary to propose a collaborative control method for flexible interconnected systems based on dynamic line loss optimization to provide support for application personnel's decision-making. Summary of the Invention

[0005] The purpose of this invention is to provide a collaborative control method for flexible interconnected systems based on dynamic line loss optimization, which realizes global line loss optimization of flexible interconnected systems, improves the energy efficiency of distribution networks, and adapts to real-time fluctuations in distributed energy resources and loads.

[0006] To achieve the objectives of this invention, on one hand, this invention provides a cooperative control method for flexible interconnected systems based on dynamic line loss optimization, comprising the following steps:

[0007] S1. Collect operational data using sensors deployed at each node and branch of the flexible interconnected system, process redundant data and eliminate measurement errors through weighted least squares state estimation, and obtain accurate operational status information of the system.

[0008] S2. Based on the state estimation results, construct a branch line loss calculation model, deduce the sensitivity of line loss to active power injected into nodes through the chain rule, and obtain the dynamic line loss sensitivity matrix.

[0009] S3. With the goal of minimizing bus loss, and in conjunction with the dynamic line loss sensitivity matrix, set cooperative control constraints, construct a cooperative control optimization model, and obtain the optimal control command of the system by solving the linear programming algorithm;

[0010] S4. The optimal control command is sent to the flexible interconnected device for execution, and feedback iteration is achieved through real-time status monitoring to dynamically update the control strategy.

[0011] On the other hand, the present invention also provides a flexible interconnection system based on dynamic line loss optimization for implementing the above-mentioned cooperative control method, characterized in that it includes the following modules:

[0012] The data acquisition and status estimation module is used to collect operational data through sensors deployed at various nodes and branches of the system, process redundant data and eliminate measurement errors using the weighted least squares method, and output accurate system operating status information.

[0013] The line loss sensitivity calculation module is used to construct a branch line loss calculation model based on the operating status information output by the state estimation module, deduce the sensitivity of line loss to the injected active power at each node through the chain rule, and output a dynamic line loss sensitivity matrix.

[0014] The collaborative control optimization module is used to minimize the system bus loss, combine the line loss sensitivity matrix, set constraints, construct a linear programming optimization model, solve for and output the optimal active power adjustment command for each flexible interconnection device;

[0015] The control execution and feedback iteration module is used to convert the optimal control command into a control signal and send it to the flexible device for execution. At the same time, it collects the real-time status of the system according to a set period, triggers the state estimation, sensitivity calculation and optimization solution process, dynamically updates the control strategy, and realizes closed-loop control.

[0016] Compared with the prior art, the significant progress of the present invention is as follows: (1) The present invention updates the line loss sensitivity based on real-time state estimation, adapts to changes in the system operating state, and improves the sustainability of the optimization effect; (2) The present invention coordinates the control strategies of each flexible device through a global optimization model to achieve system-level line loss minimization; (3) The present invention takes line loss as the core objective, does not depend on specific voltage or power settings, and is more in line with the actual needs of power distribution network energy efficiency improvement.

[0017] To more clearly illustrate the functional characteristics and structural parameters of the present invention, further explanation is provided below in conjunction with the accompanying drawings and specific embodiments. Attached Figure Description

[0018] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0019] Figure 1 This is a flowchart of the steps of the present invention. Detailed Implementation

[0020] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. 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.

[0021] This invention provides a cooperative control method for flexible interconnected systems based on dynamic line loss optimization, combined with... Figure 1 This includes the following steps:

[0022] S1. Collect operational data using sensors deployed at each node and branch of the flexible interconnected system, process redundant data and eliminate measurement errors through weighted least squares state estimation, and obtain accurate operational status information of the system.

[0023] S2. Based on the state estimation results, construct a branch line loss calculation model, deduce the sensitivity of line loss to active power injected into nodes through the chain rule, and obtain the dynamic line loss sensitivity matrix.

[0024] S3. With the goal of minimizing bus loss, and in conjunction with the dynamic line loss sensitivity matrix, set cooperative control constraints, construct a cooperative control optimization model, and obtain the optimal control command of the system by solving the linear programming algorithm;

[0025] S4. The optimal control command is sent to the flexible interconnected device for execution, and feedback iteration is achieved through real-time status monitoring to dynamically update the control strategy.

[0026] S1 includes the following steps:

[0027] S11. Utilize operational data collected by sensors, the operational data including node-injected active power. reactive power Where i = 1, 2, ..., n, and n is the number of nodes; node voltage amplitude and phase angle Branch active power reactive power Where i and j are the two endpoints of the branch; the branch resistance ;

[0028] S12. The operating data is used to perform state estimation using the weighted least squares method to obtain accurate operating state information of the system.

[0029] The objective function for state estimation in S12 is:

[0030] ;

[0031] Where z is the measurement vector including node power, voltage, and branch power, and x is the state vector including node voltage magnitude and phase angle. A measurement function is used to describe the relationship between state variables and measured values. The measurement error covariance matrix; by minimizing Obtain the optimal state estimate .

[0032] S2 includes the following steps:

[0033] S21. Construct a branch line loss calculation model, where the line loss is the active power loss of the branch resistance, as shown in the following formula:

[0034] ;

[0035] in, The branch current is calculated using the node voltages and branch parameters obtained from the state estimation:

[0036] ;

[0037] in, For branch impedance, ;

[0038] S22. Derive the sensitivity of line loss to active power injected into nodes and construct a dynamic line loss sensitivity matrix. According to the power flow equations, the relationship between active power injected into nodes and branch currents is:

[0039] ;

[0040] Using the chain rule, for about The derivative is given by the following formula for the line loss sensitivity:

[0041] ;

[0042] in, These are the elements of the node admittance matrix. The physical meaning of line loss sensitivity is the increment of line loss for every unit of active power injection at node i. The higher the sensitivity, the greater the impact of adjusting the node's power on line loss.

[0043] S3 includes the following steps:

[0044] S31. Set the control variables for the collaborative control optimization model. The control variables are the power adjustment amounts of each flexible interconnection device. , where i and j are the nodes connected by the flexible device, and represent the incremental active power transmitted by the device from node i to node j;

[0045] S32. Determine the objective function of the cooperative control optimization model. The objective function is to minimize the system bus loss, as shown in the following formula:

[0046] ;

[0047] in, The total active power injection increment for node i is equal to the power regulation of all flexible interconnection devices connected to that node. The algebraic sum;

[0048] S33. Constraints for constructing the collaborative control optimization model; the constraints include power balance constraints, flexible device capacity constraints, and node voltage constraints.

[0049] The power balance constraint is defined as the requirement that the adjusted system must satisfy the balance of active and reactive power, as shown in the following formula:

[0050] ;

[0051] in, , Let represent the active power and reactive power of the load at node i, respectively. , Contribute to distributed energy, This is the reactive power regulation amount (if the flexible interconnection device supports reactive power regulation).

[0052] The capacity constraint of the flexible device is defined as the adjustment amount of each flexible device must be within its rated capacity range, as shown in the following formula:

[0053] ;

[0054] in, , These are the maximum and minimum active power regulation capacities of the flexible interconnection device, respectively.

[0055] The node voltage constraint is defined as the adjusted node voltage needing to be within the allowable range, as shown in the following formula:

[0056] ;

[0057] in, The voltage increment at node i can be calculated using sensitivity.

[0058] S34. Obtain the optimal control command based on the aforementioned collaborative control optimization model. The collaborative control optimization model is a linear programming problem, which can be solved quickly using the interior point method and the simplex method to obtain the optimal adjustment amount for each flexible connection device.

[0059] The present invention provides a flexible interconnection system based on dynamic line loss optimization for implementing the above-mentioned cooperative control method, comprising the following modules:

[0060] The data acquisition and status estimation module is used to collect operational data through sensors deployed at various nodes and branches of the system, process redundant data and eliminate measurement errors using the weighted least squares method, and output accurate system operating status information.

[0061] The line loss sensitivity calculation module is used to construct a branch line loss calculation model based on the operating status information output by the state estimation module, deduce the sensitivity of line loss to the injected active power at each node through the chain rule, and output a dynamic line loss sensitivity matrix.

[0062] The collaborative control optimization module is used to minimize the system bus loss, combine the line loss sensitivity matrix, set constraints, construct a linear programming optimization model, solve for and output the optimal active power adjustment command for each flexible interconnection device;

[0063] The control execution and feedback iteration module is used to convert the optimal control command into a control signal and send it to the flexible device for execution. At the same time, it collects the real-time status of the system according to a set period, triggers the state estimation, sensitivity calculation and optimization solution process, dynamically updates the control strategy, and realizes closed-loop control.

[0064] Example

[0065] This embodiment selects a typical 3-node flexible interconnected microgrid system, where node 1 is the slack node and node 2 is the PQ node (load active power). 0.5MW, reactive power (0.3MVar), Node 3 is a PV node (distributed power output). (0.3MW); the flexible interconnection device connects node 2 and node 3, its Adjustment range is .

[0066] S1: Collect system data such as node 2 voltage, node 3 voltage, and branch current, and obtain the accurate state of the system at that moment through state estimation.

[0067] S2: Based on the state estimation results of S1, the system bus loss before optimization is calculated to be 429.5W. Furthermore, according to the S2 sensitivity formula, the following is calculated:

[0068] ;

[0069] S3: Combining the sensitivity calculation results of S2, and based on the flexible interconnected system cooperative control model constructed in S3, the optimal adjustment amount of this system is obtained by solving. The value is -0.1MW, meaning the flexible device delivers 0.1MW of power from node 3 to node 2.

[0070] The optimized system line loss was recalculated and the result was 380W, which is about 11.5% lower than before optimization, thus verifying the line loss optimization result of the present invention.

[0071] S4: Set the iteration period according to the system fluctuation frequency. In this embodiment, it is set to 10 minutes. In each cycle, the system data is re-collected, the state estimate and line loss sensitivity are updated, and steps S1 to S3 are repeated to realize the real-time update of the control strategy.

[0072] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0073] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for coordinated control of a flexible interconnection system based on dynamic line loss optimization, characterized in that, The method comprises the following steps: S1, collecting operation data by sensors arranged at nodes and branches of the flexible interconnected system, processing redundant data and eliminating measurement errors by weighted least square state estimation to obtain accurate system operation state information; S2, constructing a branch line loss calculation model based on the state estimation result, deriving the sensitivity of line loss to node injected active power by chain rule to obtain a dynamic line loss sensitivity matrix; S3, taking the minimum total line loss as the target, setting a coordinated control constraint condition in combination with the dynamic line loss sensitivity matrix, constructing a coordinated control optimization model, and solving the model by a linear programming algorithm to obtain optimal control instructions of the system; S4, issuing the optimal control instructions to the flexible interconnected device for execution, and realizing feedback iteration by real-time state monitoring to dynamically update the control strategy. 2.The method of claim 1, wherein The S1 comprises the following steps: S11, collecting operation data by using the sensor, wherein the operation data comprises active power injected by the node , reactive power , wherein i = 1, 2, …, n, n is the number of nodes; the voltage amplitude of the node , and the phase angle of the node , active power of the branch , reactive power of the branch , wherein i, j are the nodes at both ends of the branch; the resistance of the branch ; S12, performing state estimation on the operation data by the weighted least square method to obtain accurate system operation state information.

3. The method of claim 2, wherein, The state estimation objective function of the S12 is as follows: ； Where z is the measurement vector including node power, voltage, branch power, x is the state vector including node voltage magnitude and phase angle, is the measurement function to describe the relationship between state quantities and measurements, is the measurement error covariance matrix; by minimizing the optimal state estimation value is obtained .

4. The method of claim 3, wherein, The S2 comprises the following steps: S21, constructing a branch line loss calculation model, wherein the line loss is the active loss of the branch resistance, and the calculation model is as follows: ； wherein is the branch current, calculated from the state estimation of the node voltages and branch parameters. ； wherein is the shunt impedance, ; S22, deriving the sensitivity of line loss to node injected active power, and constructing a dynamic line loss sensitivity matrix; according to the power flow equation, the relationship between node injected active power and branch current is as follows: ； Using the chain rule, the derivative of the line loss sensitivity is given by With respect to the derivative of the line loss sensitivity is given by ； wherein, is the nodal admittance matrix element.

5. The method of claim 4, wherein the method is characterized by, The S3 comprises the following steps: S31, setting a cooperative control optimization model control variable; the control variable is a power adjustment amount of each flexible interconnection device wherein i, j are nodes connected by the flexible device, and represents an active power increment delivered by the device from node i to node j; S32, determining the objective function of the coordinated control optimization model, wherein the objective function is the minimum total line loss of the system, and the objective function is as follows: ； wherein, is the total active injection increment for node i, which has the value equal to the algebraic sum of the power regulation amounts of all flexible interconnections connected to this node is the algebraic sum; S33, constructing the constraint condition of the coordinated control optimization model; the constraint condition comprises a power balance constraint, a flexible device capacity constraint, and a node voltage constraint; The power balance constraint is defined as the adjusted system needing to satisfy active and reactive power balance, and is as follows: ； wherein, , Pi and Qj are the active and reactive power of node i, respectively, , Pdis is the distributed energy output, is the reactive power regulation amount; The flexible device capacity constraint is defined as the adjustment amount of each flexible device needing to be within the rated capacity range thereof, and is as follows: ； wherein, , are the maximum and minimum active regulation capacity of the flexible interconnection, respectively; The node voltage constraint is defined as the adjusted node voltage needing to be within the allowable range, and is as follows: ； wherein, ΔVi is the voltage increment for node i; S34, obtaining the optimal control instructions according to the coordinated control optimization model.

6. A flexible interconnection system based on dynamic line loss optimization for implementing the coordinated control method of any of claims 1-5, characterized by, The method comprises the following modules: A data acquisition and state estimation module is configured to collect operation data by sensors arranged at nodes and branches of the system, process redundant data and eliminate measurement errors by the weighted least square method, and output accurate system operation state information; A line loss sensitivity calculation module is configured to construct a branch line loss calculation model based on the operation state information output by the state estimation module, derive the sensitivity of line loss to active power injected into each node by chain rule, and output a dynamic line loss sensitivity matrix; A coordinated control optimization module is configured to take the minimum total line loss of the system as the target, set a constraint condition in combination with the line loss sensitivity matrix, construct a linear programming optimization model, and solve the model to output optimal active power adjustment instructions of each flexible tie device; A control execution and feedback iteration module is configured to convert the optimal control instructions into control signals, issue the control signals to the flexible device for execution, collect real-time system states at a set period, trigger the state estimation, sensitivity calculation and optimization solving processes, dynamically update the control strategy, and realize closed-loop regulation and control.

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