A low-voltage distribution network photovoltaic access position optimization method based on topology reconfiguration and node sensitivity analysis

Abstract

The application relates to a low-voltage distribution network photovoltaic access position optimization method based on topology reconfiguration and node sensitivity analysis, and belongs to the technical field of low-voltage distribution network photovoltaic access position optimization. The technical scheme is as follows: firstly, a node sensitivity matrix is used to accurately calculate a weak branch; secondly, a topology structure is dynamically adjusted to balance power flow and optimize a power flow path; then, a line impedance equivalent method is introduced to improve the efficiency and precision of multi-position comparison; finally, a multi-scenario access position optimization model is constructed to output an optimal distributed photovoltaic access position, thereby effectively guiding the reasonable and orderly access of distributed photovoltaic to a low-voltage distribution network. The application constructs a four-step cooperative framework including weak branch identification, dynamic topology reconstruction, impedance equivalent modeling and multi-scenario simulation optimization, accurately locates weak branches in a transformer area, dynamically balances power flow distribution, realizes optimal access position configuration of distributed photovoltaic to a low-voltage distribution network under the condition of meeting safety constraints, and effectively reduces line loss of a distribution network.

Description

Technical Field

[0001] This invention relates to a method for optimizing the location of photovoltaic (PV) access in low-voltage distribution networks based on topology reconfigurability and node sensitivity analysis, belonging to the technical field of PV access location optimization in low-voltage distribution networks. Background Technology

[0002] Currently, the integration rate of distributed photovoltaic (PV) power into low-voltage distribution networks continues to increase. As the final link in the distribution network, the transformer substation directly faces users, and its line loss management level is crucial to the energy efficiency and economic viability of the distribution network. However, the intermittent and fluctuating nature of PV power output disrupts the traditional unidirectional, radial power flow pattern of low-voltage distribution networks, leading to a series of problems such as backflow, voltage exceeding limits, and exacerbated three-phase imbalance. One of the most direct impacts is a significant increase in line losses in low-voltage distribution networks.

[0003] When photovoltaic (PV) power is concentrated at the end of the feeder in a distribution area, the "duck curve" effect causes an increase in line current during light-load periods in the daytime, resulting in additional line losses. At the same time, some lines may be overloaded due to reverse power flow, becoming "weak branches" that restrict further expansion of PV power integration. Traditional distributed PV integration planning often only considers static access capacity limitations and lacks the possibility of balancing power flow and releasing access potential by actively adjusting the grid topology.

[0004] Currently, power grid companies' responses to such issues are relatively passive, relying heavily on experience-based judgment or simple capacity expansion, lacking a scientific method to coordinate and optimize both "PV access location" and "network topology." Existing technologies for selecting distributed PV access locations or capacities in low-voltage distribution networks primarily depend on the experience of planning and design personnel, typically employing static capacity limits, generally not exceeding a certain proportion of the transformer capacity in the distribution area, or simple power flow calculations for evaluation. This evaluation method fails to fully utilize the adjustment capabilities of automated equipment such as tie switches and sectionalizing switches in low-voltage distribution networks, neglecting the possibility of optimizing power flow distribution and releasing PV access potential through dynamic adjustments to the network topology. Furthermore, existing optimization methods are mostly conducted under fixed topologies, analyzing only single typical operating scenarios, and have not fully considered the variability of PV output and load demand across different seasons and time periods. This results in poor adaptability and robustness of distributed PV access optimization schemes, making it difficult to truly achieve optimal synergy between PV absorption and loss reduction in low-voltage distribution networks under complex operating conditions. In summary, the existing technologies have the following problems:

[0005] (1) The selection criteria for low-voltage distribution network access locations are one-sided. The sensitivity of the access location affects line loss. Some nearby nodes are highly sensitive. One-sided selection leads to photovoltaic access to highly sensitive nodes, which has a significant impact on line loss.

[0006] (2) Fixed topology of low-voltage distribution network cannot offset location defects. The existing technology adopts a fixed topology. When the access location causes branch overload, it is not possible to switch to a backup branch, which limits the potential for loss reduction.

[0007] (3) Slow computation efficiency and incomplete verification in a single scenario. Existing technologies are slow to compute and have low accuracy, and can only verify a single scenario, which makes the location scheme unable to adapt to most scenarios of low-voltage distribution networks, resulting in poor adaptability of distributed photovoltaic access location schemes. Summary of the Invention

[0008] This invention proposes a method for optimizing the access location of photovoltaic (PV) power in low-voltage distribution networks based on topology reconfigurability and node sensitivity analysis. By constructing a four-step collaborative framework that includes weak branch identification, dynamic topology reconfiguration, impedance equivalent modeling, and multi-scenario simulation optimization, the method accurately locates weak branches in the distribution area, dynamically balances power flow distribution, and achieves the optimal access location configuration of distributed PV power in low-voltage distribution networks while meeting safety constraints. This effectively reduces distribution network line losses and solves the aforementioned technical problems existing in existing technologies.

[0009] The technical solution of this invention is:

[0010] A method for optimizing photovoltaic (PV) access locations in low-voltage distribution networks based on topology reconfigurability and node sensitivity analysis is proposed. This method focuses on optimizing PV access locations and reducing losses in low-voltage distribution networks. First, it uses a node sensitivity matrix to accurately calculate weak branches. Second, it dynamically adjusts the topology to balance power flow and optimize power flow paths. Then, it introduces the line impedance equivalence method to improve the efficiency and accuracy of multi-location comparisons. Finally, it constructs a multi-scenario access location optimization model to output the optimal distributed PV access location, effectively guiding the rational and orderly access of distributed PV in low-voltage distribution networks.

[0011] The specific steps are as follows:

[0012] (1) Data collection: Collect parameters of the transformer substation;

[0013] (2) Matrix construction: Construct the node sensitivity matrix ;

[0014] (3) Identification of weak points;

[0015] (4) Set the topology adjustment and optimization targets respectively;

[0016] (5) Traverse the join points;

[0017] (6) Calculation of theoretical line loss;

[0018] (7) Output optimized topology;

[0019] (8) Calculation of equivalent impedance;

[0020] (9) Establish multiple scenarios and set access point locations separately;

[0021] (10) Output the optimal intervention position.

[0022] Furthermore, the data acquisition parameters in step (1) include node voltages. Branch power That is, the power from node i to j; line impedance and load power .

[0023] Furthermore, in step (2), the node sensitivity matrix is ​​constructed. Matrix elements This represents the change in power output when node k acts as a photovoltaic grid connection point. bus loss Sensitivity;

[0024] ①

[0025] in, Let k be the square of the voltage at node k. This refers to the line impedance from node k to its associated branch j. Let be the initial power from node k to branch j. Let m be the photovoltaic power of node k, and m be the number of branches associated with node k.

[0026] Furthermore, in step (3), the weak point determination involves calculating the sensitivity values ​​of all nodes. Set threshold ,Will The nodes are marked as weak nodes; among them, The average sensitivity across all nodes.

[0027] Further, the topology adjustment settings in step (4) are specifically as follows: input the transformer area topology structure, identify all operable switches, including the branches where sectionalizing switches and tie switches are located; for each operable branch... Define a binary state variable ,in Indicates a branch The switch is in the closed state. Indicates a branch The switch is in the off state;

[0028] The optimization objective in step (4) is set as follows: minimize the bus loss of candidate access locations. The constraint condition is the branch load rate. Voltage deviation ;in Representative branch road The square of the effective value of the current, Representative branch road impedance, Representative branch road The switch state variable.

[0029] Furthermore, dynamic topology adjustment is performed through steps (5), (6), and (7):

[0030] First, for each candidate photovoltaic access node k, the power flow is calculated according to a fixed topology. and line loss Secondly, if line loss If the target value is exceeded, topology reconfiguration optimization is initiated. This involves systematically opening and closing operable switches (while maintaining the radial network structure and connectivity of all loads) to generate and evaluate the line losses for each feasible topology, ultimately selecting the topology that minimizes bus losses. This process iterates based on the current optimal topology until the line loss no longer decreases significantly, ultimately outputting the optimal topology state corresponding to each candidate node k. Its minimum line loss value provides input for subsequent multi-scenario optimization.

[0031] Furthermore, step (8) of equivalent impedance calculation requires constructing an equivalent impedance calculation model: for each candidate access node The m associated branches are simplified to equivalent impedances according to the power loss equivalence principle. Consider the power loss weight of each branch;

[0032] ②

[0033] ③

[0034] in, The power loss of the i-th branch when photovoltaic power is connected. For the first The line impedance of the branch circuit.

[0035] Furthermore, step (9) involves establishing multiple scenarios and setting access point locations, while step (10) outputs the optimal intervention location, as detailed below:

[0036] First, we select three scenarios: sunny days, etc. Photovoltaic power output =100% ;cloudy day Photovoltaic power output =30% ;partly cloudy Photovoltaic power output =60% To cover the main meteorological conditions; secondly, input the candidate node set and the corresponding optimized topology. (k), equivalent impedance Construct a multi-scenario line loss calculation model;

[0037] ④

[0038] ⑤

[0039] in, The equivalent line loss rate of node k in a specific scenario,

[0040] The equivalent line loss rate of node k in a specific scenario, For a specific scenario, when photovoltaic power is connected to point k, the power input to the distribution area from the upstream power grid,

[0041] The total output of a distributed photovoltaic system connected to the power distribution network in a specific scenario;

[0042] Secondly, for each candidate node k, calculate the average line loss rate across the entire scenario. ;

[0043] ⑥

[0044] Finally, select The smallest node is selected as the optimal access location;

[0045] ⑦

[0046] in, For the optimal grid connection location of distributed photovoltaic power, The parameter corresponding to the minimum value of the independent variable is the node with the minimum average line loss rate across the entire scenario.

[0047] The key points of this invention are as follows:

[0048] (1) A node sensitivity matrix analysis method is proposed. By calculating the sensitivity of the access point power change to the bus loss, weak nodes can be accurately identified, avoiding high-loss areas for photovoltaic access and solving the problem of blind site selection based on experience in the existing technology.

[0049] (2) Design a topology reconfigurable and adaptable structure. Dynamically adjust the topology structure for different access locations, optimize the power flow path to maximize the loss reduction effect, and solve the problem that location defects cannot be compensated for under a fixed topology.

[0050] (3) Construct an equivalent impedance model for node association. Calculate the equivalent impedance based on the coupling relationship between the access location and the branch, improving the efficiency and accuracy of multi-location comparison and solving the problem of complex and large deviation in traditional impedance calculation.

[0051] (4) Establish a multi-scenario access location optimization scenario, and select the optimal location by the average line loss rate of the whole scenario to ensure that the solution can reduce losses under different working conditions and solve the limitations of single-scenario verification.

[0052] The beneficial technical effects of this invention are as follows: By constructing a four-step collaborative framework that includes weak branch identification, dynamic topology reconstruction, impedance equivalent modeling, and multi-scenario simulation optimization, it accurately locates weak branches in the distribution area, dynamically balances power flow distribution, and achieves optimal access location configuration for distributed photovoltaic power in low-voltage distribution networks while meeting safety constraints, effectively reducing distribution network line losses. This is of great significance for improving the ability of low-voltage distribution networks to accommodate new energy sources and achieving energy conservation and loss reduction in low-voltage distribution networks. Attached Figure Description

[0053] Figure 1 This is a flowchart of an embodiment of the present invention.

[0054] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0055] A method for optimizing photovoltaic (PV) access locations in low-voltage distribution networks based on topology reconfigurability and node sensitivity analysis is proposed. Focusing on optimizing PV access locations and reducing losses in low-voltage distribution networks, the method first uses a node sensitivity matrix to accurately calculate weak branches. Second, it dynamically adjusts the topology to balance power flow and optimize power flow paths. Then, it introduces the line impedance equivalence method to improve the efficiency and accuracy of multi-location comparisons. Finally, it constructs a multi-scenario access location optimization model to output the optimal distributed PV access location, effectively guiding the rational and orderly access of distributed PV in low-voltage distribution networks.

[0056] This embodiment refers to the appendix. Figure 1 The specific steps are as follows:

[0057] (1) Data collection in the transformer area: Collect parameters of the transformer area, including node voltage.

[0058] Branch power (Power at nodes i to j), line impedance Load power Data such as...

[0059] (2) Sensitivity matrix construction: Construct the node sensitivity matrix Matrix elements This represents the change in power output when node k acts as a photovoltaic grid connection point. bus loss Sensitivity;

[0060] ①

[0061] in, Let k be the square of the voltage at node k. This refers to the line impedance from node k to its associated branch j. Let be the initial power from node k to branch j. Let m be the photovoltaic power of node k, and m be the number of branches associated with node k.

[0062] (3) Weak point identification: Calculate the sensitivity value of all nodes. Set threshold ,Will The nodes are marked as weak nodes. The average sensitivity across all nodes.

[0063] (4) Set the topology adjustment and optimization targets respectively;

[0064] (4.1) Topology Adjustment Settings: Input the transformer area topology and identify the branches containing all operable switches (including sectionalizing switches and tie switches). For each operable branch... Define a binary state variable ,in Indicates a branch The switch is in the closed state (branch connected). Indicates a branch The switch is in the open state (branch disconnected).

[0065] (4.2) Set optimization objective: Minimize bus loss at candidate access locations The constraint condition is the branch load rate. Voltage deviation .

[0066] in Representative branch road The square of the effective value of the current, Representative branch road impedance, Representative branch road The switch state variable.

[0067] (5) Traverse the join points;

[0068] (6) Calculation of theoretical line loss;

[0069] (7) Output optimized topology; perform dynamic topology adjustment through steps (5), (6) and (7): First, for each candidate photovoltaic access node k, calculate the power flow according to the fixed topology. and line loss Secondly, if line loss If the target value is exceeded, topology reconfiguration optimization is initiated. This involves systematically opening and closing operable switches (while maintaining the radial network structure and connectivity of all loads) to generate and evaluate the line losses for each feasible topology, ultimately selecting the topology that minimizes bus losses. This process can be iterated based on the current optimal topology until the line loss no longer decreases significantly, ultimately outputting each candidate node. The corresponding optimal topological state Its minimum line loss value provides input for subsequent multi-scenario optimization.

[0070] (8) Construction of equivalent impedance calculation model: For each candidate access node The m associated branches are simplified to equivalent impedances according to the power loss equivalence principle. Consider the power loss weight of each branch;

[0071] ②

[0072] ③

[0073] in, For the power loss weight of each branch, For nodes The power loss of the i-th branch when connected to photovoltaic power. For the first The line impedance of the branch circuit.

[0074] Step (9) establish multiple scenarios and set access point locations respectively.

[0075] Step (10) outputs the optimal intervention position.

[0076] Multi-scenario access location optimization is performed through steps (9) and (10): First, three scenarios are selected for a typical transformer area, namely, sunny day. Photovoltaic power output =100% ;cloudy day Photovoltaic power output =30% ;partly cloudy Photovoltaic power output =60% To cover the main meteorological conditions; secondly, input the candidate node set and the corresponding optimized topology state. (k) Equivalent impedance Construct a multi-scenario line loss calculation model.

[0077] ④

[0078] ⑤

[0079] in, The equivalent line loss rate of node k in a specific scenario, The equivalent line loss rate of node k in a specific scenario, For a specific scenario, when photovoltaic power is connected to point k, the power input to the distribution area from the upstream power grid, This refers to the total output (total active power) of a distributed photovoltaic system connected to the power distribution network in a specific scenario.

[0080] Secondly, for each candidate node k, calculate the average line loss rate across the entire scenario. ;

[0081] ⑥

[0082] Finally, select The smallest node is selected as the optimal access location;

[0083] ⑦

[0084] in, For the optimal grid connection location of distributed photovoltaic power, The parameter corresponding to the minimum value of the independent variable is the node with the minimum average line loss rate across the entire scenario.

[0085] The advantages of this embodiment are as follows:

[0086] Precise node sensitivity analysis avoids high-loss access areas. This invention identifies vulnerable nodes through a sensitivity matrix, ensuring photovoltaic grid connection in low-sensitivity areas. Compared to existing technologies, this effectively avoids increased line losses due to improper grid connection locations.

[0087] (1) Topology reconfigurable optimizes power flow and enhances the potential for positional loss reduction. This invention compensates for some inherent defects at certain positions by dynamically adjusting the topology. Compared with the fixed topology of the prior art, this invention solves the problem that the fixed topology of the prior art limits the potential for loss reduction.

[0088] (2) The impedance equivalent method is efficient and accurate, and the location scheme is adaptable to all working conditions. This invention uses power loss weighted equivalent impedance and selects multiple scenarios for simulation optimization. Compared with the existing technology, it can quickly find multiple nodes in the transformer area that meet the access conditions. It is fast, accurate, and comprehensive in dimensions.

[0089] Explanation of related terms

[0090] 1. Topology Reconfiguration: By controlling the opening and closing states of tie switches and sectionalizing switches in the power grid, the physical connection structure of the power grid is changed, thereby adjusting the power flow distribution and optimizing the network operation.

[0091] 2. Node sensitivity analysis: This refers to analyzing the response of electrical quantities such as voltage and power of a certain node in the power grid to changes in power injected into other nodes. It is used to identify the critical nodes and weak links that are most sensitive to the impact on the system.

[0092] 3. Weak branches: These refer to line sections that, under the current operating conditions, have a high load rate, a large voltage drop, or a significant impact on system stability.

[0093] 4. Line impedance equivalent method: This method simplifies a part of the lines or sub-networks in a complex power grid into an equivalent impedance model through circuit theory, thereby reducing computational complexity.

[0094] 5. Multi-scenario simulation: This refers to performing multiple simulation calculations to evaluate the robustness and adaptability of the optimization scheme under various operating conditions, taking into account different combinations of uncertain factors such as photovoltaic output and load demand.

[0095] 6. Optimization of photovoltaic access location: Under the constraints of line loss rate, voltage deviation and branch load rate, select the photovoltaic access node that minimizes line loss, including the selection of the first, middle and last nodes and the multi-node distributed configuration method.

[0096] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for optimizing the location of photovoltaic (PV) grid connection in low-voltage distribution networks based on topology reconfigurability and node sensitivity analysis, characterized in that... The following steps are required: (1) Data collection: Collect parameters of the transformer substation; (2) Matrix construction: Construct the node sensitivity matrix ; (3) Identification of weak points; (4) Set the topology adjustment and optimization targets respectively; (5) Traverse the join points; (6) Calculation of theoretical line loss; (7) Output optimized topology; (8) Calculation of equivalent impedance; (9) Establish multiple scenarios and set access point locations separately; (10) Output the optimal intervention position.

2. The method for optimizing the location of photovoltaic grid connection in low-voltage distribution networks based on topology reconfigurability and node sensitivity analysis according to claim 1, characterized in that: The parameters of the acquisition area in step (1) include node voltage. Branch power That is, the power from node i to j; line impedance and load power .

3. The method for optimizing the location of photovoltaic access in a low-voltage distribution network based on topology reconfigurability and node sensitivity analysis according to claim 2, characterized in that: The construction of the node sensitivity matrix in step (2) Matrix elements This represents the change in power output when node k acts as a photovoltaic grid connection point. bus loss Sensitivity; ① in, Let k be the square of the voltage at node k. This refers to the line impedance from node k to its associated branch j. Let be the initial power from node k to branch j. Let m be the photovoltaic power of node k, and m be the number of branches associated with node k.

4. The method for optimizing the location of photovoltaic access in a low-voltage distribution network based on topology reconfigurability and node sensitivity analysis according to claim 3, characterized in that: Step (3) Weak point identification: Calculate the sensitivity value of all nodes. Set threshold Will The nodes are marked as weak nodes; among them, The average sensitivity across all nodes.

5. The method for optimizing the location of photovoltaic access in a low-voltage distribution network based on topology reconfigurability and node sensitivity analysis according to claim 4, characterized in that: The topology adjustment settings in step (4) are as follows: Input the transformer area topology, identify all operable switches, including the branches where sectionalizing switches and tie switches are located; for each operable branch... Define a binary state variable ,in Indicates a branch The switch is in the closed state. Indicates a branch The switch is in the off state.

6. The method for optimizing the location of photovoltaic grid connection in a low-voltage distribution network based on topology reconfigurability and node sensitivity analysis according to claim 5, characterized in that: The optimization objective in step (4) is set as follows: minimize the bus loss of candidate access locations. The constraint condition is the branch load rate. Voltage deviation ;in Representative branch road The square of the effective value of the current, Representative branch road impedance, Representative branch road The switch state variable.

7. The method for optimizing the location of photovoltaic access in a low-voltage distribution network based on topology reconfigurability and node sensitivity analysis according to claim 6, characterized in that... Dynamic topology adjustment is performed through steps (5), (6), and (7): First, for each candidate photovoltaic access node k, the power flow is calculated according to a fixed topology. and line loss Secondly, if line loss If the target value is exceeded, topology reconfiguration optimization is initiated. By systematically opening and closing operable switches, the line loss corresponding to each feasible topology is generated and evaluated, and then the topology state that minimizes the bus loss is selected. This process iterates based on the current optimal topology until the line loss no longer decreases significantly, ultimately outputting the optimal topology state corresponding to each candidate node k. Its minimum line loss value provides input for subsequent multi-scenario optimization.

8. The method for optimizing the location of photovoltaic grid connection in a low-voltage distribution network based on topology reconfigurability and node sensitivity analysis according to claim 7, characterized in that: The equivalent impedance calculation in step (8) requires the construction of an equivalent impedance calculation model: for each candidate access node The m associated branches are simplified to equivalent impedances according to the power loss equivalence principle. Consider the power loss weight of each branch; ② ③ in, For the power loss weight of each branch, For nodes The power loss of the i-th branch when photovoltaic power is connected. For the first The line impedance of the branch circuit.

9. The method for optimizing the location of photovoltaic access in a low-voltage distribution network based on topology reconfigurability and node sensitivity analysis according to claim 8, characterized in that: Step (9) involves establishing multiple scenarios and setting access point locations, while step (10) outputs the optimal intervention location, as detailed below: First, three scenarios are selected: sunny day, etc. Photovoltaic power output ;cloudy day Photovoltaic power output =30% ;partly cloudy Photovoltaic power output =60% To cover the main meteorological conditions; secondly, input the candidate node set and the corresponding optimized topology. (k), equivalent impedance Construct a multi-scenario line loss calculation model; ④ ⑤ in, The equivalent line loss rate of node k in a specific scenario, The equivalent line loss rate of node k in a specific scenario, For a specific scenario, when photovoltaic power is connected to point k, the power input to the distribution area from the upstream power grid, The total output of a distributed photovoltaic system connected to the power distribution network in a specific scenario; Secondly, for each candidate node k, calculate the average line loss rate across the entire scenario. ; ⑥ Finally, select The smallest node is selected as the optimal access location; ⑦ in, For the optimal grid connection location of distributed photovoltaic power, The parameter corresponding to the minimum value of the independent variable is the node with the minimum average line loss rate across the entire scenario.

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