Methods for Coordinated Optimization of Power Flow and Voltage and Dynamic Capacity Expansion in 10kV Zero-Carbon Industrial Park Distribution Network

Abstract

This invention discloses a method for coordinated optimization of power flow and voltage and dynamic capacity expansion in a 10kV zero-carbon industrial park distribution network, relating to the field of distribution network operation and control technology. The method collects electrical quantities, environmental quantities, and equipment status data of the industrial park distribution network; through power flow calculation, it identifies voltage exceedance risk nodes and overload risk branches; for overload risk branches, it calculates the real-time theoretical dynamic allowable current based on the line thermal balance model, and after safety reduction, obtains the dynamic allowable current for operational constraints, which serves as the upper limit of the current constraint for the corresponding branch; combining voltage exceedance risk and overload risk, it uses the node voltage qualification range as the voltage constraint and the dynamic allowable current for operational constraints as the current constraint, generating a power flow-voltage coordinated control strategy, enabling voltage control, power flow distribution, and dynamic capacity expansion to be coupled in a closed loop within the same control framework; control commands are issued and executed, forming a rolling closed-loop control. This method can improve the operational flexibility and renewable energy absorption level of the zero-carbon industrial park distribution network.

Description

Technical Field

[0001] This invention relates to the field of power system distribution network operation control technology, specifically to a method for coordinated optimization of power flow voltage and dynamic capacity expansion of a 10kV zero-carbon industrial park distribution network. Background Technology

[0002] With the advancement of zero-carbon industrial park construction, a large number of distributed photovoltaic, wind power, energy storage systems, and electric vehicle charging stations have been connected to the 10kV distribution network, resulting in the following characteristics in the operation of the distribution network:

[0003] 1) The output of new energy sources fluctuates greatly, which can easily cause node voltage over-limit and line power flow fluctuations;

[0004] 2) During certain peak output or load periods, some lines or transformers experience short-term overloads, limiting the consumption of new energy sources;

[0005] 3) Existing distribution network control methods are mostly based on voltage control or load management. Some studies involve power flow optimization or dynamic capacity expansion, but there is no complete technical solution for the unified and coordinated optimization of power flow distribution, voltage control and line dynamic carrying capacity. In the scenario of a 10kV zero-carbon park with a high proportion of distributed power sources, existing methods have failed to embed the real-time calculation of dynamic capacity expansion into the power flow-voltage coordinated control framework.

[0006] Differences from existing technologies:

[0007] Existing technologies typically treat dynamic capacity expansion as an independent capacity assessment tool for offline or quasi-offline analysis of line carrying capacity, without embedding the dynamic allowable current into power flow optimization and voltage control constraints in real time. This invention calculates the dynamic allowable current online and directly uses it as a line current constraint for power flow optimization and rule-level control. This allows voltage control, power flow distribution, and dynamic capacity expansion to be coupled in a closed loop within the same control framework. Therefore, in scenarios with local voltage constraints or line capacity constraints, this helps improve the absorption of renewable energy and enhances the operational flexibility of the industrial park's distribution network. Summary of the Invention

[0008] The purpose of this invention is to provide a method for coordinated optimization of power flow and voltage, and dynamic capacity expansion in a 10kV zero-carbon industrial park distribution network, overcoming the shortcomings of existing distribution network control methods that isolate voltage control, power flow optimization, and dynamic capacity expansion. This invention achieves unified closed-loop coordinated control of these three aspects by calculating the dynamic allowable current online and directly embedding it into power flow optimization constraints and voltage control rules. Compared to existing solutions, this invention can reduce the number of heavily loaded lines and improve the distributed photovoltaic absorption level while ensuring qualified node voltages and line thermal safety. Simultaneously, through a safety backoff mechanism and operation recording function, it ensures safe operation of the system under abnormal conditions. This invention employs a solution strategy combining forward and backward power flow calculations with linear / quadratic programming, which can complete the solution within seconds in typical industrial park settings, demonstrating both real-time engineering feasibility and feasibility.

[0009] To achieve the above objectives, the present invention adopts the following technical solution:

[0010] A method for coordinated optimization of power flow voltage and dynamic capacity expansion in a 10kV zero-carbon industrial park distribution network includes the following steps:

[0011] Step S1: Collect electrical quantity data, environmental quantity data, and equipment status data of the park's power distribution network;

[0012] Step S2: Based on the collected electrical quantity data, perform power flow calculation of the distribution network to obtain the voltage amplitude of each node and the current of each branch, and identify the nodes at risk of voltage exceeding the limit and the branches at risk of overload.

[0013] Step S3: For the identified overload risk branches, calculate the real-time theoretical dynamic allowable current based on the line thermal balance model, perform a safety reduction on the theoretical dynamic allowable current to obtain the dynamic allowable current for operation constraints, and use the dynamic allowable current for operation constraints as the upper limit of the current constraint for the corresponding branch.

[0014] Step S4: Combining the identified voltage over-limit risk nodes and overload risk branches, a power flow-voltage coordinated control strategy is generated, using the node voltage acceptable range as the voltage constraint and the dynamic allowable current for operation constraints as the branch current constraint. The dynamic allowable current for operation constraints also participates in the constraint update and overload trigger judgment of the enabled dynamic capacity expansion branches in the coordinated control strategy, generating control commands for each terminal device, so that voltage control, power flow distribution and dynamic capacity expansion are coupled in a closed loop within the same control framework.

[0015] Step S5: The generated control commands are sent to each terminal device in the distribution network for execution; after execution, a new round of electrical quantities, environmental quantities and equipment status data are collected, and a new round of power flow calculation, risk assessment and strategy optimization are carried out to form a rolling closed-loop control.

[0016] Preferably, the method further includes the following steps:

[0017] Step S6: Throughout the rolling closed-loop control process, continuously record the dynamic capacity expansion operation parameters of each control cycle, as well as the execution data of the control commands generated by the power flow-voltage coordinated control strategy; when a preset abnormal operating condition is detected, trigger a safety backoff strategy: disable the dynamic capacity expansion function, restore the branch static rated current as the upper limit of the current constraint, and prioritize ensuring that the node voltage is within the qualified range; if there is still a risk of branch overload or node voltage exceeding the limit after restoring the static rated current constraint, cut off non-critical flexible loads; the constraint conditions after the safety backoff are applied to the subsequent power flow calculation and coordinated control strategy generation.

[0018] Preferably, in step S2, the power flow calculation algorithm is adaptively selected based on the topology of the distribution network to balance calculation accuracy and real-time performance.

[0019] When the distribution network operates in a radial or weak loop structure, a simplified linear power flow algorithm is used for calculation to reduce the computational burden and meet the real-time requirements of minute-level rolling optimization.

[0020] When the distribution network closes multiple ring network switches to form a strong ring network structure with multiple power supply paths, the algorithm switches to a forward-backward nonlinear power flow algorithm to ensure the accuracy of the power flow calculation results.

[0021] Preferably, in step S3, the calculation of the real-time theoretical dynamic allowable current based on the line thermal balance model specifically involves: establishing a thermal balance equation based on the steady-state thermal balance relationship between Joule heating of the conductor and heat dissipation from the environment, and then back-deriving the theoretical dynamic allowable current when the conductor temperature does not exceed the maximum allowable temperature. The calculation formula is as follows:

[0022] ;

[0023] In the formula, For the theoretically dynamic allowable current, The maximum allowable temperature for the conductor. For ambient temperature, For wind speed, , These are empirical coefficients related to conductor structure, surface properties, and environmental conditions. For equivalent radiative heat dissipation, The resistance value of the conductor at the highest permissible temperature is given; the theoretical dynamic permissible current is multiplied by a safety reduction factor ranging from 0 to 1 to obtain the dynamic permissible current for the operational constraints.

[0024] Preferably, in step S3, when calculating the real-time theoretical dynamic allowable current based on the line thermal balance model, it is necessary to obtain the branch conductor temperature parameters; if no conductor temperature sensors are installed on site and the actual conductor temperature cannot be directly collected, an empirical temperature rise model based on Joule heating and environmental heat dissipation is used to estimate the conductor temperature. The calculation formula for the empirical temperature rise model is as follows:

[0025] ;

[0026] In the formula, This is an estimated value for the conductor temperature. For ambient temperature, For line current, For wind speed, , The temperature rise coefficient is obtained by fitting historical operating data, and the temperature rise coefficient corresponding to wind speed is positive.

[0027] Preferably, after obtaining the dynamic allowable current for operational constraints in step S3, a three-level early warning linkage logic is set based on the ratio of the branch conductor temperature to the maximum allowable conductor temperature, dynamically adjusting the activation range of dynamic capacity expansion and the branch current constraint boundary throughout the process:

[0028] When the ratio is lower than the first warning threshold, dynamic capacity expansion is enabled normally, and the operating constraints obtained in step S3 are used as the upper limit of the current constraints of the corresponding branch.

[0029] When the ratio is between the first warning threshold and the second warning threshold, the dynamic capacity increase is limited, the safety reduction coefficient in step S3 is reduced, and the upper limit of the duration during which the branch is allowed to exceed the static rated current is shortened simultaneously.

[0030] When the ratio is higher than or equal to the second warning threshold, the dynamic capacity expansion function of the corresponding branch is turned off, the static rated current of the branch is restored as the upper limit of the current constraint, and the safety backoff logic is triggered.

[0031] The first warning threshold and the second warning threshold are preset according to the conductor type and operating procedures, and the second warning threshold is higher than the first warning threshold.

[0032] Preferably, in step S3, when calculating the theoretical dynamic allowable current, the line thermal balance model is used as the theoretical basis, and an engineering implementation method combining offline preprocessing and online rapid calculation is adopted:

[0033] Before implementing the rolling closed-loop control process, the line thermal balance model is used to complete the full-condition calculation based on the inherent parameters of the line, obtain the theoretical dynamic allowable current corresponding to different ambient temperatures and wind speeds, and establish a mapping relationship table between environmental parameters and theoretical dynamic allowable currents or fit a piecewise linear calculation formula with ambient temperature and wind speed as independent variables.

[0034] During step S3, the real-time ambient temperature and wind speed included in the environmental data collected in step S1 are used to quickly obtain the theoretical dynamic allowable current by looking up a table or by substituting into a piecewise linear calculation formula.

[0035] Preferably, in step S4, the power flow-voltage coordinated control strategy adopts a two-layer architecture of fast response at the rule layer and rolling optimization at the optimization layer. The fast response at the rule layer sets multiple control priorities according to the logic of voltage regulation priority and power flow regulation matching.

[0036] When a node voltage exceeds the limit, the first stage adjusts the reactive power output of the distributed photovoltaic system or static var generator. If reactive power adjustment alone cannot restore the voltage to the acceptable range, the second stage adjusts the charging and discharging active power of the energy storage system. If the voltage still exceeds the limit after the two stages of reactive power and energy storage active power adjustment, the third stage adjusts the operating power of the flexible load.

[0037] When the current of the overload risk branch identified in step S2 exceeds the dynamic allowable current for operation constraints, the current level of the overload risk branch is reduced by adjusting the active power of energy storage, adjusting the power of flexible load, or changing the power flow direction by operating the distribution network switch.

[0038] The control commands output by the rule layer have higher priority than the rolling optimization results of the optimization layer. When there is a conflict between the control commands of the rule layer and the optimization layer, the control results of the rule layer are set as additional constraints of the optimization layer, and the optimization layer re-solves the optimal control strategy based on the set additional constraints.

[0039] Preferably, in step S4, the optimization layer's rolling optimization aims to minimize the weighted sum of node voltage deviation and branch overload degree, with the objective function being:

[0040] ;

[0041] In the formula, The objective function value, , These are the weighting coefficients. For nodes voltage amplitude, Reference voltage amplitude, This refers to the number of branches whose current exceeds the dynamic allowable current of their corresponding branches.

[0042] Preferably, in step S4, during the generation of the power flow-voltage coordinated control strategy, distribution network switch operation commands and transformer tap adjustment commands are output simultaneously:

[0043] For a park distribution network with multiple power supply paths, for the overload risk branches identified in step S2, the operation of sectionalizing switches or ring network switches is performed to reconstruct the power flow distribution, share the power flow load of the overload risk branches, and give full play to the carrying capacity of dynamic capacity expansion.

[0044] When the overall bus voltage is detected to deviate from the preset qualified range, the bus voltage reference is calibrated by adjusting the transformer tap position, and reactive power regulation and energy storage charging and discharging regulation are linked to achieve voltage coordination optimization of the entire distribution network.

[0045] The present invention provides a method for coordinated optimization of power flow voltage and dynamic capacity expansion in a 10kV zero-carbon industrial park distribution network, which achieves several technical advantages:

[0046] 1) Achieved unified closed-loop collaborative control. This invention unifies dynamic capacity expansion, power flow optimization, and voltage control into the same control framework, dynamically allowing current to participate in optimization constraint updates and rule-layer triggering criteria in real time, avoiding information fragmentation and control conflicts when the three operate independently, and improving the overall coordination of the system.

[0047] 2) Improved line utilization under safe conditions. By calculating the dynamic allowable current in real time based on the thermal balance model and introducing a safety reduction factor and a short-time overload duration limit, the system can make reasonable use of the line's short-time load-bearing margin while meeting the conductor's thermal safety constraints, which helps to alleviate local overload.

[0048] 3) Improved renewable energy absorption in scenarios with local constraints. Taking a typical 10kV zero-carbon park simulation example, compared with using only voltage control schemes, this invention reduces the number of heavily loaded lines while releasing some photovoltaic output that is limited by capacity or voltage constraints, thus improving the photovoltaic absorption rate.

[0049] 4) It is feasible for engineering implementation. This invention uses forward-backward power flow calculation and linear / quadratic programming solution, combined with a hierarchical control strategy, which can meet the real-time requirements of minute-level control cycle under typical campus scale. The algorithms and communication protocols used are all commonly used engineering methods and are feasible for engineering deployment.

[0050] 5) It has a comprehensive safety assurance mechanism. This invention is equipped with an early warning layer and a safety fallback mechanism. It dynamically adjusts the capacity expansion strategy according to the ratio of conductor temperature to allowable temperature, and automatically switches to conservative operation mode when the measurement is abnormal or the temperature approaches the upper limit to ensure system safety. Attached Figure Description

[0051] Figure 1 This is a flowchart of steps S1-S5 of the 10kV zero-carbon industrial park distribution network power flow voltage collaborative optimization and dynamic capacity expansion method of the present invention.

[0052] Figure 2 This is a schematic diagram illustrating the circuit thermal model and dynamic allowable current calculation principle of the present invention.

[0053] Figure 3 This is a schematic diagram of the power flow-voltage collaborative optimization control logic of the present invention.

[0054] Figure 4 The flowchart shows steps S1-S6 of the 10kV zero-carbon industrial park distribution network power flow voltage collaborative optimization and dynamic capacity expansion method of the present invention.

[0055] Figure 5 This is a schematic diagram of the system architecture of the present invention.

[0056] Figure 6 This is a schematic diagram of the overall process of the present invention.

[0057] Figure 7 This is a schematic diagram of the security rollback mechanism and operation record process of the present invention. Detailed Implementation

[0058] The following detailed implementation of a method for coordinated optimization of power flow voltage and dynamic capacity expansion in a 10kV zero-carbon industrial park distribution network, with reference to specific embodiments, is provided. These embodiments are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.

[0059] The innovation of this invention lies in:

[0060] 1) The dynamic allowable current calculation results based on the thermal model are directly used as the line current constraints of the optimization model and the rule layer, so that voltage control, power flow distribution and dynamic capacity expansion are coupled in a closed loop in the same control framework.

[0061] 2) The dynamic allowable current not only serves as a line safety verification indicator, but also participates in the real-time optimization model constraint update and rule layer triggering criteria, enabling the line thermal state information to directly affect power flow reconstruction and voltage regulation decisions.

[0062] 3) To address the adjustability of resources such as photovoltaic, energy storage, and electric vehicle charging loads in zero-carbon parks, a hierarchical control strategy is designed. With voltage over-limit and dynamic capacity expansion as trigger conditions, reactive power, energy storage active power, and flexible loads are adjusted in sequence to achieve coordination of source-grid-load-storage, thereby realizing multi-objective collaborative optimization within a unified framework.

[0063] 4) This invention does not connect the dynamic capacity expansion module, power flow optimization module and voltage control module in series independently. Instead, it uses the dynamic allowable current to update the constraint set and rule layer triggering conditions in real time, so that the line thermal state directly participates in the control decision, thereby forming a unified closed-loop collaborative control mechanism.

[0064] Example 1: Implementation of a method for coordinated optimization of power flow voltage and dynamic capacity expansion in a 10kV zero-carbon industrial park distribution network.

[0065] Combined with appendix Figures 1-3 As shown, this invention provides a method for coordinated optimization of power flow voltage and dynamic capacity expansion in a 10kV zero-carbon industrial park distribution network.

[0066] like Figure 1 As shown, Figure 1 This is a flowchart of steps S1-S5 of the 10kV zero-carbon industrial park distribution network power flow voltage collaborative optimization and dynamic capacity expansion method in Embodiment 1 of the present invention.

[0067] This embodiment provides a method for coordinated optimization of power flow and voltage and dynamic capacity expansion in a 10kV zero-carbon industrial park distribution network, applicable to industrial park distribution networks containing distributed photovoltaic, wind power, energy storage, and electric vehicle charging stations. This method is implemented on the main station of the industrial park distribution management system. It forms a closed-loop control system by collecting measurement data, performing power flow calculations and voltage assessments, calculating dynamic allowable current, generating and executing coordinated control strategies.

[0068] The method in this embodiment includes the following five steps:

[0069] Step S1: Collect the park's power distribution network operation data and environmental data.

[0070] Step S1 involves collecting electrical quantity data, environmental quantity data, and equipment status data from the park's power distribution network. The specific process is as follows:

[0071] The main station periodically collects the following data. The data collection period can be configured from 10 seconds to 5 minutes, depending on the main station's computing power and communication conditions, with a typical value of 1 minute:

[0072] 1. Electrical quantity data: 10kV bus voltage; current, active power, and reactive power at the beginning of each feeder; voltage and current at important nodes (such as energy storage access points, photovoltaic access points, and charging pile concentration areas).

[0073] 2. Environmental data: ambient temperature and wind speed near the critical path; optional: solar radiation intensity.

[0074] 3. Equipment status data: Opening and closing status of sectionalizing switches and ring network switches; current tap position of transformers; current SOC, charging and discharging status and power of energy storage systems; current output of photovoltaic / wind power; total charging power and adjustable load status of charging piles.

[0075] The above data is accessed through power distribution automation systems, smart meters, wireless temperature sensors, weather stations, etc., and is then connected to the main station database or real-time database.

[0076] Step S2: Perform power flow calculation and voltage risk assessment.

[0077] Step S2 performs power flow calculations on the distribution network based on the collected electrical quantity data, obtains the voltage amplitude of each node and the current of each branch, and identifies nodes at risk of voltage exceeding limits and branches at risk of overload.

[0078] In step S2, the power flow calculation algorithm is adaptively selected based on the distribution network topology to balance calculation accuracy and real-time performance: when the distribution network operates in a radial or weak ring network structure, a simplified linearized power flow algorithm is used to reduce the computational burden and meet the real-time requirements of minute-level rolling optimization; when the distribution network closes multiple ring network switches, forming a strong ring network structure with multiple power supply paths, the algorithm switches to a forward-backward nonlinear power flow algorithm to ensure the accuracy of the power flow calculation results. The specific process is as follows:

[0079] The main station uses the data collected in step S1 to perform power flow calculations on the 10kV park distribution network and assess voltage risks.

[0080] 1. Using the forward-backward substitution method or simplified linearized power flow algorithm, calculate: the voltage amplitude of each node; the current and power of each branch (line, cable).

[0081] 2. For 10kV park distribution networks with radial or weak ring network structures, simplified linear power flow algorithms can be used to reduce the computational burden; for scenarios with more complex topologies or ring network operation, nonlinear power flow algorithms such as forward pushback can be used.

[0082] 3. Voltage risk assessment: Determine whether the voltage of each node exceeds the limit, for example, below 0.9Un or above 1.1Un; mark nodes whose voltage is close to exceeding the limit as “voltage risk points”; mark branches whose current is close to or exceeds the static rated current of the line as “overload risk points”.

[0083] This step outputs: voltage status of each node (qualified / risky / overloaded); power flow status of each branch (normal / near overload / overloaded); and a list of voltage risk points and overload risk points that require special attention.

[0084] For identifying voltage over-limit risk nodes and overload risk branches, the identification process relies on the output results of distribution network power flow calculations. The voltage amplitude of each node and the current value of each branch obtained from the power flow calculations are used as the core judgment criteria. Risk identification is completed through comparison with preset thresholds and hierarchical judgment. The specific process is as follows:

[0085] Based on the 10kV distribution network operation regulations and the operation and management requirements of the park's distribution network, threshold values ​​for the upper and lower limits of node voltage qualification, voltage over-limit warning thresholds, and the corresponding static rated current values ​​and overload warning thresholds for each branch are set in advance. After the power flow calculation is completed, the calculated voltage amplitude of each node is compared with the corresponding voltage threshold: if the node voltage amplitude exceeds the upper and lower limits of voltage qualification, it is determined to be a voltage over-limit node; if the node voltage amplitude is within the qualification range but falls into the preset warning interval or is close to the qualification boundary, it is determined to be a voltage over-limit risk node. Simultaneously, the calculated current values ​​of each branch are compared with the current thresholds of the corresponding branches: if the branch current value is greater than or equal to the branch static rated current, it is determined to be an overload branch; if the branch current value is less than the static rated current but greater than or equal to the overload warning threshold and is in the heavy load warning interval, it is determined to be an overload risk branch. Finally, the location identifiers and corresponding operating parameters of all voltage over-limit risk nodes and overload risk branches are summarized to form a risk identification result, which serves as the directional triggering basis for subsequent dynamic capacity expansion calculations and the generation of power flow-voltage coordinated control strategies.

[0086] Step S3: Establish a thermal model of the line / equipment and calculate the dynamic allowable current.

[0087] Step S3: For the identified overload risk branches, calculate the real-time theoretical dynamic allowable current based on the line thermal balance model, perform a safety reduction on the theoretical dynamic allowable current to obtain the dynamic allowable current for operation constraints, and use the dynamic allowable current for operation constraints as the upper limit of the current constraint for the corresponding branch.

[0088] After obtaining the dynamic allowable current for operational constraints in step S3, a three-level early warning linkage logic is set based on the ratio of the branch conductor temperature to the maximum allowable temperature of the conductor. The activation range of dynamic capacity expansion and the branch current constraint boundary are dynamically adjusted throughout the process: when the ratio is lower than the first early warning threshold, dynamic capacity expansion is enabled normally, and the dynamic allowable current for operational constraints obtained in step S3 is maintained as the upper limit of the current constraint for the corresponding branch; when the ratio is between the first and second early warning thresholds, the dynamic capacity expansion range is limited, the safety reduction coefficient in step S3 is lowered, and the upper limit of the duration of the branch's allowable short-term exceedance of the static rated current is shortened simultaneously; when the ratio is higher than or equal to the second early warning threshold, the dynamic capacity expansion function of the corresponding branch is turned off, the static rated current of the branch is restored as the upper limit of the current constraint, and the safety backoff logic is triggered.

[0089] In step S3, when calculating the theoretical dynamic allowable current, the line thermal balance model is used as the theoretical basis, and an engineering implementation method combining offline preprocessing and online rapid calculation is adopted: Before the rolling closed-loop control process is implemented, the line thermal balance model is used to complete the full-condition calculation based on the inherent parameters of the line, and the theoretical dynamic allowable current corresponding to different ambient temperatures and wind speeds is obtained. A mapping relationship table between environmental parameters and theoretical dynamic allowable current is established, or a piecewise linear calculation formula with ambient temperature and wind speed as independent variables is fitted. During the execution of step S3, the real-time ambient temperature and wind speed included in the environmental data collected in step S1 are used to quickly obtain the theoretical dynamic allowable current by looking up the table or substituting it into the piecewise linear calculation formula. The specific process is as follows:

[0090] like Figure 2 As shown, Figure 2 This is a schematic diagram illustrating the circuit thermal model and dynamic allowable current calculation principle of the present invention. Figure 2 It demonstrates the relationship between conductor heating and heat dissipation and temperature, current, ambient temperature, and wind speed, as well as the process of determining the dynamic allowable current.

[0091] For the lines marked as "overload risk points" in step S2, perform dynamic capacity expansion calculations.

[0092] Step S3.1, Line thermal balance model and dynamic allowable current calculation formula.

[0093] For critical paths, a simplified thermal balance model is adopted, which is consistent with the experience of existing dynamic capacity expansion projects for conductors.

[0094] Wire heating power Approximately:

[0095] ;

[0096] in: Line current (A); For the wire at temperature The resistance below ( ).

[0097] Heat dissipation power Approximately:

[0098] ;

[0099] in: Estimated value of conductor temperature ; For ambient temperature ; Wind speed ; , These are empirical coefficients related to conductor structure, surface properties, and environmental conditions. The equivalent term (W) represents radiative heat dissipation and other heat dissipation factors that are difficult to model independently. It can be obtained by fitting historical running data.

[0100] For example Indicates radiative heat dissipation power, according to Calculate; where ε is the surface emissivity of the conductor, and σ is the Stefan-Boltzmann constant (σ = σ / σ). If the radiative heat dissipation is difficult to model accurately due to the type of conductor or the laying method, the following can be used: This is an equivalent replacement for the constant term, which is obtained by linear regression fitting of historical operating data.

[0101] Under steady-state thermal equilibrium Therefore, we can inversely calculate the temperature of the conductor when it does not exceed the maximum allowable temperature. Theoretical dynamic allowable current at time One feasible calculation formula is as follows:

[0102] ;

[0103] In the formula, For the theoretically dynamic allowable current, The maximum allowable temperature for the conductor. For ambient temperature, Wind speed (m / s) , These are empirical coefficients related to the conductor structure and surface properties. For equivalent radiative heat dissipation, The resistance value of the conductor at the highest permissible temperature is given; the theoretical dynamic permissible current is multiplied by a safety reduction factor ranging from 0 to 1 to obtain the dynamic permissible current for the operational constraints.

[0104] This formula is derived from the heat balance equation. exist The current is directly derived. The theoretical dynamic allowable current can be calculated using a thermal balance model. For more precise engineering applications, the IEEE 738 or IEC 60853 thermal balance models can also be used for calculation.

[0105] To achieve accurate calculation and safe management of dynamic capacity expansion of power lines, this invention includes two sets of core calculation formulas. These formulas are based on the same physical laws governing conductor heat exchange, working together and each fulfilling its specific function to form a complete system for calculating the thermal state of power lines. The specific relationships are as follows:

[0106] The first group is the dynamic allowable current. The calculation formula is based on the principle of steady-state thermal balance of the conductor, using the conductor's maximum allowable design temperature. Using on-site measured ambient temperature and wind speed as inputs, the theoretical maximum current carrying capacity of the line under the condition of meeting the thermal safety red line is derived in reverse. This calculation result is the core basis for the line current constraint in the dynamic capacity expansion strategy, determining the upper limit of the branch short-term overload current. The second group is conductor temperature. The estimation formula, also based on the balance between Joule heating and natural heat dissipation, uses the real-time operating current of the line, ambient temperature, and wind speed as inputs. When temperature sensors cannot be installed on the line, it estimates the current actual operating temperature of the conductor. This temperature value is not involved in the calculation of the dynamic allowable current, but rather serves as the core criterion for thermal state monitoring, graded early warning, overload judgment, and safety backoff mechanisms. In the entire control logic, Define the current boundary for dynamic capacity expansion. Monitor the real-time thermal status during the dynamic capacity expansion process; regardless of whether the conductor temperature is measured or estimated by the model, it needs to be verified in conjunction with the dynamic allowable current calculation results to ensure that the line is always within the thermal safety range when dynamic capacity expansion is enabled or when the static rated current is exceeded for a short time. The estimation formula is only used as a supplementary means when there is no temperature measuring equipment, and does not change the original calculation logic.

[0107] Based on the above heat balance calculation requirements, this solution adopts the following measurement and estimation methods for the temperature of the critical path conductors: Measurement method for critical path temperature:

[0108] The temperature of critical circuit lines can be measured using wire clip wireless temperature sensors or cable head temperature sensors.

[0109] If temperature cannot be directly measured, it can be estimated based on ambient temperature and line load using an empirical temperature rise model to assist in the calculation of dynamic allowable current. For example, a linear or piecewise linear empirical temperature rise model based on the balance between Joule heating and ambient heat dissipation can be used.

[0110] ;

[0111] In the formula, This is an estimated value for the conductor temperature. For ambient temperature, For line current, For wind speed, , The temperature rise coefficient is obtained by fitting historical operating data, where , .

[0112] in In Joule heating, the temperature increases with the square of the current. The corresponding airflow speed enhances heat dissipation; the higher the airflow speed, the lower the temperature.

[0113] Step S3.2, Engineering Implementation Method.

[0114] Based on the line parameters, a table or formula for the correspondence between "ambient temperature - wind speed - allowable current" is obtained in advance through offline calculation;

[0115] When online, according to actual measurements , By referring to tables or substituting into formulas, the theoretical dynamic allowable current of the current line can be obtained. For example, a piecewise linear formula can be used:

[0116] ;

[0117] in , , The coefficients are obtained by fitting historical data; alternatively, a hierarchical lookup table method can be used to find the corresponding allowable current based on the temperature and wind speed range.

[0118] Step S3.3, safety reduction factor and time constraint.

[0119] Based on the theoretical dynamic allowable current calculated from steady-state thermal equilibrium, a safety reduction factor is introduced. The allowable current used for operating constraints is obtained as follows:

[0120] ;

[0121] in: For safety reduction factor; For a moment Theoretical dynamic allowable current (A); For a moment The allowable current (A) used for operating constraints.

[0122] Safety reduction factor The value can be selected based on the line type, measurement method, and operational experience. A typical range is 0.85–0.95. For example, taking… This is to offset the effects of model errors and measurement errors.

[0123] The calculation and use of dynamic allowable current meet the requirements of the maximum allowable temperature of the conductor and the duration of short-time overload in the operating procedures.

[0124] Step S3.4, Dynamic capacity expansion judgment and early warning layer.

[0125] For overload risk circuits: if the current If the line is allowed to exceed its static rated current for a short period, it is considered that "dynamic capacity expansion has been enabled"; if If the current is too high, it is considered a true overload and the current needs to be reduced immediately through control measures.

[0126] To further enhance the integrity of the safety logic, an early warning layer is added, based on the ratio of the measured / estimated conductor temperature to the maximum allowable temperature. Take different actions:

[0127] when At this time: Normal operation, dynamic capacity expansion is allowed;

[0128] when Time: Limit the increase in capacity, for example, by reducing the safety reduction factor. Further reduce or shorten the allowable overload duration;

[0129] when When: Trigger the safety rollback strategy, disable dynamic capacity expansion, restore the use of static rated current as a constraint, and disconnect some non-critical loads if necessary.

[0130] in: This is the ratio of the conductor temperature to the maximum allowable temperature. The first warning threshold; This is the second warning threshold; , For example, , .

[0131] This embodiment uses dynamic capacity expansion for some critical lines, while using static rated current as a constraint for other lines, in order to simplify the project implementation.

[0132] Step S4: Construct a power flow-voltage coordinated optimization control strategy.

[0133] Step S4 combines the identified voltage over-limit risk nodes and overload risk branches, using the node voltage acceptable range as voltage constraints and the dynamic allowable current for operation constraints as branch current constraints, to generate a power flow-voltage coordinated control strategy. The dynamic allowable current for operation constraints also participates in the constraint update and overload trigger judgment of the enabled dynamic capacity expansion branches in the coordinated control strategy, generating control commands for each terminal device, so that voltage control, power flow distribution and dynamic capacity expansion are coupled in a closed loop within the same control framework.

[0134] In step S4, the power flow-voltage coordinated control strategy adopts a two-layer architecture of fast response at the rule layer and rolling optimization at the optimization layer. The fast response at the rule layer sets multiple control priorities according to the logic of voltage regulation priority and power flow regulation matching.

[0135] When a node voltage exceeds the limit, the first stage adjusts the reactive power output of the distributed photovoltaic system or static var generator. If reactive power adjustment alone cannot restore the voltage to the acceptable range, the second stage adjusts the charging and discharging active power of the energy storage system. If the voltage still exceeds the limit after the two stages of reactive power and energy storage active power adjustment, the third stage adjusts the operating power of the flexible load.

[0136] When the current of the overload risk branch identified in step S2 exceeds the dynamic allowable current for operation constraints, the current level of the overload risk branch is reduced by adjusting the active power of energy storage, adjusting the power of flexible load, or changing the power flow direction by operating the distribution network switch.

[0137] The control commands output by the rule layer have higher priority than the rolling optimization results of the optimization layer. When there is a conflict between the control commands of the rule layer and the optimization layer, the control result of the rule layer is set as an additional constraint condition for the optimization layer, and the optimization layer re-solves for the optimal control strategy based on the set additional constraints. The specific process is as follows:

[0138] like Figure 3 As shown, Figure 3 This is a schematic diagram of the power flow-voltage collaborative optimization control logic of the present invention. Figure 3 It demonstrates the rule adjustment logic when voltage exceeds limits or line overload occurs, as well as the control strategy generation process of the optimization layer, dynamically allowing current to enter the optimization constraints.

[0139] Based on steps S2 and S3, the master station generates a collaborative control strategy, including a rule layer and an optimization layer.

[0140] The key to this invention lies in: the dynamic allowable current obtained in step S3. The line current constraint is directly used as the optimization model and rule layer, so that voltage control, power flow distribution and dynamic capacity expansion are coupled in a closed loop within the same control framework.

[0141] Step S4.1, General principles and priorities of the rule layer.

[0142] The general principle of the rule layer is: when the current of a line exceeds the static rated value, the system first calculates the dynamic allowable current of the line based on environmental conditions. If the current If so, it is allowed to continue running for a short period of time without immediate adjustment; if If this happens, the rules layer will immediately trigger load reduction or topology adjustment, and correct the line constraints in the optimization model in the next cycle.

[0143] Priority relationship between the rule layer and the optimization layer: Control commands from the rule layer have higher priority than those from the optimization layer; when there is a conflict between the rule layer and the optimization layer, the result from the rule layer is used as the constraint condition for the optimization layer. For example, if the rule layer requires energy storage to discharge to alleviate heavy-load lines, while the optimization layer originally planned to charge energy storage, then the optimization layer needs to resolve under the constraint of energy storage discharge power.

[0144] The specific execution order is as follows:

[0145] If the voltage of a node is below the lower limit: prioritize increasing the reactive power output of photovoltaic / SVG in that area; if it is still insufficient, reduce the energy storage charging power or increase the discharging power in that area; if it is still insufficient, appropriately reduce the flexible load power in that area.

[0146] If the voltage at a node is higher than the upper limit: prioritize reducing the reactive power output of photovoltaic / SVG in that area; if it is still insufficient, increase the energy storage charging power to absorb active power; if the voltage is still too high, pre-set interruptible loads can be put into operation or the transformer tap position can be adjusted.

[0147] For voltage constraints based on the node voltage acceptable range, the node voltage acceptable range is pre-set according to national standards, distribution network operation procedures and park operation requirements. On this basis, combined with the voltage tolerance characteristics and operation control objectives of distributed photovoltaic, energy storage and power consumption equipment in the zero-carbon park, the upper and lower voltage limits corresponding to each node are further determined to form a unified acceptable range.

[0148] This acceptable range has already been used as the criterion for judging voltage over-limit risk nodes in step S2. When entering step S4 to generate the collaborative control strategy, it is directly incorporated into the solution framework as a hard voltage constraint: In the fast response logic of the rule layer, it serves as the trigger criterion for voltage over-limit and the target range for multi-level voltage regulation, guiding the graded adjustment of reactive power output, energy storage active power and flexible load power; In the rolling optimization process of the optimization layer, it serves as the feasible domain boundary of the voltage amplitude of each node, and together with the dynamic allowable current constraint of the branch operation constraint, it constitutes the constraint condition set of the control strategy, ensuring that after the control command obtained by the solution is executed, the voltage of each node in the distribution network is always within the preset acceptable range.

[0149] If the current in a line exceeds the static rated value: first check the dynamic allowable current of the line. ;like It can continue to run for a short time without immediate adjustment; if The current in the line can be reduced by adjusting the energy storage, load, and switch status.

[0150] Step S4.2, optimize the layer logic (minute-level scrolling optimization).

[0151] The optimization layer is solved using linear programming or quadratic programming solvers.

[0152] The optimization layer, based on the rule layer, aims to minimize the total voltage deviation and the number of heavily loaded lines and their weighted combinations. Its objective function can be expressed as:

[0153] ;

[0154] In the formula, The objective function value, , These are the weighting coefficients. For nodes voltage amplitude, Reference voltage amplitude, This refers to the number of branches whose current exceeds the dynamic allowable current of their corresponding branches.

[0155] Constraints: Upper and lower limits for each energy storage capacity; SOC evolution constraints; adjustable power range for flexible loads; current of each line not exceeding [a certain limit]. The number of switch operations shall not exceed the preset upper limit within the rolling cycle.

[0156] Time scale: The optimization layer uses a rolling cycle of 1 to 5 minutes, and each time it considers the predicted load and output for the next 1 to 3 cycles.

[0157] The optimization model size is typically related to the number of feeders and adjustable resources in the park. In cases where the number of feeders is ≤10 and the number of adjustable resources is ≤20, commonly used linear / quadratic programming solvers such as CPLEX and Gurobi can complete the solution in seconds, satisfying 1 The real-time requirement of a 5-minute control cycle.

[0158] Based on the results of the rule layer and optimization layer, the main station generates a set of control instructions, including energy storage charging and discharging power instructions, reactive power instructions, load power limiting instructions, switch operation instructions, tap position instructions, etc.

[0159] For the dynamic allowable current used for operational constraints to simultaneously participate in the constraint update and overload trigger judgment of the enabled dynamic capacity expansion branch in the collaborative control strategy, it is executed synchronously based on the two-layer control architecture of fast response at the rule layer and rolling optimization at the optimization layer. The specific process is as follows:

[0160] In the overload trigger judgment stage, the dynamic allowable current of the operating constraints is used as the real-time judgment threshold of the rule layer, directly replacing the static rated current of the branch for the overload state judgment of the branch with enabled dynamic capacity expansion: For the overload risk branch identified in step S2, the actual operating current of the branch is collected in real time and compared with the dynamic allowable current of the corresponding branch's operating constraints; if the actual current of the branch is less than the dynamic allowable current, it is determined that the branch is in the safe bearing range of dynamic capacity expansion, and it is allowed to operate beyond the static rated current for a short time without triggering forced current limiting adjustment; if the actual current of the branch is greater than or equal to the dynamic allowable current, it is determined that the branch has reached the true overload state under the dynamic capacity expansion condition, and the hierarchical control logic of the rule layer is immediately triggered. By adjusting the energy storage charging and discharging power, adjusting the flexible load operating power, and operating the distribution network switch to reconfigure the power flow distribution, the current level of the branch is quickly reduced.

[0161] In the constraint update phase, the dynamic allowable current for operational constraints is used to dynamically refresh the constraint boundaries of the rolling optimization layer: within each rolling optimization cycle, the latest calculated dynamic allowable current for operational constraints in step S3 is used as the upper limit constraint of the current of the dynamically expanded branch, and is included in the constraint condition set of the optimization solution, replacing the original static rated current constraint; as the real-time ambient temperature and wind speed change, the dynamic allowable current for operational constraints is dynamically updated cycle by cycle, and the branch current constraint boundary corresponding to the optimization model is adjusted synchronously, so that the real-time carrying capacity of the line directly participates in the feasible domain limitation of power flow optimization, ensuring that the optimization solution results always match the current thermal safety margin of the line.

[0162] Meanwhile, the control actions of the rule layer based on the dynamic allowable current trigger have higher priority. When there is a conflict between the control result of the rule layer and the initial solution result of the optimization layer, the control output of the rule layer will be passed into the optimization layer as an additional constraint condition, driving the optimization layer to re-solve the optimal strategy, so that the result of the overload trigger judgment is consistent with the boundary of the constraint update, realizing the closed-loop coupling of voltage control, power flow distribution and dynamic capacity expansion within the same control framework.

[0163] Step S5: Perform collaborative control and dynamic capacity expansion.

[0164] Step S5 sends the generated control commands to each terminal device in the distribution network for execution; after execution, a new round of electrical quantities, environmental quantities, and equipment status data is collected, and a new round of power flow calculation, risk assessment, and strategy optimization is carried out to form a rolling closed-loop control. The specific process is as follows:

[0165] The master station will send the control commands generated in step S4 to the corresponding terminal devices:

[0166] Step S5.1: Issuance of control commands.

[0167] Send charging and discharging power commands to the energy storage converter; send reactive power commands to the photovoltaic inverter / SVG; send power limiting commands to the flexible load controller; send switching operation commands to the switch controller; and send tap position commands to the transformer tap changer controller.

[0168] Step S5.2, the actual utilization of dynamic capacity expansion.

[0169] For those identified as "overload risk" but For certain lines, it is permissible to exceed the static rated current for a certain period of time, but the duration is determined according to the line's heat capacity, conductor type, and operating procedures, typically ranging from 5 to 30 minutes, and the cumulative time is limited by day or week.

[0170] The system continuously monitors conductor temperature and environmental conditions. If the temperature approaches the upper limit or environmental conditions deteriorate, it automatically reduces the capacity increase and lowers the current.

[0171] For lines that exceed the dynamic allowable current, the rule layer adjustment is immediately triggered to reduce the load on the line or change the power flow path.

[0172] Step S5.3: Post-execution feedback and re-evaluation.

[0173] After executing the control command, the measurement data is collected again, and the power flow calculation and voltage assessment are performed again.

[0174] If the voltage and power flow still do not meet the requirements, repeat steps S4-S5 to perform rolling adjustments.

[0175] Through the above process, a closed-loop control of "monitoring-calculation-execution-re-monitoring" is formed.

[0176] Example 2, as Figures 4-7 As shown, Figure 4 This is a flowchart of steps S1-S6 of the 10kV zero-carbon industrial park distribution network power flow voltage collaborative optimization and dynamic capacity expansion method in Embodiment 2 of the present invention. Figure 5 This is a schematic diagram of the system architecture of the present invention. Figure 5 The overall system architecture of the method of the present invention is shown, including the data flow and control relationship between the master station module, the measurement module, the control module and the communication module. Figure 6 This is a schematic diagram of the overall process of the present invention. Figure 6 The invention demonstrates a complete six-step process from data acquisition to safe rollback, forming a closed-loop control. Figure 7 This is a schematic diagram of the security rollback mechanism and operation record process of the present invention. Figure 7 It demonstrates how the system reverts to a conservative operating mode and records key operating data in cases of measurement anomalies, temperature exceeding limits, or sudden environmental changes.

[0177] Based on the method described in Example 1, the method in Example 2 further includes the following steps:

[0178] Step 6: Run logs and safety rollback mechanism.

[0179] Step S6 continuously records the dynamic capacity expansion parameters of each control cycle and the execution data of the control commands generated by the power flow-voltage coordinated control strategy throughout the entire rolling closed-loop control process. When a preset abnormal operating condition is detected, a safety rollback strategy is triggered: the dynamic capacity expansion function is turned off, and the static rated current of the branch is restored as the upper limit of the current constraint to ensure that the node voltage is within the acceptable range. If there is still a risk of branch overload or node voltage exceeding the limit after restoring the static rated current constraint, non-critical flexible loads are removed. The constraint conditions after the safety rollback are applied to the subsequent power flow calculation and coordinated control strategy generation. The specific process is as follows:

[0180] To ensure the authenticity and safety of the project, the following mechanisms are added to this embodiment:

[0181] Step S6.1, Run record.

[0182] Record the time, line, current, ambient temperature, wind speed, and conductor temperature for each dynamic capacity increase activation;

[0183] Record coordinated control actions: changes in energy storage charging and discharging, reactive power regulation, load adjustment, switching operations, etc.

[0184] Used for later analysis, optimization, and maintenance.

[0185] Step S6.2, safety rollback mechanism.

[0186] In practical applications, the backoff trigger threshold can be adjusted based on field operating experience. For example, when there is no valid data at a key measurement point within three consecutive acquisition cycles, or when the measured / estimated value of the conductor temperature reaches more than 95% of the maximum allowable temperature (i.e., The system will then trigger a rollback strategy. This threshold is related to the warning layer. The rollback conditions correspond to this.

[0187] Rollback strategies include:

[0188] Dynamic capacity expansion is disabled, and static rated current is restored as the line current constraint.

[0189] Prioritize ensuring node voltage compliance, followed by power flow optimization;

[0190] Remove some non-critical loads when necessary.

[0191] Example 3 is a complete numerical simulation example based on the content of Examples 1 and 2.

[0192] This embodiment is based on the MATLAB power flow simulation environment to construct a case study, and uses the forward-backward power flow algorithm and quadratic programming solver for verification; the data are simulation results, used to illustrate the working process of the present invention, and do not constitute a limitation on the actual engineering effect.

[0193] 1. Park system configuration.

[0194] Number of 10kV feeders: 3 (feeders) ); Number of nodes: 18 nodes (including bus nodes); Distributed photovoltaic: Total capacity 2MW, connected to nodes 5, 8, and 12; Energy storage system: Access node 6; Electric vehicle charging station: 500kW, access node 10; Other loads: total capacity 1.5MW, distributed to various nodes.

[0195] 2. Line parameters and operating conditions.

[0196] Typical line parameters: L1: Length 2.5km, rated current 400A, conductor is aluminum stranded wire, maximum allowable temperature 80℃; L2: Length 3.0km, rated current 350A; L3: Length 2.0km, rated current 450A.

[0197] Environmental conditions: Ambient temperature Wind speed .

[0198] 3. Operating status before optimization (voltage control scheme only).

[0199] Under the condition of using only traditional voltage control (regulating reactive power, not enabling dynamic capacity expansion, and not performing power flow optimization), the simulation results are as follows:

[0200] Maximum line load factor: 108% (L1 current exceeds rated value during peak photovoltaic periods);

[0201] Minimum voltage: 0.91 pu (node ​​10 voltage is low during peak load periods);

[0202] L1 conductor temperature: 78℃, close to the maximum allowable temperature of 80℃;

[0203] Some photovoltaic output is limited by voltage / capacity constraints, and the photovoltaic absorption rate is about 88%.

[0204] 4. Optimized running status.

[0205] After applying the method of this invention (power flow-voltage co-optimization and dynamic capacity expansion), simulation results show:

[0206] Maximum line load rate: around 105% (L1 current is slightly higher than the rated value, but lower than the upper limit of dynamic allowable current).

[0207] Minimum voltage: 0.95 pu (node ​​10 voltage improvement);

[0208] During dynamic capacity expansion, the temperature of L1 conductor is 74℃, which is lower than the maximum allowable temperature of 80℃.

[0209] The photovoltaic grid integration rate has increased to over 90%, allowing some previously restricted photovoltaic output to be released.

[0210] Example 4 is a simplified control strategy example based on the content of Examples 1 and 2.

[0211] This embodiment further simplifies the control strategy by using only the rule layer and not the optimization layer, making it suitable for campuses with limited computing resources or relatively simple operating scenarios.

[0212] The control variables include only: energy storage charging and discharging power, photovoltaic / SVG reactive power, and some flexible load power; the switch status and tap position are not changed; dynamic capacity expansion is only enabled for 1-2 key lines.

[0213] This embodiment still ensures voltage compliance and a certain degree of power flow optimization, while further reducing implementation complexity and demonstrating engineering flexibility.

[0214] Example 5 is a simplified control strategy example based on the content of Examples 1 and 2.

[0215] As mentioned above, step S4 combines the identified voltage over-limit risk nodes and overload risk branches, using the node voltage acceptable range as voltage constraints and the dynamic allowable current for operation constraints as branch current constraints, to generate a power flow-voltage coordinated control strategy. The dynamic allowable current for operation constraints simultaneously participates in the constraint update and overload trigger judgment of the coordinated control strategy, and finally generates control commands for each terminal device, so that voltage control, power flow distribution and dynamic capacity expansion are coupled in a closed loop within the same control framework.

[0216] In step S4, during the generation of the power flow-voltage coordinated control strategy, distribution network switch operation commands and transformer tap adjustment commands are output simultaneously:

[0217] For a park distribution network with multiple power supply paths, for the overload risk branches identified in step S2, the operation of sectionalizing switches or ring network switches is performed to reconstruct the power flow distribution, share the power flow load of the overload risk branches, and give full play to the carrying capacity of dynamic capacity expansion.

[0218] When the overall bus voltage deviates from the preset acceptable range, the bus voltage reference is calibrated by adjusting the transformer tap positions, and reactive power regulation and energy storage charging and discharging regulation are linked to achieve voltage coordination optimization across the entire distribution network. The specific details are as follows:

[0219] This embodiment adds switch operation and tap adjustment:

[0220] For parks with ring networks or multiple power supply paths, the power flow path can be changed by operating sectionalizing switches / ring network switches to reduce the load on heavily loaded lines;

[0221] When the overall bus voltage is too high or too low, adjust the transformer tap position to fine-tune the bus voltage level.

[0222] Add constraints on the number of switching operations and the tap adjustment range to the optimization layer.

[0223] This embodiment is applicable to 10kV zero-carbon parks with complex topologies and multi-path power supply capabilities, and can further improve power flow optimization and dynamic capacity expansion utilization.

[0224] In summary, the present invention provides a method for coordinated optimization of power flow voltage and dynamic capacity expansion in a 10kV zero-carbon industrial park distribution network, achieving the following technical effects: 1) In a typical 10kV zero-carbon industrial park example, compared with a voltage control-only scheme, the present invention can reduce the number of heavily loaded lines and improve the utilization rate of distributed photovoltaic power output while ensuring voltage compliance. This helps improve the level of renewable energy absorption and enhances the operational flexibility of the industrial park distribution network in scenarios with local voltage constraints or line capacity constraints; 2) Based on line / equipment thermal models and environmental data, the dynamic allowable current is calculated in real time, ensuring compliance with the maximum allowable conductor temperature and the operating procedures' requirements for short-term overload duration. Under the premise of meeting the requirements, it can temporarily exceed the static rated capacity to improve the renewable energy absorption capacity; 3) It unifies power flow, voltage and dynamic capacity expansion in a coordinated control framework to achieve integrated coordinated operation of source-grid-load-storage; 4) It adopts commonly used forward-backward power flow calculation and linear / quadratic programming solvers, with a control cycle of 1 to 5 minutes. In a typical 10kV zero-carbon park scenario with ≤10 feeders and ≤20 adjustable resources, solvers such as CPLEX and Gurobi can complete the solution in a few seconds, meeting the real-time requirements and having engineering feasibility; 5) It has a safety backoff mechanism and operation record function to ensure that the system can still operate safely under various abnormal conditions.

[0225] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0226] The above embodiments are merely illustrative examples and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for coordinated optimization of power flow voltage and dynamic capacity expansion in a 10kV zero-carbon industrial park distribution network, characterized in that, Includes the following steps: Step S1: Collect electrical quantity data, environmental quantity data, and equipment status data of the park's power distribution network; Step S2: Based on the collected electrical quantity data, perform power flow calculation of the distribution network to obtain the voltage amplitude of each node and the current of each branch, and identify the nodes at risk of voltage exceeding the limit and the branches at risk of overload. Step S3: For the identified overload risk branches, calculate the real-time theoretical dynamic allowable current based on the line thermal balance model, perform a safety reduction on the theoretical dynamic allowable current to obtain the dynamic allowable current for operation constraints, and use the dynamic allowable current for operation constraints as the upper limit of the current constraint for the corresponding branch. Step S4: Combining the identified voltage over-limit risk nodes and overload risk branches, a power flow-voltage coordinated control strategy is generated, using the node voltage acceptable range as the voltage constraint and the dynamic allowable current for operation constraints as the branch current constraint. The dynamic allowable current for operation constraints also participates in the constraint update and overload trigger judgment of the enabled dynamic capacity expansion branches in the coordinated control strategy, generating control commands for each terminal device, so that voltage control, power flow distribution and dynamic capacity expansion are coupled in a closed loop within the same control framework. Step S5: The generated control commands are sent to each terminal device in the distribution network for execution; after execution, a new round of electrical quantities, environmental quantities and equipment status data are collected, and a new round of power flow calculation and operation risk assessment, dynamic constraint update and collaborative strategy optimization are carried out to form a rolling closed-loop control.

2. The method for coordinated optimization of power flow voltage and dynamic capacity expansion of a 10kV zero-carbon industrial park distribution network according to claim 1, characterized in that, The method further includes the following steps: Step S6: Throughout the rolling closed-loop control process, continuously record the dynamic capacity expansion operation parameters of each control cycle, as well as the execution data of the control commands generated by the power flow-voltage coordinated control strategy; when a preset abnormal operating condition is detected, trigger a safety backoff strategy: disable the dynamic capacity expansion function, restore the branch static rated current as the upper limit of the current constraint, and prioritize ensuring that the node voltage is within the qualified range; if there is still a risk of branch overload or node voltage exceeding the limit after restoring the static rated current constraint, cut off non-critical flexible loads; the constraint conditions after the safety backoff are applied to the subsequent power flow calculation and coordinated control strategy generation.

3. The method for coordinated optimization of power flow voltage and dynamic capacity expansion of a 10kV zero-carbon industrial park distribution network according to claim 1, characterized in that, In step S2, the power flow calculation algorithm is adaptively selected based on the topology of the distribution network, balancing calculation accuracy and real-time performance. When the distribution network operates in a radial or weak loop structure, a simplified linear power flow algorithm is used for calculation to reduce the computational burden and meet the real-time requirements of minute-level rolling optimization. When the distribution network closes multiple ring network switches to form a strong ring network structure with multiple power supply paths, the algorithm switches to a forward-backward nonlinear power flow algorithm to ensure the accuracy of the power flow calculation results.

4. The method for coordinated optimization of power flow voltage and dynamic capacity expansion of a 10kV zero-carbon industrial park distribution network according to claim 1, characterized in that, In step S3, the calculation of the real-time theoretical dynamic allowable current based on the line thermal balance model specifically involves: establishing a thermal balance equation based on the steady-state thermal balance relationship between Joule heating of the conductor and heat dissipation from the environment, and then deriving the theoretical dynamic allowable current when the conductor temperature does not exceed the maximum allowable temperature. The calculation formula is as follows: ； In the formula, For the theoretically dynamic allowable current, The maximum allowable temperature for the conductor. For ambient temperature, For wind speed, , These are empirical coefficients related to conductor structure, surface properties, and environmental conditions. For equivalent radiative heat dissipation, The resistance value of the conductor at the highest permissible temperature is given; the theoretical dynamic permissible current is multiplied by a safety reduction factor ranging from 0 to 1 to obtain the dynamic permissible current for the operational constraints.

5. The method for coordinated optimization of power flow voltage and dynamic capacity expansion of a 10kV zero-carbon industrial park distribution network according to claim 1, characterized in that, In step S3, when calculating the real-time theoretical dynamic allowable current based on the line thermal balance model, it is necessary to obtain the branch conductor temperature parameters. If no conductor temperature sensors are installed on site and the actual conductor temperature cannot be directly collected, an empirical temperature rise model based on Joule heating and environmental heat dissipation is used to estimate the conductor temperature. The calculation formula for the empirical temperature rise model is as follows: ； In the formula, This is an estimated value for the conductor temperature. For ambient temperature, For line current, For wind speed, , The temperature rise coefficient is obtained by fitting historical operating data, and the temperature rise coefficient corresponding to wind speed is positive.

6. The method for coordinated optimization of power flow voltage and dynamic capacity expansion of a 10kV zero-carbon industrial park distribution network according to claim 1, characterized in that, After obtaining the dynamic allowable current for operational constraints in step S3, a three-level early warning linkage logic is set based on the ratio of the branch conductor temperature to the maximum allowable conductor temperature, dynamically adjusting the activation range of dynamic capacity expansion and the branch current constraint boundary throughout the process: When the ratio is lower than the first warning threshold, dynamic capacity expansion is enabled normally, and the operating constraints obtained in step S3 are used as the upper limit of the current constraints of the corresponding branch. When the ratio is between the first warning threshold and the second warning threshold, the dynamic capacity increase is limited, the safety reduction coefficient in step S3 is reduced, and the upper limit of the duration during which the branch is allowed to exceed the static rated current is shortened simultaneously. When the ratio is higher than or equal to the second warning threshold, the dynamic capacity expansion function of the corresponding branch is turned off, the static rated current of the branch is restored as the upper limit of the current constraint, and the safety backoff logic is triggered. The first warning threshold and the second warning threshold are preset according to the conductor type and operating procedures, and the second warning threshold is higher than the first warning threshold.

7. The method for coordinated optimization of power flow voltage and dynamic capacity expansion of a 10kV zero-carbon industrial park distribution network according to claim 1, characterized in that, In step S3, when calculating the theoretical dynamic allowable current, the line thermal balance model is used as the theoretical basis, and an engineering implementation method combining offline preprocessing and online rapid calculation is adopted: Before implementing the rolling closed-loop control process, the line thermal balance model is used to complete the full-condition calculation based on the inherent parameters of the line, obtain the theoretical dynamic allowable current corresponding to different ambient temperatures and wind speeds, and establish a mapping relationship table between environmental parameters and theoretical dynamic allowable currents or fit a piecewise linear calculation formula with ambient temperature and wind speed as independent variables. During step S3, the real-time ambient temperature and wind speed included in the environmental data collected in step S1 are used to quickly obtain the theoretical dynamic allowable current by looking up a table or by substituting into a piecewise linear calculation formula.

8. The method for coordinated optimization of power flow voltage and dynamic capacity expansion of a 10kV zero-carbon industrial park distribution network according to claim 1, characterized in that, In step S4, the power flow-voltage coordinated control strategy adopts a two-layer architecture of fast response at the rule layer and rolling optimization at the optimization layer. The fast response at the rule layer sets multiple control priorities according to the logic of voltage regulation priority and power flow regulation matching. When a node voltage exceeds the limit, the first stage adjusts the reactive power output of the distributed photovoltaic system or static var generator. If reactive power adjustment alone cannot restore the voltage to the acceptable range, the second stage adjusts the charging and discharging active power of the energy storage system. If the voltage still exceeds the limit after the two stages of reactive power and energy storage active power adjustment, the third stage adjusts the operating power of the flexible load. When the current of the overload risk branch identified in step S2 exceeds the dynamic allowable current for operation constraints, the current level of the overload risk branch is reduced by adjusting the active power of energy storage, adjusting the power of flexible load, or changing the power flow direction by operating the distribution network switch. The control commands output by the rule layer have higher priority than the rolling optimization results of the optimization layer. When there is a conflict between the control commands of the rule layer and the optimization layer, the control results of the rule layer are set as additional constraints of the optimization layer, and the optimization layer re-solves the optimal control strategy based on the set additional constraints.

9. A method for coordinated optimization of power flow voltage and dynamic capacity expansion of a 10kV zero-carbon industrial park distribution network according to claim 8, characterized in that, In step S4, the optimization layer performs rolling optimization with the goal of minimizing the weighted sum of node voltage deviation and branch overload degree. The objective function is: ； In the formula, The objective function value, , These are the weighting coefficients. For nodes voltage amplitude, Reference voltage amplitude, This refers to the number of branches whose current exceeds the dynamic allowable current of their corresponding branches.

10. A method for coordinated optimization of power flow voltage and dynamic capacity expansion of a 10kV zero-carbon industrial park distribution network according to claim 1, characterized in that, In step S4, during the generation of the power flow-voltage coordinated control strategy, distribution network switch operation commands and transformer tap adjustment commands are output simultaneously: For a park distribution network with multiple power supply paths, for the overload risk branches identified in step S2, the operation of sectionalizing switches or ring network switches is performed to reconstruct the power flow distribution, share the power flow load of the overload risk branches, and give full play to the carrying capacity of dynamic capacity expansion. When the overall bus voltage is detected to deviate from the preset qualified range, the bus voltage reference is calibrated by adjusting the transformer tap position, and reactive power regulation and energy storage charging and discharging regulation are linked to achieve voltage coordination optimization of the entire distribution network.

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