A method and system for adjusting three-phase unbalanced load

Abstract

The application provides a three-phase unbalanced load adjustment method and system, and belongs to the technical field of power distribution network of power systems. The method acquires load information of each electric meter and calculates the three-phase unbalance degree of the total meter by collecting the power consumption data and phase information of the total meter and all single-phase electric meters in the power distribution area in real time. When the three-phase unbalance degree of the total meter exceeds the set threshold, a load prediction model is established based on the historical power consumption data. A digital power grid model containing line resistance parameters, line reactance parameters and load power parameters is constructed, and various phase modulation schemes are simulated in the model. The weighted scoring method is used to comprehensively evaluate the three-phase unbalance degree improvement effect, construction distance factors and operation time factors. According to the evaluation results, a phase modulation work order containing the list of single-phase electric meters that need to be modulated and the target phase is generated and sent to the field terminal through a communication network to guide the phase modulation operation. The application can accurately guide the phase modulation operation, reduce the number of repeated adjustments, and significantly improve the three-phase unbalance treatment efficiency.

Description

Technical Field

[0001] This invention relates to the field of power system distribution network technology, specifically to a method and system for adjusting three-phase unbalanced loads. Background Technology

[0002] In a three-phase AC power system, ideally, the three-phase voltages and currents should maintain a symmetrical relationship with equal amplitudes and a phase difference of 120°. However, in actual power distribution networks, since residential electricity consumption, commercial lighting, and other loads are mostly supplied by single-phase power, and the load distribution is often uneven, the three-phase currents become unbalanced.

[0003] Patent CN116316712B discloses an intelligent collaborative control method for three-phase loads based on electricity consumption characteristics. The method comprises the following steps: Step 1. Data acquisition, including acquiring the relationship between the transformer substation and the user substation, and acquiring current data collected by a high-frequency acquisition terminal; Step 2. Dividing the electricity meter into phases based on user electricity consumption characteristics and a phase analysis algorithm; Step 3. Constructing an intelligent adjustment calculation model for three-phase imbalance in the transformer substation, including calculating the three-phase average current from the current data collected by the high-frequency acquisition terminal, calculating the three-phase average imbalance degree, and calculating the optimal adjustment current value for the three phases; Step 4. Outputting the load adjustment method. This invention can effectively improve the three-phase imbalance in the transformer substation, reduce the number of meter phase switching operations, and improve work efficiency.

[0004] Currently, power companies mainly use the following methods to deal with three-phase imbalance problems:

[0005] The first method is to use the maximum-minimum current difference method or the average deviation method. This method measures the instantaneous values ​​of the three-phase currents and calculates the difference between the maximum and minimum phase currents, or the deviation from the average current, to determine the degree of three-phase imbalance. However, current is an instantaneous value that changes rapidly and is greatly affected by external interference factors. It cannot reflect dynamic changes and all hazards, and therefore provides insufficient support for the formulation of mitigation plans and economic benefit analysis.

[0006] The second method is to use instrument measurement, employing specialized equipment such as a three-phase power quality analyzer or a high-end clamp meter for on-site testing. This method requires purchasing specialized equipment and connecting it to the three-phase meter for testing, but it cannot test single-phase meters and can only calculate results to roughly determine whether the current main meter is unbalanced in three phases.

[0007] In practice, when the backend detects a three-phase imbalance in a certain zone, phase adjustment is performed on some meters based on the specific circumstances of the imbalance. After the phase adjustment is completed, a period of operation is required before a comprehensive analysis of the entire zone is conducted to determine if the expected effect has been achieved. If not, phase adjustment needs to be performed again. This approach cannot accurately predict the effect after phase adjustment, potentially leading to multiple operations to achieve the desired result. Furthermore, the time required for operation is also considerable.

[0008] Furthermore, because users don't know which phase their individual meters are connected to, when a three-phase imbalance occurs in the main meter, it's impossible to immediately identify which single-phase meter to adjust. The only solution is to inspect the site and rewire. After several days of operation, the situation is checked again. If the imbalance persists, another on-site inspection and adjustment are required, followed by further observation, and so on, until the three-phase imbalance is resolved. This approach is time-consuming and labor-intensive, failing to address the three-phase imbalance problem promptly, wasting significant human and material resources, and still not achieving the desired results. Summary of the Invention

[0009] To address the problem of unknown phase information in single-phase electricity meters in the background art, this invention determines the phase information through the meter's built-in phase record or system configuration. The purpose of this invention is to provide a method and system for adjusting three-phase unbalanced loads. This invention can accurately guide phase adjustment operations, reduce the number of repeated adjustments, and improve work efficiency.

[0010] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0011] A method for adjusting three-phase unbalanced load includes the following steps:

[0012] Real-time collection of electricity consumption data and phase information from the main meter and all single-phase meters within the power distribution area. The electricity consumption data includes current and voltage values.

[0013] Based on the collected electricity consumption data, the three-phase imbalance of the main meter is calculated, and the load current of each single-phase meter and its corresponding phase are obtained. The three-phase imbalance is calculated using the current imbalance formula, which is the percentage deviation between the maximum phase current and the average phase current. When the three-phase imbalance of the main meter exceeds the 15% threshold, a load prediction model is established based on historical electricity consumption data.

[0014] A digital model of the power grid is constructed, which includes line resistance parameters, line reactance parameters, and load power parameters. Various phase adjustment schemes are simulated in the digital model, including adjusting the phase of single-phase meters. A weighted scoring method is used to evaluate each phase adjustment scheme, which comprehensively considers the improvement effect of three-phase imbalance, construction distance factors, and operation time factors.

[0015] Based on the evaluation results, a phase adjustment scheme is selected, and a phase adjustment work order is generated. The phase adjustment work order includes a list of single-phase meters that need to be adjusted and the target phase. The phase adjustment work order is sent to the field terminal through the communication network to guide the phase adjustment operation.

[0016] In one embodiment of the present invention, the formula for calculating the current imbalance is as follows:

[0017] The three-phase unbalance is equal to the difference between the maximum phase current and the average phase current, divided by the average phase current, and then multiplied by 100%, where the average phase current is the arithmetic mean of the three-phase current values.

[0018] In one embodiment of the present invention, the load prediction model adopts a time series analysis method based on historical electricity consumption data, including the following steps: outlier removal and normalization processing of historical electricity consumption data; extraction of typical daily load curve features; and prediction of load change trend in the next 24 hours using an exponential smoothing algorithm, wherein the smoothing coefficient α is determined by optimization through historical data and the initial value is set to 0.3.

[0019] In practice, the smoothing coefficient α is optimized using a grid search method: the range of α values ​​[0.1, 0.9] (step size 0.1) is traversed on the historical dataset, and the α value with the smallest root mean square error is selected as the final parameter.

[0020] In one embodiment of the present invention, the power grid digital model is constructed through an equivalent circuit model, which includes resistive elements, reactive elements and load elements. Nodes and branches are defined according to the distribution network topology. Line resistance parameters and line reactance parameters are obtained through field measurements or design documents, and load power parameters are associated with each node.

[0021] In practice, the line resistance parameters are measured at the outgoing end of the distribution cabinet using a clamp meter (model Fluke 345) with an accuracy of ±1%; the line reactance parameters are entered according to the standard values ​​in Appendix B of GB / T 30844.1-2014.

[0022] In one embodiment of the present invention, the scoring indicators of the weighted scoring method include the degree of improvement of three-phase imbalance, construction distance score, and operation time score.

[0023] In one embodiment of the present invention, the construction distance score is calculated based on the geographical coordinates of the meter location, which are obtained through the meter's built-in GPS module (ublox MAX-M10S); the Euclidean distance is calculated according to a formula.

[0024] In one embodiment of the present invention, the present invention further includes an effect verification step: after the phase adjustment operation is completed, the power consumption data is re-collected to calculate the actual three-phase imbalance, the root mean square error between the predicted load curve and the actual load curve is calculated using the least squares method, and the smoothing coefficient of the exponential smoothing algorithm is adjusted according to the error.

[0025] In practice, an error-coefficient adjustment rule is established: when the root mean square error is greater than 10%, α increases by a step size of 0.05; when the error is less than 5%, α decreases by a step size of 0.02 to enhance the stability of the model.

[0026] In addition, the present invention also discloses a three-phase unbalanced load adjustment system, comprising:

[0027] The data acquisition module is used to collect electricity consumption data and phase information from single-phase electricity meters;

[0028] The calculation module is used to calculate the three-phase imbalance; the prediction module is used to build a load prediction model based on historical data.

[0029] The simulation module is used to build a digital model of the power grid and simulate phase adjustment schemes; the optimization module is used to execute the weighted scoring method.

[0030] The work order generation module is used to generate phase adjustment work orders; the communication module is used to send work orders to the field terminal.

[0031] In one embodiment of the present invention, the data acquisition module is connected to a single-phase meter via power line communication or wireless communication.

[0032] In one embodiment of the present invention, the simulation module and the optimization module are deployed on a server platform.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] This invention achieves accurate calculation and timely judgment of three-phase imbalance by collecting electricity consumption data and phase information of the main meter and all single-phase meters in the power distribution area in real time. It overcomes the delay and error problems caused by the reliance on manual inspection and instantaneous measurement in traditional methods, and ensures a rapid response capability to three-phase imbalance problems.

[0035] Based on this, a load forecasting model is established using historical electricity consumption data, which can scientifically predict future load change trends. This provides dynamic and forward-looking data support for the formulation of phase adjustment schemes, effectively avoiding the limitations of relying on experience-based judgment and blind adjustments in traditional methods, and significantly improving the accuracy and reliability of scheme formulation. This invention further combines a digital power grid model including line resistance parameters, line reactance parameters, and load power parameters to simulate multiple phase adjustment schemes in a virtual environment. It comprehensively evaluates the improvement effect of each scheme on three-phase imbalance, significantly reducing the uncertainty and trial-and-error costs of actual phase adjustment operations, and effectively preventing repeated adjustments due to unsatisfactory results. By using a weighted scoring method to comprehensively evaluate the phase adjustment schemes, taking into account the degree of improvement in three-phase imbalance, construction distance factors, and operation time factors, it achieves an organic combination of technical effectiveness and economic benefits, ensuring that the selected scheme optimizes power quality while maximizing savings in construction costs and operation time.

[0036] Meanwhile, by automatically generating work orders containing detailed phase adjustment information and distributing them to field terminals via communication networks, the phase adjustment operation has been standardized, streamlined, and remotely guided, significantly improving work efficiency. Combined with effect verification and model parameter optimization after phase adjustment, a complete closed-loop control mechanism has been formed, ensuring the continuous optimization and long-term stability of the three-phase imbalance treatment effect.

[0037] This invention can accurately guide phase adjustment operations, significantly reduce the number of repeated adjustments, lower manpower and material costs, and comprehensively improve the automation level and operational quality of three-phase imbalance management in power distribution networks. Attached Figure Description

[0038] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained from these drawings without creative effort.

[0039] Figure 1 This is a flowchart illustrating the three-phase unbalanced load adjustment method provided in an embodiment of the present invention.

[0040] Figure 2 This is a schematic diagram illustrating the construction of a power grid digital model in an embodiment of the present invention.

[0041] Figure 3 This is a schematic diagram of the module structure of a three-phase unbalanced load adjustment system provided in an embodiment of the present invention. Detailed Implementation

[0042] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of the embodiments of the invention. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0043] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0044] Example 1:

[0045] This embodiment discloses a method for adjusting a three-phase unbalanced load, including the following steps:

[0046] Real-time collection of electricity consumption data and phase information from the main meter and all single-phase meters within the power distribution area. The electricity consumption data includes current and voltage values.

[0047] Based on the collected electricity consumption data, the three-phase imbalance of the main meter is calculated, and the load current of each single-phase meter and its corresponding phase are obtained. The three-phase imbalance is calculated using the current imbalance formula, which is the percentage deviation between the maximum phase current and the average phase current. When the three-phase imbalance of the main meter exceeds the 15% threshold, a load prediction model is established based on historical electricity consumption data.

[0048] A digital model of the power grid is constructed, which includes line resistance parameters, line reactance parameters, and load power parameters. Various phase adjustment schemes are simulated in the digital model, including adjusting the phase of single-phase meters. A weighted scoring method is used to evaluate each phase adjustment scheme, which comprehensively considers the improvement effect of three-phase imbalance, construction distance factors, and operation time factors.

[0049] The weighted scoring method specifically includes:

[0050] Three-phase imbalance improvement score = (imbalance before adjustment - imbalance after adjustment) / imbalance before adjustment × 100;

[0051] Construction distance score = 1 / (1 + the sum of the Euclidean distances between each phase-adjusting meter);

[0052] Operation time score = 1 / (1 + estimated operation time);

[0053] Overall score = Improvement score of imbalance × 0.6 + Construction distance score × 0.2 + Operation time score × 0.2.

[0054] Based on the evaluation results, a phase adjustment scheme is selected, and a phase adjustment work order is generated. The phase adjustment work order includes a list of single-phase meters that need to be adjusted and the target phase. The phase adjustment work order is sent to the field terminal through the communication network to guide the phase adjustment operation.

[0055] Furthermore, a digital model of the power grid is constructed through the following steps: defining nodes and branches according to the distribution network topology; obtaining line resistance and line reactance parameters from distribution system design documents or field measurement data; and associating the real-time collected load power parameters with the corresponding nodes.

[0056] Furthermore, before establishing a load prediction model based on historical electricity consumption data, the following steps are also included: preprocessing the historical electricity consumption data, removing abnormal data, and extracting typical daily electricity consumption curve features; inputting the typical daily electricity consumption curve features into the exponential smoothing algorithm to generate a load change trend curve for a future period of time; and combining the load change trend curve to determine the load distribution in different time periods, providing a reference for subsequent phase adjustment schemes.

[0057] Furthermore, in the step of real-time collection of electricity consumption data and phase information from the main meter and all single-phase meters within the power distribution area, power line communication or wireless communication is used to achieve data transmission. Specifically, power line communication transmits electricity consumption data and phase information from the single-phase meters to the main meter via carrier signals, and then the main meter centrally uploads it to the backend server. Wireless communication transmits data directly to the backend server via LoRa or NB-IoT modules, ensuring the real-time performance and reliability of data collection.

[0058] In practical use, phase information is obtained through the phase recording unit built into the single-phase meter, or determined through the configuration information of the power distribution management system.

[0059] Furthermore, in the steps of constructing the power grid digital model, the first step is to model the line topology of the distribution network and record the connection relationships between each node; then, the line resistance parameters and line reactance parameters are entered based on actual measurement results; finally, the load power parameters are correlated with the electricity consumption data of the single-phase meters corresponding to each node to form a complete power grid digital model. This model can reflect the actual operating state of the distribution network and provide a basis for simulating phase adjustment schemes.

[0060] Furthermore, in simulating various phase adjustment schemes in the power grid digital model, for each single-phase meter requiring adjustment, the process involves attempting to switch it to another phase, and calculating the improvement effect on the three-phase imbalance after each switch. Simultaneously, a comprehensive evaluation of each phase adjustment scheme is conducted by combining construction distance and operation time scores. The construction distance score is calculated using the geographical coordinates of the meter's location, while the operation time score is quantified based on the time cost required for the phase adjustment operation.

[0061] Furthermore, in the step of evaluating each phase adjustment scheme using the weighted scoring method, the weight of the three-phase imbalance improvement effect is set to 0.6, the weight of the construction distance score is 0.2, and the weight of the operation time score is 0.2; after multiplying each score by its corresponding weight and summing them, the comprehensive score of each phase adjustment scheme is obtained; the phase adjustment scheme with the highest comprehensive score is selected as the final implementation scheme.

[0062] Furthermore, in the step of generating a phase adjustment work order, the phase adjustment work order includes the following: the number of the single-phase meter to be adjusted, the current phase, the target phase, the estimated construction time, and the estimated completion time; the phase adjustment work order is sent to the field terminal through the communication network, and after receiving the work order, the field terminal guides the staff to perform the phase adjustment operation in the specified order.

[0063] Furthermore, after the phase adjustment operation is completed, the power consumption data is collected again and the actual three-phase imbalance is calculated to verify the phase adjustment effect. If the actual three-phase imbalance does not meet the expected target, the load prediction model is optimized, the load change trend curve is updated, and the phase adjustment scheme is regenerated. This process is repeated until the three-phase imbalance meets the requirements.

[0064] This embodiment also discloses a three-phase unbalanced load adjustment system, including the following modules:

[0065] The data acquisition module is used to collect electricity consumption data and phase information from single-phase meters; the calculation module is used to calculate the three-phase imbalance.

[0066] The forecasting module is used to build load forecasting models based on historical data.

[0067] The simulation module is used to build a digital model of the power grid and simulate phase regulation schemes;

[0068] The optimization module is used to execute the weighted scoring method;

[0069] The work order generation module is used to generate phase adjustment work orders; the communication module is used to send work orders to the field terminal.

[0070] Furthermore, the data acquisition module is connected to the single-phase meter via power line communication or wireless communication. The power line communication module includes a carrier signal transmitting unit and a receiving unit, while the wireless communication module includes a LoRa or NB-IoT communication chip. The data acquisition module also has a data verification function, which performs integrity checks on the transmitted data using a CRC check algorithm.

[0071] Furthermore, the simulation module and optimization module are deployed on a server platform, which is equipped with a high-performance processor and a large-capacity storage device to support the construction of the power grid digital model and the simulation calculation of phase adjustment schemes. The simulation module uses multi-threading technology to process simulation tasks of multiple phase adjustment schemes simultaneously, thereby improving computational efficiency.

[0072] Furthermore, the work order generation module includes a work order template unit and a work order output unit; the work order template unit presets the standard format of the phase modulation work order, and the work order output unit converts the generated phase modulation work order into a readable format and sends it to the field terminal through the communication module; the communication module supports multiple communication protocols, including HTTP, MQTT and TCP / IP, to ensure the compatibility and stability of data transmission.

[0073] This embodiment achieves precise formulation and efficient execution of phase adjustment schemes by real-time collection of electricity consumption data and phase information from the main meter and all single-phase meters within the distribution area, combined with load prediction models and power grid digital models. By introducing a load prediction model, this embodiment can predict load change trends in advance, providing a scientific basis for the formulation of phase adjustment schemes. By constructing a power grid digital model, multiple phase adjustment schemes are evaluated in a simulated environment, avoiding the inefficiency of repeated phase adjustments in traditional methods. A weighted scoring method is used to comprehensively consider factors such as the improvement effect of three-phase imbalance, construction distance, and operation time, ensuring the optimality of the phase adjustment scheme. Phase adjustment work orders are sent to field terminals via a communication network, guiding staff to quickly and accurately complete the phase adjustment operation, significantly improving work efficiency.

[0074] To facilitate a better understanding of the present invention by those skilled in the art, the present invention will be further described below in conjunction with specific embodiments.

[0075] A method and system for adjusting three-phase unbalanced loads, see appendix. Figure 1 -Appendix Figure 3 Detailed explanation follows. (Attached) Figure 1 This demonstrates the overall process of three-phase unbalanced load adjustment, with appendix. Figure 2 A schematic diagram illustrating the construction of a digital model of the power grid, attached. Figure 3 This is a schematic diagram of the modular structure of a three-phase unbalanced load adjustment system.

[0076] In practical implementation, the main meter and all single-phase meters within the power distribution area collect electricity consumption data and phase information in real time through a data acquisition module. The data acquisition module includes a power line communication unit and a wireless communication unit. The power line communication unit consists of a carrier signal transmitting unit and a receiving unit, used to transmit data over the power line; the wireless communication unit uses a LoRa or NB-IoT chip to directly transmit data to the backend server. The connection between the data acquisition module and the single-phase meters is established through physical lines or wireless signals, ensuring the real-time nature and reliability of the data. Simultaneously, the data acquisition module incorporates a CRC check algorithm to verify the integrity of the received data, eliminating abnormal data to ensure the accuracy of subsequent calculations.

[0077] The calculation module is responsible for calculating the three-phase imbalance of the master meter based on the collected electricity consumption data (from the master meter). The formula for calculating the three-phase imbalance is the percentage deviation between the maximum phase current and the average phase current, i.e., the imbalance equals the maximum phase current minus the average phase current, divided by the average phase current, and then multiplied by 100%. The calculation module and the data acquisition module are connected through an internal communication interface to acquire electricity consumption data in real time and complete the calculation tasks. When the three-phase imbalance of the master meter exceeds the 15% threshold, the system triggers the load prediction model establishment process. The load prediction model is established by the prediction module. The prediction module first preprocesses the historical electricity consumption data, removes abnormal data, and extracts the typical daily electricity consumption curve features. The typical daily electricity consumption curve features are used to generate a load change trend curve for a future period of time through an exponential smoothing algorithm. Combined with the load change trend curve, the load distribution in different time periods is determined, providing a reference for subsequent phase adjustment schemes. The prediction module and the calculation module are connected through a data sharing interface to ensure that the load prediction model can accurately reflect the actual operating status of the current power distribution area.

[0078] The simulation module is responsible for building a digital model of the power grid and simulating various phase adjustment schemes. The construction of the power grid digital model includes three steps: line topology modeling, line parameter input, and load power parameter correlation. Line topology modeling records the connection relationships between nodes; line resistance and reactance parameters are input based on actual measurement results; and load power parameters are correlated with the electricity consumption data of the corresponding single-phase meters at each node. (Appendix) Figure 2 The digital model of the power grid is demonstrated, showcasing the specific components, including the relationship between line topology, line parameters, and load power parameters. The simulation module is deployed on a high-performance server platform, configured with multi-threading technology to simultaneously handle simulation tasks for multiple phase-shifting schemes, improving computational efficiency. The simulation module and the prediction module are connected via a data transmission interface, using load change trend curves as a basis for simulating phase-shifting schemes.

[0079] The optimization module uses a weighted scoring method to comprehensively evaluate the phase adjustment scheme generated by the simulation module. The weighted scoring method sets the weight of the three-phase imbalance improvement effect at 0.6, the construction distance score at 0.2, and the operation time score at 0.2.

[0080] The improvement effect of three-phase imbalance is obtained through calculations based on simulations of switching single-phase meters. The construction distance score is calculated using the geographical coordinates of the meter locations, and the operation time score is quantified based on the time cost required for the phase adjustment operation. The optimization module multiplies each score by its corresponding weight and sums them to obtain a comprehensive score for each phase adjustment scheme, selecting the scheme with the highest comprehensive score as the final implementation scheme. The optimization module and the simulation module are connected via a data interaction interface to ensure that the evaluation process can be accurately completed based on the simulation results.

[0081] The work order generation module generates phase adjustment work orders based on the evaluation results of the optimization module. Each phase adjustment work order includes the single-phase meter number requiring phase adjustment, the current phase, the target phase, the estimated construction time, and the estimated completion time. The work order generation module includes a work order template unit and a work order output unit. The template unit presets the standard format for phase adjustment work orders, while the output unit converts the generated work orders into a readable format and sends them to the field terminal via the communication module. The communication module supports multiple communication protocols, including HTTP, MQTT, and TCP / IP, ensuring data transmission compatibility and stability. The work order generation module and the optimization module are connected via a data transmission interface to ensure accurate generation and timely delivery of phase adjustment work orders.

[0082] The communication module is responsible for sending phase adjustment work orders to the field terminal, guiding staff to perform phase adjustment operations in the specified sequence. The communication module connects to the work order generation module via an internal communication interface, ensuring that phase adjustment work orders are transmitted to the field terminal quickly and accurately. After receiving the phase adjustment work order, the field terminal allows staff to perform phase adjustment operations on single-phase meters according to the work order content. After the phase adjustment operation is completed, the data acquisition module re-collects electricity consumption data and calculates the actual three-phase imbalance to verify the phase adjustment effect. If the actual three-phase imbalance does not meet the expected target, the load prediction model is optimized, the load change trend curve is updated, and a new phase adjustment scheme is generated. This process is iterated until the three-phase imbalance meets the requirements.

[0083] The data acquisition module connects to the single-phase meter via power line communication or wireless communication to collect electricity consumption data and phase information in real time, and transmits the data to the calculation module. After calculating the three-phase imbalance, the calculation module transmits the results to the prediction module. The prediction module builds a load prediction model based on historical data and feeds the results back to the simulation module. The simulation module constructs a digital model of the power grid and simulates various phase adjustment schemes. The optimization module comprehensively evaluates the phase adjustment schemes and transmits the optimal scheme to the work order generation module. The work order generation module generates a phase adjustment work order and sends it to the field terminal via the communication module to guide the staff in completing the phase adjustment operation. The entire system achieves efficient execution of three-phase unbalanced load adjustment through close cooperation between modules.

[0084] This invention achieves precise formulation and efficient execution of phase adjustment schemes by collecting real-time electricity consumption data and phase information from the main meter and all single-phase meters within the power distribution area, combined with load prediction models and power grid digital models.

[0085] In a specific application scenario, within a power distribution area, assuming the three-phase imbalance of the main meter consistently exceeds the 15% threshold for a certain period, the system immediately initiates a three-phase imbalance load adjustment process. First, the data acquisition module collects real-time electricity consumption data and phase information from the main meter and all individual phase meters via a power line communication unit or a wireless communication unit. Specifically, the power line communication unit uses a carrier signal transmitting unit to transmit the electricity consumption data from the individual phase meters to the main meter, which then centrally uploads it to the backend server. The wireless communication unit directly sends data to the backend server via a LoRa or NB-IoT chip, ensuring the real-time nature and reliability of the data acquisition. Simultaneously, the data acquisition module incorporates a CRC check algorithm to verify the integrity of the received data, eliminating abnormal data to ensure the accuracy of subsequent calculations.

[0086] The calculation module calculates the three-phase imbalance of the main meter based on the collected electricity consumption data, according to a formula. This formula is the percentage deviation between the maximum phase current and the average phase current; that is, the imbalance equals the maximum phase current minus the average phase current, divided by the average phase current, and then multiplied by 100%. When the calculation module detects that the three-phase imbalance of the main meter exceeds 15%, it triggers the prediction module to establish a load prediction model. The prediction module first preprocesses historical electricity consumption data, removing abnormal data and extracting typical daily electricity consumption curve features. Subsequently, it uses a trend extrapolation algorithm to generate a load change trend curve for a future period, and combines this curve to determine the load distribution in different time periods, providing a reference for subsequent phase adjustment schemes.

[0087] The simulation module constructs a digital model of the power grid based on load change trend curves. The digital model includes line topology, line resistance parameters, line reactance parameters, and load power parameters. The line topology records the connection relationships between nodes, line parameters are entered through actual measurements, and load power parameters are correlated with the electricity consumption data of the corresponding single-phase meters at each node. The simulation module is deployed on a high-performance server platform and uses multi-threading technology to simultaneously process simulation tasks for multiple phase adjustment schemes. For single-phase meters requiring adjustment, it attempts to switch them to other phases one by one, calculating the improvement effect on three-phase imbalance after each switch.

[0088] The optimization module employs a weighted scoring method to comprehensively evaluate the phase adjustment schemes generated by the simulation module. The weighted scoring method assigns a weight of 0.6 to the three-phase imbalance improvement effect, 0.2 to the construction distance, and 0.2 to the operation time. The three-phase imbalance improvement effect is calculated based on the simulated switching of single-phase meters. The construction distance score is calculated based on the geographical coordinates of the meter location, and the operation time score is quantified based on the time cost required for the phase adjustment operation. The optimization module multiplies each score by its corresponding weight and sums them to obtain a comprehensive score for each phase adjustment scheme, then selects the scheme with the highest comprehensive score as the final implementation scheme.

[0089] The work order generation module generates phase adjustment work orders based on the evaluation results of the optimization module. Each phase adjustment work order includes the single-phase meter number requiring phase adjustment, the current phase, the target phase, the estimated construction time, and the estimated completion time. The work order template unit in the work order generation module presets a standard format for phase adjustment work orders. The work order output unit converts the generated phase adjustment work orders into a readable format and sends them to the field terminal via the communication module. The communication module supports multiple communication protocols, including HTTP, MQTT, and TCP / IP, ensuring data transmission compatibility and stability.

[0090] After the communication module sends the phase adjustment work order to the field terminal, the staff performs the phase adjustment operation on the single-phase electricity meter according to the work order. After the phase adjustment operation is completed, the data acquisition module re-collects the electricity consumption data and transmits it to the calculation module. The calculation module recalculates the actual three-phase imbalance to verify the phase adjustment effect. If the actual three-phase imbalance does not meet the expected target, the prediction module optimizes the load prediction model, updates the load change trend curve, and regenerates the phase adjustment scheme. This process is repeated iteratively until the three-phase imbalance meets the requirements.

[0091] As can be seen from the above steps, this invention collects electricity consumption data and phase information in real time through the data acquisition module, combines this with the load change trend curve generated by the prediction module, constructs a digital model of the power grid using the simulation module, simulates various phase adjustment schemes, and finally selects the optimal scheme through the weighted scoring method of the optimization module. Throughout the system's operation, the modules collaborate closely through internal communication interfaces, ensuring the efficiency and accuracy of three-phase imbalance management. For example, in a specific scenario, when phase A is overloaded while phase B is underloaded, the system calculates the effect of switching some single-phase meters from phase A to phase B through the simulation module, and combines this with scoring based on construction distance and operation time to ultimately generate the optimal phase adjustment scheme. After the phase adjustment operation is completed, the system collects data again and verifies the effect, forming a closed-loop control, thereby significantly improving the efficiency and reliability of three-phase imbalance management.

[0092] Among them, the three-phase unbalance threshold is set at 15%, based on the GB / T 15543-2008 national standard for power quality. The load forecast adopts the triple exponential smoothing method with a smoothing coefficient α=0.3, based on historical 30-day data. The line resistance parameters are measured on-site by clamp meter with an accuracy of ±1%. The construction distance is calculated based on the meter's GPS coordinates, and the actual distance is calculated using the Haversine formula.

[0093] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0094] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. It should be noted that any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for adjusting a three-phase unbalanced load, characterized in that, Includes the following steps: Real-time collection of electricity consumption data and phase information from the main meter and all single-phase meters within the power distribution area. The electricity consumption data includes current and voltage values. Based on the collected electricity consumption data, the three-phase imbalance of the main meter is calculated, and the load current and its corresponding phase of each single-phase meter are obtained. The three-phase imbalance is calculated using the current imbalance formula, which is the percentage deviation between the maximum phase current and the average phase current. When the three-phase imbalance of the main meter exceeds the 15% threshold, a load prediction model is established based on historical electricity consumption data. The load prediction model uses time series analysis based on historical electricity consumption data, including the following steps: outlier removal and normalization of historical electricity consumption data; extraction of typical daily load curve features; and prediction of the load change trend in the next 24 hours using an exponential smoothing algorithm, where the smoothing coefficient α is determined through optimization using historical data. A digital model of the power grid is constructed, including line resistance parameters, line reactance parameters, and load power parameters. Multiple phase adjustment schemes are simulated within the digital model, including adjusting the phase of single-phase meters. A weighted scoring method is used to evaluate each phase adjustment scheme, comprehensively considering the improvement effect of three-phase imbalance, construction distance factors, and operation time factors. The scoring indicators of the weighted scoring method include the degree of improvement of three-phase imbalance, construction distance score, and operation time score. The weighted scoring method specifically includes: Three-phase imbalance improvement score = (imbalance before adjustment - imbalance after adjustment) / imbalance before adjustment × 100; Construction distance score = 1 / (1 + the sum of the Euclidean distances between each phase-adjusting meter); Operation time score = 1 / (1 + estimated operation time); Overall score = Improvement score of imbalance × 0.6 + Construction distance score × 0.2 + Operation time score × 0.2; The power grid digital model is constructed through an equivalent circuit model, which includes resistive elements, reactive elements, and load elements. Nodes and branches are defined according to the distribution network topology. Line resistance parameters and line reactance parameters are obtained through field measurements or design documents, and load power parameters are associated with each node. Based on the evaluation results, a phase adjustment scheme is selected, and a phase adjustment work order is generated. The phase adjustment work order includes a list of single-phase meters that need to be adjusted and the target phase. The phase adjustment work order is sent to the field terminal through the communication network to guide the phase adjustment operation.

2. The method for adjusting a three-phase unbalanced load according to claim 1, characterized in that, The formula for calculating the current unbalance is: The three-phase unbalance is equal to the difference between the maximum phase current and the average phase current, divided by the average phase current, and then multiplied by 100%, where the average phase current is the arithmetic mean of the three-phase current values.

3. The method for adjusting a three-phase unbalanced load according to claim 1, characterized in that, The construction distance score is calculated based on the geographical coordinates of the meter's location.

4. The method for adjusting a three-phase unbalanced load according to claim 1, characterized in that, It also includes an effect verification step: after the phase adjustment operation is completed, the power consumption data is collected again to calculate the actual three-phase imbalance, the root mean square error of the predicted load curve and the actual load curve is compared using the least squares method, and the smoothing coefficient parameter of the load prediction model is adjusted.

5. A three-phase unbalanced load adjustment system for implementing the method according to any one of claims 1 to 4, characterized in that, include: The data acquisition module is used to collect electricity consumption data and phase information from single-phase electricity meters; The calculation module is used to calculate the three-phase unbalance. The forecasting module is used to build load forecasting models based on historical data. The simulation module is used to build a digital model of the power grid and simulate phase adjustment schemes; the optimization module is used to execute the weighted scoring method. The work order generation module is used to generate phase adjustment work orders; the communication module is used to send work orders to the field terminal.

6. A three-phase unbalanced load adjustment system according to claim 5, characterized in that, The data acquisition module is connected to the single-phase meter via power line communication or wireless communication.

7. A three-phase unbalanced load adjustment system according to claim 6, characterized in that, The simulation module and optimization module are deployed on a server platform.

Images