Multi-objective optimized power quality control method

Abstract

The invention relates to the technical field of electric energy quality control, and discloses a multi-objective optimized electric energy quality control method, which comprises the following four steps of: 1, data acquisition: acquiring multiple electric energy quality parameters in real time through a key node high-precision sensor array, adaptively adjusting sampling frequency, and acquiring data; high precision and low packet loss rate are transmitted to the central control unit; secondly, multi-target construction is carried out, functions are constructed according to parameters, targets such as voltage fluctuation reduction, harmonic distortion and power factor extraction are covered, and dynamic weights are distributed; 3, generating a control strategy, solving the strategy by using a fusion algorithm, and clearly adjusting action parameters of equipment; and 4, feedback is executed, equipment executes and monitors, the strategy is optimized by using an algorithm according to deviation, and stable operation of the system is guaranteed. The method has the advantages of accurate multi-objective optimization, intelligent and efficient regulation and control and wide scene adaptation.

Description

Technical Field

[0001] The invention relates to the technical field of power quality control, and in particular to a multi-objective optimization power quality control method. Background Art

[0002] Today, modern industry is booming and the construction of smart grids is constantly advancing. But at the same time, the power quality problem in the power system is becoming more and more prominent, like a chronic disease plaguing the entire power ecosystem. A large number of nonlinear and impact loads are connected to the power grid. When arc furnaces, variable frequency speed regulation devices and various power electronic equipment are in operation, a large number of harmonics will be injected into the power grid. These harmonics seriously interfere with the communication system, causing signal distortion and a sharp drop in communication quality; they will also accelerate the aging of electrical equipment insulation, greatly reduce the service life of equipment, and even frequently cause equipment malfunctions, posing great hidden dangers to the safe and stable operation of the power system.

[0003] Traditional power quality control methods have significant limitations. When passive filters are used to control harmonics, they can only target specific frequencies, have poor adaptability to system dynamic changes, and are prone to resonating with system impedance; conventional voltage regulators have slow responses and are difficult to cope with instantaneous voltage changes. Moreover, existing solutions do not comprehensively consider the differences in power consumption characteristics of the power system at different times and the differences in regional load characteristics, and cannot achieve coordinated optimization and control of multiple power quality indicators. Therefore, it is urgent to develop an innovative multi-objective optimization power quality control method. Summary of the invention

[0004] In order to solve the above-mentioned problems, the present invention proposes a multi-objective optimization power quality control method.

[0005] In order to solve the above technical problems, the technical solution proposed by the present invention is: a multi-objective optimization power quality control method, comprising the following steps:

[0006] Data collection steps: Use high-precision sensor arrays arranged at multiple key nodes of the power system to collect voltage, current, frequency, harmonic distortion rate and power quality parameter information of each phase power factor in real time. The sensor array has an adaptive sampling frequency adjustment function and can dynamically optimize the sampling frequency according to the real-time operating conditions of the power system. The data collection accuracy reaches a high standard. The data is uploaded to the central control unit in real time through a high-speed, anti-interference communication protocol to ensure low packet loss rate during transmission;

[0007] Multi-objective construction steps: In the central control unit, a multi-objective optimization function is constructed based on the collected power quality parameters. The objectives include reducing voltage fluctuations and flickers, setting a strict allowable range of voltage fluctuations, and quantifying the voltage root mean square value fluctuation deviation by calculating it; reducing harmonic distortion, limiting the upper limit of the total harmonic distortion rate, setting limits for each harmonic component and weighting it into the objective function; and improving the power factor so that the average value of the three-phase power factor approaches the ideal value. Different objectives are assigned dynamic weight coefficients according to the load characteristics of the power system, equipment sensitivity and grid specifications to meet the needs of different time periods;

[0008] Control strategy generation steps: Use an intelligent optimization algorithm that integrates the improved particle swarm algorithm and the simulated annealing algorithm to solve the multi-objective optimization function and generate a real-time control strategy. The particle speed update in the improved particle swarm algorithm introduces a dynamic inertia weight, which is adaptively adjusted according to the number of iterations and convergence. The simulated annealing algorithm is used to jump out of the local optimum. The generated control strategy is accurate to the action parameter setting of the reactive compensation device, active power filter, and dynamic voltage restorer power quality regulation equipment;

[0009] Execution feedback step: the control strategy is issued to each power quality regulation device for execution. The device responds quickly and continuously monitors the changes in power quality parameters during execution. The control strategy is optimized and adjusted according to the feedback correction cycle based on the deviation between real-time monitoring and preset targets. The adjustment is limited to the equipment adjustment range and the system safety and stability constraints to ensure safe and stable operation of the power system.

[0010] Furthermore, the high-precision sensor array has a fault self-diagnosis function and can monitor its own working status in real time. When the measurement error exceeds the limit or the communication is interrupted for a long time, it automatically switches to the backup sensor, and the switching is rapid. At the same time, a fault alarm signal containing detailed information is sent to the central control unit, and the fault information is properly stored for operation and maintenance analysis.

[0011] Furthermore, in the multi-objective construction step, the power quality target priority is subdivided according to different power users and equipment. For example, the voltage stability weight is increased for voltage sag-sensitive equipment, and the harmonic distortion control weight is increased for harmonic-sensitive equipment. The priority is dynamically updated according to the user equipment importance level list to adapt to the needs of various users.

[0012] Furthermore, the intelligent optimization algorithm iteratively introduces an elite retention strategy, regularly screens the optimal solution and retains it to the next generation population to prevent the loss of excellent solutions, appropriately mutates and disturbs the retained elite individuals, balances the search capabilities, and accelerates convergence to a set of high-quality solutions.

[0013] Furthermore, in the feedback execution step, if the power quality still does not meet the standard after multiple feedback corrections, the emergency plan is activated, including reducing the power supply to non-critical loads, adjusting the equipment to the limit state to ensure the power quality of key buses and important loads, monitoring and troubleshooting in emergencies, and restoring normal power supply and control modes in sequence after the fault is eliminated.

[0014] Compared with the prior art, the present invention has the following advantages:

[0015] Precise multi-objective optimization: This method uniquely considers multi-dimensional power quality indicators such as voltage, harmonics, and power factor, and constructs a dynamic weight system. It accurately adjusts the optimization efforts according to different scenarios, reduces harmonics in industry to improve power factor and ensure production, and stabilizes voltage and eliminates interference to promote operations in commercial areas, like a smart tailor to customize solutions, comprehensively improving the comprehensive quality of power.

[0016] Intelligent and efficient control: Integrate improved particle swarm and simulated annealing algorithms to efficiently solve complex function generation strategies. The equipment responds quickly and the adjustment accuracy reaches the nanometer level, such as the active filter instantly taming harmonics. Real-time monitoring feedback, optimization within milliseconds when encountering deviations, full automation, always keep the power quality stable and in the best state, and reduce the cost of manual intervention.

[0017] Wide range of scenarios: From industrial plants, commercial centers to residential areas, and even special places such as data centers and new energy power stations, they can all be seamlessly embedded with adaptive sampling and flexible strategies. Old communities can stabilize voltage, data centers can resist interference, and new energy stations can be smoothly connected to the grid. One solution is applicable everywhere, laying a solid foundation for power quality for diversified power needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a principle flow chart of a multi-objective optimization power quality control method of the present invention. DETAILED DESCRIPTION

[0019] The present invention is further described in detail below with reference to the accompanying drawings.

[0020] Example 1

[0021] Power quality optimization in industrial plants

[0022] In large industrial plants, heavy equipment such as motors, welding machines, cranes, etc. are densely distributed, the power quality is worrying, harmonic pollution is serious, and voltage fluctuations are violent. After the sensor array of the present invention is accurately installed in key distribution cabinets and important equipment access points, the system is started.

[0023] In the data collection process, the sensor's adaptive function plays a key role. When the high-power welding machine is operating, it quickly captures the sharp rise of the 5th and 7th harmonics, and transmits the relevant data to the central control unit in real time; at the moment of driving, the voltage drop information is also monitored and transmitted back in time. This is due to the sensor's ability to dynamically adjust the sampling frequency according to the equipment working conditions to ensure accurate data acquisition.

[0024] During the multi-objective construction phase, the control system increases the corresponding objective weights, taking into account the high sensitivity of the equipment to voltage stability and harmonics. The intelligent algorithm then generates a strategy, the active power filter responds quickly, accurately adjusts the filter parameters, and efficiently filters out harmonics; the dynamic voltage restorer acts quickly and accurately injects compensation voltage.

[0025] After multiple rounds of feedback, the harmonic distortion rate dropped from over 20% to less than 5%, and the voltage fluctuation was stably controlled within the range of ±3%. The equipment operation tended to be stable, the product defective rate decreased by about 30%, and the production efficiency increased by about 25%, which effectively improved the economic benefits of the enterprise and ensured the smoothness of the production process.

[0026] Example 2

[0027] Power supply guarantee for commercial complexes

[0028] In a bustling commercial complex, there are many nonlinear loads such as lighting fixtures, elevators, central air conditioners, electronic display screens, etc. During peak hours, the power quality deteriorates, voltage flickers frequently occur, and harmonic interference is serious.

[0029] After the system was deployed and put into operation, sensors accurately located problems during data collection. Monitoring found that frequent starts and stops of air-conditioning compressors caused voltage flickering, and harmonics generated by electronic equipment interfered with communications and normal display of the display. Based on these data, multi-objective planning focused on power factor improvement and harmonic suppression, and intelligent algorithms generated a coordinated strategy for reactive power compensation devices and active filters.

[0030] During the execution process, the system provides real-time feedback optimization based on changes in lighting, elevators and other loads. Ultimately, the power factor rose to around 0.95, the harmonic distortion rate decreased by about 80%, the display screen was clear and flicker-free, the mall broadcast sound quality was pure, and business was in good order. The passenger flow increased by about 10% over the same period in the past, and the business turnover increased significantly, creating a good power environment for commercial operations.

[0031] Example 3

[0032] Improvement of electricity quality in residential areas

[0033] In the summer, when electricity consumption in old residential areas peaks, air conditioners are turned on in large numbers, voltage is low, and line harmonic pollution is serious. After installing this power quality control system, sensors comprehensively monitor the power parameters of each building, and the data is aggregated to the control center.

[0034] The control system construction targets voltage stabilization and harmonic control. The generated control strategy commands the precise switching of reactive compensation capacitors and the efficient purification of lines by small active filters. The feedback is fully guaranteed, the voltage returns to a reasonable range, the air conditioning and cooling of residents return to normal, and household appliances such as televisions and computers are free from harmonic interference. The rate of electricity complaints has dropped from more than 20 times per month to almost 0, and residents' satisfaction with electricity consumption has been greatly improved, effectively improving the quality of electricity consumption in residents' lives.

[0035] Example 4

[0036] Grid-connected power quality adaptation for new energy power stations

[0037] When new energy power stations such as photovoltaic power stations and wind power stations are connected to the grid, due to the intermittent and volatile nature of power generation, harmonics are easily injected into the grid and voltage fluctuations are caused. This system integrates the control system of new energy power stations. Data acquisition tracks the changes in power generation and power parameters at the grid connection point in real time. Multi-objective construction takes into account both the grid acceptance standard and the power generation efficiency of the power station. Intelligent algorithms adjust the parameters of reactive compensation and filtering equipment. For example, during the peak power generation at noon in the photovoltaic power station, the voltage rise is avoided from exceeding the limit; during low power output at night, the power factor is maintained stable. Execution feedback enables the power station to successfully achieve smooth grid connection, the harmonics meet the requirements of the grid, and the voltage fluctuations meet the standards, which improves the quality of new energy power grid connection and helps the efficient use of clean energy.

[0038] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A multi-objective optimization power quality control method, characterized in that: The steps include: Data collection steps: Use high-precision sensor arrays arranged at multiple key nodes of the power system to collect voltage, current, frequency, harmonic distortion rate and power quality parameter information of each phase power factor in real time. The sensor array has an adaptive sampling frequency adjustment function and can dynamically optimize the sampling frequency according to the real-time operating conditions of the power system. The data collection accuracy reaches a high standard. The data is uploaded to the central control unit in real time through a high-speed, anti-interference communication protocol to ensure low packet loss rate during transmission; Multi-objective construction steps: In the central control unit, a multi-objective optimization function is constructed based on the collected power quality parameters. The objectives include reducing voltage fluctuations and flickers, setting a strict allowable range of voltage fluctuations, and quantifying the voltage root mean square value fluctuation deviation by calculating it; reducing harmonic distortion, limiting the upper limit of the total harmonic distortion rate, setting limits for each harmonic component and weighting them into the objective function; And improve the power factor so that the average value of the three-phase power factor approaches the ideal value. Different goals are assigned dynamic weight coefficients according to the load characteristics of the power system, equipment sensitivity and grid specifications to meet the needs of different time periods; Control strategy generation steps: Use an intelligent optimization algorithm that integrates the improved particle swarm algorithm and the simulated annealing algorithm to solve the multi-objective optimization function and generate a real-time control strategy. The particle speed update in the improved particle swarm algorithm introduces a dynamic inertia weight, which is adaptively adjusted according to the number of iterations and convergence. The simulated annealing algorithm is used to jump out of the local optimum. The generated control strategy is accurate to the action parameter setting of the reactive compensation device, active power filter, and dynamic voltage restorer power quality regulation equipment; Execution feedback step: the control strategy is issued to each power quality regulation device for execution. The device responds quickly and continuously monitors the changes in power quality parameters during execution. The control strategy is optimized and adjusted according to the feedback correction cycle based on the deviation between real-time monitoring and preset targets. The adjustment is limited to the equipment adjustment range and the system safety and stability constraints to ensure safe and stable operation of the power system.

2. The multi-objective optimization power quality control method according to claim 1, characterized in that: The high-precision sensor array has a fault self-diagnosis function and can monitor its own working status in real time. When the measurement error exceeds the limit or the communication is interrupted for a long time, the backup sensor is automatically switched and the switching is rapid. At the same time, a fault alarm signal containing detailed information is sent to the central control unit. The fault information is properly stored for operation and maintenance analysis.

3. The multi-objective optimization power quality control method according to claim 1 is characterized in that: In the multi-objective construction step, the power quality target priority is subdivided according to different power users and equipment. For example, the voltage stability weight is increased for voltage sag-sensitive equipment, and the harmonic distortion control weight is increased for harmonic-sensitive equipment. The priority is dynamically updated according to the user equipment importance level list to adapt to the needs of various users.

4. The multi-objective optimization power quality control method according to claim 1, characterized in that: The intelligent optimization algorithm iteratively introduces an elite retention strategy, regularly screens the optimal solution and retains it to the next generation population to prevent the loss of excellent solutions, appropriately mutates and disturbs the retained elite individuals, balances the search capabilities, and accelerates convergence to a set of high-quality solutions.

5. The multi-objective optimization power quality control method according to claim 1, characterized in that: During the feedback execution step, if the power quality still does not meet the standard after multiple feedback corrections, the emergency plan will be activated, including reducing the power supply to non-critical loads, adjusting the equipment to the limit state to ensure the power quality of key buses and important loads, monitoring and troubleshooting in emergencies, and restoring normal power supply and control modes in sequence after the fault is eliminated.

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