Station electric energy quality comprehensive monitoring and cooperative control method, system, equipment and medium

Abstract

The invention provides a station electric energy quality comprehensive monitoring and cooperative control method, system and device and a medium, and the method comprises the steps: determining the operation condition of a station based on the monitored operation information of the on-site equipment of the station; the field station on-site equipment comprises primary equipment and secondary equipment; based on the operation information and the station operation condition, combining a preset multi-level and multi-dimensional power quality evaluation index, and utilizing a power quality evaluation algorithm to determine a power quality disturbance reason; and on the basis of the operation information, the station operation condition and the power quality disturbance reason, cooperative optimization control is carried out on the station local equipment by using a cooperative optimization control algorithm. According to the method, the reasons for causing the power quality disturbance can be accurately determined through the multi-level and multi-dimensional power quality evaluation indexes in combination with the power quality evaluation algorithm, and the resources in the station are controlled through coordinated optimization, so that the power quality disturbance can be reduced, the power quality capability of the station can be improved, and the safe and stable operation of a power grid can be ensured.

Description

Technical Field

[0001] This invention relates to the field of power quality monitoring and control technology, specifically to a method, system, equipment, and medium for integrated monitoring and collaborative control of power quality in power plants. Background Technology

[0002] In recent years, with the leapfrog development of charging infrastructure, the rapid improvement of charging technology, the gradual improvement of the standard system, and the steady formation of the industrial ecosystem, a charging infrastructure system with the largest number, the largest coverage area, and the most comprehensive range of vehicles has been formed. In the future, the construction of large-scale charging and discharging stations, which are important means to realize efficient electricity use and two-way interaction between power sources and loads for large-scale electric vehicles, as well as integrated photovoltaic-storage-charging stations developed to achieve intensive resource utilization, will become more widespread and dense. Large-scale stations, while meeting the charging needs of a large number of electric vehicles, can also feed power back to the grid through the battery energy storage function of electric vehicles, and can also achieve two-way flow of electrical energy through integrated photovoltaic power generation and electrochemical energy storage. This two-way interaction mode is of great significance for optimizing grid load regulation and improving energy utilization efficiency.

[0003] However, large-scale power stations still face a series of problems and challenges in practical operation, especially during the free switching between complex charging and discharging conditions. The ultra-fast charging piles and high-power battery stacks centrally configured in large-scale power stations are prone to a series of power quality problems, including voltage exceeding limits, harmonic distortion, and grid resonance, under high-frequency charging and discharging operations. These problems not only affect the safe operation of the power station itself but may also pose safety risks to other related equipment in the power grid. Therefore, how to effectively improve the power quality of large-scale power stations during free switching between multiple charging piles and various operating conditions, and ensure their safe, stable, and efficient operation, has become an important issue that urgently needs to be addressed.

[0004] Currently, the mainstream research direction of "vehicle-grid interaction" focuses on the participation of electric vehicles in regional power grid demand response management. By enabling electric vehicles to operate in good coordination with the power grid, they can provide ancillary services such as peak shaving, frequency regulation, and backup, thus alleviating the power pressure and power fluctuation problems caused by the large-scale development of electric vehicles. However, while the two-way interaction between electric vehicles and the power grid can bring significant benefits in regulating the grid load, the free switching of their charging and discharging states can also have a significant impact on the power quality of the grid, leading to power quality disturbances during the operation of power stations. Summary of the Invention

[0005] To overcome the shortcomings of power quality disturbances during the operation of power stations, this invention provides a comprehensive power quality monitoring and collaborative control method for power stations, comprising: Based on the monitored operational information of the on-site equipment at the station, the operating conditions of the station are determined; the on-site equipment at the station includes primary equipment and secondary equipment; Based on the operational information and the operating conditions of the power station, and combined with the preset multi-level and multi-dimensional power quality assessment indicators, the cause of power quality disturbances is determined using a power quality assessment algorithm. Based on the operational information, the operating conditions of the power station, and the causes of power quality disturbances, a collaborative optimization control algorithm is used to perform collaborative optimization control on the local equipment of the power station. The power quality assessment indicators include multiple levels such as medium voltage, low voltage, AC and DC; the power quality assessment indicators also include multiple dimensions such as voltage quality, frequency stability, harmonic and ripple pollution, and power supply reliability.

[0006] Optionally, the step of determining the cause of power quality disturbances based on the operational information and the station's operating conditions, combined with preset multi-level and multi-dimensional power quality assessment indicators, and using a power quality assessment algorithm, includes: Based on each of the preset multi-level and multi-dimensional power quality assessment indicators, the indicator value of the indicator is determined in the operation information. Based on the index value of each of the above indicators, the index grading standard of the power quality assessment algorithm is used to grade and evaluate each of the above indicators, and the grading and evaluation result of each of the above indicators is obtained. Based on the operating conditions of the power station and the graded evaluation results of each of the above indicators, the causes of power quality disturbances are determined. The indicator grading standard includes multiple levels for each indicator, with the multiple levels from low to high representing the power quality of the indicator from excellent to poor.

[0007] Optionally, the primary equipment includes a charging and discharging pile, an energy storage converter, a photovoltaic inverter, and a power quality management device for suppressing power quality disturbances; The secondary equipment includes a power quality monitoring device for monitoring power quality at different locations within the station.

[0008] Optionally, after determining the operating conditions of the station based on the monitored operating information of the on-site equipment, the method further includes: Under the peak-valley electricity pricing mechanism, the power station is controlled to use the energy storage system to supply power during peak electricity price periods, while limiting non-emergency charging loads; and the power station is controlled to use surplus photovoltaic power or the grid to charge the energy storage system during off-peak electricity price periods, and to open the charging station for centralized charging of electric vehicles. Under the real-time electricity price dynamic adjustment mechanism, the control station selects photovoltaic or energy storage systems for priority charging based on the real-time electricity price signal of the electricity market.

[0009] Optionally, after determining the operating conditions of the station based on the monitored operating information of the on-site equipment, the method further includes: During periods of low electricity demand, the power station is controlled to use surplus photovoltaic power or the power grid to charge the energy storage system; during periods of high electricity demand, the power station is controlled to use the energy storage system to supply power. When the grid frequency is lower than the set frequency threshold, the power station is controlled to use the energy storage system to supplement the grid power and reduce the charging power of the charging and discharging piles; when the grid frequency is not lower than the set frequency threshold, the power station is controlled to absorb excess electrical energy and reduce the photovoltaic power generation power. When the power station is used as a spinning backup power source, the energy storage system is controlled to maintain its operating state; when the power station is used as a non-spinning backup power source, the energy storage system is controlled to be in hot standby or cold standby state.

[0010] On the other hand, the present invention also provides a comprehensive monitoring and collaborative control system for power quality in power stations, comprising: The station's local equipment, collaborative control terminal, and station control platform are sequentially connected via communication. The collaborative control terminal is used to monitor the operating information of the on-site equipment at the station and forward it to the station control platform; the on-site equipment at the station includes primary equipment and secondary equipment; it is also used to issue collaborative optimization control instructions for the on-site equipment at the station, and to conduct collaborative optimization control of the on-site equipment at the station based on the collaborative optimization control instructions. The station control platform is used to determine the station's operating conditions based on the operating information of the station's local equipment; based on the operating information and the station's operating conditions, and combined with preset multi-level and multi-dimensional power quality assessment indicators, it uses a power quality assessment algorithm to determine the causes of power quality disturbances; based on the operating information, the station's operating conditions, and the causes of power quality disturbances, it uses a collaborative optimization control algorithm to generate collaborative optimization control commands for the station's local equipment and sends them to the collaborative control terminal. The power quality assessment indicators include multiple levels such as medium voltage, low voltage, AC and DC; the power quality assessment indicators also include multiple dimensions such as voltage quality, frequency stability, harmonic and ripple pollution, and power supply reliability.

[0011] Optionally, the station control platform is specifically used to determine the index value of each of the preset multi-level and multi-dimensional power quality assessment indicators in the operation information; based on the index value of each of the indicators, and using the index grading standard of the power quality assessment algorithm, to perform a graded assessment of each of the indicators, thereby obtaining a graded assessment result for each of the indicators; and based on the station operating conditions and the graded assessment results of each of the indicators, to determine the cause of power quality disturbances. The indicator grading standard includes multiple levels for each indicator, with the multiple levels from low to high representing the power quality of the indicator from excellent to poor.

[0012] Optionally, the primary equipment includes a charging and discharging pile, an energy storage converter, a photovoltaic inverter, and a power quality management device for suppressing power quality disturbances; The secondary equipment includes a power quality monitoring device for monitoring power quality at different locations in the station; The voltage quality metrics include voltage deviation, voltage fluctuation and flicker, three-phase voltage imbalance, and transient overvoltage; the frequency stability metrics include frequency deviation, frequency fluctuation, frequency offset rate, and frequency transient response; the harmonic and ripple pollution metrics include total harmonic distortion of voltage, total harmonic distortion of current, harmonic content, ripple voltage coefficient, and ripple current coefficient; and the power supply reliability metrics include power availability, outage frequency, outage duration, and average customer power outage time index.

[0013] Optionally, it may also include: a communication acquisition and control network; The collaborative control terminal is used to forward the operation information to the communication acquisition and control network; The communication acquisition and control network is used to encapsulate the operation information and send it to the station control platform using dynamic balanced dual-network technology.

[0014] Optionally, the station control platform is also used for: Under the peak-valley electricity pricing mechanism, the power station is controlled to use the energy storage system to supply power during peak electricity price periods, while limiting non-emergency charging loads; and the power station is controlled to use surplus photovoltaic power or the grid to charge the energy storage system during off-peak electricity price periods, and to activate the charging station for centralized charging of electric vehicles.

[0015] Under the real-time electricity price dynamic adjustment mechanism, the control station selects photovoltaic or energy storage systems for priority charging based on the real-time electricity price signal of the electricity market.

[0016] Optionally, the station control platform is also used for: During periods of low electricity demand, the power station is controlled to use surplus photovoltaic power or the power grid to charge the energy storage system; during periods of high electricity demand, the power station is controlled to use the energy storage system to supply power. When the grid frequency is lower than the set frequency threshold, the power station is controlled to use the energy storage system to supplement the grid power and reduce the charging power of the charging and discharging piles; when the grid frequency is not lower than the set frequency threshold, the power station is controlled to absorb excess electrical energy and reduce the photovoltaic power generation power. When the power station is used as a spinning backup power source, the energy storage system is controlled to maintain its operating state; when the power station is used as a non-spinning backup power source, the energy storage system is controlled to be in hot standby or cold standby state.

[0017] Optionally, the collaborative control terminal is further configured to determine the operating conditions of the station based on the operating information of the local equipment at the station; and to obtain the cause of the power quality disturbance from the station control platform; and to perform collaborative optimization control of the local equipment at the station based on the operating information, the operating conditions of the station, and the cause of the power quality disturbance using a collaborative optimization control algorithm.

[0018] On the other hand, the present invention also provides a comprehensive monitoring and collaborative control system for power quality in power stations, comprising: The monitoring module is used to determine the operating status of the station based on the monitored operating information of the station's local equipment; the station's local equipment includes primary equipment and secondary equipment; The power quality assessment module is used to determine the cause of power quality disturbances based on the operating information and the operating conditions of the power station, combined with preset multi-level and multi-dimensional power quality assessment indicators and using power quality assessment algorithms. The collaborative optimization control module is used to perform collaborative optimization control on the local equipment of the station based on the operating information, the station operating conditions and the causes of power quality disturbances, using a collaborative optimization control algorithm. The power quality assessment indicators include multiple levels such as medium voltage, low voltage, AC and DC; the power quality assessment indicators also include multiple dimensions such as voltage quality, frequency stability, harmonic and ripple pollution, and power supply reliability.

[0019] Optionally, the power quality assessment module includes: The grading evaluation unit is used to determine the index value of each of the preset multi-level and multi-dimensional power quality evaluation indicators in the operation information; based on the index value of each of the indicators, the unit uses the index grading standard of the power quality evaluation algorithm to perform a grading evaluation on each of the indicators, and obtain the grading evaluation result of each indicator. The disturbance cause determination unit determines the cause of power quality disturbance based on the station's operating conditions and the graded evaluation results of each indicator; The indicator grading standard includes multiple levels for each indicator, with the multiple levels from low to high representing the power quality of the indicator from excellent to poor.

[0020] Optionally, the primary equipment includes a charging and discharging pile, an energy storage converter, a photovoltaic inverter, and a power quality management device for suppressing power quality disturbances; The secondary equipment includes a power quality monitoring device for monitoring power quality at different locations within the station.

[0021] Optional, also includes: The demand response module is used to control the power station to use the energy storage system to supply power during peak electricity price periods, while limiting non-emergency charging loads, under the peak-valley electricity price mechanism; and to control the power station to use surplus photovoltaic power or the grid to charge the energy storage system during off-peak electricity price periods, and to activate the charging station for centralized charging of electric vehicles; under the real-time electricity price dynamic adjustment mechanism, the module controls the power station to select photovoltaic or energy storage systems for priority charging based on real-time electricity market price signals.

[0022] Optional, also includes: The grid auxiliary module is used to control the power station to use surplus photovoltaic power or the grid to charge the energy storage system during off-peak hours; to control the power station to use the energy storage system to supply power during peak hours; to control the power station to use the energy storage system to supplement the grid power when the grid frequency is lower than a set frequency threshold, and to reduce the charging power of the charging piles; to control the power station to absorb excess electrical energy and reduce the photovoltaic power generation when the power station is used as a spinning backup power source; to control the energy storage system to maintain its operating state when the power station is used as a non-spinning backup power source; and to control the energy storage system to be in hot standby or cold standby state when the power station is used as a non-spinning backup power source.

[0023] On the other hand, the present invention also provides a computer device, characterized in that it includes: one or more processors; The processor is used to store one or more programs; When the one or more programs are executed by the one or more processors, the integrated monitoring and collaborative control method for power quality at the power station described in any one of the above-mentioned methods is implemented.

[0024] On the other hand, the present invention also provides a computer-readable storage medium, characterized in that it stores a computer program thereon, wherein when the computer program is executed, it implements the integrated monitoring and collaborative control method for power quality of power stations as described in any one of the above.

[0025] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention provides a method, system, equipment, and medium for comprehensive monitoring and coordinated control of power quality at power stations. The method determines the station's operating conditions based on monitored operational information from local equipment, including primary and secondary equipment. Based on the operational information and station operating conditions, and combined with preset multi-level and multi-dimensional power quality assessment indicators, a power quality assessment algorithm is used to determine the causes of power quality disturbances. Based on the operational information, station operating conditions, and causes of power quality disturbances, a coordinated optimization control algorithm is used to perform coordinated optimization control on the local equipment. The multi-level power quality assessment indicators include multiple levels from medium voltage, low voltage, AC, and DC. The multi-dimensional power quality assessment indicators include multiple dimensions from voltage quality, frequency stability, harmonic and ripple pollution, and power supply reliability. This invention, through multi-level and multi-dimensional power quality assessment indicators combined with a power quality assessment algorithm, can accurately determine the causes of power quality disturbances. By coordinating and optimizing the control of resources within the power station, power quality disturbances can be reduced, the power quality capability of the power station can be improved, and the safe and stable operation of the power grid can be guaranteed. Attached Figure Description

[0026] Figure 1 This is a flowchart illustrating the integrated monitoring and collaborative control method for power quality at power stations according to the present invention. Figure 2 This is a schematic diagram of the system architecture of the large-scale power quality disturbance control system for power plants according to the present invention; Figure 3 This is a schematic diagram of the software architecture of the large-scale power quality disturbance control system platform for this invention. Figure 4 This is a schematic diagram of a certain station system of the present invention; Figure 5 This is a schematic diagram of the integrated monitoring and collaborative control system architecture for power quality at power stations according to the present invention; Figure 6 This is a schematic diagram of the electronic device of the present invention. Detailed Implementation

[0027] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0028] Example 1: This invention provides a process flow for integrated monitoring and collaborative control of power quality in power plants, such as... Figure 1 As shown, it includes: Step 101: Determine the operating conditions of the station based on the monitored operating information of the station's local equipment; the station's local equipment includes primary equipment and secondary equipment.

[0029] Step 102: Based on the operating information and the operating conditions of the power station, and combined with the preset multi-level and multi-dimensional power quality assessment indicators, use the power quality assessment algorithm to determine the cause of power quality disturbances; the multi-level power quality assessment indicators include multiple levels in medium voltage, low voltage, AC and DC; the multi-dimensional power quality assessment indicators include multiple dimensions in voltage quality, frequency stability, harmonic and ripple pollution, and power supply reliability.

[0030] Step 103: Based on the operating information, the operating conditions of the station, and the causes of power quality disturbances, the station's local equipment is controlled in a coordinated optimization control algorithm.

[0031] This invention, through multi-level and multi-dimensional power quality assessment indicators combined with power quality assessment algorithms, can accurately determine the causes of power quality disturbances. By coordinating and optimizing the control of resources within the power station, power quality disturbances can be reduced, the power station's power quality capability can be improved, and the safe and stable operation of the power grid can be guaranteed.

[0032] In the embodiments of this invention, the term "station" refers to a large-scale station, such as an electric vehicle charging and discharging station or an integrated photovoltaic, energy storage and charging station, or a distributed photovoltaic power station and an electrochemical energy storage power station.

[0033] In some scenarios, the primary equipment in the power station's on-site facilities includes charging and discharging piles, energy storage converters, photovoltaic inverters, and power quality management devices for suppressing power quality disturbances. Power quality management devices, as dedicated equipment for power quality management, may include, but are not limited to, reactive power compensation devices, active power filters, and three-phase imbalance control devices. Secondary equipment in the power station's on-site facilities includes power quality monitoring devices for monitoring power quality at different locations within the power station. Since the normal operation and free switching of operating conditions of the primary equipment both affect the power quality at different locations within the power station, this embodiment of the invention can utilize multiple distributed power quality management and monitoring devices to achieve real-time, multi-level perception of power quality conditions in large power stations. Furthermore, in this embodiment of the invention, charging pile converters, photovoltaic inverters, energy storage converters, etc., as power electronic devices, share topological similarities with power quality management devices. Considering the design redundancy and spatiotemporal complementarity of charging piles, applying these primary devices to the collaborative management of power quality issues can provide new ideas for improving the power supply quality of large power stations, optimizing power supply and usage, and reducing management investment costs.

[0034] In step 101 above, based on the collected / monitored operating information of the on-site equipment at the station, the station's operating condition can be automatically determined and identified. The station's operating condition can be shown in Table 1 below.

[0035] Table 1

[0036] Generally, power quality refers to the ability to maintain the voltage and current of the distribution bus within a near-sinusoidal waveform within the rated amplitude and frequency range. Specifically, it measures the degree to which parameters such as voltage, current, frequency, and phase deviate from standard values. These deviations can lead to various problems during power transmission and use. Power quality issues not only affect the safe and stable operation of equipment within the power system but also adversely impact user-side equipment and power supply service quality. Therefore, power quality has become a crucial and highly concerned issue in the power system field. In this embodiment of the invention, for a complex system like a large-scale power station (such as a large electric vehicle charging and discharging station) with high capacity, high dynamic response, and coupling of various power electronic devices, the power quality indicators cover multiple dimensions, including voltage, frequency, current, system reliability, and economy.

[0037] Based on this, this invention proposes a multi-level, multi-dimensional power quality assessment index tailored to the actual operational characteristics of large-scale power plants. Specifically, considering the characteristics of different voltage levels and power supply types, multi-dimensional assessments are conducted at multiple levels, including medium voltage, low voltage, AC, and DC, to systematically reflect the stability and purity of the power grid supply, helping to identify potential risks in a timely manner and providing a basis for technical improvements. Furthermore, the multi-dimensional power quality assessment will cover four aspects: voltage quality, frequency stability, harmonic and ripple pollution, and power supply reliability.

[0038] For example, voltage quality metrics include, but are not limited to, voltage deviation, voltage fluctuation and flicker, three-phase voltage imbalance, and transient overvoltage; frequency stability metrics include, but are not limited to, frequency deviation, frequency fluctuation, frequency offset rate, and frequency transient response; harmonic and ripple pollution metrics include, but are not limited to, total harmonic distortion of voltage, total harmonic distortion of current, harmonic content, ripple voltage coefficient, and ripple current coefficient; power supply reliability metrics include, but are not limited to, power availability, outage frequency, outage duration, and average customer power outage time index. Large-scale charging stations, as a crucial component of new energy vehicle charging infrastructure, undertake large-scale power conversion and rapid charging / discharging tasks. They contain numerous DC charging devices, inverters, transformers, and supporting power electronic devices. The AC / DC power quality characteristics are complex and variable, directly affecting charging efficiency, equipment lifespan, and the safe operation of the power grid. In this example, for this complex operating condition, the power quality monitoring method performs high-frequency and high-precision sampling of multiple nodes and parameters of the power station to ensure real-time capture of dynamic characteristics such as voltage fluctuations and flicker, voltage offset, frequency deviation, harmonic content and DC ripple, which can support rapid response and accurate assessment.

[0039] With the deep integration of distributed energy and energy storage systems, the power electronics level of DC power systems has significantly improved. In large power plants, rapid start-up and shutdown of charging units and frequent power fluctuations significantly increase harmonic and ripple interference introduced by inverters and charging equipment, leading to more complex and diverse power quality issues. In particular, characteristics such as DC-side voltage ripple, DC bias, and rapid current changes are difficult for traditional monitoring equipment to accurately capture and quantitatively analyze. Considering the high standards required for power quality in power plants, the monitoring equipment in the project needs to cover high-precision to ultra-high-precision levels (such as Class A, Class B, and Class S) to meet the needs of different monitoring levels and time-domain resolutions, enabling accurate measurement and analysis of subtle fluctuations and transient disturbances in voltage and current. Relying solely on equipment of a single precision level is insufficient to comprehensively reflect the operating status of the power plant; a complementary monitoring system combining multiple levels of equipment is necessary to ensure early detection and scientific diagnosis of power quality problems. Therefore, in one possible implementation of this invention, in step 102 above, the index value of each index in the preset multi-level and multi-dimensional power quality assessment index can be determined in the operating information; based on the index value of each index, the index grading standard of the power quality assessment algorithm is used to perform a graded assessment of each index, and the graded assessment result of each index is obtained; based on the station operating conditions and the graded assessment result of each index, the cause of power quality disturbance is determined. In this implementation, the index grading standard includes multiple levels for each index, and the multiple levels from low to high represent the power quality of the index from excellent to poor.

[0040] For example, in this embodiment of the invention, based on industry standards and the actual operating conditions of the power station, the main indicators are divided into five levels according to their individual indicator level limits: Excellent (Level 1), Average (Level 2), Poor (Level 3), Very Poor (Level 4), and Extremely Poor (Level 5). These levels are then used to assess the graded performance of each power quality indicator. Furthermore, the improvement effect of each indicator before and after power quality management can also be evaluated. In this example, the grading standards for some main power quality indicators are shown in Table 2.

[0041] Table 2

[0042] The causes of power quality disturbances may vary under different operating conditions of power stations. Therefore, in this embodiment of the invention, under the current operating conditions of the power station, the (main) causes of power quality disturbances can be accurately determined by combining the graded evaluation results of each indicator.

[0043] For example, Table 2 can identify power quality disturbances caused by frequent operating condition switching and power fluctuations during the operation of large electric vehicle charging and discharging stations or integrated photovoltaic-storage-charging stations. Subsequently, by coordinating and controlling adjustable resources within the station, it can participate in two-way interactive control of the power grid, thereby improving the power quality and profitability of the station.

[0044] In another possible implementation, step 102 above may also include the following process: First, multi-source operational information from primary and secondary equipment is integrated. Time-series alignment algorithms (such as interpolation synchronization and event tagging association) are used to eliminate data timestamp differences. A multi-source correlation matrix is ​​used to establish the spatiotemporal correspondence between equipment status and site operating conditions, forming a unified "equipment-operating condition" data base. Second, based on preset multi-level and multi-dimensional power quality assessment indicators, statistical analysis algorithms are used to calculate each major indicator. Then, a frequency domain decomposition algorithm is used to quantify transient disturbances, and fuzzy hierarchical analysis is used to weight the indicators, generating a comprehensive assessment score and identifying anomaly dimensions. Third, empirical mode analysis is used to analyze the quantified indicators against the original signals. The intrinsic modes of non-stationary voltage / current signals are deconstructed, and features such as "duration, amplitude abrupt change point, and frequency components" of the disturbance are extracted. A causal relationship between "disturbance features and equipment actions" is established through association rule mining (such as the Apriori algorithm). A hybrid reasoning mechanism is employed: first, a rule engine that pre-defines causal rules based on expert knowledge (e.g., "voltage drop + photovoltaic power output reduction → voltage deviation" and "negative sequence current exceeding the standard + transformer overcurrent → three-phase imbalance"); second, a machine learning classification model (e.g., random forest, support vector machine (SVM)). The input is a comprehensive evaluation score and disturbance features, and the output is a probability distribution of the disturbance's cause. Finally, a Bayesian network is used to fuse the rules and model results, correct for uncertainties, and output a ranked list of "most likely cause - secondary cause," thus obtaining the final cause of the power quality disturbance.

[0045] The collaborative optimization control algorithm in step 103 above is not limited in this embodiment of the invention. For example, it includes the following algorithms: The following algorithms can be used to achieve coordinated and optimized control of local equipment at the site: Model Predictive Control (MPC): Based on the dynamic model of the equipment and prediction of future operating conditions, it continuously optimizes control commands to balance multiple objectives such as voltage stability and harmonic suppression, and adapts to real-time requirements.

[0046] Multi-objective evolutionary algorithms (such as NSGA-II): For conflicting objectives such as "improving power quality, minimizing equipment loss, and optimizing economic cost", they search for Pareto optimal solutions and provide flexible control strategies for different operating conditions.

[0047] Reinforcement learning (such as deep deterministic policy gradient): Train an agent using historical perturbation and control data to autonomously learn equipment coordination rules and adapt to unexpected scenarios such as fluctuations in new energy output and sudden load changes.

[0048] The local equipment at power stations that enable collaborative optimization control can mainly include primary equipment such as charging and discharging piles, energy storage converters, photovoltaic inverters, and power quality management devices. This invention can collect real-time power quality information from multiple points within the power station, and utilize photovoltaic inverters, energy storage converters, charging piles, reactive power compensation devices, active filters, and other active devices to conduct collaborative power quality control and comprehensive management. It assesses the power quality within the power station and at the grid connection point, coordinates and controls locally adjustable equipment such as photovoltaic, energy storage, and charging systems, achieves two-way information and energy interaction with the distribution network, participates in power demand response and ancillary services, and improves both the power quality of the power station's generation and consumption, thereby enhancing the economic efficiency of the power station's operation.

[0049] In addition to the aforementioned power quality monitoring and comprehensive power quality control functions, the solutions proposed in this invention can also realize demand response and ancillary service functions. Charging and discharging stations or integrated photovoltaic-storage-charging stations, leveraging their flexible regulation characteristics and multi-energy synergy advantages, deeply participate in all aspects of power ancillary services, providing strong support for the safe and stable operation of the power grid and creating new profit models for themselves.

[0050] For demand response functionality, power stations can participate in grid demand response by controlling their response power, time periods, and electricity volumes according to contractual agreements, telephone invitations, or electricity pricing mechanisms. For example, under peak-valley pricing, the power station can utilize energy storage systems to supply power during peak pricing periods (such as designated weekday morning and evening peak hours) while limiting non-emergency charging loads (during which the power station reduces its purchases from the grid and instead uses energy storage systems to discharge and supply power to charging stations, thus reducing electricity costs); and during off-peak pricing periods (such as designated nighttime periods), the power station can utilize surplus photovoltaic power or grid power to charge energy storage systems and activate charging stations for centralized charging of electric vehicles. Furthermore, under a real-time electricity price dynamic adjustment mechanism, the power station can prioritize charging either photovoltaic or energy storage systems based on real-time electricity market price signals. Real-time electricity price dynamic adjustment is also a common method; the power station can prioritize photovoltaic power charging based on real-time electricity market price signals, and when prices are high, discharge energy storage and (optionally) reduce non-emergency charging loads to maximize revenue.

[0051] For ancillary services, the control station provides services such as peak shaving, frequency regulation, and system backup to the power grid as required, thereby participating in grid ancillary services. For example, during off-peak hours, the control station uses surplus photovoltaic power or grid electricity to charge the energy storage system (during this period, the integrated photovoltaic-storage-charging power station can use surplus photovoltaic power or low-cost grid electricity to charge the energy storage system, while simultaneously meeting some charging needs); during peak hours, the control station uses the energy storage system to supply power (during this period, the energy storage system discharges to supply power to the charging station, reducing the pressure on the power grid, and can even further reduce peak electricity demand by limiting unnecessary charging loads. Through this "peak shaving and valley filling" method, the power station can effectively alleviate the grid's peak shaving pressure and improve the level of new energy consumption). For example, when the grid frequency is lower than a set frequency threshold, the power station is controlled to use the energy storage system to supplement the grid power while reducing the charging power of the charging piles (in this case, the energy storage system discharges rapidly to supplement the grid power and simultaneously reduces the charging power of the charging piles); when the grid frequency is not lower than the set frequency threshold, the power station is controlled to absorb excess electrical energy while simultaneously reducing the photovoltaic power generation (in this case, when the frequency is too high, excess electrical energy is absorbed for charging while simultaneously reducing the photovoltaic power generation). For another example, when the power station is used as a spinning standby power source, the energy storage system is controlled to maintain operation and respond to dispatch commands to increase output at any time; when the power station is used as a non-spinning standby power source, the energy storage system is controlled to be in hot standby or cold standby mode, so that it can start and operate within a specified time when a sudden situation occurs in the grid, providing reliable power security for the grid.

[0052] Example 2: Based on the same inventive concept, this invention also provides a comprehensive monitoring and collaborative control system for power quality in power stations, as shown in the schematic diagram below. Figure 2 As shown, it includes on-site equipment at the station, a collaborative control terminal, and a station control platform that are connected in sequence via communication. The collaborative control terminal is used to monitor the operating information of the local equipment at the station and forward it to the station control platform. The local equipment at the station includes primary equipment and secondary equipment. It is also used to issue collaborative optimization control commands for the local equipment at the station, and to conduct collaborative optimization control of the local equipment at the station based on the collaborative optimization control commands. The station control platform is used to determine the operating conditions of the station based on the operating information of the local equipment at the station; based on the operating information and the operating conditions of the station, combined with preset multi-level and multi-dimensional power quality assessment indicators, it uses power quality assessment algorithms to determine the causes of power quality disturbances; based on the operating information, the operating conditions of the station, and the causes of power quality disturbances, it uses collaborative optimization control algorithms to generate collaborative optimization control commands for the local equipment at the station and sends them to the collaborative control terminal. The power quality assessment indicators are multi-level, including multiple levels of medium voltage, low voltage, AC and DC; the power quality assessment indicators are multi-dimensional, including multiple dimensions of voltage quality, frequency stability, harmonic and ripple pollution, and power supply reliability.

[0053] The aforementioned integrated monitoring and collaborative control method for power quality at power stations can be implemented by a station control platform, a collaborative control terminal, or both. This embodiment primarily uses a station control platform as an example for explanation; similarities are described in the above embodiments and will not be repeated here. Special cases will be explained in detail later.

[0054] In one possible implementation, the station control platform is specifically used to determine the index value of each index in the operation information based on the preset multi-level and multi-dimensional power quality assessment index; based on the index value of each index, it uses the index grading standard of the power quality assessment algorithm to perform a graded assessment of each index to obtain the graded assessment result of each index; and based on the station operating conditions and the graded assessment results of each index, it determines the cause of power quality disturbance. The indicator grading standard includes multiple levels for each indicator, with the levels ranging from low to high representing the power quality from best to worst.

[0055] In one possible implementation, the primary equipment includes a charging and discharging pile, an energy storage converter, a photovoltaic inverter, and a power quality management device for suppressing power quality disturbances; Secondary equipment includes power quality monitoring devices used to monitor power quality at different locations in the station; Voltage quality metrics include voltage deviation, voltage fluctuation and flicker, three-phase voltage imbalance, and transient overvoltage; frequency stability metrics include frequency deviation, frequency fluctuation, frequency offset rate, and frequency transient response; harmonic and ripple pollution metrics include total harmonic distortion of voltage, total harmonic distortion of current, harmonic content, ripple voltage coefficient, and ripple current coefficient; power supply reliability metrics include power availability, outage frequency, outage duration, and average customer power outage time index.

[0056] One possible implementation also includes: a communication acquisition and control network; The collaborative control terminal is used to forward operational information to the communication acquisition and control network; The communication acquisition and control network is used to encapsulate operational information and send it to the station control platform using dynamic balanced dual-network technology.

[0057] In this implementation, the system consists of four levels: local equipment at the site, communication network, collaborative control terminal, and station control platform, as follows: Figure 2As shown in the example, the communication acquisition and control network uses communication methods to collect real-time operating information of primary and secondary equipment within a large power station, and performs real-time control and adjustment. Communication methods include wired methods such as RS485, Ethernet, and power line carrier, and wireless methods such as LoRa and WiFi, primarily focusing on short-range communication. Commonly used communication protocols include MODBUS, IEC101 / 104, IEC61850, MQTT, and DL / T 698.45. Through advanced energy management systems and communication technologies, power stations can respond uniformly to grid dispatch commands, provide more stable and reliable ancillary services, and enhance their competitiveness and profitability in the electricity market.

[0058] In one possible implementation, the station control platform is also used for: Under the peak-valley electricity pricing mechanism, the control station uses the energy storage system to supply power during peak electricity price periods, while restricting non-emergency charging loads; and during off-peak electricity price periods, the control station uses surplus photovoltaic power or the grid to charge the energy storage system, and opens the charging station to centrally charge electric vehicles.

[0059] Under the real-time electricity price dynamic adjustment mechanism, the control station selects photovoltaic or energy storage systems for priority charging based on the real-time electricity price signal of the electricity market.

[0060] In one possible implementation, the station control platform is also used for: During off-peak hours, the control station uses surplus photovoltaic power or the grid to charge the energy storage system; during peak hours, the control station uses the energy storage system to supply power. When the grid frequency is lower than the set frequency threshold, the control station uses the energy storage system to supplement the grid power and reduces the charging power of the charging and discharging piles; when the grid frequency is not lower than the set frequency threshold, the control station absorbs excess electrical energy and reduces the photovoltaic power generation power. When the power station is used as a spinning backup power source, the energy storage system is kept in operation; when the power station is used as a non-spinning backup power source, the energy storage system is kept in hot standby or cold standby mode.

[0061] In one possible implementation, the collaborative control terminal is also used to determine the operating conditions of the power station based on the operating information of the local equipment; and to obtain the causes of power quality disturbances from the station control platform; based on the operating information, the operating conditions of the power station, and the causes of power quality disturbances, it uses a collaborative optimization control algorithm to perform collaborative optimization control on the local equipment. In this implementation, the station control platform and the collaborative control terminal can jointly implement the above-mentioned collaborative control method for comprehensive monitoring of power quality at the power station. Specifically, the collaborative control terminal mainly obtains operating information of local primary and secondary equipment through the acquisition and control network, possesses communication parsing and forwarding capabilities, can sense changes in the operation and operating conditions of large-scale power station equipment, performs collaborative optimization control on local equipment according to the collaborative control algorithm, and can forward relevant information to the upper-level platform, i.e., the station control platform.

[0062] The integrated monitoring and collaborative control system for power quality at power plants proposed in this invention can specifically be a power quality disturbance control system for large power plants. The system's platform architecture consists of three layers: operating system, support platform, and application functions. The system hierarchy architecture is as follows: Figure 3 As shown.

[0063] The system will use either Linux or Windows operating systems.

[0064] The support platform provides general support services for the implementation of various application functions, mainly including the following functions: Network data transmission: The network data transmission adopts dynamic balanced dual-network technology, which encapsulates the underlying network data transmission to achieve transparent network data transmission between the server and workstation nodes. At the same time, it can monitor network traffic and network transmission anomalies and automatically issue alarms.

[0065] Real-time Database: Provides real-time data services for the system. The real-time database is distributed across all nodes of the system and ensures data consistency through soft synchronization technology. Real-time data processing adopts a C / S distributed architecture and uses a standardized CIM data model to achieve efficient real-time data processing, access, and management.

[0066] Historical Database: Provides historical data services for the entire system, including data sampling, storage, and querying. The system provides a comprehensive data verification mechanism to ensure data synchronization across multiple databases. Parallel processing technology is also employed to ensure efficient data processing. Historical data types include the following: measurement data, statistical calculation data, status data, event / alarm information, accident recap data, trend data and curves, forecast data, planning data, application software calculation results cross-sections, and other data.

[0067] Graphical Interface: Designed using an integrated graphic library approach, considering the graphic characteristics of various industries, it employs vector technology for infinite scaling of graphics and SVG format for graphical interaction between different systems. Plugins, scripts, and a graphic designer are used to achieve overall management of the human-machine interface, enabling customization of the interface style and dynamic generation of the interface to meet user needs for modification. It can comprehensively display operational information through various methods such as numerical values, curves, bar charts, pie charts, and animations. Figure 4 As shown.

[0068] Reports: Built using Java, the system generates various reports through template definition and template replacement. The reporting system is compatible with various Excel operation features and can run on Linux or Windows operating systems.

[0069] Access Control: Provides all system access control services, including real-time database read / write, historical database read / write, graphical viewing and editing, etc. At the same time, it filters data on the support platform according to the principle of hierarchical partitioning, simplifying the processing of upper-layer applications.

[0070] Alarm Service: Provides alarm services for the entire system, including system alarms, new energy power generation operation alarms, electric vehicle charging operation alarms, manual operation alarms, etc.

[0071] General services include general computing services, general query services, and general data sampling services.

[0072] The system is capable of managing hardware and software in a distributed system environment, monitoring the operating status of distributed system devices, detecting faults, and automatically or manually reconfiguring the system. It adopts client / server (C / S) architecture to implement distributed system functions, ensuring efficient and reliable system operation.

[0073] The application features mainly consist of advanced functions, including the following: Data Acquisition and Processing: A data acquisition application runs on the acquisition server. Communication network equipment collects and processes the following types of data in real time: analog quantities, status quantities (including dual-position data), etc. Data sources include charging piles (machines), photovoltaic inverters, energy storage converters, active power filters, reactive power compensation devices, power quality analyzers, and measurement and protection devices. The system processes the collected real-time data and sends it to a real-time database, storing it in the corresponding historical database on the data server. To ensure the reliability of information transmission, error verification codes should be used, generally employing the CRC check method. The large-scale power station power quality disturbance control system has functions such as data rationality checking, abnormal data analysis, and event classification, and supports commonly used calculation functions; it supports flexible setting of historical data storage periods, with a storage capacity of no less than three years of historical data; it has flexible statistical calculation capabilities and provides convenient and flexible query functions.

[0074] Operating Condition Identification: The power quality disturbance control system for large power plants automatically identifies the operating conditions of the large power plants based on the collected local equipment operating status and displays it on the screen.

[0075] Power quality monitoring: Collect information from the deployed power quality monitoring terminals, including displaying power quality information of each monitoring point through wiring diagrams, bar charts, tables, etc., and issuing alarms for monitoring points where power quality exceeds the standard.

[0076] Comprehensive Power Quality Control: Based on the problems existing within the power station, equipment such as photovoltaic inverters, energy storage converters, charging piles, reactive power compensation devices, and three-phase imbalance control devices are deployed to adjust active and reactive power output and comprehensively address voltage, power factor, and three-phase imbalance within the power station. Active power filters are also deployed to compensate for harmonics at key nodes within the power station. Furthermore, the improvement in various indicators before and after power quality control can be evaluated and displayed on the screen.

[0077] Demand Response: Participating in grid demand response, the station control platform controls the power, time period, and amount of electricity supplied by the power station according to contractual agreements, telephone invitations, or electricity pricing mechanisms. Under peak-valley pricing mechanisms, the power station will reduce its purchase of electricity from the grid during peak electricity price periods (such as weekday morning and evening peak hours) and instead utilize the energy storage system to discharge and supply power to the charging station, while limiting non-emergency charging loads to reduce electricity costs. During off-peak electricity price periods (such as nighttime), it will utilize surplus photovoltaic power or low-priced grid electricity to charge the energy storage system and activate the charging station for centralized charging of electric vehicles. Real-time dynamic adjustment of electricity prices is also a common method. The power station can prioritize the use of photovoltaic power for charging based on real-time electricity market price signals. When the price is high, the energy storage system will discharge and non-emergency charging loads will be reduced to maximize revenue.

[0078] Ancillary Services: Participating in grid ancillary services, the station control platform controls the power station to provide peak shaving, frequency regulation, and system backup services to the grid as required. Integrated photovoltaic-storage-charging power stations can utilize surplus photovoltaic power or low-cost grid electricity to charge energy storage during off-peak hours, simultaneously meeting some charging needs. During peak hours, the energy storage system discharges to supply power to the charging station, reducing grid supply pressure and even further reducing peak demand by limiting unnecessary charging loads. Through this "peak shaving and valley filling" method, the power station can effectively alleviate grid peak shaving pressure and improve the level of new energy consumption. When the grid frequency is below the standard value, the energy storage system rapidly discharges to supplement grid power while reducing the charging power of the charging piles; when the frequency is too high, it absorbs excess energy for charging while reducing photovoltaic power generation. In backup ancillary services, the power station can serve as a spinning reserve or non-spinning reserve power source. When used as a spinning reserve, the energy storage system remains operational and can increase output in response to dispatch commands at any time. When used as a non-spinning reserve, the energy storage devices in the power station are in a hot or cold standby state, and can be started and put into operation within a specified time when the power grid experiences a sudden situation, providing reliable power security for the power grid.

[0079] Information interaction: It forwards the main operational information within the station to the power grid dispatching agency, virtual power plant or aggregator operation platform, and receives dispatch control instructions.

[0080] Extended functionality: The system has good scalability, making it easy to integrate and extend new application functions.

[0081] Example 3: Based on the same inventive concept, this invention also provides a comprehensive monitoring and collaborative control system for power quality in power stations, as shown in the schematic diagram below. Figure 5 As shown, it includes: The monitoring module is used to determine the operating status of the station based on the monitored operating information of the station's local equipment; the station's local equipment includes primary equipment and secondary equipment; The power quality assessment module is used to determine the causes of power quality disturbances based on operating information and station operating conditions, combined with preset multi-level and multi-dimensional power quality assessment indicators and power quality assessment algorithms. The collaborative optimization control module is used to perform collaborative optimization control on local equipment at the station based on operating information, station operating conditions, and causes of power quality disturbances, using a collaborative optimization control algorithm. The power quality assessment indicators are multi-level, including multiple levels of medium voltage, low voltage, AC and DC; the power quality assessment indicators are multi-dimensional, including multiple dimensions of voltage quality, frequency stability, harmonic and ripple pollution, and power supply reliability.

[0082] In one specific implementation, the power quality assessment module includes: The hierarchical evaluation unit is used to determine the index value of each index in the operation information based on the preset multi-level and multi-dimensional power quality evaluation index; based on the index value of each index, the power quality evaluation algorithm uses the index hierarchical standard to perform hierarchical evaluation on each index, and obtain the hierarchical evaluation result of each index. The disturbance cause determination unit determines the cause of power quality disturbances based on the station's operating conditions and the graded evaluation results of each indicator; The indicator grading standard includes multiple levels for each indicator, with the levels ranging from low to high representing the power quality from best to worst.

[0083] In one specific implementation, the primary equipment includes a charging and discharging pile, an energy storage converter, a photovoltaic inverter, and a power quality management device for suppressing power quality disturbances; Secondary equipment includes power quality monitoring devices used to monitor power quality at different locations within the station.

[0084] One specific implementation also includes: The demand response module is used to control the power station to use the energy storage system to supply power during peak electricity price periods while limiting non-emergency charging loads under the peak-valley electricity price mechanism; and to control the power station to use surplus photovoltaic power or grid power to charge the energy storage system during off-peak electricity price periods and to activate the charging station for centralized charging of electric vehicles; under the real-time electricity price dynamic adjustment mechanism, the power station selects photovoltaic or energy storage systems for priority charging based on the real-time electricity price signal of the electricity market.

[0085] One specific implementation also includes: The grid auxiliary module is used to control the power station to use surplus photovoltaic power or the grid to charge the energy storage system during off-peak hours; to control the power station to use the energy storage system to supply power during peak hours; to control the power station to use the energy storage system to supplement the grid power when the grid frequency is lower than the set frequency threshold, and to reduce the charging power of the charging piles; to control the power station to absorb excess power and reduce the photovoltaic power generation when the power station is used as a spinning backup power source; and to control the energy storage system to be in hot standby or cold standby mode when the power station is used as a non-spinning backup power source.

[0086] Example 4: like Figure 6As shown, the present invention also provides an electronic device, which may be a computer device, a microcontroller device, a smart mobile device, etc. The electronic device in this embodiment may include a processor, a memory, a transceiver component, etc. The memory, processor, and transceiver component are connected via a bus; the memory can be used to store executable programs, and an exemplary executable program may include instructions; the processor is used to execute the instructions stored in the memory. The memory can also be used to store data, which can be accessed and / or modified when instructions are executed.

[0087] The processor may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and it is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions in the storage medium to realize the corresponding method flow or corresponding function, so as to realize the steps of the integrated monitoring and collaborative control method for power quality of a power station in the above embodiments.

[0088] Example 5: Based on the same inventive concept, this invention also provides a readable storage medium, specifically an electronic device readable storage medium (Memory). This readable storage medium is a memory device within an electronic device used to store programs and data. It is understood that the storage medium here can include both built-in storage media within the electronic device and extended storage media supported by the electronic device. The storage medium provides storage space, which stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more executable programs (including program code). It should be noted that the storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. Loading and executing one or more instructions stored in the storage medium by the processor can implement the steps of the integrated monitoring and collaborative control method for power quality at a power station in the above embodiments.

[0089] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0090] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0091] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0092] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0093] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit its scope of protection. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that after reading the present invention, they can still make various changes, modifications or equivalent substitutions to the specific implementation methods of the application, but these changes, modifications or equivalent substitutions are all within the scope of protection of the claims pending approval.

Claims

1. A method for integrated monitoring and collaborative control of power quality in power stations, characterized in that, include: Based on the monitored operational information of the on-site equipment at the station, the station's operating conditions are determined; The on-site equipment at the station includes primary equipment and secondary equipment; Based on the operational information and the operating conditions of the power station, and combined with the preset multi-level and multi-dimensional power quality assessment indicators, the cause of power quality disturbances is determined using a power quality assessment algorithm. Based on the operational information, the operating conditions of the power station, and the causes of power quality disturbances, a collaborative optimization control algorithm is used to perform collaborative optimization control on the local equipment of the power station. The power quality assessment indicators are multi-level, including multiple levels of medium voltage, low voltage, AC and DC; the power quality assessment indicators are multi-dimensional, including multiple dimensions of voltage quality, frequency stability, harmonic and ripple pollution, and power supply reliability.

2. The method as described in claim 1, characterized in that, Based on the operational information and the station's operating conditions, and combined with preset multi-level and multi-dimensional power quality assessment indicators, the power quality assessment algorithm is used to determine the causes of power quality disturbances, including: Based on each of the preset multi-level and multi-dimensional power quality assessment indicators, the indicator value of the indicator is determined in the operation information. Based on the index value of each of the above indicators, the index grading standard of the power quality assessment algorithm is used to grade and evaluate each of the above indicators, and the grading and evaluation result of each of the above indicators is obtained. Based on the operating conditions of the power station and the graded evaluation results of each of the above indicators, the causes of power quality disturbances are determined. The indicator grading standard includes multiple levels for each indicator, with the multiple levels from low to high representing the power quality of the indicator from excellent to poor.

3. The method as described in claim 1 or 2, characterized in that, The primary equipment includes a charging and discharging pile, an energy storage converter, a photovoltaic inverter, and a power quality management device for suppressing power quality disturbances. The secondary equipment includes a power quality monitoring device for monitoring power quality at different locations within the station.

4. The method as described in claim 1 or 2, characterized in that, After determining the station's operating conditions based on the monitored operational information of the station's local equipment, the process also includes: Under the peak-valley electricity pricing mechanism, the power station is controlled to use the energy storage system to supply power during peak electricity price periods, while limiting non-emergency charging loads; and the power station is controlled to use surplus photovoltaic power or the grid to charge the energy storage system during off-peak electricity price periods, and to open the charging station for centralized charging of electric vehicles. Under the real-time electricity price dynamic adjustment mechanism, the control station selects photovoltaic or energy storage systems for priority charging based on the real-time electricity price signal of the electricity market.

5. The method as described in claim 1 or 2, characterized in that, After determining the station's operating conditions based on the monitored operational information of the station's local equipment, the process also includes: During periods of low electricity demand, the power station is controlled to use surplus photovoltaic power or the power grid to charge the energy storage system; during periods of high electricity demand, the power station is controlled to use the energy storage system to supply power. When the grid frequency is lower than the set frequency threshold, the power station is controlled to use the energy storage system to supplement the grid power and reduce the charging power of the charging and discharging piles; when the grid frequency is not lower than the set frequency threshold, the power station is controlled to absorb excess electrical energy and reduce the photovoltaic power generation power. When the power station is used as a spinning backup power source, the energy storage system is controlled to maintain its operating state; when the power station is used as a non-spinning backup power source, the energy storage system is controlled to be in hot standby or cold standby state.

6. A comprehensive monitoring and collaborative control system for power quality in power stations, characterized in that, include: The station's local equipment, collaborative control terminal, and station control platform are sequentially connected via communication. The collaborative control terminal is used to monitor the operating information of the on-site equipment at the station and forward it to the station control platform; the on-site equipment at the station includes primary equipment and secondary equipment; it is also used to issue collaborative optimization control instructions for the on-site equipment at the station, and to conduct collaborative optimization control of the on-site equipment at the station based on the collaborative optimization control instructions. The station control platform is used to determine the station's operating status based on the operating information of the station's local equipment. Based on the operational information and the operating conditions of the power station, and combined with the preset multi-level and multi-dimensional power quality assessment indicators, the cause of power quality disturbances is determined using a power quality assessment algorithm. Based on the operational information, the operating conditions of the power station, and the causes of power quality disturbances, a collaborative optimization control algorithm is used to generate collaborative optimization control instructions for the local equipment of the power station and send them to the collaborative control terminal. The power quality assessment indicators are multi-level, including multiple levels of medium voltage, low voltage, AC and DC; the power quality assessment indicators are multi-dimensional, including multiple dimensions of voltage quality, frequency stability, harmonic and ripple pollution, and power supply reliability.

7. The system as described in claim 6, characterized in that, The station control platform is specifically used to determine the index value of each of the preset multi-level and multi-dimensional power quality assessment indicators in the operation information; based on the index value of each indicator, it performs a graded assessment of each indicator using the index grading standard of the power quality assessment algorithm to obtain the graded assessment result of each indicator; and based on the station operating conditions and the graded assessment results of each indicator, it determines the cause of power quality disturbance. The indicator grading standard includes multiple levels for each indicator, with the multiple levels from low to high representing the power quality of the indicator from excellent to poor.

8. The system as described in claim 6 or 7, characterized in that, The primary equipment includes a charging and discharging pile, an energy storage converter, a photovoltaic inverter, and a power quality management device for suppressing power quality disturbances. The secondary equipment includes a power quality monitoring device for monitoring power quality at different locations in the station; The voltage quality metrics include voltage deviation, voltage fluctuation and flicker, three-phase voltage imbalance, and transient overvoltage; the frequency stability metrics include frequency deviation, frequency fluctuation, frequency offset rate, and frequency transient response; the harmonic and ripple pollution metrics include total harmonic distortion of voltage, total harmonic distortion of current, harmonic content, ripple voltage coefficient, and ripple current coefficient; and the power supply reliability metrics include power availability, outage frequency, outage duration, and average customer power outage time index.

9. The system as described in claim 6 or 7, characterized in that, It also includes: a communication acquisition and control network; The collaborative control terminal is used to forward the operation information to the communication acquisition and control network; The communication acquisition and control network is used to encapsulate the operation information and send it to the station control platform using dynamic balanced dual-network technology.

10. The system as described in claim 6 or 7, characterized in that, The station control platform is also used for: Under the peak-valley electricity pricing mechanism, the power station is controlled to use the energy storage system to supply power during peak electricity price periods, while limiting non-emergency charging loads; and the power station is controlled to use surplus photovoltaic power or the grid to charge the energy storage system during off-peak electricity price periods, and to open the charging station for centralized charging of electric vehicles. Under the real-time electricity price dynamic adjustment mechanism, the control station selects photovoltaic or energy storage systems for priority charging based on the real-time electricity price signal of the electricity market.

11. The system as described in claim 6 or 7, characterized in that, The station control platform is also used for: During periods of low electricity demand, the power station is controlled to use surplus photovoltaic power or the power grid to charge the energy storage system; during periods of high electricity demand, the power station is controlled to use the energy storage system to supply power. When the grid frequency is lower than the set frequency threshold, the power station is controlled to use the energy storage system to supplement the grid power and reduce the charging power of the charging and discharging piles; when the grid frequency is not lower than the set frequency threshold, the power station is controlled to absorb excess electrical energy and reduce the photovoltaic power generation power. When the power station is used as a spinning backup power source, the energy storage system is controlled to maintain its operating state; when the power station is used as a non-spinning backup power source, the energy storage system is controlled to be in hot standby or cold standby state.

12. The system as described in claim 6, characterized in that, The collaborative control terminal is also used to determine the operating conditions of the power station based on the operating information of the local equipment at the station; and to obtain the cause of the power quality disturbance from the station control platform. Based on the operational information, the operating conditions of the power station, and the causes of power quality disturbances, a collaborative optimization control algorithm is used to perform collaborative optimization control on the local equipment of the power station.

13. A comprehensive monitoring and collaborative control system for power quality in power stations, characterized in that, include: The monitoring module is used to determine the operating status of the station based on the monitored operating information of the local equipment at the station; The on-site equipment at the station includes primary equipment and secondary equipment; The power quality assessment module is used to determine the cause of power quality disturbances based on the operating information and the operating conditions of the power station, combined with preset multi-level and multi-dimensional power quality assessment indicators and using power quality assessment algorithms. The collaborative optimization control module is used to perform collaborative optimization control on the local equipment of the station based on the operating information, the station operating conditions and the causes of power quality disturbances, using a collaborative optimization control algorithm. The power quality assessment indicators are multi-level, including multiple levels of medium voltage, low voltage, AC and DC; the power quality assessment indicators are multi-dimensional, including multiple dimensions of voltage quality, frequency stability, harmonic and ripple pollution, and power supply reliability.

14. The system as described in claim 13, characterized in that, The power quality assessment module includes: The grading evaluation unit is used to determine the index value of each of the preset multi-level and multi-dimensional power quality evaluation indicators in the operation information; based on the index value of each of the indicators, the unit uses the index grading standard of the power quality evaluation algorithm to perform a grading evaluation on each of the indicators, and obtain the grading evaluation result of each indicator. The disturbance cause determination unit determines the cause of power quality disturbance based on the station's operating conditions and the graded evaluation results of each indicator; The indicator grading standard includes multiple levels for each indicator, with the multiple levels from low to high representing the power quality of the indicator from excellent to poor.

15. The system as described in claim 13 or 14, characterized in that, The primary equipment includes a charging and discharging pile, an energy storage converter, a photovoltaic inverter, and a power quality management device for suppressing power quality disturbances. The secondary equipment includes a power quality monitoring device for monitoring power quality at different locations within the station.

16. The system as described in claim 13 or 14, characterized in that, Also includes: The demand response module is used to control the power station to use the energy storage system to supply power during peak electricity price periods under the peak-valley electricity price mechanism, while limiting non-emergency charging loads. The system also controls the power station to use surplus photovoltaic power or the power grid to charge the energy storage system during off-peak electricity price periods, and to activate the charging station for centralized charging of electric vehicles; under the real-time electricity price dynamic adjustment mechanism, the system controls the power station to select photovoltaic or energy storage systems for priority charging based on real-time electricity market price signals.

17. The system as described in claim 13 or 14, characterized in that, Also includes: The grid auxiliary module is used to control the power station to charge the energy storage system using surplus photovoltaic power or the grid during off-peak hours. During peak electricity consumption periods, the power station is controlled to utilize the energy storage system for power supply; when the grid frequency is lower than a set frequency threshold, the power station is controlled to utilize the energy storage system to supplement the grid power and reduce the charging power of the charging and discharging piles; when the grid frequency is not lower than the set frequency threshold, the power station is controlled to absorb excess electrical energy and simultaneously reduce the photovoltaic power generation; when the power station is used as a spinning backup power source, the energy storage system is controlled to maintain its operating state; when the power station is used as a non-spinning backup power source, the energy storage system is controlled to be in hot standby or cold standby state.

18. An electronic device, characterized in that, include: At least one processor and memory; The memory and processor are connected via a bus; The memory is used to store one or more programs; When the one or more programs are executed by the at least one processor, the integrated monitoring and collaborative control method for power quality at power stations as described in any one of claims 1 to 5 is implemented.

19. A readable storage medium, characterized in that, It contains an execution program, which, when executed, implements the integrated monitoring and collaborative control method for power quality at power stations as described in any one of claims 1 to 5.

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