A remote intelligent operation and maintenance monitoring system for hydropower stations

Abstract

This invention relates to the field of smart grid technology, specifically disclosing a remote intelligent operation and maintenance monitoring system for hydropower stations. The system includes: a data acquisition module for acquiring the total output power of all turbines and the target output power of the hydropower station, and calculating the power gap value; an analysis module for mapping the unit flow rate and output power of the turbines to a rectangular coordinate system to generate characteristic curves, obtaining the fitting equations corresponding to the characteristic curves, and obtaining the reciprocal equation by differentiation; and an adjustment module for acquiring the unit flow rate of the turbines, calculating the output power growth rate, arranging the turbines and selecting the equipment to be adjusted, presetting the flow gradient, calculating the output power growth rate and selecting the equipment to be adjusted again, obtaining the target gradient, and substituting the target gradient into the calculation to determine whether the constraints are met. This invention optimizes gate regulation while meeting the grid dispatch requirements through intelligent operation and maintenance methods, thereby satisfying the dual requirements of power output and operational stability of hydropower stations.

Description

Technical Field

[0001] This invention relates to the field of smart grid technology, and more specifically to a remote intelligent operation and maintenance monitoring system for hydropower stations. Background Technology

[0002] Intelligent operation and maintenance of hydropower stations integrates modern information technology with power generation technology to construct an all-weather, end-to-end intelligent management system. The core of this new operation and maintenance model lies in utilizing a neural network built from the Internet of Things (IoT), making every piece of equipment in the hydropower station a perceptible and interactive intelligent terminal. Thousands of sensors, like sensitive antennae, continuously collect key parameters, and this data is transmitted in real time to the cloud-based system via high-speed communication networks, forming a digital mirror of the equipment.

[0003] This system can not only detect equipment anomalies from data fluctuations, but also continuously accumulate diagnostic experience through deep learning. When signs of cavitation appear on the turbine runner, the system can issue an early warning weeks in advance. At the same time, the virtual power plant built with digital twin technology can simulate various operating conditions in a computer, helping engineers test and optimize solutions in a virtual environment, avoiding the risks of directly operating physical equipment, and simulating the optimal solution.

[0004] In existing technologies, the gate opening of hydropower stations is typically subject to strict operational limitations and cannot be dynamically adjusted arbitrarily. These limitations stem primarily from several factors: first, the physical constraints of the gate's mechanical structure, including maximum and minimum opening limits and opening / closing rate restrictions; second, hydraulic stability requirements, as frequent or large-scale gate adjustments can lead to hydraulic oscillations such as water hammer in pressure pipelines and tailrace vortex formations; and third, grid dispatch requirements, as gate regulation needs to consider the comprehensive needs of downstream ecological flow and navigation. Therefore, when there is a deviation between the actual power generation of a hydropower station and the target power generation assigned by the dispatching department, traditional gate-priority regulation strategies often fail to simultaneously meet both power requirements and operational stability requirements. Summary of the Invention

[0005] The purpose of this invention is to provide a remote intelligent operation and maintenance monitoring system for hydropower stations to solve the above-mentioned technical problems.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] A remote intelligent operation and maintenance monitoring system for hydropower stations includes:

[0008] Data acquisition module: Obtains the total power output P of all turbines in the current hydropower station. all Obtain the preset target output power P of the hydropower station sta When P sta >P allWhen calculating the power shortage value Ps=P sta -P all ;

[0009] Analysis module: A rectangular coordinate system is established with the unit flow rate Q of the water turbine as the x-axis and the output power P as the y-axis. The unit flow rate Q of the water turbine represents the volume of water flowing through the water turbine in a preset unit time.

[0010] The unit flow rate Q and output power P of the water turbine are mapped to a rectangular coordinate system to generate corresponding characteristic curves. The fitting equation p(q) corresponding to the characteristic curve is obtained, and the derivative of the fitting equation p(q) is obtained to get the reciprocal equation. ;

[0011] Adjustment module: Obtains the current unit flow rate Q of each turbine. now Calculate the power output growth rate of the water turbine. Arrange the water turbines in descending order of power output growth rate, and designate the water turbine at the top of the list as the equipment to be adjusted;

[0012] Preset flow gradient T=λQ min Where λ represents the gradient coefficient and λ = 1, 2, 3, ..., Q min Representing the preset minimum change in unit flow rate, the gradient coefficient λ is increased sequentially, and the power output growth rate of each turbine is recalculated. The equipment to be adjusted is reselected based on the recalculated power output growth rate. If the equipment to be adjusted changes, the gradient coefficient is recorded as the target gradient λ. sta Increase the unit flow rate of the previous device to be adjusted by (λ) sta -1)×Q min Obtain the fitting equation p corresponding to the characteristic curve of the previous device to be adjusted. last (q) Determine whether the constraints are met. If the condition is met, stop adjusting; otherwise, repeat the above steps until the constraint is met.

[0013] As a further aspect of the present invention: in the data acquisition module, when P sta =P all Stop adjusting when the time is right.

[0014] When P sta <P all When the gradient coefficient λ is adjusted, the adjusted gradient coefficient λ = -1, -2, -3, ...

[0015] As a further aspect of the present invention: in the analysis module, the turbine corresponding to the sluice gate being in the closed state is recorded as a standby device, and the standby device does not participate in the selection of subsequent devices to be adjusted.

[0016] As a further aspect of the present invention: in the adjustment module, the runoff flow rate F of the turbine is obtained, if Q now ≥F, calculate Q that satisfies the condition now -λ×Q min When the gradient coefficient λ is less than F, the unit flow rate of the turbine is reduced by λ×Q. min .

[0017] As a further aspect of the present invention: In the adjustment module, when there are turbines with equal power output growth rates, the current unit flow rate Q is set... now The smaller water turbines are located earlier in the sequence.

[0018] As a further aspect of the present invention: In the adjustment module, when all turbines reach the corresponding runaway flow rate, if the power deficit value Ps≠0 at this time, the staff will be notified that there is still an energy deficiency.

[0019] As a further aspect of the present invention: in the adjustment module, each time the device to be adjusted changes, the target gradient λ of the previous device to be adjusted is... sta Retain the gradient coefficient λ of the currently adjusted equipment and the remaining turbines, and set it to zero.

[0020] As a further aspect of the present invention: the limiting conditions are modified, and the modified limiting conditions are as follows: .

[0021] The beneficial effects of this invention are as follows: First, the power gap between the total output power of all turbines in the current hydropower station and the preset target output power of the hydropower station is calculated. When the power gap value is greater than 0, it indicates that the current power supply rate of the hydropower station is insufficient to support the predetermined target plan and cannot meet the requirements of power grid dispatch, thereby causing fluctuations in the power grid and affecting the stability of the power grid. Therefore, it is necessary to adjust the unit flow rate of the turbines in the hydropower station.

[0022] In reality, not all turbines in a hydropower station are turned on; some are in operation while others are in standby mode. Furthermore, even among the turbines in operation, the varying opening degrees of each gate result in different power generation efficiencies. Therefore, to minimize the impact of gate changes on the downstream area while meeting the hydropower station's target output power, characteristic curves are generated by mapping the turbine's unit flow rate and output power to a Cartesian coordinate system. The corresponding fitting equations are then obtained, and the derivative of these equations is used to obtain their reciprocals. This process reveals the rate at which the turbine's output power changes with unit flow rate. It's understandable that to meet the hydropower station's preset target output power while minimizing gate adjustments, turbines with rapidly increasing output power that changes with unit flow rate should be selected, thus reducing the need for gate adjustments.

[0023] The power output growth rate of each turbine is calculated based on its current unit flow rate. The turbines are then arranged in descending order of power output growth rate, with the turbine at the top of the list designated as the turbine to be adjusted. This method selects the turbine that performs best under the current conditions, and adjusting this turbine will yield optimal results. However, as the adjustment process progresses, the performance of the turbine will gradually decline. Therefore, a flow gradient is established, and the limits of the turbine to be adjusted are gradually identified based on this gradient. When the turbine to be adjusted changes, it indicates that the turbine that previously performed optimally has changed. Therefore, the gradient coefficient at this point is recorded as the target gradient, and the unit flow rate of the previously selected turbine is increased by (λ). sta -1)×Q min The reason for reducing the target gradient by one here is to ensure that the gate is always kept to a minimum. Finally, a judgment is made: if the constraint condition is met, the process ends; otherwise, the adjustment continues. The constraint condition is whether the increase in output power caused by the increase in unit flow rate is greater than the power shortage value. Therefore, this invention optimizes gate regulation while meeting the grid dispatch requirements through intelligent operation and maintenance methods, thereby satisfying the dual requirements of power generation and operational stability of hydropower stations. Attached Figure Description

[0024] The invention will now be further described with reference to the accompanying drawings.

[0025] Figure 1 This is a schematic diagram of the structure of a remote intelligent operation and maintenance monitoring system for hydropower stations according to the present invention. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] Please see Figure 1 As shown, the present invention is a remote intelligent operation and maintenance monitoring system for hydropower stations, comprising:

[0028] Data acquisition module: Obtains the total power output P of all turbines in the current hydropower station. all Obtain the preset target output power P of the hydropower station sta When P sta >P all When calculating the power shortage value Ps=P sta -P all ;

[0029] Analysis module: A rectangular coordinate system is established with the unit flow rate Q of the water turbine as the x-axis and the output power P as the y-axis. The unit flow rate Q of the water turbine represents the volume of water flowing through the water turbine in a preset unit time.

[0030] The unit flow rate Q and output power P of the water turbine are mapped to a rectangular coordinate system to generate corresponding characteristic curves. The fitting equation p(q) corresponding to the characteristic curve is obtained, and the derivative of the fitting equation p(q) is obtained to get the reciprocal equation. ;

[0031] Adjustment module: Obtains the current unit flow rate Q of each turbine. now Calculate the power output growth rate of the water turbine. Arrange the water turbines in descending order of power output growth rate, and designate the water turbine at the top of the list as the equipment to be adjusted;

[0032] Preset flow gradient T=λQ min Where λ represents the gradient coefficient and λ = 1, 2, 3, ..., Q min Representing the preset minimum change in unit flow rate, the gradient coefficient λ is increased sequentially, and the power output growth rate of each turbine is recalculated. The equipment to be adjusted is reselected based on the recalculated power output growth rate. If the equipment to be adjusted changes, the gradient coefficient is recorded as the target gradient λ. sta Increase the unit flow rate of the previous device to be adjusted by (λ) sta -1)×Q min Obtain the fitting equation p corresponding to the characteristic curve of the previous device to be adjusted. last (q) Determine whether the constraints are met. If the condition is met, stop adjusting; otherwise, repeat the above steps until the constraint is met.

[0033] It should be noted that in today's complex and massive power systems, hydropower stations, as one of the important sources of electricity supply, play a crucial role in ensuring the safe and reliable power supply of the entire power grid through their stable and efficient operation. In the actual process of power production and dispatch, it is necessary to closely monitor the operating status of each turbine in the hydropower station and its overall output to ensure that it can provide a stable and sufficient amount of electricity to the power grid according to the preset target plan.

[0034] Specifically, the power gap must first be calculated based on the actual total output power of all turbines in the current hydropower station and the pre-set target output power of the hydropower station. The pre-set target output power is determined by comprehensively considering factors such as the overall load demand of the power grid, the supply and demand situation of the electricity market, and relevant dispatch instructions. It represents the level of power output that the hydropower station needs to achieve within a certain period.

[0035] Calculations revealed that a power deficit value greater than 0 indicates that the current power supply rate of the hydropower station is significantly insufficient to support the planned targets. In this situation, the hydropower station cannot provide enough power to the grid as expected, thus failing to meet the grid dispatch requirements. This mismatch between power supply and demand will lead to grid fluctuations.

[0036] As a highly complex and interconnected system, the stability of a power grid depends on the coordinated operation of its various power sources and the balance of its loads. When the output of a hydropower station cannot meet the planned output, key parameters such as voltage and frequency in the power grid may change abnormally. These changes will propagate throughout the power grid like a ripple effect, affecting the normal operation of other power sources and loads.

[0037] Therefore, to ensure the stable operation of the power grid and avoid various problems caused by insufficient power output from hydropower stations, it is necessary to adjust the unit flow rate of the turbines in the hydropower station in a timely manner. By precisely controlling the unit flow rate of the turbines, the output characteristics of the turbines can be changed, enabling them to maximize their output power under current conditions and narrow the gap with the target output power. This ensures that the hydropower station can provide stable and reliable power support to the power grid according to the predetermined plan.

[0038] In actual hydropower station operation and management, due to the dynamic changes in electricity demand and the limitations of the hydropower station's own equipment characteristics and operating strategies, the turbines in a hydropower station are usually not all on, but rather exhibit a complex operating mode of partial operation and partial standby. This choice of operating mode is based on a comprehensive consideration of multiple factors. By flexibly adjusting the number and status of the turbines in operation, the hydropower station can meet certain electricity supply needs while achieving efficient energy utilization and reasonable equipment maintenance.

[0039] Furthermore, even when a water turbine is in operation, the efficiency of its power generation varies due to differences in the opening degree of each gate. Gate opening, as a key factor affecting the operating performance of a water turbine, directly determines the flow rate and velocity of water passing through the turbine, thus significantly impacting its output power and power generation efficiency. Different gate openings cause changes in the flow pattern inside the turbine, resulting in fluctuations in the efficiency of converting water energy into electrical energy. When the gate opening is too large, although the flow rate increases, the water velocity may exceed the turbine's optimal operating range, leading to decreased efficiency and potentially causing safety hazards to the equipment.

[0040] Therefore, in the actual operation of hydropower stations, in order to minimize the impact of gate changes on downstream areas while meeting the target power output, an important method is to generate corresponding characteristic curves by mapping the unit flow rate and power output of the turbines to a Cartesian coordinate system. This process involves the collection and analysis of a large amount of actual operating data. By accurately marking the unit flow rate and corresponding power output data of the turbines under different operating conditions on a Cartesian coordinate system, the relationship between the two can be intuitively reflected. These characteristic curves are like fingerprints of the turbine's operating characteristics, containing rich information that helps operation and management personnel gain a deeper understanding of the power output performance of each turbine under different unit flow rates.

[0041] After obtaining the fitting equation corresponding to the characteristic curve, the reciprocal equation obtained by differentiating the fitting equation clearly reveals the rate at which the turbine's output power changes with unit flow rate. Specifically, the correlation coefficient in the reciprocal equation reflects the sensitivity of the turbine's output power to changes in unit flow rate under different conditions. Based on this analysis, a deeper understanding of the turbine's operating characteristics can be achieved, and operational strategies can be formulated accordingly. It is understandable that minimizing gate adjustments while meeting the hydropower station's preset target output power is crucial. Frequent or significant gate opening adjustments not only increase equipment wear and operating costs but may also adversely affect the downstream ecological environment, navigation safety, and the normal operation of other water conservancy facilities. Therefore, turbines with rapidly increasing output power that changes with unit flow rate should be prioritized for control. By rationally adjusting the operating parameters of these turbines, they can achieve a greater increase in output power within a smaller range of unit flow rate changes. This minimizes gate adjustments while meeting the target output power, achieving efficient, stable, and environmentally friendly operation of the hydropower station.

[0042] In the refined operation and management of hydropower stations, in order to achieve efficient control of water turbines and thus ensure the stable operation of hydropower stations while meeting the requirements of power grid dispatch, the first step is to calculate the power output growth rate of each water turbine based on the current unit flow of each water turbine.

[0043] After obtaining the power output growth rate of all turbines, they are arranged in descending order of power output growth rate. This ranking method is based on the assessment of the turbines' regulation potential. Turbines with higher power output growth rates mean they can generate a more significant increase in power output per unit flow change, possessing greater regulation space and potential, and therefore are more valuable for regulation under the current operating conditions. The turbine ranked first is designated as the equipment to be regulated because, under the current conditions, this turbine has the best regulation effect. Adjusting it can achieve the maximum power output increase at the lowest cost, thereby most effectively narrowing the power gap between the actual and target power output of the hydropower station.

[0044] However, it is important to note that as the adjustment process progresses, the adjustment effect of the equipment under control will gradually decline. This is because the output characteristics of a water turbine are not linearly constant; when its unit flow rate changes, the rate of increase in output power will gradually decrease due to various physical factors. Therefore, to achieve precise regulation of the water turbine, a reasonable flow gradient needs to be set. This flow gradient is determined based on the actual operating characteristics of the water turbine and reflects the sensitivity of the water turbine's output power to changes in unit flow rate at different adjustment stages.

[0045] Based on the set flow gradient, the limits of the equipment to be adjusted are gradually identified. During this process, the rate of increase in the output power of the equipment to be adjusted is closely monitored. When it is found that the rate of increase in output power decreases to a certain extent and it is no longer suitable as the current optimal adjustment target, it indicates that the turbine with the best effect has changed. At this point, the current gradient coefficient is recorded as the target gradient, and the unit flow rate of the previous equipment to be adjusted is increased by (λsta-1)×Qmin. The purpose of subtracting one from the target gradient here is to minimize the changes to the gate regulation.

[0046] Finally, if the limiting conditions are met, the adjustment process ends; otherwise, adjustments continue. The limiting conditions refer to whether the increase in power output resulting from a unit increase in flow rate exceeds the power deficit value. Specifically, after each adjustment, the total power output of the hydropower station is monitored in real time and compared with the target power output to calculate the current power deficit value. Simultaneously, based on the unit flow rate change of the turbine and the power output growth rate, the increase in power output resulting from a unit increase in flow rate is calculated. If this increase exceeds the power deficit value, the current adjustment meets the requirements of grid dispatch and no further adjustment is needed; otherwise, the adjustment process continues according to the above steps until the limiting conditions are met.

[0047] Through this intelligent operation and maintenance method, hydropower stations can perceive their own operating status and changes in grid demand in real time in a complex and ever-changing operating environment, and accurately adjust the turbines. While meeting the grid dispatch requirements, the gate regulation process is optimized, avoiding unnecessary frequent and excessive regulation, thereby effectively ensuring the power output and operational stability of the hydropower station and realizing efficient, reliable and sustainable power production.

[0048] In another preferred embodiment of the present invention, when P sta =P all Stop adjusting when the time is right.

[0049] When P sta <P all When the gradient coefficient λ is adjusted, the adjusted gradient coefficient λ = -1, -2, -3, ...

[0050] It is worth noting that when the total output power of all the turbines is exactly equal to the hydropower station's preset target output power, it indicates that the current operating state of the hydropower station is perfectly matched with the grid dispatch requirements, and the power supply and demand are balanced. In this case, no adjustments to the turbines are necessary, as any unnecessary operation could disrupt this balance, leading to a surplus or shortage of power supply, resulting in ineffective energy waste and additional equipment wear and tear. Maintaining the existing operating state of the turbines is the optimal choice, ensuring both grid stability and efficient energy utilization.

[0051] However, when the total output power of all turbines is less than the hydropower station's preset target output power, it indicates that the current power supply of the hydropower station cannot meet the grid's demand, and corresponding adjustment measures must be taken. To meet grid dispatch requirements while minimizing frequent adjustments to turbines and gates, and to avoid equipment wear and operational risks caused by excessive adjustments, these measures are necessary.

[0052] In another preferred embodiment of the present invention, the water turbine corresponding to the sluice gate being in the closed state is recorded as a standby device, and the standby device does not participate in the selection of subsequent devices to be adjusted.

[0053] Understandably, turbines with sluice gates closed are designated as standby equipment. Because the sluice gates are closed and water flow is restricted, these standby turbines temporarily lack power generation capacity and cannot participate in the current electricity production process. In the subsequent selection of equipment to be deployed, these standby turbines will be excluded and not considered as candidates.

[0054] In another preferred embodiment of the present invention, the runoff flow rate F of the water turbine is obtained, if Q now ≥F, calculate Q that satisfies the condition now -λ×Q min When the gradient coefficient λ is less than F, the unit flow rate of the turbine is reduced by λ×Q. min .

[0055] It is important to note that runoff refers to the maximum flow rate of water passing through the turbine under extreme conditions such as loss of load or guide vane failure. This parameter is a crucial basis for turbine design and safe operation, directly affecting the turbine's service life and operational safety.

[0056] When the current unit flow rate of a hydroelectric turbine is detected to be greater than or equal to its runoff flow rate, it means that the turbine is in an extremely dangerous state. In this situation, the impact of the water flow on the turbine will increase dramatically, potentially causing excessive stress on critical components such as the turbine runner and blades, and even leading to equipment damage or malfunction. This damage is often irreversible, not only affecting the turbine's normal power generation function but also potentially causing serious economic losses and safety hazards.

[0057] Therefore, if it is found that the unit flow rate of the current turbine is close to or reaches the runaway flow rate, effective measures must be taken immediately to reduce the unit flow rate of the turbine to a safe range.

[0058] In another preferred embodiment of the present invention, when there are turbines with equal power output growth rates, the current unit flow rate Q is set to... now The smaller water turbines are located earlier in the sequence.

[0059] It should be noted that turbines with lower unit flow rates typically have greater regulation potential because their current output power is relatively low. Increasing the unit flow rate can significantly boost output power, thereby quickly narrowing the power gap. Simultaneously, due to their lower initial flow rate, these turbines require less adjustment to gate opening during regulation, effectively reducing equipment wear and operational risks. Furthermore, low-flow-rate equipment is less likely to approach safety thresholds such as runaway flow during regulation, avoiding equipment damage or efficiency degradation caused by over-regulation. Therefore, prioritizing turbines with lower unit flow rates not only aligns with the regulation principle of "maximum effect with minimum modification" but also improves regulation flexibility and precision. This ensures that while meeting grid dispatch requirements, water resources are conserved to the maximum extent and equipment lifespan is extended, ultimately achieving the dual optimization goals of hydropower station power output and operational stability.

[0060] In another preferred embodiment of the present invention, when all turbines have reached the corresponding runaway flow rate, if the power deficit value Ps ≠ 0 at this time, the staff will be notified that there is still an energy deficit.

[0061] Understandably, if the power deficit Ps ≠ 0 when all turbines have reached their corresponding runoff flow rates, it indicates to staff that an energy shortage still exists. This means that although all turbines have been adjusted to their maximum safe operating flow rates, the total output power of the hydropower station still cannot meet the preset target output power requirement; that is, the power deficit Ps has not been eliminated. At this point, the system will issue a clear warning to staff, informing them that there is still a problem with insufficient energy supply. This means that, without exceeding the safe operating range of the equipment, the current power shortage cannot be completely compensated for through conventional adjustment methods, thus avoiding equipment damage or safety accidents caused by excessive adjustment.

[0062] In another preferred embodiment of the present invention, each time the device to be adjusted changes, the target gradient λ of the previous device to be adjusted is... sta Retain the gradient coefficient λ of the currently adjusted equipment and the remaining turbines, and set it to zero.

[0063] In a preferred embodiment, the limiting conditions are modified, and the modified limiting conditions are as follows: .

[0064] It is worth noting that the revised limit conditions provide a solution for the total output power exceeding the target output power.

[0065] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the present invention should still fall within the scope of the present invention.

Claims

1. A remote intelligent operation and maintenance monitoring system for a hydropower station, characterized in that, Comprising: Data acquisition module: get the total output power P of all water turbines in the current hydropower station all , get the target output power P of the hydropower station sta , when P sta >P all , calculate the power gap value Ps=P sta -P all ; an analysis module: a rectangular coordinate system is established with the unit flow Q of the water turbine as the x-axis and the output power P as the y-axis, wherein the unit flow Q of the water turbine represents the volume of water flow passing through the water turbine in a predetermined unit time; Map the unit flow Q and the output power P of the water turbine to the rectangular coordinate system to generate a corresponding characteristic curve, obtain a fitting equation p(q) corresponding to the characteristic curve, and derive the reciprocal equation by taking the derivative of the fitting equation p(q) ; Adjustment module: obtain the current unit flow Q of each water turbine now , calculate the output power increasing speed of the water turbine , arrange the water turbines in descending order of output power increasing speed, and record the first water turbine in the sequence as the device to be adjusted; Pre-set flow gradient T = λQ min Wherein, λ represents the gradient coefficient and λ = 1, 2, 3,..., Q min Represent the preset minimum change value of unit flow, increase the gradient coefficient λ in order, recalculate the output power speed of each hydraulic turbine , according to the recalculated output power speed, reselect the equipment to be adjusted, if the equipment to be adjusted changes, the gradient coefficient is recorded as the target gradient λ sta Increase the unit flow of the last equipment to be adjusted by (λ sta -1) × Q min , get the fitting equation p last (q) corresponding to the characteristic curve of the last equipment to be adjusted, judge whether the limit condition is met , if it is met, stop adjusting, otherwise repeat the above steps until the limit condition is met. 2.The remote intelligent operation and maintenance monitoring system for a hydropower station of claim 1, characterized in that, In the data acquisition module, when P sta = P all , stop adjusting; When P sta When P all The gradient coefficient λ is adjusted, and the adjusted gradient coefficient λ = -1, -2, -3,... 3.The remote intelligent operation and maintenance monitoring system of a hydropower station of claim 1, characterized in that, In the analysis module, the water turbine corresponding to the closed state of the water gate is recorded as standby equipment, and the standby equipment does not participate in the selection of subsequent standby equipment.

4. The remote intelligent operation and maintenance monitoring system for a hydropower station of claim 1, characterized in that, In the adjustment module, the runaway flow F of the water turbine is obtained, and if Q now ≥ F, the gradient coefficient λ is calculated to satisfy the condition Q now - λ × Q min <F, the value of the gradient coefficient λ is calculated, and the unit flow of the water turbine is reduced by λ × Q min .

5. The remote intelligent operation and maintenance monitoring system for a hydropower station of claim 1, characterized in that, In the adjustment module, when there is a hydraulic turbine with the same output power increasing rate, let the current unit flow Q now The smaller hydraulic turbine is located in the front position in the sequence.

6. The remote intelligent operation and maintenance monitoring system for a hydropower station of claim 1, characterized in that, In the adjustment module, when all the water turbines reach the corresponding runaway flow, if the power gap Ps≠0 at this time, the staff is prompted that there is still an energy defect.

7. The remote intelligent operation and maintenance monitoring system for a hydropower station of claim 1, characterized in that, In the adjustment module, when each time the to-be-adjusted device changes, the target gradient λ of the last to-be-adjusted device is set as the target gradient λ of the current to-be-adjusted device sta Reserved, the gradient coefficient λ of the current to-be-adjusted device and the rest of the water turbine is set to zero. 8.The remote intelligent operation and maintenance monitoring system of a hydropower station of claim 2, characterized in that, The restriction condition is modified, and the modified limit condition is .

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