A hydropower station optimization scheduling method based on unit health status

Abstract

The present invention patent discloses a method for optimizing the scheduling of hydropower stations based on the health status of units. The operating parameters of the hydropower units are included in the evaluation indicators, and a health evaluation index system for the operation of hydropower units is established. The degradation factor is introduced to calculate the degradation degree of each indicator, and the comprehensive degradation degree is used as the overall evaluation indicator of the health status of the hydropower units. Combined with the economic scheduling operation constraints of the hydropower units, a multi-objective scheduling model for optimizing the scheduling of hydropower stations based on the health status of the units is established, and a solution method based on the multi-objective hybrid frog leapfrog difference algorithm is adopted. By optimizing the operation plan, the time node when the unit status breaks through the fault limit is delayed and the degree of fault degradation at the node is reduced, so that the unit can maintain a safe and stable operating state within a controllable time and smoothly undertake the grid load adjustment task.

Description

Technical Field

[0001] The present invention relates to the technical field of hydropower generation, and in particular to a method for optimizing the scheduling of a hydropower station based on the health status of a generator set. Background Art

[0002] Hydropower generation is a crucial component of my country's smart grid power generation chain, a prime example of low-carbon, clean, and environmentally friendly power generation. It plays a leading role in the development of renewable energy generation within the smart grid. Hydropower automation technology in my country began in the early 1980s. After more than three decades of development, it has evolved into a comprehensive system encompassing field automation, plant and station computer monitoring, river basin centralized control, hydropower fault diagnosis, automatic water regime monitoring, water regulation automation, and dam engineering safety monitoring. While all these systems are designed to maintain the safe, stable, and efficient operation of hydropower station reservoirs and units, most are independently constructed and interfaced inconsistently. This results in a lack of interaction between systems with similar objectives, hindering data integration and sharing. This leads to redundant operational instructions, duplicate information entry, data redundancy, and memory usage, increasing system operation and maintenance costs while failing to meet the demands of intensive production and operational management at power plants.

[0003] Among the various systems for hydropower operation and management, the water regulation automation system, the monitoring system, the water condition automatic measurement and reporting system, the hydropower fault diagnosis system and the monitoring system have realized data interaction respectively. The water regulation automation system, the hydropower fault diagnosis system and the dam engineering safety monitoring system are still isolated from each other. The water regulation automation system is generally deployed in the hydropower station control center. After receiving the data from the monitoring system and the water condition automatic measurement and reporting system, it completes the optimization calculation and sends it to the monitoring system, which adjusts the output of the unit. The dam engineering safety monitoring and fault diagnosis system will issue an alarm when a problem is found to remind the operation and maintenance personnel to take corresponding measures in time to avoid catastrophic damage to the dam, power station and unit. The monitoring data of these two systems are not associated with the operating conditions of the power station and the unit, and the operating life of the equipment and facilities is increased through reasonable operation. In terms of extending the operating life of hydropower units, people are conducting power generation scheduling. [1,2] Avoid vibration areas [3] , by maintaining the vibration of the unit within an acceptable range to reduce the vibration energy, thereby reducing damage to the unit. However, the structure of the hydropower unit is complex, and failures often manifest as "one effect with multiple causes, one cause with multiple effects, and multiple effects with multiple causes." Considering the vibration of the unit alone is obviously not enough to achieve the optimal scheduling of the hydropower station based on the health status of the unit. The patent of this invention incorporates the operating parameters of the hydropower unit into the evaluation indicators, establishes a health evaluation index system for the operation of the hydropower unit, and combines the operating constraints of the hydropower unit to establish a multi-objective model for the optimal scheduling of the hydropower station based on the health status of the unit. By optimizing the operation plan, the time node when the unit status breaks through the fault limit is delayed and the degree of fault degradation at the node is reduced, so that the unit can maintain a safe and stable operating state within a controllable time. Summary of the Invention

[0004] The purpose of this section is to summarize some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the abstract and title of this application to avoid obscuring the purpose of this section, the abstract and the title of the invention, and such simplifications or omissions should not be used to limit the scope of the present invention.

[0005] In view of the above-mentioned problems existing in the existing hydropower station optimization scheduling method based on the health status of the units, the present invention is proposed.

[0006] Therefore, the object of the present invention is to provide a method for optimizing the scheduling of a hydropower station based on the health status of the units.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions: obtaining hydropower unit data, wherein the hydropower unit data is used to characterize the operation data results and the fault data results;

[0008] Determine a health status system of the hydropower unit according to the fault data, wherein the health status system is used to characterize an operational health index of the hydropower unit;

[0009] The turbine operation data and fault data are brought into the model for optimization calculation to obtain a load distribution plan.

[0010] As a preferred solution of the method for optimizing the scheduling of hydropower stations based on the health status of units described in the present invention, the operating data includes the number of units in the hydropower station, active power limit, active power dead zone value, vibration zone range, unit flow limit, upstream flow, reservoir water level limit, reservoir water level-storage capacity relationship, flow-water level relationship, ecological flow, etc., and the fault data includes fault category, fault mechanism, fault characteristics, and fault handling.

[0011] As a preferred solution of the hydropower station optimization scheduling method based on the health status of the unit described in the present invention, wherein: the health evaluation index system of the hydropower unit operation includes a degradation factor to calculate the degradation degree of each indicator, and the comprehensive degradation degree is used as the overall evaluation index of the health status of the hydropower unit, and a hydropower station operation evaluation model based on the health status of the unit is established;

[0012] Among them, the hydropower station operation evaluation model based on the unit health status is combined with the design of the hydropower station's in-plant economic dispatch model to establish the hydropower station optimization dispatch based on the unit health status, and the turbine operation data and fault data are brought into the model for optimization calculation to obtain the load distribution plan.

[0013] As a preferred embodiment of the hydropower station optimization scheduling method based on the health status of the unit described in the present invention, the multi-dimensional health status assessment of the hydropower station unit equipment parameterizes the abnormal conditions, fault conditions, and performance degradation predictions of the unit status in the form of degradation degrees, and determines the unit operating status in the form of zones A (safe zone), B (warning zone), C (danger zone), and D (prohibited operation zone);

[0014] Among them, the analysis of the failure phenomena of common equipment in each system of hydropower unit shows three aspects:

[0015] The unit shuts down immediately; the unit efficiency decreases; as time goes by, the temperature rise amplitude, amplitude, frequency, etc. become larger, and the unit malfunctions.

[0016] As a preferred solution of the method for optimizing the dispatching of hydropower stations based on the health status of units of the present invention, the unit degradation degree of the optimized control dispatching of hydropower stations based on the evaluation of the health status of units is the health status index G of the unit group:

[0017]

[0018] The parameters in the above formula can all be obtained based on the unit data and will not be described in detail here. Among them, T is the number of control cycles; m is the number of hydropower units; is the start-stop scheduling state of the i-th unit in the power station during the t-th control cycle, Indicates that the i-th unit in a power station is shut down during the t-th control cycle, It indicates that the i-th unit in the power station is operating in the t-th control cycle; is the comprehensive degradation value of the i-th hydropower unit in the power station during the t-th control cycle.

[0019] As a preferred solution of the method for optimizing the scheduling of a hydropower station based on the health status of a unit according to the present invention, wherein: under the data to be verified, the restriction conditions can be obtained according to the operation restrictions of different areas;

[0020] The absolute standard and D-zone limit inspection of the unit status parameters, that is, firstly, it is necessary to check whether the unit status parameters have entered the prohibited operation area. Once the prohibited operation area is entered and cannot be exited in time, the unit will be shut down;

[0021]

[0022] Where S is the set of unit status evaluation parameters, and D is the set of prohibited operation zones for the status parameters. When the unit parameters enter the fault zone, the monitoring system first detects the anomaly and issues a shutdown command;

[0023] The optimized parameters such as temperature rise and vibration are prevented from deteriorating to fault state before the maintenance period.

[0024] f i (S)=∑h i (S)·t≤d f,i (S)

[0025] Among them, f i (S) Optimized unit operation plan, h i (S) is the multi-dimensional state degradation trend evaluation function, d f,i (S) is the fault starting node in the degradation trend evaluation function, and Σ represents the cumulative sum of the running time.

[0026] As a preferred solution of the method for optimizing the scheduling of a hydropower station based on the health status of the unit described in the present invention, the unit operating status characteristic parameters are used to construct a unit status evaluation database, and the unit operation evaluation indicators are parameterized and converted into optimization constraints and optimization objectives for the economic scheduling of the hydropower units to participate in the optimal scheduling and load distribution of the hydropower station.

[0027] As a preferred solution of the method for optimizing the dispatch of a hydropower station based on the health status of a unit according to the present invention, the optimization target is established according to the operation model, wherein the optimization target is to minimize the comprehensive degradation degree. The smaller the comprehensive degradation degree, the better the unit operation state, so that the overall unit state is maintained in a good operation state:

[0028]

[0029] This section models the unit operation constraints from the starting point of the fault state, using the boundary between area C and area D to set the unit operation constraints based on the unit health state.

[0030] As a preferred solution of the method for optimizing the dispatch of a hydropower station based on the health status of a unit according to the present invention, when the status indicator of a unit is in the prohibited operation zone, the unit is immediately shut down and arranged for maintenance;

[0031]

[0032] That is, the set of unit status parameters is outside the prohibited operation area D;

[0033] The units are prioritized according to their efficiency, avoiding or limiting their operation in the vibration zone. This prevents indicators such as temperature, vibration, and water consumption from increasing over time due to adverse operating conditions. Therefore, the number of unit adjustments and operating conditions must be limited to a safe range.

[0034]

[0035] The temperature change trend is that each load operation forms an independent temperature change process, and returns to normal state after shutdown.

[0036] f(S)=T s τ≤d f (S)

[0037] Where T s is the temperature change rate, and τ is the duration of the entire process from startup to shutdown.

[0038] As a preferred solution of the method for optimizing the dispatch of a hydropower station based on the health status of a unit according to the present invention, the operating time and load of the unit are restricted according to the fault occurrence node obtained by the fault prediction module and the maintenance and safe operation requirements of the unit;

[0039] The above constraints can be unified into H ea =[H ea,min ,H ea,max ], H ea,min , H ea,max They respectively represent the available ranges of the hydropower station units in a healthy state.

[0040] The beneficial effects of the present invention are as follows: the present invention can reduce water consumption and the number of abnormal shutdowns and maintenance through calculation models, reduce the start-up and shutdown frequency of unit equipment, extend the average lifespan, optimize normal maintenance and save costs, and improve the comprehensive benefits of the hydropower station; it is the first to construct an optimized control and scheduling of hydropower station units based on the health status of the units, and by optimizing the operation plan, it delays the time node when the unit status breaks through the fault limit and reduces the degree of fault degradation at the node, so that the unit can maintain a safe and stable operating state within a controllable time. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort. Among them:

[0042] Figure 1 1 is a flow chart of an embodiment of a method for optimizing scheduling of a hydropower station based on the health status of units provided by the present invention. DETAILED DESCRIPTION

[0043] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0044] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0045] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0046] Furthermore, the present invention is described in detail with reference to schematic diagrams. For ease of illustration, when describing the embodiments of the present invention, cross-sectional views illustrating device structures may be partially enlarged and not to scale. Furthermore, the schematic diagrams are merely illustrative and should not limit the scope of protection of the present invention. Furthermore, in actual production, the three-dimensional dimensions of length, width, and depth should be included.

[0047] Example 1

[0048] Reference Figure 1 , a method for optimizing the scheduling of a hydropower station based on the health status of the units includes:

[0049] S1. Obtain complete operating characteristic curves and operating data for the turbine operating area. The operating data includes the number of units in the hydropower station, active power limit, active power dead zone value, vibration zone range, unit flow limit, upstream flow, reservoir water level limit, reservoir water level-storage capacity relationship, flow-water level relationship, ecological flow, etc.

[0050] S2. Obtain fault data from the unit fault diagnosis system library, including fault type, fault mechanism, fault characteristics, fault handling, etc.

[0051] The multi-dimensional health status assessment of hydropower station unit equipment parametrically represents abnormal conditions, fault conditions, and performance degradation predictions of the unit status in the form of degradation degrees, and determines the unit's operating status using the zoning format of A (safe zone), B (warning zone), C (danger zone), and D (prohibited operation zone). Analysis of common equipment failure phenomena in various systems of hydropower units shows that the impact of various failures on unit operation can be summarized into three aspects:

[0052] The unit will be shut down immediately. This can be caused by shear pin shearing, hydraulic system failure causing the servomotor to become stuck or loose, resulting in unstable unit output, generator or excitation system failure causing unstable voltage and current, equipment deformation causing collision, and other significantly destructive failures.

[0053] The unit efficiency decreases, which reduces the unit's operating priority. For example, a clogged trash rack or cracked runner blades can cause the unit efficiency to decrease.

[0054] Slow-changing processes such as temperature rise and vibration will not affect the operation of the unit temporarily, but as the operation time increases, they will continue to deteriorate, the temperature rise amplitude, amplitude, frequency, etc. will increase, and failures will occur, eventually leading to shutdown and maintenance. For example, shaft vibration.

[0055] The unit degradation degree of the hydropower station unit optimal control dispatch based on the unit health status evaluation is the unit group health status index G:

[0056]

[0057] Where, T is the number of control cycles; m is the number of hydropower units; is the start-stop scheduling state of the i-th unit in the power station during the t-th control cycle, Indicates that the i-th unit in a power station is shut down during the t-th control cycle, It indicates that the i-th unit in the power station is operating in the t-th control cycle; is the comprehensive degradation value of the i-th hydropower unit in the power station during the t-th control cycle.

[0058] At the same time, according to the operating restrictions of different areas, the unit operating restrictions can be obtained as follows:

[0059] (1) Absolute standard and D zone limit inspection of unit status parameters, that is, first check whether the unit status parameters have entered the prohibited operation area. Once they enter the prohibited operation area and cannot be exited in time, the unit will be shut down.

[0060]

[0061] Where S is the set of unit status assessment parameters, and D is the set of prohibited operation zones for the status parameters. When the unit parameters enter the fault zone, the monitoring system first detects the anomaly and issues a shutdown command.

[0062] (2) To prevent the deterioration of slowly changing state parameters such as temperature rise and vibration from deteriorating to a fault state before the maintenance period, the operating mode of the unit is controlled to delay the time node when the degradation degree exceeds the fault limit and reduce the degradation degree of the fault state at the node, so that the unit can maintain a relatively safe and stable operating state before the maintenance period and can smoothly undertake the power generation task assigned by the grid dispatcher.

[0063] f i (S)=∑h i (S)·t≤d f,i (S)

[0064] Among them, f i(S) is the optimized unit operation plan, hi(S) is the multi-dimensional state degradation trend evaluation function, d f,i (S) is the fault starting node in the degradation trend evaluation function, and Σ represents the cumulative sum of the running time.

[0065] Based on the above analysis, a unit optimization scheduling model based on unit health status assessment should be established. The unit operating status characteristic parameters should be selected to construct a unit status evaluation database, and the unit operation evaluation indicators should be parameterized and converted into optimization constraints and optimization objectives for economic scheduling of hydropower units to participate in the optimal scheduling and load distribution of hydropower stations. While completing the load setting instructions issued by the scheduling department, the entire hydropower station should be kept in a state of minimum energy consumption and the units should be maintained in a good operating state.

[0066] S3. Based on the above basic information, a multi-objective optimization scheduling mathematical model is established, which takes into account hydropower operating conditions such as water balance, unit output, downstream flow, power generation flow, water level control, and the unit health status that affects unit operation (safe zone, warning zone, danger zone, prohibited operation zone) when a unit failure occurs as constraints. A dual-objective optimization model is constructed with the optimization objectives of maximizing the power generation of the hydropower system or minimizing the water consumption and minimizing the comprehensive degradation degree of the health status of the hydropower unit.

[0067] S31. Design of economic dispatch model within hydropower station:

[0068] S311. Optimization goal

[0069] This patent establishes a model with the minimum total water consumption of the power station as the economic optimization goal:

[0070] Minimum water consumption objective function:

[0071] In actual operation, the number of units with load adjustment should be minimized:

[0072]

[0073] Where: W ST is the total water consumption of the hydropower station; the stage variable i is the unit number; the decision variable N (i) is the output of unit i; Q i (N (i)) The output of unit i is N (i) Power generation flow rate at time; X t,i is the power-on status of unit i in the tth period, the power-on status is 1, and the power-off status is 0; S i S is the water loss conversion cost of the start-up and shutdown cost of unit i i =Y iBS +M i / (9.81η diH di p), where Y iBS is the water consumption of the start-up and shutdown of the i-th unit, M t is the maintenance cost and equipment life loss cost caused by the start-up and shutdown of unit i, η di is the design efficiency of unit i, H di is the design head for unit No., P is the average on-grid electricity price of the power station; f is the number of units participating in load regulation.

[0074] S312. Constraints

[0075] Vibration zone constraints:

[0076] Output balance constraint:

[0077] Head constraint: H min <H<H max

[0078] Avoid large-scale transfer constraints of unit output:

[0079]

[0080] Flow constraint: 0≤L(N (i) )≤L max

[0081] Output balance constraint: V t+1 =V t +(I t -G t )ΔT

[0082] Water level control constraint: Z min ≤Z≤Z max

[0083] Quasi-real-time constraint / load regulation threshold: ΔN ≥ K

[0084] Where, After the reward and penalty function is modified, the output of unit i is Power generation flow under The output of unit i before the reward and penalty function is modified is Power generation current consumption under (i) is the output of unit i, MW; are the lower and upper limits of the permissible output of unit i, MW; H is the water head of the hydropower station, m; H min 、H max are the minimum and maximum allowable water heads of the hydropower station, m; is the output command issued by the power grid at time t; is the total output of unit i at time t; is the output of unit i at time t; is the output of unit i after adjustment through the unit linkage mechanism; B is the penalty amount (B = 200 in this paper); c is the coefficient, when the unit output shifts over a large area, c = 1; otherwise, c = 0; is the power generation flow rate of unit i at output before the reward and penalty function is modified; After the reward and penalty function is modified, the output of unit i is Power generation flow under (i) ) is the water flow capacity of a single unit, m 3 / s; L is the maximum water flow capacity of a single turbine, m 3 / s;V t+1 is the storage capacity at the end of the calculation period, m 3 ; V t is the storage capacity at the beginning of the calculation period, m 3 ;I t is the inflow flow during the calculation period, m 3 ; G t is the outbound flow rate during the calculation period, m 3 ; ΔT is the calculation period, s; ​​K is the output change critical value, MW. When the output change ΔN exceeds K, the output distribution between units is adjusted.

[0085] S32. Design of unit operation optimization model based on unit health status assessment:

[0086] S321. Optimization goals

[0087] The optimization goal is to minimize the comprehensive degradation degree. The smaller the comprehensive degradation degree, the better the unit operating state, so that the overall unit state is maintained in a good operating state:

[0088]

[0089] S322. Constraints

[0090] The modeling starts from the fault state and, based on S2, sets the unit operation constraints with the boundary between area C and area D. The following unit operation constraints based on the unit health status are proposed:

[0091] (1) When the status indicator of a unit is in the prohibited operation zone, shut it down immediately and arrange for maintenance;

[0092]

[0093] That is, the set of unit status parameters is outside the prohibited operation area D.

[0094] (2) The units shall determine the operation priority from the highest to the lowest according to their operation efficiency;

[0095] (3) Avoid or limit the operation of the unit in the vibration zone;

[0096] (4) To prevent the temperature, vibration, water consumption rate and other indicators from increasing with the duration of operation under severe working conditions, the number of unit adjustments and operating conditions must be limited to a safe range; for example, faults and abnormalities that continue to evolve and expand due to vibrations will continue to evolve over time until they expand into faults before they are repaired and handled.

[0097] f i (S)=∑h i (S)·t≤d f,i (S)

[0098] The temperature change trend is that each load operation forms an independent temperature change process, and returns to normal state after shutdown.

[0099] (5) Based on the fault occurrence node obtained by the fault prediction module, the unit operation time and load size should be limited according to the unit maintenance and safe operation needs.

[0100] The above constraints can be unified into H ea =[H ea,min ,H ea,max ], H ea,min , H ea,max They respectively represent the available ranges of the hydropower station units in a healthy state.

[0101] S33. Establish a multi-objective optimization scheduling model for hydropower stations based on the health status of the units:

[0102] S331. Obtain basic information data of the power station and reservoir. The basic information data includes: the normal water level Z of the reservoir; 正 , flood control limit water level Z 防 , dead water level Z 死 , Reservoir capacity-water level relationship curve S~Z, Reservoir downstream water level-discharge flow relationship curve Z~Q, Reservoir generator unit output constraint value N, Unit health status constraint value H ea , reservoir discharge flow constraint value u, reservoir generator set flow capacity value q, reservoir water inflow W.

[0103] S332. Based on the basic information data, a multi-objective optimization scheduling mathematical model is established that takes into account the water balance, unit output, downstream flow and power generation flow and unit health status constraints, wherein the objective function is an objective function established with the minimum water consumption and the optimal unit status under the target power generation.

[0104] Wherein, the multi-objective optimization scheduling mathematical model is:

[0105] minF(x)={f1(x),f2(x),f3(x)}

[0106]

[0107] Where n represents the target number of power station optimization scheduling, n = 1, 2, 3; F(x) represents the target function set; f n (x) represents the objective function established with the minimum water consumption under power generation, the minimum number of units under load regulation, and the units in a healthy state.

[0108] S4. Based on the fault data and turbine operation data, the fault diagnosis system is used to analyze the unit fault evolution trend and the time node of the fault occurrence under different working conditions. With the maintenance time as the limit, the interpolation method is used to obtain the lower limit value of the fault evaluation index that should be maintained at the end of each operation cycle.

[0109] S5. Use the multi-objective hybrid frog leaping difference algorithm to solve the Pareto optimal solution of the multi-objective optimization scheduling mathematical model in S33 and design the solution process.

[0110] S51. Initialize data.

[0111] S511. Read the load plan curve issued by the dispatch center, the power plant reservoir parameters, unit parameters, unit operating characteristic curve and vibration zone data, the unit typical operating condition fault evolution trend, the time point of the fault occurrence, etc.;

[0112] S512. For some operating points near typical operating conditions, the spatial interpolation method is used, with parameters such as head, flow, and output as independent variables, and the fault evolution trend and the time node of the fault occurrence as dependent variables, to interpolate the fault evolution trend and the time node of the fault occurrence of the corresponding operating point.

[0113] S513. Divide the hydropower station scheduling cycle into time periods, select the power generation in each time period as a decision variable, and determine the upper and lower limits of the output allowed by the unit in each time period.

[0114] S52. Set calculation parameters.

[0115] S521. Determine the number of variables, the initial population size, the number of subpopulations, the number of individuals in each subpopulation, the number of global iterations, the crossover probability, the mutation probability, the number of subpopulation iterations, and the number of external archive sets.

[0116] S522. Based on the chaos theory in the literature [5], the initial population is generated according to the output range of each unit, the objective function value of each individual in the population is calculated and sorted, and when the objective function decision variable does not meet the constraint conditions, its fitness value is set to a data close to zero and less than the preset threshold, so that the output decision variable meets the constraint conditions.

[0117] S53. Mix all populations together, sort all individuals according to fitness values, divide sub-populations according to the sorting, and identify the optimal and worst solutions in each population.

[0118] S54. Based on the adaptive difference algorithm, use crossover calculation to update the worst solution in each group:

[0119] Cross calculation: Where N i,t With N j,t is the tth element in the i-th and j-th individuals in the population, i≠j, x 1,t with x 2,t are the new elements generated by cross calculation, β t is a random variable that is not less than 0.

[0120] S55. Mix the newly generated elements with individuals in all populations. When the number of individuals in the population is greater than the set value, dynamic crowding calculation is used to remove individuals with a smaller crowding distance to maintain the uniformity of population distribution and the total number of individuals. The crowding distance calculation formula is used.

[0121] S56. Sort the individuals in each updated subpopulation by fitness value, regenerate the subpopulation, and identify the optimal solution and the worst solution in the population.

[0122] S57. Determine whether the predetermined number of global iterations has been reached. If not, jump to S54. Otherwise, output the optimal solution set.

[0123] S58. According to the number of optimization targets, a relative superiority matrix is ​​established and the optimal dispatching scheme of the hydropower station is determined by adopting a multi-objective decision-making method. ea The index characteristic matrix of the solution is

[0124]

[0125] The relative superiority matrix based on characteristic index is:

[0126]

[0127] Assume that the optimal relative superiority is g1 = (1, 1, ..., 1) T , the worst relative goodness is g2=(0,0,…,0)T , g1 and g2 contain N ea elements;

[0128] S52. Assign weights w1, w2, and w3 to the three optimization sub-goals, w1+w2+w3=1, and calculate the relative membership according to the formula Calculate the relative membership u of each solution j =(j=1,2,…,N ea ), take u j The one with the largest value is the optimal scheduling solution for the hydropower station.

[0129] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for optimizing the scheduling of a hydropower station based on the health status of a generating unit, characterized by: include, Acquiring hydropower unit data, wherein the hydropower unit data is used to represent operation data results and fault data results; Determine a health status system of the hydropower unit based on the fault data, wherein the health status system includes an operational health indicator of the hydropower unit; Bringing the operation data results and fault data into the operation model for optimization calculation to obtain a load distribution plan; The health evaluation index system for the operation of the hydropower unit introduces a degradation factor to calculate the degradation degree of each indicator, uses the comprehensive degradation degree as the overall evaluation index of the health status of the hydropower unit, and establishes a hydropower station operation evaluation model based on the health status of the unit; The hydropower station operation evaluation model based on the health status of the unit is combined with the design of the in-plant economic dispatch model of the hydropower station to establish the optimal dispatch of the hydropower station based on the health status of the unit. The operation data and fault data of the hydropower unit are brought into the model for optimization calculation to obtain the load distribution plan; Based on the multi-dimensional health status assessment results obtained from the hydropower unit equipment, the abnormal conditions, fault conditions, and performance degradation predictions of the unit status are parameterized in the form of degradation degree, and the unit operating status is judged in the form of zoning into safe zone A, warning zone B, danger zone C, and prohibited operation zone D; Among them, the analysis of the failure phenomena of common equipment in each system of hydropower unit shows three aspects: The unit shuts down immediately; the unit efficiency decreases; as time goes on, the temperature rise amplitude, amplitude, and frequency increase, and the unit malfunctions; The optimized slow-changing state parameters that prevent temperature rise and vibration will be degraded to a fault state before the maintenance period. f i (S)=∑h i (S)·t≤d f,i (S) Among them, f i (S) is the optimized unit operation plan, h i (S) is the multi-dimensional state degradation trend evaluation function, d f,i (S) is the fault starting node in the degradation trend evaluation function, Σ represents the cumulative sum of the running time, and t is the time starting from the fault starting node.

2. The method for optimizing the scheduling of a hydropower station based on the health status of a generating unit according to claim 1, characterized in that: The operating data includes the number of units in the hydropower station, active power limit, active power dead zone value, vibration zone range, unit flow limit, upstream flow, reservoir water level limit, reservoir water level-storage capacity relationship, flow-water level relationship, and ecological flow; the fault data includes fault type, fault mechanism, fault characteristics, and fault handling.

3. The method for optimizing the dispatch of a hydropower station based on the health status of a generating unit according to claim 1, characterized in that: According to the unit degradation degree of the hydropower station unit optimal control dispatch based on the unit health status assessment, the unit group health status index G is: Wherein, T is the number of control cycles; m is the number of hydropower units; is the start-stop scheduling state of the i-th unit in the power station during the t-th control cycle, Indicates that the i-th unit in a power station is shut down during the t-th control cycle, It indicates that the i-th unit in the power station is operating in the t-th control cycle; is the comprehensive degradation value of the i-th hydropower unit in the power station during the t-th control cycle.

4. The method for optimizing the scheduling of a hydropower station based on the health status of a generating unit according to claim 1 or 2, characterized in that: Under the data to be verified, the restriction conditions are obtained according to the operation restrictions of different areas; The absolute standard and D-zone limit inspection of the unit status parameters, that is, firstly, it is necessary to check whether the unit status parameters have entered the prohibited operation area. Once the prohibited operation area is entered and cannot be exited in time, the unit will be shut down; Among them, S is the set of unit status evaluation parameters, and D is the set of prohibited operation zones of status parameters. When the unit parameters enter the fault zone, the monitoring system first detects the abnormality and issues a shutdown command.

5. The method for optimizing the dispatch of a hydropower station based on the health status of a generating unit according to claim 4, characterized in that: A unit status evaluation database is constructed based on the unit operating status parameters, and the unit operation evaluation indicators are parameterized and converted into hydropower unit economic dispatch optimization constraints and optimization objectives to participate in the optimal dispatch and load distribution of the hydropower station.

6. The method for optimizing the dispatch of a hydropower station based on the health status of a generating unit according to claim 5, characterized in that: The optimization target is established based on the operation model, where the minimum comprehensive degradation degree is the optimization target. The smaller the comprehensive degradation degree, the better the unit operation status: The modeling starts from the fault state and sets the unit operation constraints based on the boundary between area C and area D, which is the unit operation constraints of the hydropower station based on the unit health state.

7. The method for optimizing the dispatch of a hydropower station based on the health status of a generating unit according to claim 6, characterized in that: When the unit status indicators are in the prohibited operation zone, shut down the unit immediately and arrange for maintenance; That is, the set of unit status parameters is outside the prohibited operation area D; The units are prioritized according to their efficiency, avoiding or limiting operation in the vibration zone. This prevents the temperature, vibration, and water consumption rates from increasing with time under harsh operating conditions. Therefore, the number of unit adjustments and operating conditions must be limited to a safe range. The temperature change trend is that each load operation forms an independent temperature change process, and returns to normal state after shutdown.

8. The method for optimizing the dispatch of a hydropower station based on the health status of a generating unit according to claim 7, characterized in that: Based on the fault occurrence node obtained by the fault prediction module, the unit operation time and load size should be limited according to the unit maintenance and safe operation needs; Operation constraints of hydropower station units based on the health status of the units: (1) When the status indicator of a unit is in the prohibited operation zone, shut it down immediately and arrange for maintenance; That is, the set of unit status parameters is outside the prohibited operation area D; (2) The units shall determine the operation priority from the highest to the lowest according to their operation efficiency; (3) Avoid or limit the operation of the unit in the vibration zone; (4) To prevent the temperature, vibration and water consumption rate from increasing with the duration of operation under severe working conditions, the number of unit adjustments and operating conditions must be limited to a safe range; Faults and anomalies that evolve and expand from vibrations continue to evolve over time before they are repaired and addressed, until they expand into faults: f i (S)=∑h i (S)·t≤d f,i (S) The temperature change trend is that each load operation forms an independent temperature change process, and returns to normal state after shutdown; (5) Based on the fault occurrence node obtained by the fault prediction module, the unit operation time and load size should be limited according to the unit maintenance and safe operation needs; The above constraints are unified into H ea =[H ea,min ,H ea,max ], H ea,min , H ea,max They respectively represent the available ranges of the hydropower station units in a healthy state.

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