A multi-station collaborative monitoring system and method for a hydropower station with intelligent remote control

Abstract

The present invention relates to the field of intelligent monitoring technology, and specifically, to an intelligent remote-controlled multi-station collaborative monitoring system and method for hydropower stations. It includes: a collection and transmission unit, which is used to collect data from hydropower stations in real time; a monitoring management unit is used to receive and process data from each hydropower station transmitted by the collection and transmission unit; an optimization scheduling unit establishes a power generation scheduling optimization model, a reservoir scheduling optimization model and an environmental impact minimization model, generates an optimization scheduling plan based on the solution of the model, converts the optimization scheduling plan into a control instruction and sends the instruction to a remote control unit; the remote control unit is used to send the received control instruction to each hydropower station. The intelligent remote-controlled multi-station collaborative monitoring system and method for hydropower stations can more accurately predict the power generation capacity under different temperature conditions, formulate a more reasonable power generation plan, and can more accurately predict the water level change of the reservoir to ensure that the water level is within a safe range.

Description

Technical Field

[0001] The present invention relates to the field of intelligent monitoring technology, and in particular to an intelligent remote-controlled multi-station collaborative monitoring system and method for a hydropower station. Background Art

[0002] With the development of science and technology and the application of intelligent technology, the intelligent remote-controlled multi-station collaborative monitoring system of hydropower stations came into being. This system integrates advanced communication technology, computer network technology and automatic control technology to achieve real-time, efficient and safe remote monitoring and management of multiple hydropower stations distributed in a wide geographical area. It can not only collect the operating data of each hydropower station in real time, such as key indicators such as power generation, water level, flow, etc., but also automatically adjust the operating status of the power station based on these data, optimize power generation efficiency, and ensure the stability of the power grid. At the same time, it greatly reduces the cost and risk of manual inspections, improves the speed and accuracy of emergency response, and is an important part of modern hydropower energy management.

[0003] However, in the prior art, the impact of temperature on power generation capacity is not considered in power generation prediction and water level management, resulting in inaccurate prediction results. At the same time, the impact of temperature on evaporation rate is not considered, resulting in inaccurate water level prediction, and the water level is prone to being too high or too low. Therefore, an intelligent remote-controlled hydropower station multi-station collaborative monitoring system and method are provided. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent remote-controlled hydropower station multi-station collaborative monitoring system and method to solve the problem proposed in the above background technology that the influence of temperature on power generation capacity is not taken into account, resulting in inaccurate prediction results, and the influence of temperature on evaporation rate is not taken into account, resulting in inaccurate water level prediction and prone to water level being too high or too low.

[0005] To achieve the above objectives, on the one hand, the present invention aims to provide a multi-station coordinated monitoring system for a hydropower station with intelligent remote control, comprising:

[0006] A collection and transmission unit, which is used to collect data of the hydropower station in real time and transmit the collected data to the monitoring and management unit;

[0007] A monitoring management unit, which is used to receive and process the data of each hydropower station transmitted by the collection and transmission unit, display the operation data and key indicators of each hydropower station in real time, and automatically monitor abnormal conditions. When an abnormality occurs, an alarm message is generated and the staff is notified; wherein the monitoring management unit includes a data processing module, a data storage module, a data display module and an abnormal alarm module;

[0008] An optimization dispatching unit, wherein the optimization dispatching unit establishes a power generation dispatching optimization model, a reservoir dispatching optimization model and an environmental impact minimization model based on the historical data of the power station and the data of the power station monitored in real time, and at the same time, introduces the influence of temperature into the power generation dispatching optimization model for optimization, and introduces the influence of upstream water, downstream demand and water supply demand into the reservoir dispatching optimization model for optimization, generates an optimization dispatching plan according to the solutions of the power generation dispatching optimization model, the reservoir dispatching optimization model and the environmental impact minimization model, converts the optimization dispatching plan into a control instruction and sends the instruction to a remote control unit;

[0009] A remote control unit is used to send received control instructions to each hydropower station and feed back the control effect of the hydropower station to the optimization scheduling unit.

[0010] As a further improvement of the present technical solution, the data of the hydropower station in the acquisition and transmission unit includes at least power generation, flow, water quality, temperature, upstream water, downstream demand, reservoir water level and unit operation status.

[0011] As a further improvement of the technical solution, in the monitoring management unit:

[0012] The data processing module is used to clean and standardize the data received from each hydropower station, package the data of each power station together to form different first data sets, and then assign the same label to the data from the same data source, and package the data with the same label together to form different second data sets;

[0013] The data storage module includes a first storage submodule and a second storage submodule, wherein the first storage submodule is used to store a first data set, and the second storage submodule is used to store a second data set;

[0014] The data display module is used to display and update the real-time data of each hydropower station in real time;

[0015] The abnormal alarm module is used to compare the real-time data with the pre-set threshold and issue an alarm if the threshold is exceeded.

[0016] As a further improvement of the present technical solution, the data storage module also includes a historical storage submodule, which is used to store historical data of the power plant. The data in the first storage submodule and the second storage submodule will be automatically transmitted to the historical storage submodule after reaching a preset time period; the historical storage submodule is also provided with space for storing the first data set and the second data set.

[0017] As a further improvement of the technical solution, the reservoir scheduling optimization model established in the optimization scheduling unit is specifically as follows:

[0018] Objective function:

[0019]

[0020] Where A is the objective function of the reservoir operation optimization model; T is the total number of time periods; NNN is the number of hydropower stations; t = 1, 2, ..., T; i = 1, 2, ..., N; V i，t is the reservoir water level of the i-th hydropower station in the t-th period; V i，target (S t ) is the target water level of the ith hydropower station after considering seasonal effects; S t is the seasonal factor; α and β are weight coefficients; Q out，i，t is the outflow of the i-th hydropower station in the t-th period; Q target，i，t (S t ) is the target outflow of the i-th hydropower station after considering seasonal effects;

[0021] Reservoir water level constraints:

[0022]

[0023]

[0024] Among them, V i，t+1 is the reservoir water level of the i-th hydropower station in the t+1 period; Q in，i，t is the inflow of the i-th hydropower station in the t-th period; V i，min is the minimum allowable water level of the ith hydropower station; V i，max is the maximum allowable water level of the i-th hydropower station;

[0025] Outbound traffic constraints:

[0026]

[0027] Q max，i (R i，t )=Q i，base +d i ·R i，t ;

[0028] Among them, Q max，i (R i，t ) is the maximum allowable outflow of the i-th hydropower station in the t-th period considering the influence of precipitation; R i，t is the precipitation of the ith hydropower station in the tth period; Q i，base is the maximum allowable outflow flow of the i-th hydropower station; d i It is the coefficient that represents the influence of precipitation on the maximum allowable outflow flow.

[0029] As a further improvement of the technical solution, the optimization scheduling unit introduces the influence of upstream water, downstream demand and water supply demand into the reservoir scheduling optimization model for optimization. After optimization, the specific results are as follows:

[0030]

[0031] Among them, A′ is the objective function of the optimized reservoir operation optimization model; ε is the weight coefficient related to the water supply deviation; Q supply，i，t is the actual water supply of the i-th hydropower station in the t-th period; Q demand，i，t is the water supply demand of the i-th hydropower station in the t-th period;

[0032] The newly added constraints include meeting downstream demand and water supply constraints, specifically:

[0033] Meeting downstream needs:

[0034]

[0035] Among them, Q demand，i，t is the downstream demand of the i-th hydropower station in the t-th period;

[0036] Water supply constraints:

[0037]

[0038]

[0039] Among them, Q supply，i，t is the actual water supply of the i-th hydropower station in the t-th period.

[0040] As a further improvement of the technical solution, the power generation scheduling optimization model established in the optimization scheduling unit is specifically as follows:

[0041] Objective function:

[0042]

[0043] Where B is the objective function of the power generation dispatch optimization model; P i，t is the power generation of the ith hydropower station in the tth period;

[0044] Power demand constraints:

[0045]

[0046] Among them, D t is the power demand in period t;

[0047] Power generation capacity constraints:

[0048]

[0049] P i，max (R i，t )=P i，base +c·Q in，i，t ;

[0050] Q in，i，t =Q upstream，i，t +k i ·R i，t ;

[0051] Among them, P i，max (R i，t ) is the maximum power generation capacity of the ith hydropower station after considering the influence of precipitation; P i，base is the basic power generation capacity of the i-th hydropower station; c is the coefficient representing the influence of the inflow on the power generation capacity; Q upstream，i，t is the upstream water flow of the i-th hydropower station in the t-th period; k i is the conversion coefficient from precipitation to inflow;

[0052] Unit startup or shutdown constraints:

[0053]

[0054]

[0055]

[0056]

[0057] Among them, U i，t is the unit operation status of the i-th hydropower station in the t-th period; U i，t-1 is the operating status of the unit of the i-th hydropower station in the t-1 period; S i，t is the unit startup status of the i-th hydropower station in the t-th period;

[0058] The power generation scheduling optimization model is also constrained by the reservoir water level.

[0059] As a further improvement of the technical solution, the optimization scheduling unit introduces the influence of air temperature into the power generation scheduling optimization model for optimization, and the optimization is as follows:

[0060] The optimized power generation capacity constraint is:

[0061]

[0062] P i，max (R i，t , T t )=P i，base +c·Q in，i，t -e i·T t ;

[0063] Among them, P i,max (R i，t , T t ) is the maximum power generation capacity of the ith hydropower station after considering the influence of precipitation and temperature; T t is the temperature during period t; e i is the influence coefficient of temperature on power generation capacity;

[0064] The optimized reservoir water level constraint is:

[0065]

[0066]

[0067] Among them, V i,t+1 ′ is the optimized reservoir water level of the ith hydropower station in the t+1th period; E i，t (T t ) is the evaporation rate of the ith hydropower station in the tth period.

[0068] As a further improvement of the technical solution, the environmental impact minimization model established in the optimization scheduling unit is specifically as follows:

[0069] Objective function:

[0070]

[0071] Among them, C is the objective function of the environmental impact minimization model; Q ecological，i，t is the ecological flow of the ith hydropower station in the tth period; Q ecological，i，min (S t ) is the minimum ecological flow requirement of the ith hydropower station after considering seasonal effects; γ and δ are weight coefficients; W i,t is the water quality parameter of the ith hydropower station in the tth period; W i,target (S t ) is the water quality target value of the i-th hydropower station after considering seasonal effects;

[0072] Ecological flow constraints:

[0073]

[0074] Water quality constraints:

[0075]

[0076] Among them, W i,min (S t ) is the minimum allowable water quality parameter value of the i-th hydropower station; W i,max (S t) is the maximum allowable water quality parameter value of the ith hydropower station.

[0077] On the other hand, the present invention provides a method for cooperative monitoring of multiple stations of a hydropower station by intelligent remote control, based on the above-mentioned cooperative monitoring system of multiple stations of a hydropower station by intelligent remote control, comprising the following steps:

[0078] S1, the collection and transmission unit collects data of the hydropower station in real time and transmits the collected data to the monitoring and management unit;

[0079] S2, the monitoring management unit receives and processes the data of each hydropower station transmitted by the collection and transmission unit, displays the operation data and key indicators of each hydropower station in real time, and automatically monitors abnormal conditions. When an abnormality occurs, an alarm message is generated and the staff is notified;

[0080] S3, the optimization dispatching unit establishes a power generation dispatching optimization model, a reservoir dispatching optimization model and an environmental impact minimization model based on the historical data of the power station and the data of the power station monitored in real time, generates an optimization dispatching plan according to the solutions of the power generation dispatching optimization model, the reservoir dispatching optimization model and the environmental impact minimization model, converts the optimization dispatching plan into a control instruction and sends the instruction to the remote control unit;

[0081] S4. The remote control unit sends the received control instructions to each hydropower station.

[0082] Compared with the prior art, the present invention has the following beneficial effects:

[0083] 1. In the intelligent remote-controlled hydropower station multi-station collaborative monitoring system and method, by comprehensively considering upstream water, downstream demand and water supply demand, the optimized model can dispatch water resources more accurately, reduce waste, improve the utilization efficiency of water resources, make the dispatching plan more flexible, adapt to demand changes in different environments, and improve the ability to respond to emergencies;

[0084] 2. In the intelligent remote-controlled hydropower station multi-station collaborative monitoring system and method, the influence coefficient of temperature on power generation capacity is introduced, which can more accurately predict the power generation capacity under different temperature conditions and formulate a more reasonable power generation plan; the influence of temperature on evaporation rate is introduced, which can more accurately predict the water level changes of the reservoir and ensure that the water level is within a safe range. BRIEF DESCRIPTION OF THE DRAWINGS

[0085] Figure 1 It is the overall flow chart of the present invention;

[0086] Figure 2 A flow chart of the overall method of the present invention;

[0087] The meaning of each number in the figure is:

[0088] 1. Data collection and transmission unit; 2. Monitoring and management unit; 3. Optimization and scheduling unit; 4. Remote control unit. DETAILED DESCRIPTION

[0089] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0090] Embodiment 1:

[0091] See also Figure 1 As shown, a multi-station cooperative monitoring system for a hydropower station with intelligent remote control is provided, comprising a collection and transmission unit 1, a monitoring and management unit 2, an optimization and scheduling unit 3 and a remote control unit 4;

[0092] The data of the hydropower station includes at least power generation, flow, water quality, temperature, upstream water, downstream demand, reservoir water level and unit operation status;

[0093] First, by installing online monitoring equipment, such as flow meters, water quality analyzers, etc., at key locations in each hydropower station, real-time and accurate monitoring of the operating status of the hydropower station can be achieved, which not only helps to promptly detect equipment failures or abnormal conditions and take measures in advance to avoid potential safety hazards, but also ensures the efficient and stable operation of the hydropower station and improves power generation efficiency. Secondly, the collection and transmission of real-time data to the monitoring management unit 2 realizes a high degree of information integration and sharing, which is conducive to managers to conduct remote monitoring and decision support, greatly improving management efficiency and response speed. Furthermore, the application of this system can also help optimize the scheduling and utilization of water resources. Through coordinated control among multiple hydropower stations, water resources can be reasonably allocated to meet the electricity demand in different time periods and promote the effective use of energy. Finally, this intelligent monitoring method can also reduce the frequency and intensity of manual inspections, reduce operation and maintenance costs, and at the same time reduce the workload of staff and improve work safety.

[0094] The monitoring management unit 2 is used to receive and process the data of each hydropower station transmitted by the collection and transmission unit 1, display the operation data and key indicators of each hydropower station in real time, and automatically monitor abnormal conditions. When an abnormality occurs, an alarm message is generated and the staff is notified; wherein the monitoring management unit 2 includes a data processing module, a data storage module, a data display module and an abnormal alarm module;

[0095] In monitoring management unit 2,

[0096] The data processing module is used to clean and standardize the data received from each hydropower station, package the data of each power station together to form different first data sets, and then assign the same label to the data from the same data source, and package the data with the same label together to form different second data sets; the data from different hydropower stations are packaged and processed according to the source and type to form an orderly first data set and second data set, which is convenient for subsequent analysis and application. This data organization method not only simplifies the data management process, but also improves the efficiency of data retrieval and use;

[0097] The data storage module includes a first storage submodule and a second storage submodule, wherein the first storage submodule is used to store a first data set, and the second storage submodule is used to store a second data set; this hierarchical storage strategy helps to achieve efficient management and fast access to data, and also facilitates in-depth analysis of specific types of data;

[0098] The data storage module also includes a historical storage submodule, which is used to store historical data of the power station. The data in the first storage submodule and the second storage submodule will be automatically transmitted to the historical storage submodule after reaching a preset time period; the historical storage submodule is also provided with a space for storing the first data set and the second data set;

[0099] Setting up a special historical storage submodule to store the historical data of the power station is helpful for tracking the operation trend of the hydropower station in the long term, which is extremely important for fault diagnosis, performance evaluation and future planning. In addition, when the data in the first storage submodule and the second storage submodule reaches the preset time period, it is automatically migrated to the historical storage submodule, which not only saves the storage space required for the current operation, but also ensures the integrity and traceability of the historical data;

[0100] The data display module is used to display and update the real-time data of each hydropower station in real time; it helps managers quickly understand the real-time status of the power station and make timely and effective decisions. The good interface design and interactive experience enable people with non-technical backgrounds to easily master system operations and improve work efficiency;

[0101] The abnormal alarm module is used to compare real-time data with its pre-set threshold and issue an alarm when the threshold is exceeded; by discovering and solving potential problems in advance, the downtime and economic losses caused by failures can be minimized.

[0102] The optimization dispatching unit 3 establishes a power generation dispatching optimization model, a reservoir dispatching optimization model and an environmental impact minimization model based on the historical data of the power station and the data of the power station monitored in real time. At the same time, the temperature influence is introduced into the power generation dispatching optimization model for optimization, and the influence of upstream water, downstream demand and water supply demand is introduced into the reservoir dispatching optimization model for optimization. The power generation dispatching optimization is to optimize the power generation plan of each hydropower station on the premise of meeting the power demand and improve the overall power generation efficiency; the reservoir dispatching optimization can reasonably adjust the reservoir water level and balance the power generation and flood control needs; the environmental impact minimization takes into account factors such as ecological flow and water quality to reduce the negative impact on the environment. By simulating the optimal operation strategy under different scenarios, it guides each hydropower station to minimize the impact on the environment while meeting the power generation demand. According to the solutions of the power generation dispatching optimization model, the reservoir dispatching optimization model and the environmental impact minimization model, an optimization dispatching plan is generated, and the optimization dispatching plan is converted into a control instruction and the instruction is sent to the remote control unit 4;

[0103] The reservoir operation optimization model established in the optimization operation unit 3 is as follows:

[0104] Objective function:

[0105]

[0106] Where A is the objective function of the reservoir operation optimization model; T is the total number of time periods; N is the number of hydropower stations; t = 1, 2, ..., T; i = 1, 2, ..., N; V i，t is the reservoir water level of the i-th hydropower station in the t-th period; V i，target (S t ) is the target water level of the ith hydropower station after considering seasonal effects; S t is a seasonal factor, which is a coefficient reflecting seasonal changes; α and β are weight coefficients used to balance water level and outflow; Q out，i，t is the outflow of the i-th hydropower station in the t-th period; Q target，i，t (S t ) is the target outflow of the i-th hydropower station after considering seasonal effects;

[0107] The objective function aims to minimize the sum of squares of the deviations between the reservoir water level and the target water level and between the outflow and the target outflow of all hydropower stations. By adjusting the two weight coefficients α and β, a suitable balance can be found between water level control and flow regulation.

[0108] Reservoir water level constraints:

[0109]

[0110]

[0111] Among them, V i，t+1 is the reservoir water level of the i-th hydropower station in the t+1 period; Q in，i，t is the inflow of the i-th hydropower station in the t-th period; V i，min is the minimum allowable water level of the ith hydropower station; V i，max is the maximum allowable water level of the i-th hydropower station;

[0112] The upper and lower limits of the water level in each hydropower station’s reservoir are set to ensure that the reservoir water level remains within a safe and reasonable range to prevent problems caused by too low or too high water levels;

[0113] Outbound traffic constraints:

[0114]

[0115] The range of outflow from each hydropower station is specified to ensure that it does not exceed the maximum allowable value and is also greater than or equal to zero to prevent illegal operations;

[0116] Q max，i (R i，t )=Q i，base +d i ·R i，t ;

[0117] Among them, Q max，i (R i，t ) is the maximum allowable outflow of the i-th hydropower station in the t-th period considering the influence of precipitation; R i，t is the precipitation of the ith hydropower station in the tth period; Q i，base is the maximum allowable outflow flow of the i-th hydropower station; d i is the coefficient that represents the influence of precipitation on the maximum allowable outflow;

[0118] The above formula can effectively realize the coordinated scheduling of multiple hydropower stations. It not only takes into account the dynamic balance of water level and flow, but also combines the influence of seasonal and weather factors, thereby ensuring that the hydropower station group achieves maximum economic benefits while meeting safety, environmental protection and other requirements.

[0119] The influence of upstream water inflow, downstream demand and water supply demand is introduced into the reservoir operation optimization model for optimization. The optimization results are as follows:

[0120]

[0121] Among them, A′ is the objective function of the optimized reservoir operation optimization model; ε is the weight coefficient related to the water supply deviation; Q supply，i，t is the actual water supply of the i-th hydropower station in the t-th period; Q demand，i，tis the water supply demand of the i-th hydropower station in the t-th period; by minimizing the deviation between water supply and demand, it can ensure that the water demand of users is better met, improve the utilization rate of water resources and social satisfaction;

[0122] The newly added constraints include meeting downstream demand and water supply constraints, specifically:

[0123] Meeting downstream needs:

[0124]

[0125] Among them, Q demand，i，t is the downstream demand of the i-th hydropower station in the t-th period; ensuring that the outflow of each hydropower station in each period is not less than the downstream demand. This constraint is crucial to maintaining the ecological balance of the river and meeting the water demand of downstream users such as agricultural irrigation and urban water supply;

[0126] Water supply constraints:

[0127]

[0128] It is stipulated that the actual water supply must be equal to the outflow flow, ensuring the accuracy and reliability of the water supply;

[0129]

[0130] Among them, Q supply，i，t is the actual water supply of the i-th hydropower station in the t-th period;

[0131] It is emphasized again that the actual water supply must meet or exceed the water supply demand in order to ensure that the needs of users are fully met and to avoid social problems caused by insufficient water supply;

[0132] By comprehensively considering upstream water, downstream demand and water supply demand, the optimized model can dispatch water resources more accurately, reduce waste, improve water resource utilization efficiency, introduce more variables and constraints, make the dispatch plan more flexible, adapt to demand changes in different environments, and improve the ability to respond to emergencies;

[0133] The power generation scheduling optimization model established in the optimization scheduling unit 3 is as follows:

[0134] Objective function, maximize total power generation:

[0135]

[0136] Where B is the objective function of the power generation dispatch optimization model; P i，t is the power generation of the ith hydropower station in the tth period;

[0137] Power demand constraints:

[0138]

[0139] Among them, D t is the power demand in the tth period; ensure that in each period, the total power generation of all hydropower stations is not less than the power demand D in that period t , ensuring the stability and reliability of power supply;

[0140] Power generation capacity constraints:

[0141]

[0142] Ensure that the power generation of each hydropower station in each period does not exceed its maximum power generation capacity P i，max (R i，t ), and the power generation cannot be negative;

[0143] P i，max (R i，t )=P i，base +c·Q in，i，t ;

[0144] Q in，i，t =Q upstream，i，t +k i ·R i，t ;

[0145] Among them, P i，max (R i，t ) is the maximum power generation capacity of the ith hydropower station after considering the influence of precipitation; P i，base is the basic power generation capacity of the i-th hydropower station; c is the coefficient representing the influence of the inflow on the power generation capacity; Q upstream，i，t is the upstream water flow of the i-th hydropower station in the t-th period; k i It is the conversion coefficient from precipitation to inflow, reflecting the hydrological characteristics of the basin;

[0146] The power generation capacity constraint limits the power generation of each hydropower station to no more than its maximum power generation capacity in each time period;

[0147] Unit startup or shutdown constraints:

[0148]

[0149] Ensure power generation P i，t Only when the unit is running (i.e. U i，t =1) can be generated and does not exceed the maximum power generation capacity;

[0150]

[0151] If the unit operating status U of the i-th hydropower station in the t-th period i，t is 1, then it has either run U in the previous period i，t-1 =1, either start S in this period i，t =1;

[0152]

[0153] If the unit operating status U of the i-th hydropower station in the t-th period i，t is 0, then it has either been shut down in the previous period i，t-1 =0, or shut down the machine during this period S i，t =1;

[0154]

[0155] Among them, U i，t is the operating status of the unit in the tth period of the i-th hydropower station (1 means operation, 0 means shutdown); U i，t-1 is the operating status of the unit of the i-th hydropower station in the t-1 period; S i，t is the startup status of the unit in the tth period of the i-th hydropower station (1 means startup, 0 means not startup);

[0156] Unit startup or shutdown constraints ensure that the startup and shutdown operations of the unit are in line with the actual situation, avoiding additional costs and wear caused by frequent startup and shutdown;

[0157] The generation dispatch optimization model is also constrained by the reservoir water level;

[0158] By optimizing the objective function, we ensure that the total power generation is maximized while meeting all constraints. The power demand constraint ensures that the total power generation in each time period is not less than the power demand, ensuring the stability and reliability of power supply. The power generation capacity constraint ensures that the power generation of each hydropower station in each time period does not exceed its maximum power generation capacity, while taking into account the impact of upstream water and precipitation. The unit start-up or shutdown constraint ensures that the start-up and shutdown operations of the unit are in line with the actual situation, avoiding the additional costs and wear caused by frequent start-ups and shutdowns. It can more comprehensively consider various factors in actual operation, improve the scientificity and practicality of the scheduling plan, and ensure that the hydropower station group maximizes economic benefits while meeting power demand.

[0159] The temperature effect is introduced into the power generation dispatch optimization model for optimization. The optimization results are as follows:

[0160] The optimized power generation capacity constraint is:

[0161]

[0162] Ensure that the power generation of each hydropower station in each period does not exceed its maximum power generation capacity Pi，max (R i，t , T t ), and the power generation cannot be negative;

[0163] P i，max (R i，t , T t )=P i，base +c·Q in，i，t -e i ·T t ;

[0164] Among them, P i，max (R i，t , T t ) is the maximum power generation capacity of the ith hydropower station after considering the influence of precipitation and temperature; T t is the temperature during period t; e i is the influence coefficient of temperature on power generation capacity;

[0165] The optimized reservoir water level constraint is:

[0166]

[0167]

[0168] Among them, V i，t+1 ′ is the optimized reservoir water level of the ith hydropower station in the t+1th period; E i，t (T t ) is the evaporation rate of the ith hydropower station in the tth period;

[0169] The upper and lower limits of the water level in each hydropower station’s reservoir are set to ensure that the reservoir water level remains within a safe and reasonable range to prevent problems caused by too low or too high water levels;

[0170] The influence coefficient of temperature on power generation capacity is introduced i , can more accurately predict the power generation capacity under different temperature conditions, because high temperature may reduce the efficiency of the turbine, while low temperature may improve the efficiency. Introducing temperature can make more reasonable power generation plans; introducing the effect of temperature on evaporation rate E i，t (T t ), can more accurately predict reservoir water level changes, because high temperature will increase the evaporation rate, causing the reservoir water level to drop, the introduction of air temperature can better manage the reservoir water level and ensure that the water level is within a safe range.

[0171] The environmental impact minimization model established in scheduling unit 3 is as follows:

[0172] Objective function:

[0173]

[0174] Among them, C is the objective function of the environmental impact minimization model; Q ecological，i，t is the ecological flow of the ith hydropower station in the tth period; Q ecological,i,min (S t ) is the minimum ecological flow requirement of the ith hydropower station after considering seasonal effects; γ and δ are weight coefficients used to balance the importance of ecological flow and water quality; W i，t is the water quality parameter (such as dissolved oxygen, pH value, etc.) of the ith hydropower station in the tth period; W i,target (S t ) is the water quality target value of the i-th hydropower station after considering seasonal effects;

[0175] Ecological flow constraints:

[0176]

[0177] Ensure that the ecological flow of each hydropower station in each period is not less than the minimum ecological flow requirement Q ecological,i,min (S t ), which helps maintain the health of the river ecosystem and protect the living environment of aquatic organisms;

[0178] Water quality constraints:

[0179]

[0180] Among them, W i,min (S t ) is the minimum allowable water quality parameter value of the i-th hydropower station; W i，max (S t ) is the maximum permissible water quality parameter value of the i-th hydropower station; ensuring that the water quality parameters (such as dissolved oxygen, pH value, etc.) of each hydropower station in each time period are within the permissible range;

[0181] The environmental impact minimization model can not only more comprehensively consider various environmental factors in actual operation, but also effectively improve the scientificity and practicality of dispatching decisions, ensuring that the hydropower station group can achieve maximum economic and social benefits while meeting environmental protection requirements;

[0182] The remote control unit 4 is used to send the received control instructions to each hydropower station, and feed back the control effect of the hydropower station to the optimization scheduling unit 3.

[0183] Embodiment 2:

[0184] The difference between Example 2 of the present invention and Example 1 is that this example introduces a static mechanical performance collection and analysis method used in a multi-station collaborative monitoring system of a hydropower station with intelligent remote control.

[0185] See also Figure 2As shown, the intelligent remote-controlled hydropower station multi-station collaborative monitoring method, based on the above-mentioned intelligent remote-controlled hydropower station multi-station collaborative monitoring system, includes the following steps:

[0186] S1, the collection and transmission unit 1 collects the data of the hydropower station in real time, and transmits the collected data to the monitoring and management unit 2;

[0187] S2, the monitoring management unit 2 receives and processes the data of each hydropower station transmitted by the collection and transmission unit 1, displays the operation data and key indicators of each hydropower station in real time, and automatically monitors abnormal conditions. When an abnormality occurs, an alarm message is generated and the staff is notified;

[0188] S3, the optimization dispatching unit 3 establishes a power generation dispatching optimization model, a reservoir dispatching optimization model and an environmental impact minimization model based on the historical data of the power station and the data of the power station monitored in real time, generates an optimization dispatching plan according to the solutions of the power generation dispatching optimization model, the reservoir dispatching optimization model and the environmental impact minimization model, converts the optimization dispatching plan into a control instruction and sends the instruction to the remote control unit 4;

[0189] S4. The remote control unit 4 is used to send the received control instructions to each hydropower station.

[0190] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments, and the above embodiments and descriptions are only preferred examples of the present invention, and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

Claims

1. An intelligent remote-controlled multi-station collaborative monitoring system for hydropower stations, characterized in that: include: A collection and transmission unit (1), the collection and transmission unit (1) is used to collect data of the hydropower station in real time and transmit the collected data to the monitoring and management unit (2); A monitoring management unit (2), the monitoring management unit (2) is used to receive and process the data of each hydropower station transmitted by the collection and transmission unit (1), display the operation data and key indicators of each hydropower station in real time, and automatically monitor abnormal conditions. When an abnormality occurs, an alarm message is generated and a staff member is notified; wherein the monitoring management unit (2) includes a data processing module, a data storage module, a data display module and an abnormal alarm module; An optimization dispatching unit (3), wherein the optimization dispatching unit (3) establishes a power generation dispatching optimization model, a reservoir dispatching optimization model and an environmental impact minimization model based on historical data of the power station and data of the power station monitored in real time, and at the same time, introduces the influence of temperature into the power generation dispatching optimization model for optimization, and introduces the influence of upstream water, downstream demand and water supply demand into the reservoir dispatching optimization model for optimization, generates an optimization dispatching plan according to the solutions of the power generation dispatching optimization model, the reservoir dispatching optimization model and the environmental impact minimization model, converts the optimization dispatching plan into a control instruction and sends the instruction to a remote control unit (4); A remote control unit (4), wherein the remote control unit (4) is used to send received control instructions to each hydropower station and feed back the control effect of the hydropower station to the optimization dispatching unit (3).

2. The intelligent remote-controlled multi-station cooperative monitoring system for hydropower stations according to claim 1 is characterized by: The data of the hydropower station in the acquisition and transmission unit (1) at least includes power generation, flow, water quality, temperature, upstream water, downstream demand, reservoir water level and unit operation status.

3. The intelligent remote-controlled multi-station cooperative monitoring system for hydropower stations according to claim 2 is characterized in that: In the monitoring management unit (2): The data processing module is used to clean and standardize the data received from each hydropower station, package the data of each power station together to form different first data sets, and then assign the same label to the data from the same data source, and package the data with the same label together to form different second data sets; The data storage module includes a first storage submodule and a second storage submodule, wherein the first storage submodule is used to store a first data set, and the second storage submodule is used to store a second data set; The data display module is used to display and update the real-time data of each hydropower station in real time; The abnormal alarm module is used to compare the real-time data with the pre-set threshold and issue an alarm if the threshold is exceeded.

4. The intelligent remote-controlled multi-station cooperative monitoring system for hydropower stations according to claim 3 is characterized by: The data storage module also includes a historical storage submodule, which is used to store historical data of the power station. The data in the first storage submodule and the second storage submodule will be automatically transmitted to the historical storage submodule after reaching a preset time period; the historical storage submodule is also provided with space for storing the first data set and the second data set.

5. The intelligent remote-controlled multi-station cooperative monitoring system for hydropower stations according to claim 4 is characterized in that: The reservoir scheduling optimization model established in the optimization scheduling unit (3) is specifically as follows: Objective function: Where A is the objective function of the reservoir operation optimization model; T is the total number of time periods; N is the number of hydropower stations; t = 1, 2, ..., T; i = 1, 2, ..., N; V i,t is the reservoir water level of the i-th hydropower station in the t-th period; V i,target (S t ) is the target water level of the ith hydropower station after considering seasonal effects; S t is the seasonal factor; α and β are weight coefficients; Q out,i,t is the outflow of the i-th hydropower station in the t-th period; Q target,i,t (S t ) is the target outflow of the i-th hydropower station after considering seasonal effects; Reservoir water level constraints: Among them, V i,t+1 is the reservoir water level of the i-th hydropower station in the t+1 period; Q in,i,t is the inflow of the i-th hydropower station in the t-th period; V i,min is the minimum allowable water level of the ith hydropower station; V i,max is the maximum allowable water level of the i-th hydropower station; Outbound traffic constraints: Q max,i (R i,t )=Q i,base +d i ·R i,t ; Among them, Q max,i (R i,t ) is the maximum allowable outflow of the i-th hydropower station in the t-th period considering the influence of precipitation; R i,t is the precipitation of the ith hydropower station in the tth period; Q i,base is the maximum allowable outflow flow of the i-th hydropower station; d i It is the coefficient that represents the influence of precipitation on the maximum allowable outflow flow.

6. The intelligent remote-controlled multi-station cooperative monitoring system for hydropower stations according to claim 5 is characterized by: The optimization scheduling unit (3) introduces the influence of upstream water, downstream demand and water supply demand into the reservoir scheduling optimization model for optimization. After optimization, the specific results are: Among them, A' is the objective function of the optimized reservoir operation optimization model; ε is the weight coefficient related to the water supply deviation; Q supply,i,t is the actual water supply of the i-th hydropower station in the t-th period; Q demand,i,t is the water supply demand of the i-th hydropower station in the t-th period; The newly added constraints include meeting downstream demand and water supply constraints, specifically: Meeting downstream needs: Among them, Q demand,i,t is the downstream demand of the i-th hydropower station in the t-th period; Water supply constraints: Among them, Q supply,i,t is the actual water supply of the i-th hydropower station in the t-th period.

7. The intelligent remote-controlled multi-station cooperative monitoring system for hydropower stations according to claim 6 is characterized by: The power generation scheduling optimization model established in the optimization scheduling unit (3) is specifically as follows: Objective function: Where B is the objective function of the power generation dispatch optimization model; P i,t is the power generation of the ith hydropower station in the tth period; Power demand constraints: Among them, D t is the power demand in period t; Power generation capacity constraints: P i,max (R i,t )=P i,base +c·Q in,i,t ; Q in,i,t =Q upstream,i,t +k i ·R i,t ; Among them, P i,max (R i,t ) is the maximum power generation capacity of the ith hydropower station after considering the influence of precipitation; P i,base is the basic power generation capacity of the i-th hydropower station; c is the coefficient representing the influence of the inflow on the power generation capacity; Q upstream,i,t is the upstream water flow of the i-th hydropower station in the t-th period; k i is the conversion coefficient from precipitation to inflow; Unit startup or shutdown constraints: Among them, U i,t is the unit operation status of the i-th hydropower station in the t-th period; U i,t-1 is the operating status of the unit of the i-th hydropower station in the t-1 period; S i,t is the unit startup status of the i-th hydropower station in the t-th period; The power generation scheduling optimization model is also constrained by the reservoir water level.

8. The intelligent remote-controlled multi-station cooperative monitoring system for hydropower stations according to claim 7 is characterized by: The optimization scheduling unit (3) introduces the influence of temperature into the power generation scheduling optimization model for optimization. After optimization, the specific results are: The optimized power generation capacity constraint is: P i,max (R i,t ,T t )=P i,base +c·Q in,i,t -e i ·T t ; Among them, P i,max (R i,t ,T t ) is the maximum power generation capacity of the ith hydropower station after considering the influence of precipitation and temperature; T t is the temperature during period t; e i is the influence coefficient of temperature on power generation capacity; The optimized reservoir water level constraint is: Among them, V i,t+1 ' is the optimized reservoir water level of the ith hydropower station in the t+1 period; E i,t (T t ) is the evaporation rate of the ith hydropower station in the tth period.

9. The intelligent remote-controlled multi-station cooperative monitoring system for hydropower stations according to claim 8 is characterized by: The environmental impact minimization model established in the optimization scheduling unit (3) is specifically as follows: Objective function: Among them, C is the objective function of the environmental impact minimization model; Q ecological,i,t is the ecological flow of the ith hydropower station in the tth period; Q ecological,i,min (S t ) is the minimum ecological flow requirement of the ith hydropower station after considering seasonal effects; γ and δ are weight coefficients; W i,t is the water quality parameter of the ith hydropower station in the tth period; W i,target (S t ) is the water quality target value of the i-th hydropower station after considering seasonal effects; Ecological flow constraints: Water quality constraints: Among them, W i,min (S t ) is the minimum allowable water quality parameter value of the i-th hydropower station; W i,max (S t ) is the maximum allowable water quality parameter value of the ith hydropower station.

10. A method for cooperative monitoring of multiple stations of a hydropower station by intelligent remote control, based on the cooperative monitoring system of multiple stations of a hydropower station by intelligent remote control as claimed in any one of claims 1 to 9, characterized in that: The steps include: S1, the collection and transmission unit (1) collects data of the hydropower station in real time, and transmits the collected data to the monitoring and management unit (2); S2, the monitoring management unit (2) receives and processes the data of each hydropower station transmitted by the collection and transmission unit (1), displays the operation data and key indicators of each hydropower station in real time, and automatically monitors abnormal conditions. When an abnormality occurs, an alarm message is generated and the staff is notified; S3, the optimization dispatching unit (3) establishes a power generation dispatching optimization model, a reservoir dispatching optimization model and an environmental impact minimization model based on the historical data of the power station and the data of the power station monitored in real time, generates an optimization dispatching plan according to the solutions of the power generation dispatching optimization model, the reservoir dispatching optimization model and the environmental impact minimization model, converts the optimization dispatching plan into a control instruction and sends the instruction to the remote control unit (4); S4. The remote control unit (4) is used to send the received control instructions to each hydropower station.

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