Energy-saving pumped storage power station technology water supply intelligent regulation system

Abstract

The application discloses an energy-saving pumped storage power station technical water supply intelligent regulation and control system, which comprises a real-time monitoring module, a data analysis module, a dispatching control module and a data interaction module. The main feature of the application is that the hydraulic model calculation is carried out by considering the actual seasonal multi-mode, which is mainly divided into summer & large flow condition and winter & small flow condition. For the winter & small flow condition, the valve opening degree of each valve is kept unchanged to adjust the water pump rotating speed. For the summer & large flow condition, the water pump rotating speed is adjusted to the maximum, and the water distribution of each pipeline is realized by adjusting the valve opening degree. The application has the advantages that the suitable regulation mode can be selected according to different conditions, so that the energy saving and emission reduction are realized, and the efficiency of the water supply system is improved.

Description

Technical Field

[0001] The present invention relates to the field of technical water supply systems for power stations, and in particular to an energy-saving intelligent water supply control system for pumped storage power stations. Background Art

[0002] To achieve carbon neutrality and carbon peak targets, current technologies are actively developing clean energy sources such as solar, hydro, nuclear, wind, and tidal energy to gradually replace fossil fuels, while also promoting industrial transformation to conserve energy and reduce emissions. However, while pumped-storage power stations can produce clean energy, they also consume energy, with a major source of this energy consumption coming from their water supply systems.

[0003] The water supply of a pumped-storage power station primarily provides cooling water for the generator sets and their auxiliary equipment. This equipment includes generator air coolers, water-cooled air compressors, thrust and guide bearings, mainshaft seal cooling water, and governor oil sump coolers. The power station's technical water supply system ensures the safe operation of the plant's production processes. However, due to a lack of scientific and effective theoretical guidance and a low level of digitalization and intelligence in operational maintenance, power stations often blindly improve system cooling performance to meet production needs, causing the circulating cooling water system to operate at high loads and resulting in significant energy waste. While precise regulation of water volume is a prerequisite for energy conservation, emission reduction, and water security, most power stations currently use a saturated water supply, failing to consider the varying water demands of individual users. Furthermore, the water supply pumps are typically regulated to their maximum power.

[0004] Based on the above situation, the present invention proposes an energy-saving pumped storage power station technical water supply intelligent control system to effectively solve the above problems. Summary of the Invention

[0005] In order to solve the problems existing in the background technology, the present invention provides an energy-saving pumped storage power station technical water supply intelligent control system.

[0006] The present invention adopts the following technical solutions:

[0007] An energy-saving pumped storage power station water supply intelligent control system, including intelligent monitoring module, data analysis module, dispatching control module, data interaction module,

[0008] At the same time, all data are uploaded to the database;

[0009] The data analysis module uses the data collected from the technical water supply system in typical years and trains it through a deep learning model to obtain the mapping relationship between the index data of the technical water supply system and the index data of the pumped storage unit and the cooling water volume required by each water-using equipment. It also uses the partial data collected in real time as input to obtain the flow rate required by each water-using equipment and provide the target adjustment amount for the scheduling control module.

[0010] The scheduling control module includes a hydraulic calculation unit and a scheduling optimization unit. The hydraulic calculation unit establishes a pipeline loss model based on the branch pipelines where each water-using device in the technical water supply system is located and the devices on the pipelines, and iteratively solves the flow rate. The flow rate is used as the call calculation part of the scheduling optimization unit. The scheduling optimization unit selects different control modes based on actual conditions and user needs. The system is divided according to seasons and selected based on the relationship between the total flow rate required by the water-using devices and the set threshold value.

[0011] The data interaction module consists of a storage unit and a human-computer interaction unit. The storage unit is used to store and organize the data collected by the technical water supply system, and store the operation log generated by the control results. The human-computer interaction unit is used to retrieve the data from the storage unit and visualize the data.

[0012] Furthermore: the system monitoring module uses a set time interval as a sampling frequency to collect water supply system equipment and pipeline information data, as well as some information collected from the pumped storage unit.

[0013] Further: the data analysis module is based on the deep learning of each water-using equipment to obtain the mapping relationship of the required flow rate of the indicator, and the system acquisition module collects the indicators and inputs them into the system to obtain the cooling water flow required by each water-using equipment.

[0014] Furthermore: the hydraulic calculation unit of the scheduling control module is used to establish a technical water supply system pipe network model and a variable frequency pump model and solve the parameter calculations therein:

[0015] Technical water supply system network model: Based on the various node pipe sections and pipeline equipment of the pumped storage power station technical water supply system, a pipeline hydraulic loss model is established and the flow distribution ratio of the branch pipeline is derived. Then, the hydraulic loss related to the technical water supply main pipeline of the water supply system is calculated and combined with the hydraulic loss of the branch pipeline where each water-using equipment is located to obtain the overall pipeline network characteristic curve;

[0016] Variable frequency pump model: According to the pump characteristic curve, the flow-efficiency (Q-η) curve and flow-head (QH) curve of the pump at different speeds are obtained, and the speed ratio-motor efficiency (k-η) curve of the motor is established. e) and the inverter speed ratio-inverter efficiency (k-η b ) curve model.

[0017] Furthermore: The hydraulic calculation unit technology water supply system pipe network model construction includes various hydraulic losses of each pipe, and its specific modeling and solution process is as follows:

[0018] S1. First, the water supply system pipe network model is used to build various hydraulic loss calculation models and then the entire pipe network model is built. Various hydraulic resistances are modeled separately, including:

[0019] S1a, along-the-line resistance model: When a fluid flows in a pipe, the viscous friction between the fluid and the pipe wall creates resistance to movement, resulting in energy loss, denoted as h f The present invention adopts the Hazen-Williams formula to calculate the hydraulic loss along the way, and its expression is:

[0020]

[0021] Where Q is the flow rate, m 3 / h; d is the pipe diameter, in m; L is the pipe length, in m; f is the friction coefficient; m is the flow index, which is taken as 2 in the present invention; b is the pipe diameter index.

[0022] S1b, Local resistance model: When a fluid encounters local resistance during motion, it generates vortex motion, dissipating a portion of the fluid's mechanical energy, which can be expressed as velocity head:

[0023]

[0024] Where A is the cross-sectional area of ​​the pipe, g is the acceleration due to gravity which is 9.81 m / s 2 , Q is the flow rate, m 3 / h, ζ can be determined by empirical formula and actual situation of power station;

[0025] S1c, Valve local resistance model: The valve resistance coefficient can be defined as:

[0026]

[0027] Where h k is the valve hydraulic loss, m; ρ is the water density, unit is kg / m 3 ; g is the acceleration due to gravity m / s -2 ;

[0028] Reference fitting formula for valve local resistance coefficient:

[0029] S=A×exp(-K / t)+C;

[0030] Wherein K is the valve opening, °; A, t, C are to be determined constant.

[0031] S2, the whole pipe network model is established according to different resistance model:

[0032] The total pipe resistance technology water supply system main pipe total hydraulic loss, main water supply pipe resistance mainly considers the resistance and local resistance along the way:

[0033]

[0034] U main = h main / Q total 2 ;

[0035] Wherein h main is the total hydraulic loss of the main pipe of the technical water supply system; f main is the main pipe friction coefficient; d main is the main pipe diameter ζ main is the main pipe local resistance coefficient; A main is the main pipe cross-sectional area, unit m 2 ; Q total is the total water quantity, m 3 / h; U main is the main pipe resistance coefficient;

[0036] Secondly, the total hydraulic loss of each water using equipment in the branch pipe is calculated, and the total hydraulic loss of each branch pipe is the sum of the resistance along the way and the local resistance of the bend, the local resistance of the valve and the local resistance of the water using equipment:

[0037] Wherein h i is the total hydraulic loss of the branch pipe of the i-th water using equipment in the technical water supply system; is the resistance along the way of the branch pipe of the i-th water using equipment; h j i is the local hydraulic loss of the branch pipe of the i-th water using equipment; h k i is the hydraulic loss of the electric valve of the branch pipe of the i-th water using equipment; f i is the friction coefficient of the branch pipe of the i-th water using equipment; d i is the diameter of the branch pipe of the i-th water using equipment, unit m; ζ i is the local resistance coefficient of the branch pipe of the i-th water using equipment; A i is the cross-sectional area of the branch pipe of the i-th water using equipment, unit m 2 ; Q i is the total water quantity, m3 / h; ρ is the water density, unit is kg / m 3 ;S i is the resistance characteristic number of the valve in the branch pipeline where the i-th water-using equipment is located;

[0038] The proportion of water allocated to each branch pipe can then be determined based on the resistance of the branch pipe, and the calculation method is:

[0039]

[0040] Where U i is the resistance coefficient of the valve in the branch pipeline where the i-th water-using equipment is located, Φ i is the ratio of the flow rate of the branch pipeline where the i-th water-using equipment is located.

[0041] Finally, the characteristic curve of the pipe network is obtained. Since water must possess a certain amount of energy to reach the water-using equipment through the pipe network, it must overcome the hydraulic loss in the pipe, the upstream and downstream water level difference, and the upstream and downstream water surface pressure difference. When the water energy and these three energies are balanced, the pipe network can operate stably. These three energies can be expressed as follows:

[0042] S t =U main +U dis ;

[0043] Where H G is the total head required by the water supply system, in m, and Q is the total flow rate currently required by the pipe network, in m 3 / h;S t is the tube resistance coefficient, unit is h 2 / m 2 ;H st is the hydrostatic pressure, unit is m; U dis is the total score; λ is the pipe network resistance index coefficient, which is 2.

[0044] Further: It is characterized in that the variable frequency pump model in the hydraulic calculation unit includes the characteristic curve flow-efficiency (Q-η) curve and flow-head (QH) curve of the water pump. The specific modeling process is: the performance curve at different pump frequency conversions can be expressed as:

[0045]

[0046] H=a1Q 2 +a2kQ+a3k 2 ;

[0047] Where H is the pump head; Q is the total flow of the pump, m 3 / h; η is the pump efficiency; k is the defined speed ratio; n0 is the rated speed; n is the pump operating speed; a1, a2, a3 are the pump flow-head curve parameters obtained by fitting; b1, b2, b3 are the pump flow-efficiency curves;

[0048] Then solve the motor efficiency and inverter efficiency according to the speed ratio:

[0049] η m =0.94187×(1-e -9.04k );

[0050] η v =0.5087+1.283k-1.42k 2 +0.5834k 3 ;

[0051] Where η m is the motor efficiency; η v is the motor efficiency; k is the defined speed ratio; e is the natural index;

[0052] Then, based on the pump flow-head characteristic curve and the pipe network characteristic curve, an equation is established to solve the total power efficiency:

[0053]

[0054] N=ρgH w Q w ηη m η v ;

[0055] Where H w is the working head of the water pump; Qw is the working flow of the water pump, m 3 / h;Φ i is the distribution ratio of the i-th water-using equipment; ρ is the water density, unit is kg / m 3 ; g is the acceleration due to gravity m / s -2 .

[0056] Further: The winter & small flow mode adjustment method in the scheduling optimization unit system of the scheduling control module is to keep the valve opening of each water-using equipment unchanged and optimize the water pump speed. Its specific scheduling optimization model and optimization solution are:

[0057] S1. Calculate the difference between the target demand flow and the current flow:

[0058]

[0059] Where dQ i is the difference between the required flow and the current flow; Q i needis the cooling water flow required by the i-th user equipment; Q i current is the current cooling water flow of the i-th water-using equipment;

[0060] S2. Calculate the required water flow rate of the total pipeline based on the current water distribution ratio of each branch network and select the maximum value:

[0061]

[0062] Where Q i increase The additional flow rate of the total pipeline required for the i-th water-using equipment; Φ i current The flow distribution ratio of the branch pipe where the i-th water-using equipment is located is obtained based on the hydraulic model; Q m increase For all Q i increase Maximum value.

[0063] S3. Calculate the water volume adjusted by the water pump. The calculation method is:

[0064]

[0065] Where Q Z is the target regulating flow of the pump, k a The safety factor is 1.1 to 1.2;

[0066] S4. Calculate the target water pump speed:

[0067]

[0068] Where n t is the target speed.

[0069] Further: the scheduling optimization unit system of the scheduling control module has multiple objectives in the summer and large flow modes, including the minimum sum of the difference between the working flow and the demand flow of each water-using equipment pipeline and the minimum total power. The minimum objective function is simplified to a single objective by weighted sum; after setting the water pump speed n to the rated speed, the electric valve opening K of each pipeline and the branch where each water-using equipment is located is calculated. i Perform parameter optimization, its specific scheduling optimization model and optimization solution:

[0070] Take total power consumption and minimum as the objective function:

[0071]

[0072] Where N z Refer to formula (19) for the calculation method of the total power consumption of the water pump; Qi need Q is the required cooling water flow for the ith water-using equipment; Q i w Q is the optimized flow for the ith water-using equipment; {w1, w2} are the multi-objective weight values. Constraints:

[0073] Speed constraint:

[0074] n = n0;

[0075] Lift constraint:

[0076]

[0077] Flow constraint for branch pipe:

[0078]

[0079] Pressure constraint:

[0080]

[0081] Total flow constraint:

[0082]

[0083] where n is the speed, n0is the rated speed; Q i max Q is the maximum flow allowed for the pipe where the ith water-using equipment is located; Q i need Q is the required cooling water flow for the ith water-using equipment; Q t Q is the calculated total flow of the pipe; Q is the total flow threshold of the pipe for winter & small flow and summer & large flow mode; Q t max P is the maximum flow allowed for the total pipe; P j max P is the maximum pressure value that the jth node pipe can withstand; P j min P is the minimum pressure value for the safe operation of the jth node pipe; P j P is the pressure value of the jth node pipe; Q i w Q is the calculated flow of the pipe where the ith water-using equipment is located;

[0084] Further: the system implementation steps are as follows:

[0085] Step one: on-site terminal equipment inspection and system start-up stage:

[0086] Inspection, calibration and debugging of the terminal equipment involved in each module of the technical water supply dispatching and control system of the pumped storage power station are carried out, including debugging and checking the information interaction system of the intelligent monitoring module in the control center of the Chushu Pumped Storage Power Station and the technical water supply system monitoring equipment, inspection and debugging of the control equipment involved in the dispatching and control module, setting relevant parameters and preliminary construction of the built-in models of the data analysis module, the hydraulic calculation unit in the dispatching and control module, and the dispatching optimization unit, and debugging and checking the interaction between the information and data interaction module of the dispatching and control module and the communication station network of the intelligent monitoring module; pre-startup is carried out after completing the inspection and debugging of all terminal equipment. If the system prompts that the operating status conditions of the terminal equipment do not meet the specifications, the system will be checked again and the parameters will be reset until the startup conditions are met;

[0087] Step 2: Information collection and operation data monitoring:

[0088] After the system is started, the intelligent monitoring module automatically collects information and measures data from various sensors on the pumped storage power station control center and technical water supply system equipment and pipelines. The collected information from each part is uploaded in real time to the storage unit of the data interaction module to complete the collection of typical historical data for a typical year. During the operation of the system, if the collected pipeline pressure exceeds the set maximum value or the water temperature at the water intake exceeds the set safety temperature, prompts and alarms will be issued in a timely manner at this stage, providing the actual location of the power station where the problem occurs to the power station operation and maintenance personnel, and making decisions on whether to shut down the system for adjustment.

[0089] Step 3: Data analysis and target flow determination:

[0090] The data from the intelligent monitoring module is preprocessed and normalized, and new eigenvalues ​​are extracted to obtain a set of eigenvalues ​​as input. This is then input into the mapping relationship between the indicator data of the technical water supply system and the pumped storage unit trained based on typical historical data using a deep learning model, and the cooling water volume required by each water-using device. The required flow rate of each water device is then obtained. This data set is then transmitted to the dispatching control module as the target parameter and uploaded to the storage unit of the data interaction module for backup.

[0091] Step 4: Determine and calculate the scheduling control model:

[0092] The data analysis module calculates the overall flow rate based on the demand flow of each water device. The system selects a mode based on the current seasonal conditions and the total demand flow rate. After selecting a specific control optimization mode, the system calls the model to perform calculations and generates scheduling instructions based on the calculation results. The electric valves of the relevant pipeline equipment are then adjusted to the corresponding openings and the water pumps are adjusted to the corresponding speeds.

[0093] Step five: data dynamic update and analysis:

[0094] After the system performs step four, the intelligent monitoring module, data analysis module and scheduling control module of the system update and analyze the data;

[0095] Step six: repeat steps two to five during the entire system startup and operation period.

[0096] The energy-saving pumped storage power station technical water supply intelligent control system provided by the application realizes the relationship between the required flow of unit load, technical water supply system water temperature, and the temperature of each water-using equipment, ensures water supply safety, considers the difference in control mode caused by the different total flow demand of water-using equipment in different seasons, realizes pump valve optimization scheduling of the technical water supply system based on the hydraulics model of the technical water supply system pipeline, and meets the flow demand of each water-using equipment; the appropriate adjustment mode can be selected according to different conditions, so that energy saving and emission reduction and the efficiency of the water supply system are improved. BRIEF DESCRIPTION OF DRAWINGS

[0097] Figure 1 The system module diagram of the application;

[0098] Figure 2 The system diagram of the application for determining the control process according to the seasonality and water demand. DETAILED DESCRIPTION

[0099] The application will be further described in detail below in combination with the drawings and specific embodiments.

[0100] Referring to the drawings Figure 1 The energy-saving pumped storage power station technical water supply intelligent control system considers the energy-saving pumped storage power station technical water supply intelligent control system, which comprises an intelligent monitoring module, a data analysis module, a scheduling control module and a data interaction module.

[0101] The intelligent monitoring module is used for automatically acquiring the information of the technical water supply system equipment, pipe network and the pumped storage unit of the power station layer in real time, collecting information by interacting with the pumped storage power station control center, accepting the data transmission signals of the sensors and equipment arranged in the technical water supply system, and uploading each data to the database to provide training data support for the data analysis system, so as to improve the module and provide information support for other modules.

[0102] The data analysis module utilizes data collected by the technical water supply system in a typical year to train a deep learning model to obtain a mapping relationship between index data of the technical water supply system and the pumped storage unit and cooling water required by each water-using equipment, and to obtain the flow required by each water-using equipment according to part of the real-time collected data as an input, thereby providing a target regulation quantity for the dispatching control module,

[0103] The dispatching control module includes a hydraulic calculation unit and a dispatching optimization unit. The hydraulic calculation unit establishes a pipe loss model according to each water-using equipment in the branch pipe and the equipment on the pipe, and iteratively solves the flow (and pressure condition) to serve as a calculation part called by the dispatching optimization unit. The dispatching optimization unit selects different control modes according to actual conditions and user requirements. The system selects a winter & small flow mode dispatching control mode in December-February and a summer & large flow mode in May-August according to seasons, and selects the winter & small flow mode or the summer & large flow mode according to the relationship between the total flow required by the water-using equipment and the set threshold value in the remaining time periods. If the total flow required by the water-using equipment is greater than the threshold value, the summer & large flow mode is selected, otherwise the winter & small flow mode is selected. The boundary is that the winter & large flow mode is satisfied in time in the year. In addition, the pump-valve combined control mode and the single pump mode can be selected according to human selection in the winter & large flow mode. According to different modes, the system selects a corresponding dispatching optimization model, and then performs parameter optimization on the frequency pump speed and the electric valve opening degree of each water-using equipment pipe.

[0104] The data interaction module includes a storage unit and a human-computer interaction unit. The storage unit is used for storing and sorting the collected data of the technical water supply system, and storing the operation log generated by the regulation result, and is an important part of the data source for subsequent development of the system. The human-computer interaction unit is used for uploading the data of the intelligent monitoring module and the dispatching control module to the storage unit, and visualizing the data according to the needs of the monitoring personnel. The human-computer interaction unit can also transmit the selected results of the mode in the dispatching control module to the dispatching control module.

[0105] The data analysis module is obtained by deep learning of each water-using equipment, and the mapping relationship between the temperature of the water-using equipment, the temperature of the pumped storage unit, the water temperature of the technical water supply intake, and other index input quantities and the required flow is obtained. The training data of this part is derived from the index data set sampled in a typical year of a pumped storage power station, and the optimized deep learning is embedded into the data analysis system as the core calculation part. According to the system collection module, the temperature of the water-using equipment, the temperature of the pumped storage unit, the water temperature of the technical water supply intake, and other index input quantities are input into the system to obtain the cooling water flow Q i need .

[0106] The system monitoring module samples data at 10-minute intervals, collecting data that is primarily divided into two parts. The first part contains water supply system equipment and pipeline information, including the temperature and hydraulic information of each technical water supply system device. These devices include the generator / motor air cooler, thrust lower guide bearing cooler, upper guide bearing cooler, upper / lower labyrinth rings, water guide bearing cooler, governor oil sump cooler, upper guide bearing cooler, main shaft seal, governor oil sump cooler, and main transformer. This hydraulic information includes the flow rate and pressure of each branch pipeline containing these devices, the opening of each branch's electric valves, the speed and power of the technical water supply pumps, the cooling water flow rate and pressure of the technical water supply system's main pipeline, and the water temperature at the technical water supply system's intake. The second part of the data comes from pumped-storage unit information, including the power / load of the pumped-storage unit and the water levels of the upper and lower reservoirs. The data collected by the system module is uploaded to the data exchange module's storage unit for backup.

[0107] The hydraulic calculation unit in the dispatching and control module primarily establishes a technical water supply system network model and a variable frequency pump model, solving the associated parameter calculations. The technical water supply system network model establishes a pipeline hydraulic loss model based on each node section and pipeline equipment in the pumped-storage power station's technical water supply system, and derives the flow distribution ratio for each branch pipeline. The hydraulic losses involved primarily come from two sources: along-the-line resistance and local resistance. Local resistance stems from hydraulic losses caused by valves, elbows, diffusers, and water-using equipment, while along-the-line resistance stems from losses caused by overcoming viscous forces during flow in the technical water supply pipeline. The hydraulic losses associated with the main technical water supply pipeline of the water supply system are then calculated and combined with the hydraulic losses of the branch pipelines where each water-using equipment is located to obtain the overall network characteristic curve. The variable frequency pump model, based on the pump characteristic curve, derives the flow-efficiency (Q-η) curve and the flow-head (QH) curve for the pump at different speeds. Furthermore, a speed ratio-motor efficiency (k-η) curve is established for the motor. e ) and the inverter speed ratio-inverter efficiency (k-η b ) curve model.

[0108] The specific modeling and solution process:

[0109] S1. First, the water supply system pipe network model is used to build various hydraulic loss calculation models and then the entire pipe network model is built. Various hydraulic resistances are modeled separately, including:

[0110] S1a, along-the-line resistance model: When a fluid flows in a pipe, the viscous friction between the fluid and the pipe wall creates resistance to movement, resulting in energy loss, denoted as h fThe present invention adopts the Hazen-Williams formula to calculate the hydraulic loss along the way, and its expression is:

[0111]

[0112] Where Q is the flow rate, m 3 / h; d is the pipe diameter, in m; L is the pipe length, in m; f is the friction coefficient; m is the flow index, which is taken as 2 in the present invention; b is the pipe diameter index.

[0113] S1b, Local resistance model: When a fluid encounters local resistance (such as closed valves, pipe bends, and thick-thin pipe interfaces) during its motion, the fluid will generate vortex motion due to flow separation, secondary flow, and other reasons, dissipating part of the fluid's mechanical energy, which can be expressed as velocity head:

[0114]

[0115] Where A is the cross-sectional area of ​​the pipe, g is the acceleration due to gravity which is 9.81 m / s 2 , Q is the flow rate, m 3 / h, ζ can be selected according to the empirical formula and the actual situation of the power station.

[0116] S1c, Valve local resistance model: The valve resistance coefficient can be defined as:

[0117]

[0118] Where h k is the valve hydraulic loss, m; ρ is the water density, unit is kg / m 3 ; g is the acceleration due to gravity m / s -2 Reference fitting formula for valve local resistance coefficient:

[0119] S=A×exp(-K / t)+C;

[0120] Where K is the valve opening, °; A, t, and C are unknown constants.

[0121] S2. Then build the overall pipe network model based on different resistance models:

[0122] Calculate the total hydraulic loss of the main pipeline of the water supply system using the total pipe resistance technology. The pipe resistance of the main water supply pipeline mainly considers the resistance along the pipeline and the local resistance:

[0123]

[0124] U main =h main / Q total 2 ;

[0125] Where hmain is the total hydraulic loss of the main pipeline of the technical water supply system; f main is the friction coefficient of the main line; d main is the main pipe diameter main is the local resistance coefficient of the main pipeline; A main is the cross-sectional area of ​​the main pipeline, in m 2 ;Q total is the total water volume in the pipeline, m 3 / h; U main is the resistance coefficient of the main line.

[0126] Secondly, calculate the overall hydraulic loss of each branch pipeline where the water-using equipment is located. The total hydraulic loss of each branch pipeline is the sum of the resistance along the pipeline, the local resistance of the elbow, the local resistance of the valve, and the local resistance of the water-using equipment:

[0127]

[0128] Where hi is the total hydraulic loss of the branch pipeline where the i-th water-using equipment is located in the technical water supply system; is the hydraulic loss along the branch pipeline where the i-th water-using equipment is located; h j i is the local hydraulic loss of the branch pipeline where the i-th water-using equipment is located; h k i is the hydraulic loss of the electric valve of the branch pipeline where the i-th water-using equipment is located; f i The friction coefficient of the branch pipe where the i-th water-using equipment is located; d i is the diameter of the branch pipe where the i-th water-using equipment is located, in meters; ζ i is the local resistance coefficient of the branch pipe where the i-th water-using equipment is located; A i The cross-sectional area of ​​the branch pipe where the i-th water-using equipment is located, in m 2 ;Q i is the total water volume in the pipeline, m 3 / h; ρ is the water density, unit is kg / m 3 ;S i is the resistance characteristic number of the valve in the branch pipeline where the i-th water-using equipment is located;

[0129] The proportion of water allocated to each branch pipe can then be determined based on the resistance of the branch pipe, and the calculation method is:

[0130]

[0131] Where U i is the resistance coefficient of the valve in the branch pipeline where the i-th water-using equipment is located, Φ i is the ratio of the flow rate of the branch pipeline where the i-th water-using equipment is located.

[0132] Finally, the characteristic curve of the pipe network is obtained. Since water must possess a certain amount of energy to reach the water-using equipment through the pipe network, it must overcome the hydraulic loss in the pipe, the upstream and downstream water level difference, and the upstream and downstream water surface pressure difference. When the water energy and these three energies are balanced, the pipe network can operate stably. These three energies can be expressed as follows:

[0133]

[0134]

[0135] S t =U main +U dis ;

[0136] Where H G is the total head required by the water supply system, in m, and Q is the total flow rate currently required by the pipe network, in m 3 / h;S t is the tube resistance coefficient, unit is h 2 / m 2 ;H st is the hydrostatic pressure, unit is m; U dis is the total score; λ is the pipe network resistance index coefficient, which is 2.

[0137] Establish relevant models for variable frequency pumps and solve

[0138] First, establish the characteristic curves of the water pump, the flow-efficiency (Q-η) curve and the flow-head (QH) curve. The performance curves at different pump frequency conversions can be expressed as:

[0139]

[0140] H=a1Q 2 +a2kQ+a3k 2 ;

[0141] Where H is the pump head; Q is the total flow of the pump, m 3 / h; η is the pump efficiency; k is the defined speed ratio; n0 is the rated speed; n is the operating speed of the pump; a1, a2, a3 are the parameters of the pump flow-head curve obtained by fitting; b1, b2, b3 are the pump flow-efficiency curve.

[0142] Then solve the motor efficiency and inverter efficiency according to the speed ratio:

[0143] η m =0.94187×(1-e -9.04k );

[0144] η v =0.5087+1.283k-1.42k2 +0.5834k 3 ;

[0145] Where η m is the motor efficiency; η v is the motor efficiency; k is the defined speed ratio; e is the natural index.

[0146] Then, based on the pump flow-head characteristic curve and the pipe network characteristic curve, an equation is established to solve the total power efficiency:

[0147] N=ρgH w Q w ηη m η v ;

[0148] Where H w is the working head of the water pump; Qw is the working flow of the water pump, m 3 / h; Qi is the flow rate of the i-th water-using equipment m 3 / h;Φ i ρ is the water density, unit is kg / m 3 ; g is the acceleration due to gravity m / s -2 .

[0149] like Figure 2 As shown in the figure, the control strategy logic diagram is determined according to seasonality and water demand. The system can obtain different optimization scheduling results according to different modes by selecting different seasonal modes. For the large flow mode in summer, two different optimization energy-saving modes can be selected. One is a monotonic pump mode that keeps the valve regulating the water pump to meet the water demand of each pipeline. The other is a pump-valve joint control mode in which the opening of each valve and the speed of the water pump can be adjusted. For small flow conditions, the water pump speed is adjusted to the maximum, and the water distribution of each pipeline is achieved by adjusting the valve opening.

[0150] The winter & low flow mode in the scheduling optimization unit system of the scheduling control module is to keep the valve opening of each water-using equipment unchanged and optimize the water pump speed. Its specific scheduling optimization model and optimization solution are as follows: S1. Calculate the difference between the target demand flow and the current flow:

[0151]

[0152] Where dQ i is the difference between the required flow and the current flow; Q i need is the cooling water flow required by the i-th user equipment; Q i current is the current cooling water flow of the i-th water-consuming equipment.

[0153] (2) According to the current branch pipe network water distribution ratio to solve the total pipe required to improve the water flow and filter the maximum value:

[0154]

[0155] In the formula Q i increase The total pipe flow required for the i-th water using equipment; Φ i current The flow distribution ratio of the i-th water using equipment in the branch pipe is obtained according to the hydraulic model; Q m increase The total Q i increase Maximum value.

[0156] S3, calculate the water pump regulating water quantity, the calculation method is:

[0157]

[0158] In the formula Q Z The target regulating flow of the water pump, k a The safety factor is 1.1-1.2;

[0159] S4, solve the target water pump speed:

[0160]

[0161] In the formula n t The target speed.

[0162] The scheduling optimization unit system of the scheduling control module, the target function in the summer and large flow mode is multi-objective, which includes the minimum value of the difference between the pipe working flow and the demand flow of each water using equipment and the minimum value of the total power, and the minimum value is obtained by weighting and summing; After the water pump speed n is set to the rated speed, the electric valve opening K i of each pipe and the branch of each water using equipment is optimized, and the specific scheduling optimization model and optimization solution:

[0163] The total power consumption and the minimum value are taken as the target function:

[0164]

[0165] In the formula N z The total power consumption of the water pump is calculated according to formula (19); Q i need The cooling water flow required for the i-th water using equipment; Q i wCalculate the optimized flow for the i-th book-using device; {w1, w2} are the multi-objective parameter weights.

[0166] Constraints:

[0167] Speed ​​constraint:

[0168] n=n0;

[0169] Lift constraints:

[0170]

[0171] Flow constraints of branch lines:

[0172]

[0173] Pressure constraints:

[0174]

[0175] Total flow constraint:

[0176]

[0177] Where n is the speed and n0 is the rated speed; Q i max is the maximum flow rate allowed in the pipeline where the i-th water-using equipment is located; Q i need is the cooling water flow required by the i-th user equipment; Q t is the calculated total pipeline flow; Q is the total flow threshold of the pipeline in winter & low flow and summer & high flow modes; t max is the maximum flow allowed by the total pipeline; P j max is the maximum pressure value that the j-th node pipeline can withstand; P j min is the minimum pressure value for safe operation of the j-th node pipeline; P j is the pressure value of the j-th node pipeline; Q i w The flow rate calculated from the pipeline where the i-th water-using device is located;

[0178] The following is a specific calculation case:

[0179] The assumed period is a time in the morning of December in winter when the pumped storage power station faces an increase in unit load.

[0180] The equipment status and pipeline hydraulic parameters collected by the intelligent control module at a certain moment are shown in Table 1:

[0181]

[0182] Table 1

[0183] The demand flow obtained through calculation in the data analysis module is shown in Table 2:

[0184]

[0185] Table 2

[0186] In this case, the system is selected as winter & small flow mode. The calculated control parameters and hydraulic calculation results are shown in Table 3:

[0187]

[0188] Table 3

[0189] The system implementation steps are as follows:

[0190] Step 1: On-site terminal equipment inspection and system startup phase:

[0191] Inspection, calibration and debugging of the terminal equipment involved in each module of the technical water supply dispatching and control system of the pumped storage power station are carried out, including debugging and checking the information interaction system of the intelligent monitoring module in the control center of the Chushu Pumped Storage Power Station and the technical water supply system monitoring equipment, inspection and debugging of the control equipment involved in the dispatching and control module, setting relevant parameters and preliminary construction of the built-in models of the data analysis module, the hydraulic calculation unit in the dispatching and control module, and the dispatching optimization unit, and debugging and checking the interaction between the information and data interaction module of the dispatching and control module and the communication station network of the intelligent monitoring module; pre-startup is carried out after completing the inspection and debugging of all terminal equipment. If the system prompts that the operating status conditions of the terminal equipment do not meet the specifications, the system will be checked again and the parameters will be reset until the startup conditions are met;

[0192] Step 2: Information collection and operation data monitoring:

[0193] After the system is started, the intelligent monitoring module automatically collects information and measures data from various sensors on the pumped storage power station control center and technical water supply system equipment and pipelines. The collected information from each part is uploaded in real time to the storage unit of the data interaction module to complete the collection of typical historical data for a typical year. During the operation of the system, if the collected pipeline pressure exceeds the set maximum value or the water temperature at the water intake exceeds the set safety temperature, prompts and alarms will be issued in a timely manner at this stage, providing the actual location of the power station where the problem occurs to the power station operation and maintenance personnel, and making decisions on whether to shut down the system for adjustment.

[0194] Step 3: Data analysis and target flow determination:

[0195] The data of the intelligent monitoring module is preprocessed, normalized and new characteristic values are extracted, so as to obtain a group of characteristic values as input, which is input into the mapping relationship between the index data of the technical water supply system and the pumped storage unit trained by the deep learning model based on the typical year historical data and the cooling water demand of each water equipment, to obtain the demand flow of each water equipment, and the data set is transmitted to the scheduling control module as a target parameter and uploaded to the storage unit of the data interaction module for backup;

[0196] Step four: scheduling control model determination and calculation:

[0197] According to the seasonal conditions and the total demand flow, the mode selection is judged, the specific control optimization mode is selected, the system calls the model for operation, the operation result is generated into the scheduling instruction, and then the related pipeline equipment electric valve is adjusted to the corresponding opening and the water pump is adjusted to the corresponding speed;

[0198] Step five: data dynamic update and analysis:

[0199] After the system executes step four, the intelligent monitoring module, the data analysis module and the scheduling control module of the system update and analyze the data;

[0200] Step six: steps two to five are repeatedly executed during the running period after the whole system is started.

[0201] Note that the above is only the preferred embodiment of the present application and the technical principle applied. Those skilled in the art will understand that the present application is not limited to the specific embodiments described herein, and those skilled in the art can make various obvious changes, readjustments and substitutions without departing from the scope of the present application. Therefore, although the present application has been described in more detail through the above embodiments, the present application is not limited to the above embodiments, and can include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the appended claims.

Claims

1. An energy-saving pumped storage power station water supply intelligent control system, characterized in that: Including intelligent monitoring module, data analysis module, scheduling control module, data interaction module, At the same time, all data are uploaded to the database; The data analysis module uses the data collected from the technical water supply system in typical years and trains it through a deep learning model to obtain the mapping relationship between the index data of the technical water supply system and the index data of the pumped storage unit and the cooling water volume required by each water-using equipment. It also uses the partial data collected in real time as input to obtain the flow rate required by each water-using equipment and provide the target adjustment amount for the scheduling control module. The scheduling control module includes a hydraulic calculation unit and a scheduling optimization unit. The hydraulic calculation unit establishes a pipeline loss model based on the branch pipelines where each water-using device in the technical water supply system is located and the devices on the pipelines, and iteratively solves the flow rate. The flow rate is used as the call calculation part of the scheduling optimization unit. The scheduling optimization unit selects different control modes based on actual conditions and user needs. The system is divided according to seasons and selected based on the relationship between the total flow rate required by the water-using devices and the set threshold value. The data interaction module consists of a storage unit and a human-computer interaction unit. The storage unit is used to store and organize the data collected by the technical water supply system, and store the operation log generated by the control results. The human-computer interaction unit is used to retrieve the data from the storage unit and visualize the data. The variable frequency pump model in the hydraulic calculation unit includes the pump's characteristic curves flow-efficiency (Q-η) curve and flow-head (QH) curve. The specific modeling process is as follows: the performance curve at different pump frequency conversions can be expressed as: H=a1Q 2 +a2kQ+a3k 2 ; Where H is the pump head; Q is the total flow of the pump, m 3 / h; η is the pump efficiency; k is the defined speed ratio; n0 is the rated speed; n is the pump operating speed; a1, a2, a3 are the pump flow-head curve parameters obtained by fitting; b1, b2, b3 are the pump flow-efficiency curves; Then solve the motor efficiency and inverter efficiency according to the speed ratio: or m =0.94187×(1-e -9.04k ); or v =0.5087+1.283k-1.42k 2 +0.5834k 3 ; Where η m is the motor efficiency; η v is the motor efficiency; k is the defined speed ratio; e is the natural index; Then, based on the pump flow-head characteristic curve and the pipe network characteristic curve, an equation is established to solve the total power efficiency: N=ρgH w Q w dd m or v ; Where H w is the working head of the water pump; Qw is the working flow of the water pump, m 3 / h;Φ i is the allocation ratio of the i-th water-using equipment; ρ is the water density, unit is kg / m 3 ; g is the acceleration due to gravity m / s -2 ; The scheduling optimization unit system of the scheduling control module has multiple objectives in the summer and large flow modes, including the minimum sum of the differences between the working flow and the demand flow of each water-using equipment pipeline and the minimum total power. The minimum objective function is simplified to a single objective by weighted sum; after setting the water pump speed n to the rated speed, the electric valve opening K of each pipeline and the branch where each water-using equipment is located is calculated. i Perform parameter optimization, its specific scheduling optimization model and optimization solution: Take total power consumption and minimum as the objective function: Where N z is the total power consumption of the water pump; Q i need is the cooling water flow required by the i-th user equipment; Q i w Calculate the optimized flow rate for the i-th water-consuming device; {w1, w2} are the multi-objective parameter weights; Constraints: Speed ​​constraint: n=n0; Lift constraints: Flow constraints of branch lines: Pressure constraints: Total flow constraint: Where n is the speed and n0 is the rated speed; is the maximum flow rate allowed in the pipeline where the i-th water-using equipment is located; is the cooling water flow required by the i-th user equipment; Q t is the calculated total pipeline flow; Q is the total flow threshold of the pipeline in winter & low flow and summer & high flow modes; t max is the maximum flow allowed by the total pipeline; P j max is the maximum pressure value that the j-th node pipeline can withstand; P j min is the minimum pressure value for safe operation of the j-th node pipeline; P j is the pressure value of the j-th node pipeline; Q i w The flow rate calculated from the pipeline where the i-th water-using device is located.

2. The energy-saving pumped storage power station water supply intelligent control system according to claim 1, characterized in that: The intelligent monitoring module uses a set time interval as a sampling frequency to collect water supply system equipment and pipeline information data, as well as some information collected from the pumped storage unit.

3. The energy-saving pumped storage power station water supply intelligent control system according to claim 1, characterized in that: The data analysis module is based on the deep learning of each water-using equipment to obtain the mapping relationship of the required flow rate of the indicators, and the system acquisition module collects the indicators and inputs them into the system to obtain the cooling water flow required by each water-using equipment.

4. The energy-saving pumped storage power station water supply intelligent control system according to claim 1, characterized in that: The hydraulic calculation unit of the scheduling control module is used to establish a technical water supply system pipe network model and a variable frequency pump model and solve the parameter calculations therein: Technical water supply system network model: Based on the various node pipe sections and pipeline equipment of the pumped storage power station technical water supply system, a pipeline hydraulic loss model is established and the flow distribution ratio of the branch pipeline is derived. Then, the hydraulic loss related to the technical water supply main pipeline of the water supply system is calculated and combined with the hydraulic loss of the branch pipeline where each water-using equipment is located to obtain the overall pipeline network characteristic curve; Variable frequency pump model: According to the pump characteristic curve, the flow-efficiency (Q-η) curve and flow-head (QH) curve of the pump at different speeds are obtained, and the speed ratio-motor efficiency (k-η) curve of the motor is established. e ) and the inverter speed ratio-inverter efficiency (k-η b ) curve model.

5. The energy-saving pumped storage power station water supply intelligent control system according to claim 2, characterized in that: The hydraulic calculation unit technology water supply system pipe network model construction includes various hydraulic losses of each pipe. The specific modeling and solution process is as follows: S1. First, the water supply system pipe network model is used to build various hydraulic loss calculation models and then the entire pipe network model is built. Various hydraulic resistances are modeled separately, including: S1a, along-the-line resistance model: When a fluid flows in a pipe, the viscous friction between the fluid and the pipe wall creates resistance to movement, resulting in energy loss, denoted as h f The present invention adopts the Hazen-Williams formula to calculate the hydraulic loss along the way, and its expression is: Where Q is the flow rate, m 3 / h; d is the pipe diameter, in m; L is the pipe length, in m; f is the friction coefficient; m is the flow index, which is 2; b is the pipe diameter index; S1b, Local resistance model: When a fluid encounters local resistance during motion, it generates vortex motion, dissipating a portion of the fluid's mechanical energy, which can be expressed as velocity head: Where A is the cross-sectional area of ​​the pipe, g is the acceleration due to gravity which is 9.81 m / s 2 , Q is the flow rate, m 3 / h, ζ can be determined by empirical formula and actual situation of power station; S1c, Valve local resistance model: The valve resistance coefficient can be defined as: Where h k is the valve hydraulic loss, m; ρ is the water density, unit is kg / m 3 ; g is the acceleration due to gravity m / s -2 ; Reference fitting formula for valve local resistance coefficient: S=A×exp(-K / t)+C; Where K is the valve opening; A, t, and C are constants to be determined; S2. Then build the overall pipe network model based on different resistance models: Calculate the total hydraulic loss of the main pipeline of the water supply system using the total pipe resistance technology. The pipe resistance of the main water supply pipeline mainly considers the resistance along the pipeline and the local resistance: U main =h main / Q total 2 ; Where h main is the total hydraulic loss of the main pipeline of the technical water supply system; f main is the friction coefficient of the main line; d main is the main pipe diameter main is the local resistance coefficient of the main pipeline; A main is the cross-sectional area of ​​the main pipeline, in m 2 ;Q total is the total water volume in the pipeline, m 3 / h; U main is the resistance coefficient of the main line; Secondly, calculate the overall hydraulic loss of each branch pipeline where the water-using equipment is located. The total hydraulic loss of each branch pipeline is the sum of the resistance along the pipeline, the local resistance of the elbow, the local resistance of the valve, and the local resistance of the water-using equipment: Where h i is the total hydraulic loss of the branch pipeline where the i-th water-using equipment is located in the technical water supply system; is the hydraulic loss along the branch pipeline where the i-th water-using equipment is located; h j i is the local hydraulic loss of the branch pipeline where the i-th water-using equipment is located; h k i is the hydraulic loss of the electric valve of the branch pipeline where the i-th water-using equipment is located; f i The friction coefficient of the branch pipe where the i-th water-using equipment is located; d i is the diameter of the branch pipe where the i-th water-using equipment is located, in meters; ζ i is the local resistance coefficient of the branch pipe where the i-th water-using equipment is located; A i The cross-sectional area of ​​the branch pipe where the i-th water-using equipment is located, in m 2 ;Q i is the total water volume in the pipeline, m 3 / h; ρ is the water density, unit is kg / m 3 ;S i is the resistance characteristic number of the valve in the branch pipeline where the i-th water-using equipment is located; The proportion of water allocated to each branch pipe can then be determined based on the resistance of the branch pipe, and the calculation method is: Where U i is the resistance coefficient of the valve in the branch pipeline where the i-th water-using equipment is located, Φ i is the ratio of the flow rate of the branch pipe where the i-th water-using equipment is located; Finally, the characteristic curve of the pipe network is obtained. Since water needs to have a certain amount of energy to reach the water-using equipment through the pipe network, it must overcome the hydraulic loss in the pipe, the upstream and downstream water level difference, and the upstream and downstream water surface pressure difference. When the water energy and these three energies are balanced, the pipe network can operate stably. These three parts of energy can be expressed in the following formula: WITH t =U main +U dis ; Where H G is the total head required by the water supply system, in m, and Q is the total flow rate currently required by the pipe network, in m 3 / h;S t is the tube resistance coefficient, unit is h 2 / m 2 ;H st is the hydrostatic pressure, unit is m; U dis is the total score; λ is the pipe network resistance index coefficient, which is 2.

6. The energy-saving pumped storage power station water supply intelligent control system according to claim 1, characterized in that: The winter & small flow mode adjustment method in the scheduling optimization unit system of the scheduling control module is to keep the valve opening of each water-using equipment unchanged and optimize the water pump speed. Its specific scheduling optimization model and optimization solution are: S1. Calculate the difference between the target demand flow and the current flow: Where dQ i is the difference between the demand flow and the current flow; Q i need is the cooling water flow required by the i-th user equipment; Q i current is the current cooling water flow of the i-th user; S2. Calculate the required water flow rate of the total pipeline based on the current water distribution ratio of each branch network and select the maximum value: Where Q i increase The additional flow rate of the total pipeline required for the i-th water-using equipment; Φ i current The flow distribution ratio of the branch pipe where the i-th water-using equipment is located is obtained based on the hydraulic model; Q m increase For all Q i increase Maximum value; S3. Calculate the water volume adjusted by the water pump. The calculation method is: Where Q Z is the target regulating flow of the pump, k a The safety factor is 1.1 to 1.2; S4. Calculate the target water pump speed: Where n t is the target speed.

7. The energy-saving pumped storage power station technical water supply intelligent control system according to claim 1 is carried out according to the following steps: Step 1: On-site terminal equipment inspection and system startup phase: Inspection, calibration and debugging of the terminal equipment involved in each module of the technical water supply dispatching and control system of the pumped storage power station are carried out, including debugging and checking the information interaction system of the intelligent monitoring module in the control center of the Chushu Pumped Storage Power Station and the technical water supply system monitoring equipment, inspection and debugging of the control equipment involved in the dispatching and control module, setting relevant parameters and preliminary construction of the built-in models of the data analysis module, the hydraulic calculation unit in the dispatching and control module, and the dispatching optimization unit, and debugging and checking the interaction between the information and data interaction module of the dispatching and control module and the communication station network of the intelligent monitoring module; pre-startup is carried out after completing the inspection and debugging of all terminal equipment. If the system prompts that the operating status conditions of the terminal equipment do not meet the specifications, the system will be checked again and the parameters will be reset until the startup conditions are met; Step 2: Information collection and operation data monitoring: After the system is started, the intelligent monitoring module automatically collects information and measures data from various sensors on the pumped storage power station control center and technical water supply system equipment and pipelines. The collected information from each part is uploaded in real time to the storage unit of the data interaction module to complete the collection of typical historical data for a typical year. During the operation of the system, if the collected pipeline pressure exceeds the set maximum value or the water temperature at the water intake exceeds the set safety temperature, prompts and alarms will be issued in a timely manner at this stage, providing the actual location of the power station where the problem occurs to the power station operation and maintenance personnel, and making decisions on whether to shut down the system for adjustment. Step 3: Data analysis and target flow determination: The data from the intelligent monitoring module is preprocessed and normalized, and new eigenvalues ​​are extracted to obtain a set of eigenvalues ​​as input. This is then input into the mapping relationship between the indicator data of the technical water supply system and the pumped storage unit trained based on typical historical data using a deep learning model, and the cooling water volume required by each water-using device. The required flow rate of each water device is then obtained. This data set is then transmitted to the dispatching control module as the target parameter and uploaded to the storage unit of the data interaction module for backup. Step 4: Determine and calculate the scheduling control model: The data analysis module calculates the overall flow rate based on the demand flow of each water device. The system selects a mode based on the seasonal conditions and the total demand flow. After selecting a specific control optimization mode, the system calls the model to perform calculations and generates scheduling instructions based on the calculation results. The electric valves of the relevant pipeline equipment are then adjusted to the corresponding openings and the water pumps are adjusted to the corresponding speeds. Step 5: Dynamic data update and analysis: After the system completes step 4, the system's intelligent monitoring module, data analysis module, and dispatch control module update and analyze the data; Step 6: Repeat steps 2 to 5 throughout the system startup period.

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