Intelligent control method and device of power generation system

Abstract

This application discloses an intelligent control method and device for a power generation system, belonging to the field of pipeline energy control technology. By acquiring operational data from multiple pipeline nodes and sections, the equivalent energy storage state quantities of these nodes and sections are determined based on the operational data. This yields a distribution matrix of the energy storage state quantities of the urban pipeline system. Based on this distribution matrix, target pipeline nodes and / or target sections, along with their corresponding target energy fluctuation periods, are identified. This allows for the determination of energy release time windows and the generation of a power generation control strategy to control the power generation system. This achieves global quantitative perception, dynamic fluctuation identification, power generation time window determination, and targeted recovery and power generation of dispersed energy in the urban pipeline system. It overcomes technical problems such as dispersed energy representation, insufficient adaptability to dynamic energy fluctuations, and lack of energy release timing identification, thereby improving the overall energy utilization efficiency of the urban pipeline system.

Description

Technical Field

[0001] This application belongs to the field of pipeline energy regulation technology, specifically relating to an intelligent regulation method, device, electronic equipment, and storage medium for a power generation system. Background Technology

[0002] Urban pipeline systems (including water supply, heating, and gas supply) serve as core infrastructure for urban energy and resource transmission and distribution, containing a large amount of recyclable energy in the form of pressure potential energy, thermal energy, and kinetic energy. With the increasing demand for refined urban energy management, effectively identifying, extracting, and utilizing the dynamically changing energy storage within the pipeline network has become a crucial issue for optimizing the operation of urban energy systems.

[0003] However, the operational data in urban pipeline systems, such as physical quantities like pressure, flow, and temperature, involve multiple forms of energy. The mapping relationship between each physical quantity and available energy is complex, and energy fluctuations are frequent and time-varying during pipeline operation. Existing technologies mostly rely on fixed threshold judgment methods, which are insufficient to adapt to dynamic fluctuations and make it difficult to achieve flexible identification and effective utilization of pipeline energy fluctuations. Summary of the Invention

[0004] The purpose of this application is to provide an intelligent control method and device for a power generation system, which can solve technical problems such as dispersed energy representation, insufficient adaptability to dynamic energy fluctuations, and lack of energy release timing identification.

[0005] To solve the above-mentioned technical problems, this application is implemented as follows: In a first aspect, embodiments of this application provide an intelligent control method for a power generation system, applied to an urban pipeline network system, the urban pipeline network system including multiple pipeline nodes and multiple pipeline segments, the method comprising: Obtain operational data for the multiple pipeline nodes and multiple pipeline segments; Based on the operational data, the equivalent energy storage state quantities of the multiple pipeline nodes and multiple pipeline segments are determined, and based on the equivalent energy storage state quantities, the energy storage state quantity distribution matrix of the urban pipeline network system is obtained. Based on the energy storage state quantity distribution matrix, the target pipeline node and / or target pipeline segment and the corresponding target energy fluctuation period are determined, and the energy release time window is determined based on the target energy fluctuation period. Based on the target pipeline node, and / or the target pipeline segment and the energy release time window, a power generation control strategy is generated, and the power generation system is controlled to generate electricity according to the power generation control strategy.

[0006] Optionally, the operational data includes multiple physical quantities related to energy. Based on the operational data, the equivalent energy storage state quantities of the multiple pipeline nodes and multiple pipeline segments are determined, and based on the equivalent energy storage state quantities, the energy storage state quantity distribution matrix of the urban pipeline network system is obtained, including: Based on the correspondence between the multiple physical quantities and energy, the operating data is converted into energy to obtain the corresponding energy characterization parameters; Based on the energy characterization parameters, the equivalent energy storage state quantities of the multiple pipeline nodes and multiple pipeline segments are determined. Based on the network topology of the urban pipeline system and the equivalent energy storage state quantity, the distribution matrix of the energy storage state quantity of the urban pipeline system is obtained.

[0007] Optionally, the plurality of physical quantities include pressure, flow rate, and temperature. Based on the energy characterization parameters, the equivalent energy storage state quantities of the plurality of pipeline nodes and the plurality of pipeline segments are determined, including: For each pipeline node and each pipe segment, the energy characterization parameters corresponding to the pressure, flow rate, and temperature are weighted to obtain the equivalent energy storage state quantity for each pipeline node and each pipe segment.

[0008] Optionally, based on the energy storage state quantity distribution matrix, the target pipeline node, and / or target pipeline segment, and the corresponding target energy fluctuation period are determined, including: Based on the energy storage state quantity distribution matrix, time difference calculation is performed on the multiple pipeline nodes and multiple pipeline segments to obtain the corresponding energy state difference sequence. Based on the energy state difference sequence and the preset fluctuation threshold, candidate pipeline nodes and / or candidate pipeline segments are determined from the multiple pipeline nodes and multiple pipeline segments; Based on the energy state difference sequence of the candidate pipeline nodes and / or the candidate pipeline segments, the corresponding candidate energy fluctuation period is determined; Based on the preset average amplitude and preset duration, a target energy fluctuation period is determined from the candidate energy fluctuation periods corresponding to the candidate pipeline nodes and / or the candidate pipe segments, and the candidate pipeline nodes and / or the candidate pipe segments corresponding to the target energy fluctuation period are taken as the target pipeline nodes and / or the target pipe segments.

[0009] Optionally, based on the target energy fluctuation period, an energy release time window is determined, including: Obtain the historical equivalent energy storage state sequence of the target pipeline node and / or the target pipeline segment within a preset historical time period, and determine historical fluctuation information based on the historical equivalent energy storage state sequence; Obtain the current load change information of the urban pipeline network system; Based on the historical fluctuation information and the current load change information, the target energy fluctuation period corresponding to the target pipeline node and / or the target pipeline segment is continuously predicted, and the energy release time window corresponding to the target pipeline node and / or the target pipeline segment is determined according to the prediction results.

[0010] Optionally, the power generation system includes a power generation storage device, a power generation unit, and a pipeline regulation device. Based on the target pipeline node and / or the target pipeline segment and the energy release time window, a power generation control strategy is generated, and the power generation system is controlled to generate electricity according to the power generation control strategy, including: Based on the target pipeline node, and / or the target pipeline segment and the energy release time window, a power generation control strategy is generated for the energy storage device, the power generation device and the pipeline regulation device. The energy storage device, the power generation device, and the pipeline regulation device are controlled to operate in coordination according to the power generation control strategy.

[0011] Optionally, it also includes: During the coordinated operation of the energy storage device, the power generation device and the pipeline regulation device according to the power generation control strategy, the safety parameters corresponding to the target pipeline node and / or the target pipeline segment are monitored to obtain the safety parameter monitoring values. Based on a preset safety threshold, it is determined whether the monitored value of the safety parameter triggers a safety warning, and if the safety parameter value triggers a safety warning, the power generation control strategy is adjusted.

[0012] Optionally, adjusting the power generation control strategy includes: The adjustment range of the pipeline regulating equipment and the energy extraction power of the power generation device are reduced according to the preset adjustment ratio, or the charging and discharging operation of the energy storage device is suspended.

[0013] Optionally, it also includes: Based on the energy storage state quantity distribution matrix, the equivalent energy storage state quantity of each pipeline node is obtained. Based on the equivalent energy storage state of each pipeline node and the topology of the urban pipeline system, the multiple pipeline nodes are divided into one or more node partitions.

[0014] Optionally, it also includes: For each node partition, determine the target partition node, and / or target partition pipe segment and the corresponding local energy release time window, and generate the corresponding local power generation control strategy.

[0015] Optionally, it also includes: The equivalent energy storage state quantities between different node partitions are monitored to obtain the difference in equivalent energy storage state quantities between adjacent node partitions. If the difference in the equivalent energy storage state quantity is greater than a preset gradient threshold, energy transfer operation is performed on the adjacent node partitions.

[0016] Secondly, embodiments of this application provide an intelligent control device for a power generation system, applied to an urban pipeline network system, the urban pipeline network system including multiple pipeline nodes and multiple pipeline segments, the device comprising: The data acquisition module is used to acquire the operating data of the multiple pipeline nodes and multiple pipeline segments; The energy distribution module is used to determine the equivalent energy storage state of the multiple pipeline nodes and multiple pipeline segments based on the operating data, and to obtain the energy storage state distribution matrix of the urban pipeline system based on the equivalent energy storage state. The window determination module is used to determine the target pipeline node and / or target pipeline segment and the corresponding target energy fluctuation period based on the energy storage state quantity distribution matrix, and to determine the energy release time window based on the target energy fluctuation period; The strategy control module is used to generate a power generation control strategy based on the target pipeline node and / or the target pipeline segment and the energy release time window, and control the power generation system to generate electricity according to the power generation control strategy.

[0017] Thirdly, embodiments of this application provide an electronic device including a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the method described in the first aspect.

[0018] Fourthly, embodiments of this application provide a readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method described in the first aspect.

[0019] Fifthly, embodiments of this application provide a chip, the chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the method as described in the first aspect.

[0020] In this embodiment, by acquiring the operational data of the multiple pipeline nodes and multiple pipe segments, the equivalent energy storage state of the multiple pipeline nodes and multiple pipe segments is determined based on the operational data. Based on the equivalent energy storage state, an energy storage state distribution matrix of the urban pipeline system is obtained. Based on the energy storage state distribution matrix, target pipeline nodes and / or target pipe segments and corresponding target energy fluctuation periods are determined. Based on the target energy fluctuation periods, an energy release time window is determined. Based on the target pipeline nodes and / or target pipe segments and the energy release time window, a power generation control strategy is generated. The power generation system is then controlled to generate electricity according to the power generation control strategy. This achieves global quantitative perception, dynamic fluctuation identification, power generation time window determination, and targeted recovery and power generation of dispersed energy in the urban pipeline system. This overcomes technical problems such as dispersed energy representation, insufficient adaptability to dynamic energy fluctuations, and lack of energy release timing identification, thereby improving the overall energy utilization efficiency of the urban pipeline system. Attached Figure Description

[0021] To more clearly illustrate the technical solution of this application, the drawings used in the description of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart of the steps of an intelligent control method for a power generation system provided in some embodiments of this application; Figure 2 This is a structural block diagram of an intelligent control device for a power generation system provided in some embodiments of this application; Figure 3 This is a schematic diagram of the hardware structure of an electronic device provided in some embodiments of this application. Detailed Implementation

[0023] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0024] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0025] The intelligent control method for a power generation system provided in this application will be described in detail below with reference to the accompanying drawings, through specific embodiments and application scenarios.

[0026] Reference Figure 1 This document illustrates a flowchart of steps in an intelligent control method for a power generation system according to some embodiments of this application. The method is applied to an urban pipeline network system, which includes multiple pipeline nodes and multiple pipeline segments. Specifically, it may include the following steps: Step 101: Obtain the operating data of the multiple pipeline nodes and multiple pipeline segments.

[0027] In step 101, the urban pipeline network system may include multiple pipeline nodes and multiple pipe segments. There are multiple sources of operational data on the multiple pipeline nodes and multiple pipe segments. In order to obtain the operational data of the multiple pipeline nodes and multiple pipe segments, corresponding sensors can be installed on the multiple pipeline nodes and multiple pipe segments to obtain the multi-source operational data.

[0028] Step 102: Based on the operating data, determine the equivalent energy storage state quantities of the multiple pipeline nodes and multiple pipeline segments, and based on the equivalent energy storage state quantities, obtain the energy storage state quantity distribution matrix of the urban pipeline network system.

[0029] In step 102, after acquiring the multi-source operating data of multiple pipeline nodes and multiple pipeline segments, the multi-source operating data can be converted into energy to determine the equivalent energy storage state quantity corresponding to the multi-source operating data of multiple pipeline nodes and multiple pipeline segments. After determining the equivalent energy storage state quantity corresponding to the multi-source operating data of multiple pipeline nodes and multiple pipeline segments, a distribution matrix of energy storage state quantity of the urban pipeline network system for multiple pipeline nodes and multiple pipeline segments can be formed.

[0030] In some embodiments of this application, the operational data includes multiple physical quantities associated with energy. Based on the operational data, the equivalent energy storage state quantities of the multiple pipeline nodes and multiple pipeline segments are determined, and based on the equivalent energy storage state quantities, the energy storage state quantity distribution matrix of the urban pipeline network system is obtained, including: Sub-step 11: Based on the correspondence between the multiple physical quantities and energy, the running data is converted into energy to obtain the corresponding energy characterization parameters.

[0031] Multi-source operational data can include multiple physical quantities, such as pressure, flow rate, and temperature. In other words, multi-source operational data can include pressure data, flow rate data, and temperature data.

[0032] As an example, pressure data can be collected by pressure sensors deployed at various pipeline nodes and sections, with a fixed sampling period (e.g., 1 minute) to obtain real-time pressure values ​​and form a corresponding pressure time series. Flow data can be collected by flow meters to obtain instantaneous flow data of each pipeline section, recording the fluid flow direction and velocity to form a pipeline flow time series. Temperature data can be collected by temperature sensors at various pipeline nodes in heating or process pipelines to obtain the heat energy distribution status.

[0033] In addition, multi-source operation data can also include equipment operation status data. Equipment operation status data can be collected through SCADA (Supervisory Control And Data Acquisition) systems or equipment control interfaces to collect operation status parameters of pump stations, valves, energy storage devices and power generation devices in the pipeline network, including equipment on / off status, operating power, cumulative running time, etc.

[0034] In sub-step 11, based on the physical correspondence between various physical quantities and energy, the acquired multi-source operating data can be converted into energy correlation. Pressure data is converted into pressure potential energy contained in a unit volume of fluid, flow data is converted into fluid kinetic energy by combining pipe section cross-sectional parameters, and temperature data is converted into thermal energy equivalent by combining fluid heat capacity parameters. All energy conversion results are uniformly converted to the same dimension to form a unified set of energy characterization parameters.

[0035] Sub-step 12: Based on the energy characterization parameters, determine the equivalent energy storage state quantities of the multiple pipeline nodes and multiple pipeline segments.

[0036] In sub-step 12, after obtaining the corresponding energy characterization parameters, the equivalent energy storage state quantities corresponding to multiple network nodes and multiple pipe segments in the urban pipeline network system can be determined based on the energy characterization parameters.

[0037] In some embodiments of this application, the equivalent energy storage state quantities of the plurality of pipeline nodes and the plurality of pipeline segments are determined based on the energy characterization parameters, including: For each pipeline node and each pipe segment, the energy characterization parameters corresponding to the pressure, flow rate, and temperature are weighted to obtain the equivalent energy storage state quantity for each pipeline node and each pipe segment.

[0038] Specifically, the equivalent energy storage state quantity E(i, t) can comprehensively reflect the following three types of energy: first, pressure potential energy derived from the pressure in the urban pipeline network; second, kinetic energy derived from the fluid flow in the urban pipeline network; and third, thermal equivalent energy derived from the fluid temperature in the urban pipeline network. These three types of energy can be weighted and superimposed based on the actual release ratio of each component under the current operating state of the urban pipeline network, thereby obtaining an equivalent energy storage state quantity that can uniformly characterize the releaseable energy of nodes and pipe segments.

[0039] In E(i, t), i is the pipeline node or pipeline segment number, and t is the current time.

[0040] Sub-step 13: Based on the network topology of the urban pipeline system and the equivalent energy storage state quantity, obtain the energy storage state quantity distribution matrix of the urban pipeline system.

[0041] In sub-step 13, after obtaining the equivalent energy storage state quantities corresponding to multiple network nodes and multiple pipe segments in the urban pipeline network system, the equivalent energy storage state quantities of multiple network nodes and multiple pipe segments can be spatially correlated by combining the network topology of the urban pipeline network system, thereby forming an energy storage state quantity distribution matrix covering the entire urban pipeline network.

[0042] By uniformly converting multiple physical quantities such as pressure, flow rate, and temperature into energy characterization parameters, and constructing an equivalent energy storage state quantity and energy storage state quantity distribution matrix covering the urban pipeline network, a global quantitative description of the energy distribution state within the urban pipeline network is achieved, overcoming the shortcomings of the dispersed energy characterization of multiple physical quantities in existing technologies.

[0043] Step 103: Based on the energy storage state quantity distribution matrix, determine the target pipeline node and / or target pipeline segment and the corresponding target energy fluctuation period, and based on the target energy fluctuation period, determine the energy release time window.

[0044] In step 103, after obtaining the energy storage state quantity distribution matrix, the difference in equivalent energy storage state quantities between adjacent moments can be calculated based on the continuous change process of the energy storage state quantity distribution matrix. Energy fluctuations are then determined by combining this with a preset fluctuation threshold. Target energy fluctuation periods suitable for energy recovery are selected based on a preset average amplitude and a preset duration. Then, based on the variation patterns of equivalent energy storage state quantities within a preset historical period and the current load change information of the urban pipeline network system, the persistence and development direction of the target energy fluctuation periods are inferred to determine the energy release time window.

[0045] In some embodiments of this application, based on the energy storage state quantity distribution matrix, the target pipeline node, and / or target pipeline segment, and the corresponding target energy fluctuation period are determined, including: Sub-step 21: Based on the energy storage state quantity distribution matrix, perform time difference calculation on the multiple pipeline nodes and multiple pipeline segments to obtain the corresponding energy state difference sequence.

[0046] In sub-step 21, specifically, at multiple consecutive sampling times, the equivalent energy storage state quantity E(i, t) of each pipeline node and pipe segment is calculated using time difference to obtain the corresponding energy state difference sequence ΔE(i, t) = E(i, t) - E(i, t-1) for adjacent times, which is used to reflect the instantaneous changes in energy of each pipeline node and pipe segment.

[0047] Sub-step 22: Based on the energy state difference sequence and the preset fluctuation threshold, determine candidate pipeline nodes and / or candidate pipeline segments from the multiple pipeline nodes and multiple pipeline segments.

[0048] In sub-step 22, after obtaining the energy state difference sequence corresponding to each pipeline node and pipe segment, a preset fluctuation threshold εE can be set. When |ΔE(i, t)|>εE, it is determined that the pipeline node or pipe segment has experienced energy fluctuation at the current moment; otherwise, it is determined to be in a stable energy state. Furthermore, candidate pipeline nodes and / or candidate pipe segments experiencing energy fluctuations can be identified. Here, the preset fluctuation threshold is not specifically limited and can be set according to actual conditions.

[0049] Sub-step 23: Based on the energy state difference sequence of the candidate pipeline nodes and / or the candidate pipeline segments, determine the corresponding candidate energy fluctuation period.

[0050] In sub-step 23, after determining the candidate network nodes and / or candidate pipe segments where energy fluctuations occur, the energy state difference sequences corresponding to the candidate network nodes and / or candidate pipe segments can be combined to perform a continuity analysis on the energy state difference sequences that are determined to have energy fluctuations, so as to extract the duration of the fluctuations, that is, to determine the corresponding candidate energy fluctuation periods.

[0051] Sub-step 24: Based on the preset average amplitude and preset duration, determine the target energy fluctuation period from the candidate energy fluctuation periods corresponding to the candidate pipeline nodes and / or the candidate pipe segments, and take the candidate pipeline nodes and / or candidate pipe segments corresponding to the target energy fluctuation period as the target pipeline nodes and / or target pipe segments.

[0052] In sub-step 24, after determining the candidate pipeline nodes and / or the candidate energy fluctuation periods corresponding to the candidate pipe segments, the average fluctuation amplitude and duration of each candidate energy fluctuation period can be calculated. Then, based on preset average amplitude and preset duration as dual screening conditions—that is, the average fluctuation amplitude must be greater than or equal to the preset average amplitude, and the duration must be greater than or equal to the preset duration—target energy fluctuation periods that meet the conditions can be screened out. The candidate pipeline nodes and / or candidate pipe segments corresponding to the target energy fluctuation periods are the target pipeline nodes and / or target pipe segments. Here, the preset average amplitude and preset duration are not specifically limited and can be set according to actual conditions.

[0053] As can be seen, the fluctuation identification method based on the calculation of the difference in equivalent energy storage state quantities and the determination of preset fluctuation thresholds does not require the establishment of a complex pipeline physical model. It can complete the screening of target energy fluctuation periods by relying solely on data-driven methods, which significantly reduces the difficulty of actual engineering deployment. In some embodiments of this application, determining the energy release time window based on the target energy fluctuation period includes: Sub-step 31: Obtain the historical equivalent energy storage state sequence of the target pipeline node and / or the target pipeline segment within a preset historical time period, and determine the historical fluctuation information based on the historical equivalent energy storage state sequence.

[0054] In sub-step 31, the historical equivalent energy storage state quantity sequence corresponding to the target pipeline node and / or target pipeline segment within a preset historical period can be obtained, and its typical change direction, magnitude and duration can be analyzed to determine the historical fluctuation information corresponding to the target pipeline node and / or target pipeline segment.

[0055] Sub-step 32: Obtain the current load change information of the urban pipeline network system.

[0056] In sub-step 32, the real-time changes in the current urban pipeline system load (water consumption, heat consumption, gas consumption, etc.) can be obtained, the direction (rise / fall) and rate of change of load can be analyzed, and the energy demand trend driven by the load can be determined, that is, the current load change information of the urban pipeline system can be obtained.

[0057] Sub-step 33: Based on the historical fluctuation information and the current load change information, continuously predict the target energy fluctuation period corresponding to the target pipeline node and / or the target pipeline segment, and determine the energy release time window corresponding to the target pipeline node and / or the target pipeline segment according to the prediction results.

[0058] In sub-step 33, the historical fluctuation information and current load change information, the target pipeline node, and / or the target energy fluctuation period corresponding to the target pipeline segment can be combined to predict the continuity (whether the expected fluctuation range will continue) and the development direction (whether the equivalent energy storage state quantity will further increase or decrease). If the historical fluctuation information shows that this type of fluctuation usually lasts for a long time and the change direction of the current load change information is consistent with the energy release direction, then the target pipeline node and / or the energy release time window corresponding to the target pipeline segment are determined.

[0059] As can be seen, by using a trend inference mechanism that integrates historical fluctuation information with current load change information, potential energy release time windows can be identified in advance, avoiding energy waste caused by regulatory lag, and helping to improve the energy recovery and utilization rate of urban pipeline networks.

[0060] Step 104: Based on the target pipeline node and / or the target pipeline segment and the energy release time window, generate a power generation control strategy, and control the power generation system to generate electricity according to the power generation control strategy.

[0061] In step 104, after determining the target pipeline node and / or target pipeline segment and the energy release time window, an electrical control strategy can be generated, and the power generation system can be controlled to generate electricity according to the power generation control strategy.

[0062] It should be further noted that the total number of the identified target pipeline nodes and / or target pipeline segments can be one or more.

[0063] In some embodiments of this application, the power generation system includes a power generation storage device, a power generation unit, and a pipeline regulation device. Based on the target pipeline node and / or the target pipeline segment and the energy release time window, a power generation control strategy is generated, and the power generation system is controlled to generate electricity according to the power generation control strategy, including: Sub-step 41: Based on the target pipeline node and / or the target pipeline segment and the energy release time window, generate the power generation control strategy for the energy storage device, the power generation device and the pipeline regulation device.

[0064] In sub-step 41, the power generation system installed in the urban pipeline network system may include pipeline regulation equipment (valves, pumping stations, etc.), power generation devices, and energy storage devices. Power generation control strategies for the energy storage devices, the power generation devices, and the pipeline regulation equipment can be generated based on the target pipeline node and / or target pipeline segment and the energy release time window.

[0065] Specifically, the total number of target pipeline nodes and / or target pipeline segments can be one or more. Therefore, the corresponding energy release time window can also be one or more. Thus, the target time window can be further determined with the goal of maximizing energy recovery and power generation utilization within the energy release time window, so as to regulate the power generation system within the target time window. Power generation control strategies for energy storage devices, power generation devices, and pipeline regulation equipment can be generated according to preset control rules.

[0066] As an example, in a power generation control strategy, pipeline regulation equipment can adjust the opening degree of upstream valves or pump station output of target pipeline nodes and / or target pipeline segments to moderately increase the energy gradient of target pipeline nodes and / or target pipeline segments within a safe range, creating favorable conditions for energy release; power generation devices can start or adjust the operating power of power generation devices (such as differential pressure generators or thermal power generation units) according to the equivalent energy storage state level of target pipeline nodes and / or target pipeline segments, converting the urban pipeline energy gradient into electrical energy output; energy storage devices can dynamically adjust the charging and discharging state of energy storage devices according to the real-time relationship between the output power of power generation devices and the system's electricity demand, smoothing power generation fluctuations and achieving stable output and local consumption of generated energy.

[0067] The preset control rules can be a set of standardized control logic, action execution instructions, and core parameter thresholds used to generate a city-wide coordinated control strategy. These rules are based on the overall safe operation constraints of the urban pipeline network, the working characteristics of energy storage devices, power generation devices, and pipeline regulation equipment, as well as the energy recovery and efficient power generation utilization control objectives of coordinated energy storage at pipeline nodes and sections. The preset control rules use the equivalent energy storage state of each pipeline node and section, the energy fluctuation characteristics of the interval, and the energy release time window as core judgment criteria to clarify the control actions, adjustment ranges, and execution sequences of each device for pipeline nodes and sections under different urban pipeline energy states, providing an initial control benchmark for the power generation system.

[0068] Sub-step 42: Control the energy storage device, the power generation device, and the pipeline regulation device to operate in coordination according to the power generation control strategy.

[0069] In sub-step 42, the energy storage device, the power generation device, and the pipeline regulation equipment are controlled to operate collaboratively according to the power generation control strategy. Specifically, the target path of fluid between upstream regulation points, target pipeline nodes, and / or pipe segments can be determined by the topology of the urban pipeline network. Then, the pipeline regulation equipment corresponding to the upstream regulation point is adjusted (e.g., closing upstream valves or increasing the output of upstream pumping stations) to create a pressure difference between the upstream regulation point and the target pipeline node and / or pipe segment: the upstream pressure increases, and the pressure on the target pipeline node and / or pipe segment side decreases relatively, thereby forming an artificial energy gradient locally in the urban pipeline network. Subsequently, driven by the artificial energy gradient, the fluid in the urban pipeline network will naturally flow from high pressure areas to low pressure areas along the target path.

[0070] As can be seen, the coordinated control of energy storage devices, power generation units, and pipeline regulation equipment, through artificial guidance of the local energy gradient in the pipeline network, enables the directional release and efficient conversion of the energy contained in the urban pipeline network into electrical energy, thus expanding the technological pathways for the energy utilization of urban pipeline networks. In this embodiment, by acquiring the operational data of the multiple pipeline nodes and multiple pipe segments, the equivalent energy storage state of the multiple pipeline nodes and multiple pipe segments is determined based on the operational data. Based on the equivalent energy storage state, an energy storage state distribution matrix of the urban pipeline system is obtained. Based on the energy storage state distribution matrix, target pipeline nodes and / or target pipe segments and corresponding target energy fluctuation periods are determined. Based on the target energy fluctuation periods, an energy release time window is determined. Based on the target pipeline nodes and / or target pipe segments and the energy release time window, a power generation control strategy is generated. The power generation system is then controlled to generate electricity according to the power generation control strategy. This achieves global quantitative perception, dynamic fluctuation identification, power generation time window determination, and targeted recovery and power generation of dispersed energy in the urban pipeline system. This overcomes technical problems such as dispersed energy representation, insufficient adaptability to dynamic energy fluctuations, and lack of energy release timing identification, thereby improving the overall energy utilization efficiency of the urban pipeline system.

[0071] In some embodiments of this application, it also includes: Step 201: During the coordinated operation of the energy storage device, the power generation device and the pipeline regulation device according to the power generation control strategy, the safety parameters corresponding to the target pipeline node and / or the target pipeline segment are monitored to obtain the safety parameter monitoring values.

[0072] In step 201, during the coordinated operation of the energy storage device, power generation unit, and pipeline regulation equipment according to the power generation control strategy, the target pipeline node and / or the safety parameters corresponding to the target pipeline segment can be continuously monitored at high frequency (e.g., every 30 seconds). The safety parameters may include pressure value P(i, t) and flow rate value Q(i, t).

[0073] Step 202: Based on a preset safety threshold, determine whether the monitored value of the safety parameter triggers a safety warning, and if the safety parameter value triggers a safety warning, adjust the power generation control strategy.

[0074] In step 202, a preset safety threshold can be used to determine whether the monitored value of the safety parameter triggers a safety warning. If the safety parameter value triggers a safety warning, the power generation control strategy can be adjusted.

[0075] As an example, the preset safety thresholds may include pressure safety thresholds and flow safety thresholds. Both pressure safety thresholds and flow safety thresholds can be ranges containing upper and lower limits, such as pressure safety ranges [Pmin, Pmax] and flow safety ranges [Qmin, Qmax]. When any safety monitoring value enters the warning range of the safety range (such as reaching 90% of the upper limit or 110% of the lower limit), a safety warning is triggered, and the power generation control strategy is adjusted.

[0076] In some embodiments of this application, adjusting the power generation control strategy includes: The adjustment range of the pipeline regulating equipment and the energy extraction power of the power generation device are reduced according to the preset adjustment ratio, or the charging and discharging operation of the energy storage device is suspended.

[0077] Specifically, when the pressure or flow rate approaches the warning range of the safe range, the adjustment range of the pipeline regulation equipment and the energy extraction power of the power generation device can be reduced according to the preset adjustment ratio, or the charging and discharging operation of the energy storage device can be suspended, so that the pipeline status returns to the safe operating range; if the pressure or flow rate returns to the normal range, the execution of the original power generation control strategy can be gradually restored.

[0078] The mechanism continuously monitors pressure and flow during the execution of the power generation strategy and dynamically limits the intensity of the power generation control strategy execution to ensure that the operation of the power generation control strategy is always carried out within the safe operation boundary of the pipeline network, effectively preventing urban pipeline network anomalies caused by the execution of the power generation control strategy.

[0079] In some embodiments of this application, it also includes: Step 301: Based on the energy storage state quantity distribution matrix, obtain the equivalent energy storage state quantity of each pipeline node.

[0080] In step 301, the equivalent energy storage state quantity of each pipeline node can be obtained based on the energy storage state quantity distribution matrix of the urban pipeline network system.

[0081] Step 302: Based on the equivalent energy storage state of each pipeline node and the topology of the urban pipeline system, divide the multiple pipeline nodes into one or more node partitions.

[0082] In step 302, based on the equivalent energy storage state quantity of each pipeline node and the topology of the urban pipeline system, an energy state clustering method (such as a region merging algorithm based on energy state similarity) can be used to classify pipeline nodes and pipe segments with similar equivalent energy storage state quantities and connected topologies into the same partition, forming several node partitions with relatively uniform energy distribution.

[0083] In some embodiments of this application, it also includes: For each node partition, determine the target partition node, and / or target partition pipe segment and the corresponding local energy release time window, and generate the corresponding local power generation control strategy.

[0084] Specifically, within each node partition, the generated local collaborative control strategy can be executed independently based on the distribution of equivalent energy storage state quantity and the target energy fluctuation period of the node partition. This allows the control parameters of each node partition to be independent of each other, avoiding the neglect of local characteristics by the global single control strategy.

[0085] In some embodiments of this application, it also includes: Step 303: Monitor the equivalent energy storage state quantity between different node partitions to obtain the difference value of the equivalent energy storage state quantity between adjacent node partitions.

[0086] In step 303, the equivalent energy storage state quantity between different node partitions can be monitored to obtain the dynamic changes of the equivalent energy storage state quantity of each node partition, and then the difference value of the equivalent energy storage state quantity of adjacent node partitions can be obtained.

[0087] Step 304: If the difference in the equivalent energy storage state quantity is greater than a preset gradient threshold, perform energy transfer operation on the adjacent node partition.

[0088] In step 304, when a significant energy gradient appears between adjacent node partitions, that is, when the difference in equivalent energy storage state quantity is greater than the preset gradient threshold, the redundant energy of the high-energy partition can be transferred to the low-energy partition by adjusting the valves or pump stations at the boundary of the two adjacent node partitions, thereby achieving cross-partition energy balance and improving the overall energy utilization efficiency of the entire network.

[0089] Based on the uneven distribution of equivalent energy storage state quantity, the urban pipeline network node zoning and node inter-regional coordination mechanism enables the power generation control strategy to take into account both local energy characteristics and the overall balance of the entire network. It is especially suitable for large-scale urban pipeline networks with numerous nodes and significant differences in energy distribution.

[0090] Furthermore, the method described above in this application may also include feedback correction and adaptive rule adjustment, as detailed below. (1) Data acquisition after regulation: After each power generation control strategy is completed, the equivalent energy storage state of each pipeline node and pipeline segment is recalculated by acquiring multi-source operation data and actual urban pipeline operation data after regulation, and the energy storage state distribution matrix after regulation is formed.

[0091] (2) Comparison of regulation effect: Compare the energy storage state quantity distribution matrix after regulation with the energy storage state quantity distribution matrix before regulation, calculate the deviation ΔEerr(i) between the energy recovery amount of each target pipeline node and / or target pipeline segment and the expected value, and the deviation ΔPerr between the actual output power of the power generation device and the strategy setting value.

[0092] (3) Rule adaptive adjustment: Based on the deviation results, the following two types of rules are adaptively corrected: Energy correlation conversion rule correction: If there is a systematic deviation between the energy characterization parameters and the actual recoverable energy, the energy conversion coefficient of each physical quantity will be corrected according to a certain preset ratio so that the conversion result can more accurately reflect the actual energy level of the pipeline network.

[0093] Regulation rule correction: If there is a deviation between the power generation or energy storage charging and discharging and the expected target, the parameters such as the valve opening adjustment, the power setting value of the power generation device, and the energy storage charging and discharging power threshold in the power generation control strategy will be adjusted according to the direction and magnitude of the deviation, so that the regulation effect gradually approaches the target value.

[0094] By comparing the actual effects of each power generation control strategy cycle and adaptively adjusting the rules, the energy correlation conversion rules and control rules will adaptively evolve with the changes in the actual operating characteristics of the urban pipeline network system, gradually improving the control accuracy and forming a long-term optimization mechanism with self-learning capabilities.

[0095] Existing urban pipeline network control strategies generally lack regional coordination mechanisms. When dealing with large-scale pipeline networks with uneven energy distribution, a single global control strategy struggles to balance local energy balance with overall optimization goals. Furthermore, the control process lacks closed-loop adaptive correction capabilities, preventing continuous correction of control deviations and limiting the long-term operational efficiency of the system. This application presents an intelligent control method that achieves unified energy representation of multiple physical quantities, dynamic identification of urban pipeline network energy fluctuations, trend inference to guide energy release time windows, coordinated control of energy storage and power generation devices, and continuous optimization through regional control and closed-loop correction. This method aims to fully tap the potential of urban pipeline network energy storage and power generation, thereby improving the overall utilization efficiency of the urban energy system.

[0096] In this embodiment, by acquiring the operational data of the multiple pipeline nodes and multiple pipe segments, the equivalent energy storage state of the multiple pipeline nodes and multiple pipe segments is determined based on the operational data. Based on the equivalent energy storage state, an energy storage state distribution matrix of the urban pipeline system is obtained. Based on the energy storage state distribution matrix, target pipeline nodes and / or target pipe segments and corresponding target energy fluctuation periods are determined. Based on the target energy fluctuation periods, an energy release time window is determined. Based on the target pipeline nodes and / or target pipe segments and the energy release time window, a power generation control strategy is generated. The power generation system is then controlled to generate electricity according to the power generation control strategy. This achieves global quantitative perception, dynamic fluctuation identification, power generation time window determination, and targeted recovery and power generation of dispersed energy in the urban pipeline system. This overcomes technical problems such as dispersed energy representation, insufficient adaptability to dynamic energy fluctuations, and lack of energy release timing identification, thereby improving the overall energy utilization efficiency of the urban pipeline system.

[0097] It should be noted that, for the sake of simplicity, the method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments of this application are not limited to the described order of actions, because according to the embodiments of this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of this application.

[0098] Reference Figure 2 This paper illustrates a structural schematic diagram of an intelligent control device for a power generation system according to some embodiments of this application. The device is applied to an urban pipeline network system, which includes multiple pipeline nodes and multiple pipeline segments. Specifically, it may include the following modules: The data acquisition module 201 is used to acquire the operating data of the multiple pipeline nodes and multiple pipeline segments; The energy distribution module 202 is used to determine the equivalent energy storage state of the multiple pipeline nodes and multiple pipeline segments based on the operating data, and to obtain the energy storage state distribution matrix of the urban pipeline system based on the equivalent energy storage state. The window determination module 203 is used to determine the target pipeline node and / or target pipeline segment and the corresponding target energy fluctuation period based on the energy storage state quantity distribution matrix, and to determine the energy release time window based on the target energy fluctuation period; The strategy control module 204 is used to generate a power generation control strategy based on the target pipeline node and / or the target pipeline segment and the energy release time window, and control the power generation system to generate electricity according to the power generation control strategy.

[0099] In one embodiment of this application, the operating data includes multiple physical quantities associated with energy, and the energy distribution module 202 includes: The parameter conversion submodule is used to perform energy conversion on the operating data based on the correspondence between the multiple physical quantities and energy to obtain the corresponding energy characterization parameters; The state quantity determination submodule is used to determine the equivalent energy storage state quantities of the multiple pipeline nodes and multiple pipeline segments based on the energy characterization parameters. The matrix acquisition submodule is used to obtain the energy storage state quantity distribution matrix of the urban pipeline network system based on the pipeline topology and the equivalent energy storage state quantity.

[0100] In one embodiment of this application, the plurality of physical quantities include pressure, flow rate, and temperature, and the state quantity determination submodule includes: The weighting unit is used to weight the energy characterization parameters corresponding to the pressure, flow rate and temperature for each pipeline node and each pipe segment to obtain the equivalent energy storage state quantity for each pipeline node and each pipe segment.

[0101] In one embodiment of this application, the window determination module 203 includes: The differential sequence submodule is used to perform time difference calculations on the multiple pipeline nodes and multiple pipeline segments based on the energy storage state quantity distribution matrix to obtain the corresponding energy state difference sequence. The node and pipe segment determination submodule is used to determine candidate pipe network nodes and / or candidate pipe segments from the multiple pipe network nodes and multiple pipe segments based on the energy state difference sequence and the preset fluctuation threshold. The candidate time period determination submodule is used to determine the corresponding candidate energy fluctuation time period based on the energy state difference sequence of the candidate pipeline nodes and / or the candidate pipeline segments; The time period determination submodule is used to determine the target energy fluctuation period from the candidate energy fluctuation periods corresponding to the candidate pipeline nodes and / or the candidate pipeline segments based on the preset average amplitude and preset duration, and to take the candidate pipeline nodes and / or candidate pipeline segments corresponding to the target energy fluctuation period as the target pipeline nodes and / or target pipeline segments.

[0102] In one embodiment of this application, the window determination module 203 includes: The historical information acquisition submodule is used to acquire the historical equivalent energy storage state quantity sequence of the target pipeline node and / or the target pipeline segment within a preset historical period, and to determine historical fluctuation information based on the historical equivalent energy storage state quantity sequence. The load change acquisition submodule is used to acquire the current load change information of the urban pipeline network system; The window determination submodule is used to continuously predict the target energy fluctuation period corresponding to the target pipeline node and / or the target pipeline segment based on the historical fluctuation information and the current load change information, and to determine the energy release time window corresponding to the target pipeline node and / or the target pipeline segment based on the prediction results.

[0103] In one embodiment of this application, the power generation system includes a power generation and storage device, a power generation unit, and a pipeline regulation device. The strategy control module 204 includes: The strategy generation submodule is used to generate power generation control strategies for the energy storage device, the power generation device, and the pipeline regulation device based on the target pipeline node, and / or the target pipeline segment and the energy release time window. The control submodule is used to control the energy storage device, the power generation device and the pipeline regulation device to operate in coordination according to the power generation control strategy.

[0104] In one embodiment of this application, it further includes: The safety monitoring module is used to monitor the safety parameters corresponding to the target pipeline node and / or the target pipeline segment during the coordinated operation of the energy storage device, the power generation device and the pipeline regulation device according to the power generation control strategy, and to obtain the safety parameter monitoring value. The strategy adjustment module is used to determine whether the monitored value of the safety parameter triggers a safety warning based on a preset safety threshold, and to adjust the power generation control strategy if the safety parameter value triggers a safety warning.

[0105] In one embodiment of this application, the strategy adjustment module includes: The strategy adjustment submodule is used to reduce the adjustment range of the pipeline regulation equipment and the energy extraction power of the power generation device according to a preset adjustment ratio, or to suspend the charging and discharging operation of the energy storage device.

[0106] In one embodiment of this application, it further includes: The status bar acquisition module is used to acquire the equivalent energy storage status of each pipeline node based on the energy storage status distribution matrix. The partitioning module is used to divide the multiple pipeline nodes into one or more node partitions based on the equivalent energy storage state of each pipeline node and the topology of the urban pipeline system.

[0107] In one embodiment of this application, it further includes: The local strategy generation module is used to determine the target partition node and / or target partition pipe segment and the corresponding local energy release time window for each node partition, and generate the corresponding local power generation control strategy.

[0108] In one embodiment of this application, it further includes: The difference value determination module is used to monitor the equivalent energy storage state quantity between different node partitions and obtain the difference value of the equivalent energy storage state quantity between adjacent node partitions. The energy transfer strategy module is used to perform energy transfer operations on the adjacent node partitions when the difference in the equivalent energy storage state quantity is greater than a preset gradient threshold.

[0109] The intelligent control device for a power generation system in this application embodiment can be a device, or a component, integrated circuit, or chip in a terminal. The device can be a mobile electronic device or a non-mobile electronic device. For example, mobile electronic devices can be mobile phones, tablets, laptops, PDAs, in-vehicle electronic devices, wearable devices, ultra-mobile personal computers (UMPCs), netbooks, or personal digital assistants (PDAs), etc., while non-mobile electronic devices can be servers, network-attached storage (NAS), personal computers (PCs), televisions (TVs), ATMs, or self-service machines, etc. This application embodiment does not impose specific limitations.

[0110] The intelligent control device for a power generation system in this application embodiment can be a device with an operating system. This operating system can be Android, iOS, or other possible operating systems; this application embodiment does not specifically limit the specific operating system used.

[0111] The intelligent control device for a power generation system provided in this application embodiment can achieve… Figure 1 The various processes implemented by the intelligent control device of a power generation system in the method embodiment are not described in detail here to avoid repetition.

[0112] In this embodiment, by acquiring the operational data of the multiple pipeline nodes and multiple pipe segments, the equivalent energy storage state of the multiple pipeline nodes and multiple pipe segments is determined based on the operational data. Based on the equivalent energy storage state, an energy storage state distribution matrix of the urban pipeline system is obtained. Based on the energy storage state distribution matrix, target pipeline nodes and / or target pipe segments and corresponding target energy fluctuation periods are determined. Based on the target energy fluctuation periods, an energy release time window is determined. Based on the target pipeline nodes and / or target pipe segments and the energy release time window, a power generation control strategy is generated. The power generation system is then controlled to generate electricity according to the power generation control strategy. This achieves global quantitative perception, dynamic fluctuation identification, power generation time window determination, and targeted recovery and power generation of dispersed energy in the urban pipeline system. This overcomes technical problems such as dispersed energy representation, insufficient adaptability to dynamic energy fluctuations, and lack of energy release timing identification, thereby improving the overall energy utilization efficiency of the urban pipeline system.

[0113] Optionally, this application embodiment also provides an electronic device, including a processor 310, a memory 309, and a program or instructions stored in the memory 309 and executable on the processor 310. When the program or instructions are executed by the processor 310, they implement the various processes of the above-described intelligent control method embodiment for the power generation system and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0114] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0115] Figure 3 A schematic diagram of the hardware structure of an electronic device to implement an embodiment of this application. The electronic device 300 includes, but is not limited to, components such as: a radio frequency unit 301, a network module 302, an audio output unit 303, an input unit 304, a sensor 305, a display unit 306, a user input unit 307, an interface unit 308, a memory 309, and a processor 310. The user input unit 307 includes a touch panel 3071 and other input devices 3072; the display unit 306 includes a display panel 3061; and the input unit includes a graphics processor 3041 and a microphone 3042.

[0116] Those skilled in the art will understand that the electronic device 300 may also include a power supply (such as a battery) for supplying power to various components. The power supply may be logically connected to the processor 310 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system. Figure 3 The electronic device structure shown does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements, which will not be elaborated here. This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described intelligent control method embodiment for the power generation system and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0117] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0118] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above-described intelligent control method embodiment for the power generation system, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0119] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0120] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0121] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0122] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A method for intelligent control of a power generation system, characterized in that, Applied to urban pipeline network systems, the urban pipeline network system including multiple pipeline nodes and multiple pipeline segments, the method includes: Obtain operational data for the multiple pipeline nodes and multiple pipeline segments; Based on the operational data, the equivalent energy storage state quantities of the multiple pipeline nodes and multiple pipeline segments are determined, and based on the equivalent energy storage state quantities, the energy storage state quantity distribution matrix of the urban pipeline network system is obtained. Based on the energy storage state quantity distribution matrix, the target pipeline node and / or target pipeline segment and the corresponding target energy fluctuation period are determined, and the energy release time window is determined based on the target energy fluctuation period. Based on the target pipeline node, and / or the target pipeline segment and the energy release time window, a power generation control strategy is generated, and the power generation system is controlled to generate electricity according to the power generation control strategy.

2. The method according to claim 1, characterized in that, The operational data includes multiple physical quantities related to energy. Based on the operational data, the equivalent energy storage state quantities of the multiple pipeline nodes and multiple pipeline segments are determined. Based on the equivalent energy storage state quantities, the energy storage state quantity distribution matrix of the urban pipeline network system is obtained, including: Based on the correspondence between the multiple physical quantities and energy, the operating data is converted into energy to obtain the corresponding energy characterization parameters; Based on the energy characterization parameters, the equivalent energy storage state quantities of the multiple pipeline nodes and multiple pipeline segments are determined. Based on the network topology of the urban pipeline system and the equivalent energy storage state quantity, the distribution matrix of the energy storage state quantity of the urban pipeline system is obtained.

3. The method of claim 2, wherein, The multiple physical quantities include pressure, flow rate, and temperature. Based on the energy characterization parameters, the equivalent energy storage state quantities of the multiple pipeline nodes and multiple pipeline segments are determined, including: For each pipeline node and each pipe segment, the energy characterization parameters corresponding to the pressure, flow rate, and temperature are weighted to obtain the equivalent energy storage state quantity for each pipeline node and each pipe segment.

4. The method according to any one of claims 1 to 3, characterized in that, Based on the energy storage state quantity distribution matrix, the target pipeline nodes and / or target pipeline segments, as well as the corresponding target energy fluctuation periods, are determined, including: Based on the energy storage state quantity distribution matrix, time difference calculation is performed on the multiple pipeline nodes and multiple pipeline segments to obtain the corresponding energy state difference sequence. Based on the energy state difference sequence and the preset fluctuation threshold, candidate pipeline nodes and / or candidate pipeline segments are determined from the multiple pipeline nodes and multiple pipeline segments; Based on the energy state difference sequence of the candidate pipeline nodes and / or the candidate pipeline segments, the corresponding candidate energy fluctuation period is determined; Based on the preset average amplitude and preset duration, a target energy fluctuation period is determined from the candidate energy fluctuation periods corresponding to the candidate pipeline nodes and / or the candidate pipe segments, and the candidate pipeline nodes and / or the candidate pipe segments corresponding to the target energy fluctuation period are taken as the target pipeline nodes and / or the target pipe segments.

5. The method according to any one of claims 1 to 3, characterized in that, Based on the target energy fluctuation period, the energy release time window is determined, including: Obtain the historical equivalent energy storage state sequence of the target pipeline node and / or the target pipeline segment within a preset historical time period, and determine historical fluctuation information based on the historical equivalent energy storage state sequence; Obtain the current load change information of the urban pipeline network system; Based on the historical fluctuation information and the current load change information, the target energy fluctuation period corresponding to the target pipeline node and / or the target pipeline segment is continuously predicted, and the energy release time window corresponding to the target pipeline node and / or the target pipeline segment is determined according to the prediction results.

6. The method according to any one of claims 1 to 3, characterized in that, The power generation system includes energy storage equipment, power generation devices, and pipeline regulation equipment. Based on the target pipeline node and / or the target pipeline segment and the energy release time window, a power generation control strategy is generated, and the power generation system is controlled to generate electricity according to the power generation control strategy, including: Based on the target pipeline node, and / or the target pipeline segment and the energy release time window, a power generation control strategy is generated for the energy storage device, the power generation device and the pipeline regulation device. The energy storage device, the power generation device, and the pipeline regulation device are controlled to operate in coordination according to the power generation control strategy.

7. The method of claim 6, wherein, Also includes: During the coordinated operation of the energy storage device, the power generation device and the pipeline regulation device according to the power generation control strategy, the safety parameters corresponding to the target pipeline node and / or the target pipeline segment are monitored to obtain the safety parameter monitoring values. Based on a preset safety threshold, it is determined whether the monitored value of the safety parameter triggers a safety warning, and if the safety parameter value triggers a safety warning, the power generation control strategy is adjusted.

8. The method of claim 7, wherein, The adjustment of the power generation control strategy includes: The adjustment range of the pipeline regulating equipment and the energy extraction power of the power generation device are reduced according to the preset adjustment ratio, or the charging and discharging operation of the energy storage device is suspended.

9. The method according to any one of claims 1-3, characterized in that, Also includes: Based on the energy storage state quantity distribution matrix, the equivalent energy storage state quantity of each pipeline node is obtained. Based on the equivalent energy storage state of each pipeline node and the topology of the urban pipeline system, the multiple pipeline nodes are divided into one or more node partitions.

10. The method of claim 9, wherein, Also includes: For each node partition, determine the target partition node, and / or target partition pipe segment and the corresponding local energy release time window, and generate the corresponding local power generation control strategy.

11. The method of claim 9, wherein, Also includes: The equivalent energy storage state quantities between different node partitions are monitored to obtain the difference in equivalent energy storage state quantities between adjacent node partitions. If the difference in the equivalent energy storage state quantity is greater than a preset gradient threshold, energy transfer operation is performed on the adjacent node partitions.

12. An intelligent regulating device for a power generation system, characterized by, Applied to urban pipeline network systems, the urban pipeline network system includes multiple pipeline nodes and multiple pipeline segments, the device includes: The data acquisition module is used to acquire the operating data of the multiple pipeline nodes and multiple pipeline segments; The energy distribution module is used to determine the equivalent energy storage state of the multiple pipeline nodes and multiple pipeline segments based on the operating data, and to obtain the energy storage state distribution matrix of the urban pipeline system based on the equivalent energy storage state. The window determination module is used to determine the target pipeline node and / or target pipeline segment and the corresponding target energy fluctuation period based on the energy storage state quantity distribution matrix, and to determine the energy release time window based on the target energy fluctuation period; The strategy control module is used to generate a power generation control strategy based on the target pipeline node and / or the target pipeline segment and the energy release time window, and control the power generation system to generate electricity according to the power generation control strategy.

13. An electronic device, comprising: It includes a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the method as described in any one of claims 1 to 11.

14. A readable storage medium, characterized by, A computer program is stored on the readable storage medium, which, when executed by a processor, implements the method as described in any one of claims 1 to 11.

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