Energy supply regulation method, device, apparatus and storage medium

Abstract

The application discloses an energy supply regulation method, device, equipment and storage medium. The method comprises the following steps: supplying energy to a corresponding energy supply network according to a predetermined energy supply strategy, and acquiring current energy supply parameter information of the energy supply network; determining a to-be-regulated node according to a preset energy supply regulation condition and temperature information in the current energy supply parameter information; extracting to-be-regulated energy supply parameters corresponding to the to-be-regulated node from the current energy supply parameter information, determining an optimized control parameter corresponding to the to-be-regulated node according to the to-be-regulated energy supply parameters; and regulating a variable frequency water pump and / or a pipe valve corresponding to the to-be-regulated node according to the optimized control parameter. The technical scheme of the embodiment of the application realizes targeted regulation of different parts in the energy supply network, improves the regulation efficiency, guarantees dynamic balance of the energy supply network and high equipment load rate operation, and realizes energy saving and emission reduction on the basis of meeting user demand.

Description

Technical Field

[0001] This invention relates to the field of energy and power technology, and in particular to an energy supply regulation method, device, equipment and storage medium. Background Technology

[0002] Building energy consumption mainly refers to the various forms of energy consumed to maintain the normal operation of a building, such as energy consumed for heating, cooling, ventilation, and lighting. In large public buildings, heating and cooling account for approximately two-thirds of the total energy consumption. Therefore, energy-saving operation is a key issue that needs to be considered in the application of energy supply systems. However, existing building energy supply systems generally suffer from problems such as insufficient operation and management, low equipment load rates, and low system efficiency.

[0003] To improve the utilization efficiency of energy supply systems, existing energy supply systems often rely on the effect of energy supply to infer the real-time load. In this way, the operating parameters can be changed through a proportional-integral-derivative (PID) controller to achieve the matching of energy supply with the real-time load demand of the building.

[0004] However, the aforementioned regulation is lagging, failing to achieve real-time energy balance in the energy supply system and increasing the uncertainty of equipment energy consumption, which is detrimental to energy distribution and regulation. Furthermore, existing energy supply system regulation often relies on the experience of operation and maintenance personnel to adjust the system's energy supply, making it difficult to efficiently and accurately adjust system parameters to optimal values. Summary of the Invention

[0005] This invention provides an energy supply regulation method, device, equipment, and storage medium, which enables targeted regulation of different parts of the energy supply network, improves regulation efficiency, ensures the dynamic balance of the energy supply network and high equipment load rate operation, and achieves energy conservation and emission reduction while meeting user needs.

[0006] In a first aspect, embodiments of the present invention provide an energy supply regulation method, the method comprising:

[0007] According to the predetermined energy supply strategy, power is supplied to the corresponding energy supply network, and the current energy supply parameter information of the energy supply network is obtained; the energy supply network includes at least one energy source, at least two nodes, and at least one pipe segment;

[0008] Based on the preset energy supply adjustment conditions and the temperature information in the current energy supply parameters, determine the node to be regulated;

[0009] Extract the controllable energy parameters corresponding to the node to be controlled from the current energy supply parameter information, and determine the optimized control parameters corresponding to the node to be controlled based on the controllable energy supply parameters; the optimized control parameters are at least one of the target operating frequency and the target valve opening.

[0010] The variable frequency pumps and / or pipeline valves corresponding to the nodes to be controlled are adjusted based on the optimized control parameters.

[0011] Secondly, embodiments of the present invention also provide an energy supply regulation device, which includes:

[0012] The parameter acquisition module is used to supply energy to the corresponding energy supply network according to the predetermined energy supply strategy and to acquire the current energy supply parameter information of the energy supply network; the energy supply network includes at least the energy source, at least two nodes and at least one pipe segment;

[0013] The node determination module is used to determine the node to be controlled based on preset energy supply adjustment conditions and temperature information in the current energy supply parameter information;

[0014] The optimization parameter determination module is used to extract the energy supply parameters to be controlled corresponding to the node to be controlled from the current energy supply parameter information, and to determine the optimized control parameters corresponding to the node to be controlled based on the energy supply parameters to be controlled; the optimized control parameters are at least one of the target operating frequency and the target valve opening.

[0015] The node control module is used to control the variable frequency pumps and / or pipeline valves corresponding to the node to be controlled based on optimized control parameters.

[0016] Thirdly, embodiments of the present invention also provide an energy supply regulation device, which includes:

[0017] At least one processor; and

[0018] A memory that is communicatively connected to at least one processor; wherein,

[0019] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor can implement the power supply regulation method of any embodiment of the present invention.

[0020] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing computer instructions, which are used to cause a processor to execute and implement the power supply regulation method of any embodiment of the present invention.

[0021] This invention provides an energy supply regulation method, apparatus, equipment, and storage medium. It supplies energy to an energy supply network according to a predetermined energy supply strategy, achieving forward feedback regulation of the network. This eliminates the negative impact of time lag, avoids equipment operating at low load rates, and enables on-demand energy supply. For each node to be regulated in the energy supply network, the operating frequency of the variable frequency pump or the opening degree of the pipeline valve, etc., are adjusted to achieve negative feedback regulation of the network. This ensures hydraulic balance during actual operation, reduces heat loss in the pipeline network, improves energy supply efficiency, and achieves dynamic balance between energy supply and consumption. The combination of forward and negative feedback regulation effectively improves energy supply regulation efficiency, ensures dynamic balance of the energy supply network and high equipment load rate operation, and achieves energy conservation and emission reduction while meeting user needs.

[0022] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0023] Figure 1 This is a flowchart of an energy supply regulation method according to Embodiment 1 of the present invention;

[0024] Figure 2 This is a flowchart of an energy supply regulation method according to Embodiment 2 of the present invention;

[0025] Figure 3 This is a flowchart illustrating a method for determining the energy supply strategy of an energy supply network based on the output short-term energy supply forecast results, as shown in Embodiment 2 of the present invention.

[0026] Figure 4 This is a flowchart illustrating a method for training an energy load prediction model according to Embodiment 2 of the present invention.

[0027] Figure 5 This is a schematic diagram of a ring network structure according to Embodiment 2 of the present invention;

[0028] Figure 6 This is an example diagram of a heat network topology drawn according to a program in Embodiment 2 of the present invention;

[0029] Figure 7 This is a schematic diagram of the structure of an energy supply regulation device according to Embodiment 3 of the present invention;

[0030] Figure 8 This is a schematic diagram of the structure of an energy supply regulation device according to Embodiment 4 of the present invention. Detailed Implementation

[0031] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0032] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0033] Example 1

[0034] Figure 1 This is a flowchart of a power supply regulation method provided in Embodiment 1 of the present invention. The embodiments of the present invention are applicable to situations where power supply anomalies are located in a power supply network and nodes with abnormal power supply are dynamically regulated. The method can be executed by a power supply regulation device, which can be implemented by software and / or hardware. The power supply regulation device can be configured on a power supply regulation equipment, such as a laptop, desktop computer, or smart tablet.

[0035] In this embodiment of the invention, to achieve energy supply regulation of the energy supply network, it is necessary to collect relevant parameter information from the energy supply network in advance. This parameter information can be obtained using a dynamic data acquisition device to construct an energy supply regulation system. Specifically, this system may include an equipment layer, a dynamic data acquisition device, an energy controller, and a visualization platform. The system encompasses visualization services, scheduling services, monitoring services, and data services, realizing intelligent automatic adjustment and user-friendliness of the energy supply regulation system.

[0036] The hardware equipment includes energy supply and energy supply terminal equipment, as well as heat meters (for both heating and cooling), temperature sensors, pressure sensors, small weather stations, indoor occupancy counters, smart meters, valves, water pumps, and alarms, used for measuring indoor and outdoor environmental and energy supply parameters.

[0037] The dynamic data acquisition device can include functions such as data acquisition, protocol conversion, data storage and processing, and uploading to the energy controller and visualization platform.

[0038] Among them, the energy controller can be a control device that receives data uploaded by the dynamic acquisition device, analyzes and regulates it according to the optimal value algorithm, and sends control commands to the actuator. The actuator can be used to issue specific commands to adjust the optimal parameters of the system, water pump and energy supply equipment.

[0039] The visualization platform can display the topology corresponding to the energy supply and control system, and display the data transmitted by the real-time data acquisition device in the system topology. At the same time, it can receive the optimal value data transmitted by the energy controller, and display the current system operating parameters and optimal operating parameters, as well as hydraulic failure scheduling, on the platform. The operation and control process is visualized in real time on the platform, so that the control personnel can have a clearer understanding of the energy supply status of the energy supply network, which is convenient for subsequent energy supply and control.

[0040] like Figure 1 As shown, the energy supply regulation method provided in Embodiment 1 of the present invention specifically includes the following steps:

[0041] S101. Supply energy to the corresponding energy supply network according to the predetermined energy supply strategy, and obtain the current energy supply parameter information of the energy supply network.

[0042] The energy supply network includes at least the energy source, at least two nodes, and at least one pipeline segment.

[0043] In this embodiment, the energy supply strategy can be specifically understood as an energy supply strategy determined based on historical energy supply conditions, used to supply energy to the energy supply network so that the temperature of each node in the energy supply network meets the demand. The energy supply network can be specifically understood as a mesh structure of distributed energy transmission based on energy supply, nodes, and pipe segments, achieving interconnection. Current energy supply parameter information can be specifically understood as parameter information affecting the energy supply situation in the energy supply network at the current moment. For example, in a cooling and heating energy supply network, the current energy supply parameter information may include parameters such as the current temperature information, current pressure information, current load data, current environmental parameters, and current personnel data of the energy supply, each node, and pipe segment in the energy supply network.

[0044] In this embodiment, the energy supply can be understood as the source of all transmitted energy in the energy supply network. Energy supply can be cooling, heating, ventilation, or lighting, etc., and this embodiment of the invention is not limited in this respect. A node can be understood as an energy input or output point in the energy supply network. Energy supply and energy-consuming devices can be connected to the energy supply network through nodes for energy provision and acquisition. A pipe segment can be understood as a device used for energy transmission in the energy supply network, which can utilize pressurization or the energy's own gravity to achieve energy transmission within the pipe segment. It should be noted that there is one pipe segment connecting every two adjacent nodes, and at least two pipe segments connecting every three nodes.

[0045] Specifically, when the energy supply network has energy demand, the energy supply strategy of the energy supply network can be pre-determined based on historical data, and the energy supply network can be supplied according to the determined energy supply strategy. After the energy supply network has entered the energy supply state, the energy supply parameter information of each node and pipe segment in the energy supply network is acquired in real time during the energy supply process, and the energy supply parameter information corresponding to the current moment is determined as the current energy supply parameter information.

[0046] For example, energy can be supplied to the cooling and heating network according to a predetermined cooling and heating strategy, and the current temperature information, current pressure information, current load data, current environmental parameters and current personnel data of the energy supply network can be obtained as the current energy supply parameter information.

[0047] S102. Based on the preset energy supply adjustment conditions and the temperature information in the current energy supply parameter information, determine the node to be controlled.

[0048] In this embodiment, the preset energy supply adjustment conditions can be understood as conditions pre-set according to actual conditions to determine whether the energy supply network receiving the energy supply has achieved the expected effect, that is, whether adjustment is needed. Temperature information can be understood as information in the current energy supply parameter information used to characterize the energy supply, temperature of each node, and temperature of each pipe segment in the energy supply network. A node to be regulated can be understood as a node in the energy supply network whose temperature information has not achieved the expected energy supply effect, and whose energy supply effect needs to be regulated.

[0049] Specifically, the energy supply, temperature information of each node and pipe segment in the energy supply network at the current moment is determined from the current energy supply parameter information. Each temperature information is compared with the preset energy supply conditions. If there is temperature information that meets the preset energy supply adjustment conditions, it can be considered that the node corresponding to the temperature information has not achieved the expected energy supply effect. At this time, the node is determined as the node to be adjusted.

[0050] S103. Extract the energy supply parameters to be controlled corresponding to the node to be controlled from the current energy supply parameter information, and determine the optimized control parameters corresponding to the node to be controlled based on the energy supply parameters to be controlled.

[0051] Among them, the optimized control parameters can be at least one of the target operating frequency and the target valve opening.

[0052] In this embodiment, the energy supply parameters to be regulated can be specifically understood as parameters collected by a dynamic data acquisition device to indicate the energy supply status of the nodes to be regulated. Optimized control parameters can be understood as target parameters based on each node to be regulated in the energy supply network, enabling it to achieve the expected energy supply effect. The target operating frequency can be specifically understood as the operating frequency of the variable frequency pump to achieve the expected energy supply effect. The target valve opening can be specifically understood as the degree to which the valves in each pipe segment of the energy supply network are open to achieve the expected energy supply effect. The valve opening can be expressed as a percentage; for example, if the valve in the current pipe segment is half open, it can be expressed as the valve opening of the current pipe segment is 50%.

[0053] Specifically, based on each node to be regulated, the parameter information corresponding to each node in the current energy supply parameter information is determined and identified as the parameters to be regulated. According to the regulation requirements, each energy supply parameter to be regulated is substituted into its corresponding equation or pre-set model to calculate the parameter information of the current node, and the calculation result is determined as the optimal control parameter corresponding to the node to be regulated.

[0054] Optionally, the parameter to be controlled can be the operating frequency of the variable frequency pump extracted from the node to be controlled. The extracted operating frequency can be substituted into the equation corresponding to this parameter, such as the variable frequency pump speed equation. The target operating frequency is then determined based on the calculation results and used as the optimized control parameter for the node to be controlled. Alternatively, the parameter to be controlled can be the valve opening of the pipe section connected to one end of the node to be controlled. The extracted valve opening can be substituted into the hydraulic calculation model corresponding to this parameter. The target valve opening is then determined based on the calculation results and used as the optimized control parameter for the node to be controlled. It should be noted that the optimized control parameter can include both the target operating frequency and the target valve opening; it is not limited to one.

[0055] S104. Adjust the variable frequency pump and / or pipeline valve corresponding to the node to be controlled based on the optimized control parameters.

[0056] In this embodiment, the variable frequency water pump can be understood as a water pump driven by a variable frequency motor that can adjust the water flow rate by adjusting the speed (operating frequency) to achieve energy saving. The pipeline valve can be understood as a valve device that can control the flow or stop of the medium within a pipe section and adjust the flow rate according to the degree of valve rotation; for example, it can be a device used to adjust the water flow rate in various pipe sections of an energy supply network.

[0057] Optionally, the variable frequency pumps and / or pipeline valves corresponding to the node to be controlled can be adjusted based on the optimized control parameters. This can be achieved in the following ways:

[0058] Adjust the operating frequency of the variable frequency pump corresponding to the node to be controlled to the target operating frequency in the optimized control parameters; and / or

[0059] Adjust the valve opening of the pipeline corresponding to the node to be controlled to the target valve opening in the optimized control parameters.

[0060] Specifically, if the hardware device to be adjusted at the node to be controlled is a variable frequency water pump, the target operating frequency that the node to be controlled should achieve can be determined based on the optimization parameters, and the operating frequency of the variable frequency water pump can be adjusted to the target operating frequency. If the hardware device to be adjusted at the node to be controlled is a pipeline valve, the target valve opening that the corresponding pipeline valve should achieve can be determined based on the optimization parameters, and the valve opening can be adjusted to the target valve opening.

[0061] The technical solution of this embodiment supplies energy to the energy supply network according to a predetermined energy supply strategy, realizing forward feedback regulation of the energy supply network, eliminating the negative impact of time lag, avoiding equipment operating at low load rates, and achieving on-demand energy supply. For each node to be regulated in the energy supply network, the operating frequency of the variable frequency water pump or the opening degree of the pipeline valve of each node is adjusted to realize negative feedback regulation of the energy supply network, ensuring hydraulic balance in actual operation, reducing heat loss in the pipeline network, improving energy supply efficiency, and achieving dynamic balance between energy supply and consumption. The combination of forward and negative feedback regulation effectively improves the efficiency of energy supply regulation, ensures the dynamic balance of the energy supply network and high equipment load rate operation, and achieves energy conservation and emission reduction while meeting user needs.

[0062] Example 2

[0063] Figure 2This is a flowchart of an energy supply regulation method provided in Embodiment 2 of the present invention. The technical solution of this embodiment further optimizes the above-mentioned optional technical solutions, further clarifying the determination method and specific content of the predetermined energy supply strategy. Before supplying energy to the corresponding energy supply network, predicted energy supply parameter information is collected based on a data dynamic acquisition device, and the collected predicted energy supply parameter information is input into a preset energy load prediction model. The energy supply strategy of the energy supply network is determined based on the model output results, and the energy supply network is dynamically regulated. This energy supply strategy can be understood as an energy supply strategy employing a forward feedback regulation method.

[0064] This invention also provides training steps for the energy load prediction model. Historical energy supply parameter information is collected using a dynamic data acquisition device. This collected parameter information is processed, filtered, and categorized. The categorized parameter information is then input into different energy load prediction models for training until the training termination condition is met, and the final energy load prediction model suitable for the energy supply strategy is determined. Selecting different energy load prediction models at different times to determine the energy supply strategy makes the feedforward adjustment of the energy supply network more accurate. Simultaneously, based on the temperature difference information between different nodes, the parameters required for the control of the nodes to be regulated are determined. The operating frequency of the variable frequency pumps or the opening degree of the pipeline valves at each node to be regulated are adjusted to achieve negative feedback regulation of the energy supply network. This ensures hydraulic balance during actual operation, reduces heat loss in the pipeline network, improves energy supply efficiency, and achieves dynamic balance between energy supply and consumption. The combination of feedforward and negative feedback regulation effectively improves energy supply regulation efficiency, ensures dynamic balance of the energy supply network and high equipment load rate operation, and achieves energy conservation and emission reduction while meeting user needs.

[0065] like Figure 2 As shown in Embodiment 2 of the present invention, an energy supply regulation method specifically includes the following steps:

[0066] S201. Obtain the predicted energy supply parameter information corresponding to the energy supply network.

[0067] The predicted energy supply parameter information may include at least the first historical load data, the first historical environmental parameters, the first historical personnel data, and environmental forecast parameters.

[0068] In this embodiment, the predicted energy supply parameter information can be based on information collected by a dynamic data acquisition device, which can be used to predict the energy supply parameters for the next day. The first historical load data can be specifically understood as the hourly energy supply load data in the energy supply network within the most recent historical period, or as the energy required to maintain the temperature or other parameters of each node in the energy supply network within a certain range per unit time. The first historical environmental parameters can be specifically understood as the parameters of the natural environment corresponding to each node and pipe segment in the energy supply network that affect the energy supply status within the most recent historical period, such as temperature, humidity, and solar radiation. The first historical personnel data can be specifically understood as the parameter data of the number and status of personnel within the corresponding node of the energy supply network within the most recent historical period. The environmental forecast parameters can be specifically understood as environmental parameters obtained from weather forecasts or other methods for the desired prediction time. It should be clarified that the aforementioned most recent historical period can be the historical parameter information within the week preceding the current time, or it can be historical parameter information of other time lengths; this embodiment of the invention does not impose any limitations on this.

[0069] Specifically, when power needs to be supplied to the energy supply network, in order to estimate the energy required for power supply and to allocate energy to each node in the network in advance, the energy supply status of each node needs to be estimated. First, various historical data of the energy supply network in the previous historical period before the current time, as well as environmental parameters for the time to be predicted, are obtained. The first historical load data, the first historical environmental parameters, and the first historical personnel data in the obtained historical data, as well as the environmental forecast parameters used for prediction, are determined as the predicted energy supply parameter information for the energy supply network.

[0070] S202. Input the predicted energy supply parameter information into the preset energy load prediction model, and determine the energy supply strategy of the energy supply network based on the output short-term energy supply prediction results.

[0071] In this embodiment, the energy load forecasting model can be specifically understood as a neural network model used to predict energy supply parameters for a future period of time based on input energy supply parameter information. The short-term energy supply forecast result can be understood as a target forecast result obtained by the energy load forecasting model based on a short historical period. This forecast result is one that theoretically can be consistent with the actual situation.

[0072] Specifically, the predicted energy supply parameters collected within a short historical period corresponding to the energy supply network are used as the model input dimension and substituted into the pre-determined energy load prediction model. The results calculated and output by the model are then determined as the short-term energy supply prediction results.

[0073] Optional, Figure 3This is a flowchart illustrating a method for determining the power supply strategy of a power supply network based on the output short-term power supply forecast results, as provided in Embodiment 2 of the present invention. Figure 3 As shown, the specific steps may include the following:

[0074] S2021. Determine the energy demand of the energy supply network in different time periods based on the output short-term energy supply forecast results.

[0075] In this embodiment, the energy demand can be specifically understood as the total amount of energy that the energy supply network needs to provide in different time periods to achieve a pre-set energy supply target. The energy demand of the energy supply network in different time periods can be understood as the amount of heat or cooling required in each time period after dividing the total energy supply time into multiple time periods. The length of each time period can be adjusted according to demand, for example, it can be one hour or one day, etc. This embodiment does not limit the length of the aforementioned time periods.

[0076] Specifically, since the number of people in the energy supply network varies and the ambient temperature varies at different times, the amount of energy required for energy supply also varies at different times. Furthermore, since the energy supply load prediction model uses hourly historical load data during training, the short-term energy supply prediction results output by the energy supply load prediction model can also output hourly prediction data, thereby determining the energy supply demand of the energy supply network at different times.

[0077] S2022. Determine the number of units in operation for each time period based on the preset power supply unit correspondence.

[0078] In this embodiment, the preset energy supply unit correspondence can be specifically understood as the correspondence between the maximum energy information that each energy supply device in the energy supply unit can provide and the total energy demand. The number of operating units can be understood as the amount of energy required by the energy supply network to maintain normal energy supply.

[0079] For example, if the energy demand for the current time period is the maximum energy that 4 machines can provide, then it can be determined that at least 4 units should be operating during the current time period. To ensure unit safety and electricity costs, and to extend the service life, a threshold can be set for the energy supply of each machine, and the number of machines can be increased. For example, the safe energy supply of a machine can be set to 80% of its maximum energy supply. In this case, to ensure that the energy demand for the current time period can be met, more machines need to be added, i.e., the number of units operating should be 5.

[0080] S2023. The set of each time period and the corresponding number of operating units is determined as the power supply strategy of the power supply network.

[0081] Specifically, the number of operating units corresponding to each time period is determined, and the relationship between the two is generated. That is, each time period corresponds to a number of operating units. The set of information after association is determined as the power supply strategy of the power supply network. In other words, when the power supply strategy is defined, the number of units that the power supply network needs to start in different time periods can be known.

[0082] In this embodiment, power generation and energy storage plans are allocated based on short-term forecasts of heating and cooling loads. The total energy supply time is divided into multiple time periods. The number of operating units is determined for each time period to formulate an energy supply strategy. Energy supply targets are set for the next day. The power consumption plan is determined with the goal of minimizing electricity costs while considering carbon emissions. The number of operating units and the operating schedule of heating and cooling sources are adjusted according to the short-term forecasts of heating and cooling loads. This achieves front-feedback regulation of the energy supply network, eliminates the negative impact of time lag, avoids equipment operating at low load rates, and achieves on-demand energy supply. Energy conservation and emission reduction are achieved while meeting user needs.

[0083] Furthermore, Figure 4 This is a flowchart illustrating a training method for an energy load prediction model provided in Embodiment 2 of the present invention. Figure 4 As shown, the specific steps may include the following:

[0084] S301. Obtain historical energy supply parameter information corresponding to the energy supply network within a preset historical time period.

[0085] The historical energy supply parameter information includes at least the second historical load data, the second historical environmental parameters, and the second historical personnel data.

[0086] In this embodiment, historical energy supply parameter information can be specifically understood as energy supply parameter information used to reflect the average energy supply demand of the energy supply network within a preset historical time period. The preset historical time can be specifically understood as a historical period of a preset length preceding the current moment. It should be noted that the length of the preset historical time should be longer than the time length corresponding to the preset energy supply parameter information. Optionally, the preset historical time can be one or two months preceding the current moment; this embodiment of the invention does not impose any limitation on this.

[0087] In this embodiment, the second historical load data can be specifically understood as the hourly energy load data in the energy supply network within a preset historical period, or as the energy that needs to be supplied to each node per unit time to maintain the temperature or other parameters of each node in the energy supply network within a certain range. The second historical environmental data can be specifically understood as the parameters of the natural environment corresponding to each node and pipe segment in the energy supply network within a preset historical period that affect the energy supply status. The second historical personnel data can be specifically understood as the parameter data of the number and status of personnel within the corresponding nodes of the energy supply network within a preset historical period.

[0088] Specifically, to train the energy load prediction model, the dynamic data acquisition device will collect energy parameters in real time within a preset historical time period, and the collected parameter information will be used as historical energy parameter information.

[0089] S302. Preprocess historical energy supply parameter information and screen major influencing factors to determine target energy supply parameter information, and construct load forecasting training sample set and load forecasting test sample set based on target energy supply parameter information.

[0090] The load forecasting training sample set and the load forecasting test sample set may include the real dataset in the target energy supply parameter information, as well as the calibration dataset corresponding to the real dataset. The calibration dataset is the second historical load data in the calibrated real dataset.

[0091] In this embodiment, data preprocessing of historical energy supply parameter information may include data cleaning, integration, reduction, and transformation. Specifically, it can be understood as obtaining more accurate parameter data compared to the initially collected historical energy supply parameter data. Key influencing factors may include collected parameter information irrelevant to the training of the energy load prediction model, and parameter information whose values ​​differ significantly from other collected parameter information, clearly indicating errors. The target parameter information can be understood as the parameter information that meets the criteria for training the energy load prediction model, after preprocessing and filtering the historical energy supply parameter information.

[0092] In this embodiment, the load forecasting training sample set can be specifically understood as the set of training objects determined based on real data used to train the energy load forecasting model. The load forecasting test sample set can be specifically understood as the set of data samples used to test the performance of the finally selected energy load forecasting model. The real dataset can be specifically understood as the set of target energy supply parameter information directly obtained. The calibration dataset can be specifically understood as the set of data calibrated from the second historical load data in the real dataset, in order to be output in the energy load forecasting model.

[0093] Specifically, historical energy supply parameter information is preprocessed to remove obviously abnormal data. Then, the preprocessed historical energy supply parameter information is screened for major influencing factors. The energy supply parameter information corresponding to the types that have a significant impact on the energy load is determined as the target energy supply parameter information. This target energy supply parameter information is used directly as the real dataset, or it is randomly sampled and used as the real dataset. The second historical load data in the real dataset is labeled to obtain the corresponding calibration dataset. The real dataset and the calibration dataset are divided according to a preset ratio to obtain the corresponding load prediction training sample set and load prediction test sample set. Optionally, the screening methods for major influencing factors may include different screening methods such as Pearson correlation analysis and principal component analysis. The intersection of the major influencing factors obtained through different screening methods is determined as the target energy supply parameter information. This embodiment of the invention does not limit the screening method. Optionally, when determining the load forecasting training sample set and the load forecasting test sample set, the first 90% of the determined real dataset and calibration dataset can be determined as the load forecasting training sample set, and the last 10% can be determined as the load forecasting test sample set. This embodiment of the invention does not limit the specific proportion division.

[0094] S303. Input the load prediction training sample set into a preset number of different types of initial energy load prediction models for training until a preset convergence condition is met to obtain a preset number of intermediate energy load prediction models.

[0095] In this embodiment, the initial energy load prediction model can be specifically understood as an untrained energy load prediction model. The preset convergence condition can be understood as a pre-set condition used to determine whether the model has completed training. For example, the preset convergence condition may be that the model output error is less than a preset error threshold, the weight change between two iterations is less than a preset change threshold, or the number of iterations exceeds a preset number threshold, etc. This embodiment of the invention does not impose any limitations on these conditions. The intermediate energy load prediction model can be specifically understood as the model obtained after different types of initial energy load models have been trained to convergence.

[0096] For example, the initial energy load forecasting model can employ different types of models, such as XGBoost (eXtreme GradientBoosting) and LMST (Long Short-Term Memory). The load forecasting training sample set data, representing 90% of the parameter data, is used as the model input dimension and substituted into the initial energy load forecasting models of both the XGBoost and LMST models for training. The trained models can then serve as intermediate energy load forecasting models. This embodiment does not limit the number or type of models.

[0097] S304. Test each intermediate energy load prediction model using the load prediction test sample set, and determine the energy load prediction model based on the prediction results of each intermediate energy load prediction model.

[0098] In this embodiment, the energy load prediction model can be understood as the final energy load prediction model, which is determined by comparing various intermediate energy load prediction models and whose prediction results are more stable and closer to reality.

[0099] Specifically, the prediction results of the intermediate energy load prediction model are tested using a load prediction test sample set. The optimal intermediate energy load prediction model is determined from several intermediate energy load prediction models, and the prediction model is then modified to obtain the final energy load prediction model.

[0100] For example, the calculation results of MRE (mean absolute relative error), R2 (coefficient of determination), and CV-RMSE (circulation volume-root mean square error coefficient of variation) can be used as evaluation criteria. For instance, in the comparison of several intermediate energy load prediction models, an intermediate energy load prediction model with a CV-RMSE of no more than 30% for the cold and heat load prediction results can be used as the final energy load prediction model.

[0101] In this embodiment of the invention, by preprocessing and screening the historical energy supply parameter information within a preset historical time period, target energy supply parameter information is constructed. Then, based on the target energy supply parameter information, a load prediction training sample set and a load prediction test sample set are constructed for training the energy load prediction model. This ensures that when training the model, factors with a significant impact on the prediction are primarily considered. Training the energy load prediction model based on the target energy supply parameter information reduces the data processing pressure on the model. Simultaneously, by screening different types of intermediate energy load prediction models, a suitable energy load prediction model for predicting the current environment is selected, improving prediction accuracy and applicability, effectively increasing the efficiency of energy supply regulation, and ensuring the load prediction results are feasible for practical engineering applications.

[0102] S203. Provide energy to the corresponding energy supply network according to the predetermined energy supply strategy, and obtain the current energy supply parameter information of the energy supply network.

[0103] The energy supply network includes at least the energy source, at least two nodes, and at least one pipeline segment.

[0104] S204. Determine the first difference between the temperature information of each node in the power supply network and the preset temperature, identify the node whose first difference is greater than the first temperature difference threshold as the first node to be controlled, and execute step S206.

[0105] In this embodiment, the preset temperature can be understood as the expected temperature value corresponding to the expected energy supply effect set according to the actual needs of the node. The first difference can be understood as the difference between the node temperature and the preset temperature. The first temperature difference threshold can be understood as a temperature threshold preset according to the actual situation to indicate that the actual temperature of the node has not reached the expected energy supply effect. This embodiment of the invention does not limit the specific value of the first temperature difference threshold. The first node to be regulated can be understood as the node whose actual temperature has not reached the expected functional effect and needs to be regulated.

[0106] For example, by supplying energy to the current building according to a preset energy supply strategy, the temperature parameter information of each energy supply node can be maintained at a preset temperature of 26 degrees Celsius. The current energy supply network includes the energy source, the first node, the second node, the third node, the fourth node, and the pipe segments between the four nodes. The first temperature difference threshold is 3 degrees Celsius. The current node temperature of the first and second nodes is 26 degrees Celsius, the current node temperature of the third node is 25 degrees Celsius, and the current node temperature of the fourth node is 22 degrees Celsius. The difference between each node and the preset temperature is obtained and recorded as the first difference. The first differences of the four nodes are 0 degrees, 0 degrees, 1 degree, and 4 degrees Celsius, respectively. It can be determined that the difference between the fourth node and the preset temperature is greater than the first temperature difference threshold, that is, the fourth node can be determined as the first node to be controlled.

[0107] S205. Determine the second difference between the temperature information of each adjacent node in the energy supply network. When the second difference is greater than the second temperature difference threshold, determine the node located downstream in the energy supply network corresponding to the second difference as the second node to be controlled, and execute step S210.

[0108] In this embodiment, the second difference can be understood as the temperature difference between adjacent upstream and downstream nodes connected in the same pipe segment. The second temperature difference threshold can be specifically understood as a pre-set threshold based on actual conditions, indicating that the temperature difference between two adjacent nodes is too large, i.e., there is hydraulic imbalance in the pipe segment. This embodiment of the invention does not limit the specific value of the second temperature difference threshold. The second node to be regulated can be specifically understood as a node in the pipe segment with hydraulic imbalance that can be regulated. Generally, it is a node located downstream of the energy supply network in the pipe segment, i.e., the node farther from the energy source among two corresponding nodes in the pipe segment is designated as the second node to be regulated. It should be clarified that upstream and downstream nodes are relative concepts, not a fixed upstream or downstream node within the energy supply network.

[0109] For example, the second temperature difference threshold is 3 degrees, the current temperature information of the first node is 29 degrees, the temperature information of the second node is 25 degrees, the first node and the second node are adjacent and in the current power supply network, the second node is the downstream power supply node relative to the first node, the second difference is obtained, the second difference is 4 degrees, which is greater than the second temperature difference threshold, it can be determined that the second node is the current second node to be controlled among the two nodes.

[0110] It should be clarified that in the energy supply network, the first node to be regulated and the second node to be regulated can be the same node.

[0111] It should also be clarified that steps S204 and S205 can be executed simultaneously or in any order. In this embodiment of the invention, the simultaneous execution of both steps is taken as an example.

[0112] S206. The first temperature information and the variable frequency pump speed value corresponding to the first node to be controlled, extracted from the current energy supply parameter information, are determined as the energy supply parameters to be controlled for the first node to be controlled.

[0113] In this embodiment, the first temperature information can be specifically understood as the temperature of the energy supply target corresponding to the first controllable node at the current moment. The variable frequency pump speed value can be the number of revolutions per minute of the pump shaft when the power unit drives the pump to pump water, or it can be understood as the operating frequency of the variable frequency pump. The variable frequency pump speed value can include the pump's maximum operating speed, minimum operating speed, and the operating speed at the previous sampling time of the nth sampling time, which is determined by the control frequency value and can be represented by Speed. max Speed min and Speed n-1 This indicates that the pump speed at the nth sampling time can be represented by Speed. n This indicates that the speed of a variable frequency water pump can be approximately proportional to its operating frequency.

[0114] S207. The difference between the first temperature information and the preset temperature is determined as the temperature difference to be controlled for the first node to be controlled.

[0115] In this embodiment, the temperature difference to be controlled can be specifically understood as the temperature difference required to adjust the temperature of the first node to be controlled to meet the energy supply requirements, thereby raising or lowering it to the preset temperature.

[0116] S208. Based on the temperature difference to be controlled, the speed of the variable frequency pump, and the preset temperature control correlation coefficient, determine the target operating frequency of the variable frequency pump corresponding to the first node to be controlled.

[0117] In this embodiment, the preset temperature control correlation coefficient can be specifically understood as a coefficient related to the desired temperature value.

[0118] Specifically, since the adjustable range of the variable frequency pump speed is limited, when determining the target operating frequency, the maximum and minimum operating speeds of the variable frequency pump must be considered. When the temperature difference to be controlled is large, it can be assumed that the power supply network should increase the power supply as much as possible to meet the power supply demand of the first node to be controlled. When the temperature difference to be controlled is low, it can be assumed that the power supply network should decrease the power supply as much as possible to meet the power supply demand of the first node to be controlled. The target operating frequency required by the variable frequency pump can be determined by matching the temperature difference to be controlled with the preset temperature control correlation coefficient.

[0119] For example, suppose the temperature difference to be controlled is represented by ΔT, and the speed of the variable frequency water pump is represented by Speed, where the maximum operating speed is represented by Speed. max The minimum operating speed is expressed as Speed. min The operating speed at the nth sampling time is denoted as Speed. n And the operating speed at the previous sampling time before the nth sampling time is represented as Speed. n-1 The preset temperature control correlation coefficients are represented by M, N, and k, where k > 0, and k is determined by the time interval of the detected temperature difference. M and N can be set according to requirements; for example, M = -1℃ and N = 3℃. This embodiment does not impose any restrictions on this. Assuming the current time is the (n-1)th sampling time, and the target operating frequency corresponds to the nth sampling time, the target operating frequency can be expressed by the following formula:

[0120]

[0121] Furthermore, taking the air conditioner as an example of the energy supply equipment in the first controllable node, the change in the variable frequency water pump speed directly affects the cooling capacity and electrical power of the air conditioner. According to relevant experiments and research, the air conditioner's cooling (heating) capacity, electrical power, and water pump (or compressor) speed are approximately linearly related, as shown in the following formula:

[0122] P a (t)=a·Speed(t)+b

[0123] Q a (t)=c·Speed(t)+d

[0124]

[0125] Where a, b, c, and d are coefficients, and a and c are both greater than 0; η represents the thermoelectric conversion coefficient of the air conditioner. The first temperature information, the variable frequency water pump speed, and the cooling capacity are coupled together. The power supply network adjusts the variable frequency water pump speed according to the temperature difference between the first temperature information and the preset temperature, which acts on the electrical model of the air conditioner, thereby changing its cooling (heating) capacity and the electrical power it draws from the system. The change in cooling (heating) capacity is reflected in the indoor temperature through the room model, and the change in indoor temperature will affect the variable frequency water pump speed, and so on.

[0126] S209. Adjust the operating frequency of the variable frequency pump corresponding to the node to be controlled to the target operating frequency in the optimized control parameters.

[0127] S210. Extract the node flow rate and valve opening corresponding to the second node to be controlled from the current energy supply parameter information, as well as the pipe flow rate and pipe pressure drop of the second node to be controlled in the energy supply network that is closest to the upstream pipe segment.

[0128] In this embodiment, node flow rate can be specifically understood as the flow rate of users connected to the node exiting from that node. Valve opening degree can be specifically understood as the opening degree of the pipeline valve set at the second node to be regulated. Pipeline segment flow rate can be specifically understood as the flow rate in the upstream pipeline segment closest to the second node to be regulated, which has a hydraulic imbalance problem and is downstream of the second node to be regulated. Pipeline segment pressure drop can be specifically understood as the difference between the pressure at the upstream node and the pressure at the second node to be regulated in the aforementioned upstream pipeline segment.

[0129] Specifically, the discrepancy between the actual flow and the required flow for each user in the energy supply network is called hydraulic imbalance for that user. Hydraulic imbalance can be measured by the ratio of actual flow to the specified flow. The node flow corresponding to the second node to be regulated can be understood as the water flow information of that node within the current unit time period, i.e., the actual flow; the valve opening corresponding to the second node to be regulated can be understood as the percentage of valve opening within the current unit time period. Based on the pipe segment flow and pressure drop at each moment within the current time period of that node, the parameter information of the closest upstream pipe segment can be determined.

[0130] S211. Substitute the node flow rate, valve opening, pipe section flow rate, and pipe section pressure drop into the hydraulic calculation model corresponding to the power supply network to determine the node pressure corresponding to the second node to be regulated when hydraulically balanced.

[0131] In this embodiment, the hydraulic calculation model can be understood as a model that corrects for hydraulic imbalances. The node pressure can be the medium pressure within the second node to be controlled, which can be understood as water pressure.

[0132] The hydraulic calculation model may include:

[0133] The system of continuity equations for nodal flow is [A]·[q]=[Q].

[0134] The pipe section pressure drop equations [ΔP] = [A] T [P]

[0135] The flow equations for the pipe section are: [q] = [C]·[ΔP]

[0136] From the above three equations, the system of equations for solving the nodal pressures is [A·C·A]. T ]·[P]=[Q]. In the formula, A can represent a basic correlation matrix of the directed graph of the pipeline network, such as the correlation matrix A in Example 1; q can represent the flow vector of the pipe segment; Q can represent the node flow vector, the flow vector taken by the user at the current node; P can represent the node pressure vector; ΔP can represent the pressure drop vector of the pipe segment, which can be understood as the pressure difference between the upstream and downstream nodes within the pipe segment; A T It can be represented as the transpose of a matrix; C can be represented as a matrix composed of elements The nodes form a diagonal matrix, where α is a constant determined based on the fluid flow regime within the pipe section, and S is the pipe section resistance coefficient. Its equation is:

[0137]

[0138] Where f can represent the damping coefficient; d can represent the valve opening degree; and l can represent the pipe section length; d It can represent the equivalent length, which has a corresponding relationship with the valve opening degree d. The equivalent length l can be looked up in a table. d The corresponding valve opening degree d; ρ can represent density information.

[0139] Specifically, by substituting the node flow rate, valve opening, pipe segment flow rate, and pipe segment pressure drop into the above hydraulic calculation model and solving it, the node pressure corresponding to the second controllable node when the hydraulic calculation model reaches hydraulic equilibrium can be determined.

[0140] S212. Determine the target valve opening of the pipeline valve corresponding to the second controllable node based on the node pressure.

[0141] In this embodiment, the ideal resistance coefficient value of each pipe section when hydraulic balance is achieved can be obtained by combining the network topology of the pipeline network with the hydraulic calculation model, and then the corresponding flow rate and pressure drop value can be obtained, that is, the node pressure corresponding to the second controllable node when the hydraulic balance is obtained in the above steps, and the opening of the pipeline valve can be adjusted according to the node pressure.

[0142] Specifically, the target valve opening can be determined based on the nodal pressure vector P obtained from the hydraulic calculation model, the damping coefficient f, and the formula mentioned above: Obtain the valve opening degree d.

[0143] Furthermore, after determining the target valve opening of the pipeline valve corresponding to the second controllable node based on the node pressure, the process also includes:

[0144] (1) Extract the ambient temperature corresponding to the second node to be regulated and the upstream node temperature of the upstream adjacent node of the second node to be regulated from the current energy supply parameter information.

[0145] In this embodiment, the upstream adjacent node can be specifically understood as the node located upstream in the pipe segment with hydraulic imbalance, corresponding to the second node to be regulated. The upstream node temperature can be understood as the temperature of the node in the pipe segment with hydraulic imbalance that is closer to the energy supply node than the second node to be regulated.

[0146] (2) Substitute the target valve opening, pipe flow rate and upstream node temperature into the pipeline temperature loss equation to determine the adjustment node temperature of the second node to be controlled.

[0147] In this embodiment, the pipe temperature loss equation can be understood as a calculation equation for calculating heat loss within the pipe. Adjusting the node temperature can be understood as obtaining the target temperature after calculation using the equation.

[0148] Following the example above, the pipe temperature loss equation can specifically include the following two equations:

[0149] Heating:

[0150] Cooling:

[0151] in, Indicates adjustment of node temperature; C p This indicates specific heat capacity.

[0152] (3) If the third difference between the temperature of the adjusted node and the temperature of the upstream node is greater than the second temperature difference threshold, the target valve opening is used as the new valve opening, and the process is returned to perform the step of substituting the node flow, valve opening, pipe flow and pipe pressure drop into the hydraulic calculation model corresponding to the power supply network to determine the node pressure corresponding to the second node to be controlled when the hydraulic balance is achieved.

[0153] Specifically, after determining the adjustment node temperature of the second node to be regulated, the difference between this adjustment node temperature and the upstream node temperature is calculated and recorded as the third difference. If the third difference is less than the second temperature difference threshold, it indicates that the current energy supply regulation has met the energy supply regulation target, and the target valve opening determined at this time is the target valve opening that can be used to adjust the pipeline valve. If the third difference is greater than the second temperature difference threshold, it indicates that one node temperature adjustment is insufficient to reduce the temperature difference between two adjacent nodes to the target range, and further energy supply feedback regulation of the energy supply network is required. At this time, the target valve opening obtained from the previous feedback is used as the new valve opening, and the process is repeated to substitute the node flow, valve opening, pipe flow, and pipe pressure drop into the hydraulic calculation model corresponding to the energy supply network to determine the node pressure corresponding to the second node to be regulated when hydraulically balanced, until the third difference is less than the second temperature difference threshold, the current energy supply network system is determined to be in the optimal operating state, and the target valve opening obtained in this step is used as the target valve opening for regulating the pipeline valve of the second node to be regulated.

[0154] S213. Adjust the opening degree of the pipeline valve corresponding to the node to be controlled to the target valve opening degree in the optimized control parameters.

[0155] The technical solution of this embodiment involves: acquiring predicted energy supply parameter information corresponding to the energy supply network; inputting the energy supply parameter information into a preset energy load prediction model; determining the energy supply strategy of the energy supply network based on the output short-term energy supply prediction results; supplying energy to the corresponding energy supply network according to the predetermined energy supply strategy; acquiring the current energy supply parameter information of the energy supply network; determining the first difference between the temperature information of each node in the energy supply network and a preset temperature; identifying nodes with a first difference greater than a first temperature difference threshold as first nodes to be controlled; determining the second difference between the temperature information of each adjacent node in the energy supply network; identifying nodes located downstream in the energy supply network when the second difference is greater than a second temperature difference threshold as second nodes to be controlled; extracting the energy supply parameters to be controlled corresponding to the nodes to be controlled from the current energy supply parameter information; determining the optimized control parameters corresponding to the nodes to be controlled based on the energy supply parameters to be controlled; and regulating the variable frequency pumps and / or pipeline valves corresponding to the nodes to be controlled based on the optimized control parameters. By adopting the above technical solutions, the load forecasting model is pre-trained, enabling it to adapt to different environments and ensuring that the forecast results closely match the actual energy demand, thus achieving accurate energy forecasting. Based on the forecast results and actual temperature, the number of operating units and their operating schedules are adjusted through forward feedback regulation, achieving energy conservation and emission reduction while meeting user needs. Each node to be regulated is determined based on the difference between the preset temperature and the node temperature, as well as the temperature difference between adjacent nodes in the same pipe section, and negative feedback regulation is applied to that node. The combination of forward and negative feedback regulation achieves a dynamic balance between energy supply and consumption, facilitating power distribution and regulation. This effectively improves energy regulation efficiency, ensures the dynamic balance of the energy supply network and high equipment load rate operation, effectively saves energy, and reduces harmful emissions.

[0156] Furthermore, in this embodiment of the invention, the variable frequency water pump in the power supply network can be analogized to a transformer in a power system, and the on / off regulating valve (pipeline valve) in the power supply network can be analogized to a circuit breaker in a power system. The pipe segment pressure P is analogized to voltage, and the pipe segment flow rate m is analogized to current. The flow resistance of the pipe segment or equipment is defined and analogized to resistance, and the energy supply (variable frequency water pump) is analogized to a voltage source. Based on the adaptability of Kirchhoff's voltage law, the equations are adapted to be applicable to the power supply network model, analogous to a power network, and solved using loop equations in the power supply network. Simultaneously, Kirchhoff's current law is adapted to be adapted to a hydraulic calculation model, solved using node equations in the power supply network, and the hydraulic imbalance regulation calculation is based on topology. The power supply network treats the entire thermal system as a node, and the pipe segments as branches. If the flow direction of energy within the pipes is considered, a directed topology graph is constructed to simulate an electrical network, and mature theories of electrical networks are used to analyze the power supply system.

[0157] Specifically, before supplying energy to the corresponding energy network according to the predetermined energy supply strategy, the following steps are also included:

[0158] (1) Obtain the pipe section construction parameters, energy supply source construction parameters, node construction parameters, water pump construction parameters, and environmental construction parameters of the energy supply network.

[0159] In this embodiment, the pipe section construction parameters can be understood as the parameter information included in constructing the pipe section, and specifically can include parameters such as the starting node, ending node, pipe length, pipe diameter, roughness coefficient, thermal conductivity, hydraulic friction, pressure drop, and flow rate of the pipeline.

[0160] The energy supply source construction parameters can be understood as the parameter information included in the energy supply source, and specifically can include parameters such as the heat source fluid composition, heat source equipment capacity, rated heat supply output, rated water supply temperature, node connected to the heat source, and fluid density.

[0161] The node construction parameters can be understood as the parameter information included in constructing the node, and specifically can include parameters such as the node number, heat demand, rated outlet temperature, node pressure, node inlet temperature / outlet temperature, and node flow rate.

[0162] The water pump construction parameters can include parameter information such as the node number and the water pump outlet pressure.

[0163] The environmental model can include parameter information such as the environmental temperature.

[0164] (2) Construct a topology diagram of the energy supply network according to the pipe section construction parameters, energy supply source construction parameters, node construction parameters, water pump construction parameters, and environmental construction parameters, so as to display the parameter information of the energy supply source, each node, and each pipe section in the topology diagram.

[0165] Exemplarily, Figure 5 is a schematic diagram of a ring-shaped pipe network structure provided in Embodiment 2 of the present invention. As Figure 5 shown, there are 12 pipe sections and 10 nodes in this ring-shaped pipe network. Starting from the energy supply source 10, the energy flows to the first downstream node 9, and the energy obtained in node 9 flows to node 5 through pipe section (7), to node 8 through pipe section (9), and to node 6 through pipe section (8). Specifically, a matrix can be generated:

[0166]

[0167] Furthermore, according to the pipeline model, if there are m devices, which are connected by n pipes (m < n), let i represent the sorting of the devices and j represent the sorting of the pipes, and define the incidence matrix A(m×n) to represent the connection relationship between m devices (rows) and n pipes (columns) and the adjacency matrix X(m×m). The calculation equations are as follows:

[0168] A = A iji = 1, 2, ..., mj = 1, 2, ..., n

[0169]

[0170] The corresponding adjacency matrix and incidence matrix can be represented by the following formula:

[0171] The correlation matrix is ​​as follows:

[0172] The adjacency matrix is:

[0173] Furthermore, the topology can be automatically drawn by the program based on the generated correlation matrix and adjacency matrix. First, the pipeline model, heat source / cold source model, and user model of the energy supply network are read; the correlation matrix and adjacency matrix are generated based on the model; the bus level and y-axis coordinate value of the bus are determined; the x-axis coordinate position relationship of buses with the same y-axis coordinate value is determined based on the bus level; the buses are translated according to the correspondence between them; the bus length is checked for suitability, and whether the buses overlap. If either the length is unsuitable or the buses overlap, the check step is repeated; if the length is suitable and the buses do not overlap, the next step can be executed: draw the buses; determine the x-axis coordinate value of the bus connection based on the connection of the corresponding bus crossing endpoints; draw the bus connection; draw the load corresponding to the bus based on the load model; draw valves on the bus connection and load connection lines, and retrieve the heat (cold) source and water pump on the bus connecting the heat (cold) source; complete the drawing of the heat (cold) topology; and mark the real-time values ​​collected by the system at the corresponding bus, load, and connection positions.

[0174] Furthermore, Figure 6 This is an example diagram of a heat network topology drawn according to a program, as provided in Embodiment 2 of the present invention. Figure 6 As shown, this topology diagram represents a thermal network topology, while the cold network topology is similar. The thermal topology is represented in gray in the diagram, and the status of users and equipment is also distinguished by color. For example, when the node load is not zero, the load color is the same gray as the thermal topology, and when the load is zero, the load color is black.

[0175] In this embodiment, a visualization platform is described, including functions for automatically drawing cold and hot topologies and displaying system parameters and control processes in real time. It receives data transmitted by the data acquisition unit in real time and displays the system parameters in the system topology. At the same time, it receives the optimal value data transmitted by the energy controller and displays the current system operating parameters and optimal operating parameters, as well as hydraulic outages, on the platform, presenting the operation and control process in real time on the platform.

[0176] The automatic topology drawing function uses graph theory to draw the topology of the heating and cooling system by reading the pipe segment model (the return pipe is not considered because the supply and return water pipes are symmetrical), the energy supply model, and the user model. The system's real-time parameters and optimal values ​​are displayed by data uploaded by the dynamic data acquisition device and the energy controller, thus visualizing the system control process.

[0177] Example 3

[0178] Figure 7 This is a schematic diagram of a power supply regulation device provided in Embodiment 3 of the present invention. The power supply regulation device includes a parameter acquisition module 31, a node determination module 32, an optimization parameter determination module 33, and a node regulation module 34.

[0179] The parameter acquisition module 31 is used to supply energy to the corresponding energy supply network according to a predetermined energy supply strategy and acquire the current energy supply parameter information of the energy supply network; the energy supply network includes at least a power source, at least two nodes, and at least one pipe segment; the node determination module 32 is used to determine the node to be controlled according to the preset energy supply adjustment conditions and the temperature information in the current energy supply parameter information; the optimization parameter determination module 33 is used to extract the energy supply parameters to be controlled corresponding to the node to be controlled from the current energy supply parameter information and determine the optimized control parameters corresponding to the node to be controlled according to the energy supply parameters to be controlled; the optimized control parameters are at least one of the target operating frequency and the target valve opening; the node control module 34 is used to control the variable frequency pump and / or pipeline valve corresponding to the node to be controlled according to the optimized control parameters.

[0180] By adopting the above technical solution, energy is supplied to the energy supply network according to a predetermined energy supply strategy, achieving forward feedback regulation of the energy supply network. This eliminates the negative impact of time lag, avoids equipment operating at low load rates, and achieves on-demand energy supply. For each controllable node in the energy supply network, the operating frequency of the variable frequency pump or the opening degree of the pipeline valve, etc., of each controllable node are adjusted to achieve negative feedback regulation of the energy supply network. This ensures hydraulic balance during actual operation, reduces heat loss in the pipeline network, improves energy supply efficiency, and achieves dynamic balance between energy supply and consumption. The combination of forward and negative feedback regulation effectively improves energy supply regulation efficiency, ensures dynamic balance of the energy supply network and high equipment load rate operation, and achieves energy conservation and emission reduction while meeting user needs.

[0181] Optionally, the power supply control device may also include:

[0182] The first parameter acquisition module is used to acquire the predicted energy supply parameter information corresponding to the energy supply network before supplying energy to the corresponding energy supply network according to the predetermined energy supply strategy; the predicted energy supply parameter information includes at least the first historical load data, the first historical environmental parameters, the first historical personnel data, and environmental forecast parameters.

[0183] The strategy determination module is used to input the predicted energy supply parameter information into the preset energy load prediction model before supplying energy to the corresponding energy supply network according to the predetermined energy supply strategy, and to determine the energy supply strategy of the energy supply network based on the output short-term energy supply prediction results.

[0184] Optionally, the power supply control device may also include:

[0185] The second parameter acquisition module is used to acquire historical energy supply parameter information of the energy supply network within a preset historical period before acquiring the predicted energy supply parameter information of the energy supply network; the historical energy supply parameter information includes at least the second historical load data, the second historical environmental parameters, and the second historical personnel data;

[0186] The sample set construction module is used to preprocess historical energy supply parameter information and screen major influencing factors before obtaining the predicted energy supply parameter information corresponding to the energy supply network, determine the target energy supply parameter information, and construct a load prediction training sample set and a load prediction test sample set based on the target energy supply parameter information. The load prediction training sample set and the load prediction test sample set include the real dataset in the target energy supply parameter information and the calibration dataset corresponding to the real dataset. The calibration dataset is the second historical load data in the calibrated real dataset.

[0187] The intermediate model determination module is used to input the load prediction training sample set into a preset number of different types of initial energy load prediction models for training before obtaining the predicted energy supply parameter information corresponding to the energy supply network, until a preset number of intermediate energy load prediction models are obtained by meeting the preset convergence conditions.

[0188] The model determination module is used to test each intermediate energy load prediction model through a load prediction test sample set before obtaining the predicted energy supply parameter information corresponding to the energy supply network, and to determine the energy load prediction model based on the prediction results of each intermediate energy load prediction model.

[0189] Optional, the strategy determination module, specifically used for:

[0190] The energy demand of the energy supply network in different time periods is determined based on the output short-term energy supply forecast results; the number of units in operation in each time period is determined based on the preset correspondence of energy supply units; and the set of each time period and the corresponding number of units in operation is determined as the energy supply strategy of the energy supply network.

[0191] Optionally, the node determination module 32 includes:

[0192] The first node determination unit is used to determine the first difference between the temperature information of each node in the energy supply network and the preset temperature, and to determine the node whose first difference is greater than the first temperature difference threshold as the first node to be controlled.

[0193] The second node determination unit is used to determine the second difference between the temperature information of each adjacent node in the energy supply network. When the second difference is greater than the second temperature difference threshold, the node located downstream in the energy supply network corresponding to the second difference is determined as the second node to be controlled.

[0194] Optionally, if the node to be controlled is the first node to be controlled, then the optimization parameter determination module 33 is specifically used for:

[0195] The first temperature information and the variable frequency pump speed value corresponding to the first node to be controlled, extracted from the current energy supply parameter information, are determined as the energy supply parameters to be controlled corresponding to the first node to be controlled.

[0196] The difference between the first temperature information and the preset temperature is determined as the temperature difference to be controlled for the first node to be controlled.

[0197] Based on the temperature difference to be controlled, the speed of the variable frequency pump, and the preset temperature control correlation coefficient, the target operating frequency of the variable frequency pump corresponding to the first node to be controlled is determined.

[0198] Optionally, if the node to be controlled is the second node to be controlled, then the optimization parameter determination module 33 is specifically used for:

[0199] Extract the node flow rate and valve opening corresponding to the second node to be controlled from the current energy supply parameter information, as well as the flow rate and pressure drop of the pipe segment closest to the upstream pipe segment in the energy supply network for the second node to be controlled;

[0200] Substitute the node flow rate, valve opening, pipe section flow rate, and pipe section pressure drop into the hydraulic calculation model corresponding to the power supply network to determine the node pressure corresponding to the second node to be regulated when hydraulically balanced.

[0201] The target valve opening degree of the pipeline valve corresponding to the second controllable node is determined based on the node pressure.

[0202] Optionally, after determining the target valve opening of the pipeline valve corresponding to the second controllable node based on the node pressure, the method further includes:

[0203] Extract the ambient temperature corresponding to the second node to be regulated, and the upstream node temperature of the upstream adjacent node of the second node to be regulated from the current energy supply parameter information;

[0204] Substitute the target valve opening, pipe flow rate, and upstream node temperature into the pipeline temperature loss equation to determine the adjustment node temperature of the second node to be controlled.

[0205] If the third difference between the temperature of the adjusted node and the temperature of the upstream node is greater than the second temperature difference threshold, the target valve opening is used as the new valve opening, and the process returns to the step of substituting the node flow, valve opening, pipe flow, and pipe pressure drop into the hydraulic calculation model corresponding to the power supply network to determine the node pressure corresponding to the second node to be regulated when hydraulically balanced.

[0206] Optionally, the node control module 34 includes:

[0207] The operating frequency control unit is used to adjust the operating frequency of the variable frequency water pump corresponding to the node to be controlled to the target operating frequency in the optimized control parameters;

[0208] The valve opening control unit is used to adjust the opening of the pipeline valve corresponding to the node to be controlled to the target valve opening in the optimized control parameters.

[0209] Optionally, the power supply regulation device also includes:

[0210] The topology construction module is used to obtain the construction parameters of the pipeline segment, energy supply, node, pump, and environment of the energy supply network before supplying energy to the corresponding energy supply network according to the predetermined energy supply strategy. Based on the construction parameters of the pipeline segment, energy supply, node, pump, and environment, the module constructs a topology map of the energy supply network to display the parameter information of the energy supply, each node, and each pipeline segment in the topology map.

[0211] The power supply regulation device provided in the embodiments of the present invention can execute the power supply regulation method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method.

[0212] Example 4

[0213] Figure 8 This is a schematic diagram of a power supply regulation device according to Embodiment 4 of the present invention. The power supply regulation device 40 can be an electronic device, intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0214] like Figure 8As shown, the power supply regulation device 40 includes at least one processor 41 and a memory, such as a read-only memory (ROM) 42 or a random access memory (RAM) 43, communicatively connected to the at least one processor 41. The memory stores computer programs executable by the at least one processor. The processor 41 can perform various appropriate actions and processes based on the computer program stored in the ROM 42 or loaded from storage unit 48 into the RAM 43. The RAM 43 can also store various programs and data required for the operation of the power supply regulation device 40. The processor 41, ROM 42, and RAM 43 are interconnected via a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0215] Multiple components in the power supply control device 40 are connected to the I / O interface 45, including: an input unit 46, such as a keyboard, mouse, etc.; an output unit 47, such as various types of displays, speakers, etc.; a storage unit 48, such as a disk, optical disk, etc.; and a communication unit 49, such as a network card, modem, wireless transceiver, etc. The communication unit 49 allows the power supply control device 40 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0216] Processor 41 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 41 performs the various methods and processes described above, such as power regulation methods.

[0217] In some embodiments, the power supply regulation method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or installed on the power supply regulation device 40 via ROM 42 and / or communication unit 49. When the computer program is loaded into RAM 43 and executed by processor 41, one or more steps of the power supply regulation method described above may be performed. Alternatively, in other embodiments, processor 41 may be configured to perform the power supply regulation method by any other suitable means (e.g., by means of firmware).

[0218] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0219] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0220] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0221] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0222] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0223] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0224] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0225] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. An energy supply regulation method, characterized in that, include: According to the predetermined energy supply strategy, power is supplied to the corresponding energy supply network, and the current energy supply parameter information of the energy supply network is obtained; The energy supply network includes at least a power source, at least two nodes, and at least one pipe segment; Based on the preset energy supply adjustment conditions and the temperature information in the current energy supply parameter information, the node to be controlled is determined; Extract the energy supply parameters to be controlled corresponding to the node to be controlled from the current energy supply parameter information, and determine the optimized control parameters corresponding to the node to be controlled based on the energy supply parameters to be controlled. The optimized control parameter is at least one of the target operating frequency and the target valve opening. The variable frequency pumps and / or pipeline valves corresponding to the nodes to be controlled are adjusted according to the optimized control parameters. The step of determining the node to be regulated based on preset energy supply adjustment conditions and temperature information in the current energy supply parameter information includes: Determine the first difference between the temperature information of each node in the energy supply network and the preset temperature, and identify the node whose first difference is greater than the first temperature difference threshold as the first node to be controlled. A second difference between the temperature information of each adjacent node in the energy supply network is determined. When the second difference is greater than a second temperature difference threshold, the node in the adjacent node corresponding to the second difference that is located downstream in the energy supply network is determined as the second node to be regulated. Wherein, if the node to be regulated is the second node to be regulated, the step of extracting the energy supply parameters corresponding to the node to be regulated from the current energy supply parameter information, and determining the optimized control parameters corresponding to the node to be regulated based on the energy supply parameters to be regulated, includes: Extract the node flow rate and valve opening corresponding to the second node to be regulated from the current energy supply parameter information, as well as the pipe flow rate and pipe pressure drop of the second node to be regulated in the energy supply network that is closest to the upstream pipe segment; Substitute the node flow rate, the valve opening, the pipe section flow rate, and the pipe section pressure drop into the hydraulic calculation model corresponding to the energy supply network to determine the node pressure corresponding to the second node to be regulated when hydraulic balance is achieved; The target valve opening degree of the pipeline valve corresponding to the second controllable node is determined based on the node pressure.

2. The method according to claim 1, characterized in that, Before supplying power to the corresponding power supply network according to the predetermined power supply strategy, the method further includes: Obtain the predicted energy supply parameter information corresponding to the energy supply network; the predicted energy supply parameter information includes at least the first historical load data, the first historical environmental parameters, the first historical personnel data, and environmental forecast parameters; The predicted energy supply parameter information is input into a preset energy load prediction model, and the energy supply strategy of the energy supply network is determined based on the output short-term energy supply prediction results.

3. The method according to claim 2, characterized in that, Before obtaining the predicted energy supply parameter information corresponding to the energy supply network, the method further includes: Obtain historical energy supply parameter information corresponding to the energy supply network within a preset historical time period; the historical energy supply parameter information includes at least second historical load data, second historical environmental parameters, and second historical personnel data. The historical energy supply parameter information is preprocessed and the main influencing factors are screened to determine the target energy supply parameter information. Based on the target energy supply parameter information, a load prediction training sample set and a load prediction test sample set are constructed. The load prediction training sample set and the load prediction test sample set include the real dataset in the target energy supply parameter information and the calibration dataset corresponding to the real dataset. The calibration dataset is the second historical load data in the calibrated real dataset. The load prediction training sample set is input into a preset number of different types of initial energy load prediction models for training until a preset convergence condition is met to obtain the preset number of intermediate energy load prediction models. The intermediate energy load prediction models are tested using the load prediction test sample set, and the energy load prediction model is determined based on the prediction results of each intermediate energy load prediction model.

4. The method according to claim 2, characterized in that, The step of determining the energy supply strategy of the energy supply network based on the output short-term energy supply forecast results includes: The energy demand of the energy supply network in different time periods is determined based on the output short-term energy supply forecast results. Based on the preset power supply unit correspondence, determine the number of units operating in each time period; The set of each time period and the corresponding number of operating units is determined as the power supply strategy of the power supply network.

5. The method according to claim 1, characterized in that, If the node to be regulated is the first node to be regulated, the step of extracting the energy supply parameters corresponding to the node to be regulated from the current energy supply parameter information, and determining the optimized control parameters corresponding to the node to be regulated based on the energy supply parameters to be regulated, includes: The first temperature information and the variable frequency pump speed value corresponding to the first node to be controlled, extracted from the current energy supply parameter information, are determined as the energy supply parameters to be controlled for the first node to be controlled. The difference between the first temperature information and the preset temperature is determined as the temperature difference to be controlled for the first node to be controlled. Based on the temperature difference to be controlled, the speed of the variable frequency water pump, and the preset temperature control correlation coefficient, the target operating frequency of the variable frequency water pump corresponding to the first node to be controlled is determined.

6. The method according to claim 5, characterized in that, After determining the target valve opening of the pipeline valve corresponding to the second controllable node based on the node pressure, the method further includes: The ambient temperature corresponding to the second node to be regulated and the upstream node temperature of the upstream adjacent node of the second node to be regulated are extracted from the current energy supply parameter information. Substitute the target valve opening, the pipe section flow rate, and the upstream node temperature into the pipeline temperature loss equation to determine the adjustment node temperature of the second node to be controlled. If the third difference between the temperature of the adjusted node and the temperature of the upstream node is greater than the second temperature difference threshold, the target valve opening is taken as the new valve opening, and the process returns to the step of substituting the node flow rate, the valve opening, the pipe section flow rate and the pipe section pressure drop into the hydraulic calculation model corresponding to the power supply network to determine the node pressure corresponding to the second node to be regulated when hydraulically balanced.

7. The method according to claim 1, characterized in that, The regulation of the variable frequency pump and / or pipeline valve corresponding to the node to be regulated based on the optimized control parameters includes: Adjust the operating frequency of the variable frequency pump corresponding to the node to be controlled to the target operating frequency in the optimized control parameters; and / or The opening degree of the pipeline valve corresponding to the node to be controlled is adjusted to the target valve opening degree in the optimized control parameters.

8. The method according to claim 1, characterized in that, Before supplying power to the corresponding power supply network according to the predetermined power supply strategy, the method further includes: Obtain the pipeline construction parameters, energy supply construction parameters, node construction parameters, water pump construction parameters, and environmental construction parameters of the energy supply network; A topology diagram of the power supply network is constructed based on the pipeline construction parameters, the energy supply construction parameters, the node construction parameters, the water pump construction parameters, and the environmental construction parameters, so as to display the parameter information of the energy supply, each node, and each pipeline segment in the topology diagram.

9. An energy supply regulation device, characterized in that, include: The parameter acquisition module is used to supply energy to the corresponding energy supply network according to a predetermined energy supply strategy and to acquire the current energy supply parameter information of the energy supply network. The energy supply network includes at least a power source, at least two nodes, and at least one pipe segment; The node determination module is used to determine the node to be controlled based on preset energy supply adjustment conditions and temperature information in the current energy supply parameter information; The optimization parameter determination module is used to extract the energy supply parameters to be controlled corresponding to the node to be controlled from the current energy supply parameter information, and to determine the optimization control parameters corresponding to the node to be controlled based on the energy supply parameters to be controlled. The optimized control parameter is at least one of the target operating frequency and the target valve opening. The node control module is used to control the variable frequency pump and / or pipeline valve corresponding to the node to be controlled according to the optimized control parameters. The node determination module includes: The first node determination unit is used to determine the first difference between the temperature information of each node in the energy supply network and the preset temperature, and to determine the node whose first difference is greater than the first temperature difference threshold as the first node to be controlled. The second node determination unit is used to determine the second difference between the temperature information of each adjacent node in the energy supply network. When the second difference is greater than the second temperature difference threshold, the node in the adjacent node corresponding to the second difference that is located downstream in the energy supply network is determined as the second node to be controlled. Specifically, if the node to be controlled is the second node to be controlled, the optimization parameter determination module is used for: Extract the node flow rate and valve opening corresponding to the second node to be controlled from the current energy supply parameter information, as well as the flow rate and pressure drop of the pipe segment closest to the upstream pipe segment in the energy supply network for the second node to be controlled; Substitute the node flow rate, valve opening, pipe section flow rate, and pipe section pressure drop into the hydraulic calculation model corresponding to the power supply network to determine the node pressure corresponding to the second node to be regulated when hydraulically balanced. The target valve opening degree of the pipeline valve corresponding to the second controllable node is determined based on the node pressure.

10. An energy supply regulation device, characterized in that, include: At least one processor, and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the power supply regulation method according to any one of claims 1-8.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the power supply regulation method according to any one of claims 1-8.

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