Comprehensive energy steady-state parameter configuration method, system, equipment and medium

Abstract

The invention provides an integrated energy steady-state parameter configuration method, system and device and a medium, and the method comprises the steps: taking historical actual power data as input, carrying out the full-operation link simulation through a transient simulation model of an integrated energy system, and outputting the full-link simulation operation data; fusing the full-link simulation operation data with the corresponding historical actual operation data to obtain fused data; constructing a parameter identification model based on the multiple pieces of fusion data, solving the parameter identification model by adopting an interior point method to obtain model optimal transient parameters of the transient simulation model, deriving to obtain optimal steady-state parameters of the integrated energy system, and completing steady-state parameter configuration; according to the method and the system, the full-link simulation operation data and the historical actual operation data are fused, the parameter configuration model is constructed to obtain the steady-state parameters, the precision of system steady-state parameter configuration is effectively improved, and the steady-state simulation precision of the comprehensive energy system is further improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of power distribution and utilization, and specifically relates to a comprehensive energy steady-state parameter configuration method, system, equipment and medium. Background Art

[0002] Against the backdrop of global warming and the sharp decline of fossil resources, low carbonization has become the key to achieving global sustainable development. As an important subject of carbon emissions, the energy industry is an important link in achieving low carbon emission reduction goals. One of its focuses is to develop economical and efficient energy conversion and multi-energy complementary technologies, such as energy storage, trigeneration, P2G (Power to Gas), etc., to build an integrated energy system (IES) integrating power system, thermal system and natural gas system, to achieve deep integration between different energy systems, improve overall energy utilization efficiency, promote large-scale consumption of renewable energy, and reduce energy supply costs.

[0003] However, due to the high complexity of the integrated energy system and the complex thermal, dynamic and electric power conversion processes, the existing steady-state simulation that relies on equipment operation data for parameter identification has low accuracy. Therefore, it is of great significance to accurately identify and configure the model steady-state parameters of various types of equipment in the integrated energy system. Summary of the invention

[0004] In order to overcome the above-mentioned deficiencies of the prior art, the present invention proposes a comprehensive energy steady-state parameter configuration method, comprising:

[0005] Obtain historical actual power data and historical actual operation data of the integrated energy system in multiple historical periods;

[0006] Based on each of the historical time periods, the historical actual power data in the historical time period is used as input, a pre-built transient simulation model of the integrated energy system is used to simulate the entire operation process, and the simulation operation data of the entire operation process of the integrated energy system is output;

[0007] The simulated operation data of all links in each of the historical time periods are merged with the historical actual operation data in the same historical time period to obtain a plurality of fused data;

[0008] Building a parameter identification model based on the plurality of fused data, solving the parameter identification model using an interior point method, and obtaining an optimal output of the transient simulation model and an optimal transient parameter of the model corresponding to the optimal output;

[0009] Based on the optimal transient parameters and in combination with the equipment operation mechanism of the integrated energy system, the optimal steady-state parameters of the integrated energy system are derived to complete the steady-state parameter configuration.

[0010] Preferably, based on each of the historical time periods, the historical actual power data in the historical time period is used as input, a pre-built transient simulation model of the integrated energy system is used to simulate the entire operation link, and the simulation operation data of the entire link of the integrated energy system is output, including:

[0011] Based on each of the historical time periods, the historical actual power data in the historical time period is used as input, and simulation of a set time length is performed through the transient simulation model. When the operation of the transient simulation model reaches a steady state, the simulation result of the transient simulation model is output as the full-link simulation operation data of the integrated energy system.

[0012] Preferably, the full-link simulation operation data in each of the historical time periods is fused with the historical actual operation data in the same historical time period to obtain a plurality of fused data, including:

[0013] Based on each of the historical time periods, taking the simulated operation data of all links in the historical time period as the data benchmark, determining the data deviation of the historical actual operation data in the same historical time period, treating the data in the historical actual operation data whose data deviation exceeds the set threshold as abnormal data, and eliminating the abnormal data;

[0014] Extracting the intermediate link simulation operation data from the full link simulation operation data in the historical period;

[0015] The simulated operation data of the intermediate links are fused with the historical actual operation data after eliminating abnormal data to obtain fused data in the historical period.

[0016] Preferably, the constructing of a parameter identification model based on the plurality of fused data comprises:

[0017] Based on each of the historical time periods, determining the difference between the fusion data in the historical time period and the full-link simulation operation data output by the transient simulation model;

[0018] Based on the difference, an approximate evaluation function based on a voting method is used to determine an output deviation of the transient simulation model in the historical period;

[0019] Constructing an objective function with the goal of minimizing the sum of the output deviations of the transient simulation model in the plurality of historical time periods;

[0020] According to the objective function, the constraint conditions corresponding to each device in the integrated energy system are formulated and a parameter identification model is constructed.

[0021] Preferably, the expression corresponding to the objective function is as follows:

[0022]

[0023] Wherein, N is the number of measuring points, that is, the number of the historical time periods, and the data in each measuring point includes a historical actual power data in the historical time period and the fusion data corresponding to the historical actual power data, f i (e i ) represents the approximate evaluation function of the measurement point i based on the voting method, e i represents the difference between the output of the transient simulation model and the fused data at the measuring point i, e is the base, and satisfies f i (e i )≥0 and when e i The closer it is to 0, the i (e i ) is closer to 0; i and c represent the correlation coefficient, Z i represents the fused data at the measuring point i, x represents the transient parameter, h i (x) is the output of the transient simulation model under the transient parameter x, and θ represents the constraint condition.

[0024] Preferably, the constraint conditions include energy conservation constraints of each device in the integrated energy system and upper and lower limit constraints of transient parameters.

[0025] Preferably, the transient simulation model is constructed by the following steps:

[0026] Based on the mathematical model of each device in the integrated energy system, construct a transient simulation sub-model of each device;

[0027] Based on the transient simulation sub-models of each of the devices, and according to the topological connection relationship of each device in the integrated energy system, determining the structure of the transient simulation model;

[0028] According to the actual operation data of the integrated energy system in a typical historical period, the initial transient parameters of the transient simulation model are determined, and combined with the structure of the transient simulation model, the transient simulation model is preliminarily constructed.

[0029] Preferably, each device in the integrated energy system includes: at least one of energy production equipment, energy conversion equipment and energy storage equipment.

[0030] Based on the same inventive concept, the present invention also provides a comprehensive energy steady-state parameter configuration system, including:

[0031] An operation data acquisition module is used to acquire historical actual power data and historical actual operation data of the integrated energy system in multiple historical periods;

[0032] A simulation data acquisition module is used to use the historical actual power data in each historical period as input, use a pre-built transient simulation model of the integrated energy system to simulate all operation links, and output the simulation operation data of all links of the integrated energy system;

[0033] A data fusion module, used for fusing the simulation operation data of all links in each historical period with the historical actual operation data in the same historical period to obtain a plurality of fused data;

[0034] A transient parameter determination module, used to construct a parameter identification model based on the plurality of fused data, solve the parameter identification model using an interior point method, and obtain an optimal output of the transient simulation model and an optimal transient parameter of the model corresponding to the optimal output;

[0035] The steady-state parameter configuration module is used to derive the optimal steady-state parameters of the integrated energy system based on the optimal transient parameters and in combination with the equipment operation mechanism of the integrated energy system, and complete the steady-state parameter configuration.

[0036] Preferably, the simulation data acquisition module is specifically used for:

[0037] Based on each of the historical time periods, the historical actual power data in the historical time period is used as input, and simulation of a set time length is performed through the transient simulation model. When the operation of the transient simulation model reaches a steady state, the simulation result of the transient simulation model is output as the full-link simulation operation data of the integrated energy system.

[0038] Preferably, the data fusion module is specifically used for:

[0039] Based on each of the historical time periods, taking the simulated operation data of all links in the historical time period as the data benchmark, determining the data deviation of the historical actual operation data in the same historical time period, treating the data in the historical actual operation data whose data deviation exceeds the set threshold as abnormal data, and eliminating the abnormal data;

[0040] Extracting the intermediate link simulation operation data from the full link simulation operation data in the historical period;

[0041] The simulated operation data of the intermediate links are fused with the historical actual operation data after eliminating abnormal data to obtain fused data in the historical period.

[0042] Preferably, the transient parameter determination module is specifically used for:

[0043] Based on each of the historical time periods, determining the difference between the fusion data in the historical time period and the full-link simulation operation data output by the transient simulation model;

[0044] Based on the difference, an approximate evaluation function based on a voting method is used to determine an output deviation of the transient simulation model in the historical period;

[0045] Constructing an objective function with the goal of minimizing the sum of the output deviations of the transient simulation model in the plurality of historical time periods;

[0046] According to the objective function, the constraint conditions corresponding to each device in the integrated energy system are formulated and a parameter identification model is constructed.

[0047] Preferably, the expression corresponding to the objective function is as follows:

[0048]

[0049] Wherein, N represents the number of measuring points, that is, the number of the historical time periods, and the data in each measuring point includes a historical actual power data in the historical time period and the fusion data corresponding to the historical actual power data, f i (e i ) represents the approximate evaluation function of the measurement point i based on the voting method, e i represents the difference between the output of the transient simulation model and the fused data at the measuring point i, e is the base, and satisfies f i (e i )≥0 and when e i The closer it is to 0, the i (e i ) is closer to 0; i and c represent the correlation coefficient, Z i represents the fused data at the measuring point i, x represents the transient parameter, h i (x) is the output of the transient simulation model under the transient parameter x, and θ represents the constraint condition.

[0050] Preferably, the constraint conditions include energy conservation constraints of each device in the integrated energy system and upper and lower limit constraints of transient parameters.

[0051] Preferably, the simulation data acquisition module is also used for:

[0052] Based on the mathematical model of each device in the integrated energy system, construct a transient simulation sub-model of each device;

[0053] Based on the transient simulation sub-models of each of the devices, and according to the topological connection relationship of each device in the integrated energy system, determining the structure of the transient simulation model;

[0054] According to the actual operation data of the integrated energy system in a typical historical period, the initial transient parameters of the transient simulation model are determined, and combined with the structure of the transient simulation model, the transient simulation model is preliminarily constructed.

[0055] Preferably, each device in the integrated energy system includes: at least one of energy production equipment, energy conversion equipment and energy storage equipment.

[0056] Based on the same inventive concept, the present invention also provides a computer device, including: one or more processors;

[0057] A memory for storing one or more programs;

[0058] When the one or more programs are executed by the one or more processors, a comprehensive energy steady-state parameter configuration method as described above is implemented.

[0059] Based on the same inventive concept, the present invention also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed, it implements a comprehensive energy steady-state parameter configuration method as described above.

[0060] Compared with the closest prior art, the present invention has the following beneficial effects:

[0061] The present invention provides a method and system for configuring steady-state parameters of an integrated energy system, including obtaining historical actual power data and historical actual operation data of an integrated energy system in multiple historical time periods; based on each of the historical time periods, using the historical actual power data in the historical time period as input, using a pre-constructed transient simulation model of the integrated energy system to simulate all operation links, and outputting all-link simulation operation data of the integrated energy system; fusing the all-link simulation operation data in each of the historical time periods with the historical actual operation data in the same historical time period to obtain multiple fused data; constructing a parameter identification model based on the multiple fused data, using an interior point method to solve the parameter identification model, and obtaining the transient simulation model. The optimal output and the optimal transient parameters of the model corresponding to the optimal output; based on the optimal transient parameters, combined with the equipment operation mechanism of the integrated energy system, the optimal steady-state parameters of the integrated energy system are derived to complete the steady-state parameter configuration; the method and system fuse the acquired full-link simulation operation data of the integrated energy system with the historical actual operation data, build a parameter configuration model through the fused data, and further obtain the steady-state parameters. Compared with the technical solution of only using the historical actual operation data for optimization configuration to obtain the steady-state parameters, the error of the steady-state parameters configured in the present application is greatly reduced, that is, combining the full-link simulation operation data effectively improves the accuracy of the system steady-state parameter configuration, and further improves the steady-state simulation accuracy of the integrated energy system. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 A schematic diagram of a flow chart of a comprehensive energy steady-state parameter configuration method provided by the present invention;

[0063] Figure 2 A schematic diagram of the data fusion technology roadmap provided by the present invention;

[0064] Figure 3 The ideal cycle principle diagram of the gas turbine provided by the present invention;

[0065] Figure 3 (a) is a simplified schematic diagram of the connection relationship between the components in the ideal gas turbine cycle;

[0066] Figure 3 (b) is a schematic diagram of the pv (pressure-volume) relationship in the ideal cycle of a gas turbine;

[0067] Figure 3 (c) is a schematic diagram of the Ts (temperature-entropy) relationship in the ideal cycle of a gas turbine;

[0068] Figure 4 A schematic diagram of a dynamic response curve of various parameters of a gas turbine according to load changes provided by the present invention;

[0069] Figure 4 (a) is a schematic diagram of the dynamic response curve of speed changing with load;

[0070] Figure 4 (b) is a schematic diagram of the dynamic response curve of fuel flow and compressor flow with load changes;

[0071] Figure 4 (c) is a schematic diagram of the dynamic response curves of turbine inlet temperature and compressor outlet temperature as the load changes;

[0072] Figure 4 (d) is a schematic diagram of the dynamic response curve of compressor power consumption and turbine power with load changes;

[0073] Figure 5 A schematic diagram of the first-layer structure of the transient simulation model provided by the present invention;

[0074] Figure 6 A schematic diagram of the topological structure of the SM subsystem provided by the present invention;

[0075] Figure 7 A schematic diagram of the cable topology connection of the SS subsystem A provided by the present invention;

[0076] Figure 8 A schematic diagram of the cable topology connection of the SS subsystem B provided by the present invention;

[0077] Fig. 9 A schematic diagram of the structure of a comprehensive energy steady-state parameter configuration system provided by the present invention;

[0078] Fig.10 The present invention provides a schematic diagram of the structure of an electronic device. DETAILED DESCRIPTION

[0079] The specific implementation modes of the present invention are further described in detail below with reference to the accompanying drawings.

[0080] Embodiment 1:

[0081] The present invention provides a comprehensive energy steady-state parameter configuration method, such as Figure 1 As shown, including:

[0082] S1. Obtaining historical actual power data and historical actual operation data of the integrated energy system in multiple historical periods;

[0083] S2. Based on each historical period, the historical actual power data in the historical period is used as input, and the pre-built transient simulation model of the integrated energy system is used to simulate the entire operation process, and the simulation operation data of the entire process of the integrated energy system is output;

[0084] S3, fusing the simulation operation data of all links in each historical period with the historical actual operation data in the same historical period to obtain multiple fused data;

[0085] S4. Construct a parameter identification model based on multiple fusion data, use the interior point method to solve the parameter identification model, and obtain the optimal output of the transient simulation model and the optimal transient parameters of the model corresponding to the optimal output;

[0086] S5. Based on the optimal transient parameters and combined with the equipment operation mechanism of the integrated energy system, the optimal steady-state parameters of the integrated energy system are derived and the steady-state parameter configuration is completed.

[0087] Considering that the existing steady-state simulation that relies on typical equipment operation data for parameter identification has low accuracy, lacks intermediate data of integrated energy equipment operation, and lacks the ability to identify, eliminate and correct erroneous and distorted bad data, the errors generated have a certain impact on the optimized operation of the integrated energy system. The present invention provides a method for configuring steady-state parameters of an integrated energy system, which more effectively obtains data from the intermediate links of the integrated energy system, and will help improve the accuracy of parameter identification. By fusing the acquired full-link simulation operation data of the integrated energy system with the historical actual operation data, a parameter configuration model is constructed through the fusion data, and the steady-state parameters are further obtained. Compared with the technical solution of only using historical actual operation data for optimization configuration to obtain steady-state parameters, the error of the steady-state parameters configured in this application is greatly reduced, that is, the combination of the full-link simulation operation data effectively improves the accuracy of the system steady-state parameter configuration, and further improves the steady-state simulation accuracy of the integrated energy system.

[0088] Considering the need to obtain corresponding data to correct and supplement the actual operation data of typical equipment, in the above S2, the simulation of the entire operation link is obtained through the pre-built transient simulation model, which can provide a basis for the correction and supplement of the actual operation data.

[0089] In this embodiment, before S2, the transient simulation model is constructed by the following steps:

[0090] Based on the mathematical models of each device in the integrated energy system, a transient simulation sub-model of each device is constructed;

[0091] Based on the transient simulation sub-model of each device and the topological connection relationship of each device in the integrated energy system, the structure of the transient simulation model is determined;

[0092] According to the actual operation data of the integrated energy system in a typical historical period, the initial transient parameters of the transient simulation model are determined, and combined with the structure of the transient simulation model, the transient simulation model is preliminarily constructed.

[0093] In this embodiment, each device in the integrated energy system includes: at least one of energy production equipment, energy conversion equipment and energy storage equipment.

[0094] Specifically, the transient simulation method of typical equipment in the integrated energy system uses an integrated energy simulation platform for transient simulation. The typical equipment model of the integrated energy system, that is, the transient simulation model, is a digital model built on the integrated energy simulation platform. The integrated energy simulation platform consists of three parts: an integrated energy digital simulation cabinet, a simulation management host and display (simulation management equipment), and a physical simulation test platform. Figure 2 As shown in the figure, through transient simulation, the data of the intermediate operation links of the integrated energy system can be obtained more effectively, which will help improve the accuracy of parameter identification.

[0095] Furthermore, typical equipment in the integrated energy system includes energy production equipment such as photovoltaics, energy storage equipment such as energy storage, energy conversion equipment such as electric refrigerators, gas turbines, gas boilers, absorption refrigerators and other types of equipment, which can support the simulation of the integrated energy system.

[0096] Among them, the gas turbine is used as an example to carry out mathematical modeling of thermodynamic processes. The gas turbine is a rotating impeller heat engine, which can be simplified into an ideal Brayton cycle consisting of three major components: compressor, combustion chamber and turbine. The integrated energy simulation platform idealizes the actual cycle: (1) The working fluid is regarded as air, which is an ideal gas, and the specific heat capacity is a constant. (2) The working fluid undergoes a reversible process (the model provides an internal loss interface). The cycle schematic diagram is as follows: Figure 3 As shown, specifically, Figure 3 As shown in (a), the components of the simplified ideal gas turbine cycle include an oil pump, a combustion chamber, an impeller compressor, a gas turbine and a generator. The air is sucked in by the impeller compressor and compressed to increase its temperature. The compressed gas enters the combustion chamber, and the fuel delivered by the oil pump burns in the combustion chamber, releasing heat, which further increases the gas temperature. The high-temperature and high-pressure gas expands through the gas turbine, doing work externally to drive the compressor and other loads. The temperature of the expanded gas is still high, and it releases heat to the environment through the cooler, reducing its temperature to the temperature of the compressor inlet. The closed gas turbine ideal cycle consists of a constant-entropy compression process 1-2, a constant-pressure endothermic process 2-3, a constant-entropy expansion process 3-4 and a constant-pressure exothermic process 4-1. The pv (pressure-volume) relationship in each process is as follows: Figure 3 (b) shows that the relationship between Ts (temperature-entropy) is Figure 3 (c) as shown.

[0097] Thermal efficiency η of ideal Brayton cycle t , you can follow To calculate, the endothermic and exothermic processes are both constant pressure processes of ideal gases, so q 1 =c p (T 3 -T 2 ), q 2 =c p (T 4 -T 1 ), where q 1 is the amount of heat absorbed, q 2 is the heat release, T 1 , T 2 , T 3 , T 4are respectively the compressor inlet temperature, the gas temperature after the constant entropy compression process, the temperature at the turbine inlet, and the gas temperature after the constant entropy expansion process, c p is the specific heat capacity at constant pressure;

[0098] Q 1 ,q 2 Substitute the value of into the thermal efficiency formula and we get:

[0099]

[0100] 1-3 and 3-4 are both constant entropy processes, with Where k is the specific heat ratio, p 1 、p 2 、p 3 、p 4 are respectively the compressor inlet pressure, compressor outlet pressure, turbine outlet pressure, and cooler outlet pressure, p 1 =p 4 , p 2 =p 3 , so T 4 / T 3 =T 1 / T 2 ;

[0101] Introducing a parameter that reflects cycle characteristics - cycle pressure ratio π = p 1 / p 2 , put it into the thermal efficiency formula, then we have:

[0102]

[0103] Therefore, the cycle compression ratio (compressor pressure ratio) affects the cycle thermal efficiency and also affects the cycle net work (the area enclosed by the cycle).

[0104] like Figure 4 As shown in FIG. 1 , through the simulation experiment, the dynamic response curves of the parameters of the gas turbine in the transient process and the final steady state with the load change can be obtained. Specifically, the dynamic response curves of the speed of the gas turbine in the transient process and the final steady state with the load change can be obtained. Figure 4 (a); Dynamic response curve of fuel flow and compressor air flow of gas turbine in transient process and final steady state with load change, see Figure 4 (b) Dynamic response curves of compressor outlet temperature and turbine inlet temperature of gas turbine with load change in transient process and final steady state, see Figure 4 (c) Dynamic response curves of compressor power consumption and turbine power of gas turbine with load changes in transient process and final steady state, see Figure 4(d); and the dynamic response curves of parameters such as unit power and unit efficiency (i.e., the full-link data of the gas turbine). Through the above analysis and application, the intermediate temperature, pressure and other parameters of the gas turbine can be calculated, that is, the missing, difficult to measure or inaccurate data in the actual equipment operation, which helps to assist in eliminating abnormal data in the actual operation data and obtain better parameter identification results.

[0105] Furthermore, the Simulink simulation method based on the equipment transient model can construct the simulation scenario of the equipment transient model through a scenario building process including system topology construction, model parameter configuration and control strategy setting.

[0106] 1) System topology construction: According to the topology of power equipment and thermal equipment, select the corresponding model from the typical equipment transient model library, connect the equipment model according to the characteristics of the thermal working medium flow network and electrical network, and modify the overall parameters of the model. Then, according to the characteristics of the control and monitoring signals, integrate them into the form of BUS input and output.

[0107] SM (Master calculation subsystem), SS (Slave subsystem), and SC (Console subsystem) are the subsystem division methods of the real-time laboratory RTLab. The comprehensive energy simulation platform is developed based on RTLab. SM, SS, and SC are set as various energy subsystems such as cooling, heating, and electricity according to the situation. Divide the model into models of subsystems such as SM, SS, and SC, such as thermal subsystems and power subsystems, connect the subsystems with signal lines, set the internal solution step of each subsystem, and then the comprehensive energy multi-energy flow simulation scene can be constructed. Among them, the number of SM subsystems is one and only one, the number of SS subsystems is greater than or equal to 0, and the number of SC subsystems is less than or equal to 1.

[0108] 2) Model parameter configuration: Add the model in the typical equipment transient model library to the Simulink workspace and configure the equipment model parameters. Usually, it is necessary to configure the equipment ID, rated parameters, design parameters and inlet flow parameters.

[0109] 3) Control strategy setting: The power model library provides control strategies based on electrical characteristics as input, and the thermal model library provides control strategies based on flowing working fluid as input. The basic control strategy is set according to the actual equipment control strategy parameters.

[0110] Furthermore, the parameter configuration method of the typical equipment model of the integrated energy system combined with the operation and simulation data first makes assumptions and parameter settings for the dynamic model driven by physical mechanism and operation data, adopts dynamic modeling under variable working conditions, and establishes an equivalent model that approximately represents the dynamic characteristics of the original system. Secondly, the equipment parameters determined based on the operation data are verified using transient simulation data. If the simulation results are reasonable, the simulation method is considered feasible, otherwise the simulation parameters are debugged to obtain reasonable results; further, mainly using the operation data that can be collected, the missing equipment intermediate data is supplemented or fitted through simulation, and the accuracy of the equivalent model parameters of typical equipment in the energy system is further improved.

[0111] Furthermore, for various types of equipment or subsystems in the integrated energy system, it is necessary to select assumptions suitable for dynamic modeling. These assumptions directly affect the dynamic behavior of the model during transient periods. For the assumptions and parameter settings of dynamic models driven by operating data, the factors that need to be considered in the assumptions can be determined based on the operating mechanism and characteristics of the physical entity. By simulating the characteristic curves of each device, adjusting the physical equations corresponding to different assumptions, and obtaining assumptions that are similar to the measured characteristic curves or laws. Furthermore, parameter identification technology can be introduced to simulate the output state of each device, compare the difference between the simulated state and the actual measurement, and reduce the difference between the two by adjusting the parameters of the model, thereby determining the model parameters.

[0112] Furthermore, each device in the integrated energy system usually has nonlinear working characteristics, and changes in the system state may cause the device to be in a variable operating state, causing its operating characteristics to change. In view of the problem that it is difficult to meet the needs of accurate simulation of complex scenarios, the present invention adopts the "dominant factor method" modeling in the dynamic modeling of variable operating conditions. Based on mechanism analysis and actual operation data, the characteristic parameters of each device are studied, and the dominant factors that play a decisive role in the characteristic parameters are determined. The actual parameters of the equipment are identified according to the actual operation data, and a mapping relationship between the characteristic parameters of the equipment and the dominant factors is established. On the basis of the general model of constant operating conditions, a mapping relationship is established by using a table lookup method to construct a dynamic general model of variable operating conditions. In addition, a data-driven dynamic equivalent modeling method can be used to set the area in the integrated energy system that is more difficult to model through mechanism analysis as an equivalent area, and keep the network topology of the non-equivalent area unchanged. Multiple disturbances such as step, switching, and faults and complex operating conditions such as different mass flow and temperature are set in the non-equivalent area to form a dynamic operation history data sample set. Using the data-driven modeling method, the dependency between the input and output of the equivalent area is analyzed, and an equivalent model that approximately characterizes the dynamic characteristics of the original system is established.

[0113] In this embodiment, when obtaining the full-link simulation operation data in S2, it may include:

[0114] Based on each historical period, the historical actual power data in the historical period is used as input, and a simulation of a set time length is performed through the transient simulation model. When the operation of the transient simulation model reaches a steady state, the simulation results of the transient simulation model are output as the simulation operation data of all links of the integrated energy system.

[0115] Considering that there may be abnormal data in addition to missing data in the historical actual power data obtained during the historical period, the abnormal data must be eliminated before data fusion in S3 to further improve the accuracy of the data. In this embodiment, S3 may include:

[0116] Based on each historical period, the data deviation of the historical actual operation data in the same historical period is determined by taking the simulation operation data of all links in the historical period as the data benchmark, and the data in the historical actual operation data whose data deviation exceeds the set threshold is regarded as abnormal data, and the abnormal data is eliminated;

[0117] Extracting the intermediate link simulation operation data from the full link simulation operation data in the historical period;

[0118] The simulated operation data of the intermediate links are fused with the historical actual operation data after eliminating abnormal data to obtain the fused data for the historical period.

[0119] Specifically, when using the historical data of the test set to identify the model parameters, the collected historical actual power data is first used for simulation, which can obtain the simulation operation data of the intermediate links, such as the input and output temperatures of each part of the lithium bromide unit, and can assist in eliminating some erroneous data, and then perform parameter identification or verification. After the simulation, the estimated error statistics are still used for calculation.

[0120] In this embodiment, when constructing a parameter identification model based on multiple fusion data in S4, it may include:

[0121] Based on each historical period, determine the difference between the fusion data in the historical period and the full-link simulation operation data output by the transient simulation model;

[0122] Based on the difference, an approximate evaluation function based on the voting method is used to determine the output deviation of the transient simulation model in the historical period;

[0123] The objective function is constructed with the goal of minimizing the sum of the output deviations of the transient simulation model in multiple historical periods;

[0124] According to the objective function, the constraints corresponding to each device in the integrated energy system are formulated and a parameter identification model is constructed.

[0125] The principle of constructing the objective function is that when there are N measurement points in the system, that is, N historical periods, and the number of erroneous measurement points is k, The parameter that maximizes the number of qualified measurement points is to find Therefore, in this embodiment, the expression corresponding to the objective function is as follows:

[0126]

[0127] Wherein, N represents the number of measuring points, that is, the number of the historical time periods, and the data in each measuring point includes the historical actual power data in the historical time period and the fusion data corresponding to the historical actual power data, f i (e i ) represents the approximate evaluation function of the measurement point i based on the voting method, e i represents the difference between the output of the transient simulation model and the fusion data at the measuring point i, e is the base, and satisfies f i (e i )≥0 and when e i The closer it is to 0, the i (e i ) is closer to 0; i and c represent the correlation coefficient, Z i represents the fused data at the measuring point i, x represents the transient parameter, h i (x) is the output of the transient simulation model under the transient parameter x, and θ represents the constraint condition.

[0128] In this embodiment, the constraint conditions include energy conservation constraints of each device in the integrated energy system and upper and lower limit constraints of transient parameters.

[0129] In this embodiment, when the interior point method is used to solve the parameter identification model in S4, the following steps may be included:

[0130] Based on the objective function, under the set constraints, an initial feasible solution x0 is selected, and then the barrier function is constructed. The objective function and the barrier function are combined to form an augmented Lagrangian function for subsequent iterative processes; in each iteration, the interior point method moves along the central path, which is the path on the barrier function contour line, calculates the gradient and Hessian matrix of the augmented Lagrangian function, and then solves the Newton equation to find the descent direction, and then selects an appropriate step size to determine the new iteration point to ensure that the new iteration point is still within the feasible domain, that is, the constraint condition, and uses the new iteration point to update the model parameters until the set iteration termination condition is reached, and the optimal transient parameters of the model are output.

[0131] In this embodiment, when the optimal steady-state parameters of the integrated energy system are derived in S5 based on the optimal transient parameters and combined with the equipment operation mechanism of the integrated energy system, taking a gas turbine as an example, the state of the gas turbine can be described by the following parameterized model:

[0132]

[0133] Among them, P GT,t is the power generated by the gas turbine; η GT,E is the power generation efficiency of gas turbine; L GAS is the calorific value of natural gas; F GT,t is the natural gas consumption rate; Q GT,H,t is the thermal power recovered from the gas turbine; η GT,H is the heat recovery efficiency; E GT,t is the carbon emission of gas turbine; β GT and δ GT is the carbon emission intensity parameter of the gas turbine; ρ GT is the load factor, α GT,3 is the cubic correlation coefficient of load rate, α GT,2 is the quadratic correlation coefficient of load factor, α GT,1 is the first correlation coefficient of load factor, α GT,0 The constant term is used to calculate the efficiency. Since the power generation efficiency of the gas turbine is closely related to the load factor, the efficiency curve is used to simulate the gas turbine and establish it as a high-order polynomial relationship.

[0134] By solving the parameter identification model, a set of gas turbine parameter vectors can be obtained. The measured data of the verification set, including purchased electricity power, purchased gas power and load power, are input for simulation. The simulation results are recorded, the simulation curve can be drawn, and the error between the simulation value and the actual value can be calculated.

[0135] For example, the steps of checking steady-state parameters of an integrated energy system (IES) model combined with simulation data include:

[0136] 1) First, build a typical equipment transient simulation model in Simulink based on the mathematical model of each typical equipment;

[0137] 2) Construct the IES integrated energy system simulation model based on the topological connection relationship of multiple typical equipment transient simulation models;

[0138] 3) Preliminary configuration of the parameters of the integrated energy system simulation model based on the acquired basic equipment parameters and actual operation data;

[0139] 4) Control strategy setting: Set the equipment operation status according to the actual control strategy of IES, such as changing the working condition of lithium bromide absorption chiller according to the demand for heating or cooling;

[0140] 5) Input the power data of the comprehensive energy system under the actual control strategy, including the purchased electricity power, purchased gas power and load power, and perform simulation. When the simulation results tend to be stable, record the simulation results such as the energy conversion efficiency change curve, obtain the intermediate parameter values, and obtain the gas temperature, pressure and other data of the processes such as constant entropy compression, constant pressure heat absorption, constant entropy expansion and constant pressure heat release according to the simulation results. Use the thermodynamic theory that describes the operation mechanism of the equipment, such as substituting the calculation formula of the thermal efficiency of the Brayton cycle, to derive the parameter values ​​of the steady-state parameters;

[0141] 6) After further enriching the data set, the intermediate parameter values ​​are added to the data set in the model verification based on the operation data to obtain a data set based on the operation and simulation data;

[0142] 7) Establish the parameter identification model as shown below:

[0143]

[0144] Where g(x) is the energy conservation constraint, x is the lower limit of the transient parameter x, is the upper limit value of the transient parameter x;

[0145] 8) The parameter identification model is solved by the interior point method to obtain a set of optimal parameters x*. This set of parameters can minimize the sum of the approximate evaluation function of the voting method, that is, the number of measurement points with errors close to 0 is as large as possible, that is, the number of qualified measurement points is maximized. Therefore, this set of parameters can fit the results of the data set more accurately and can be considered as the parameters of the actual equipment. Here, the parameters are the optimal transient model parameters;

[0146] 9) The optimal steady-state parameters are derived based on the optimal transient model parameters, and simulation can be performed using the steady-state parameters to obtain more accurate steady-state simulation results.

[0147] The transient simulation method is explained by taking the energy center of a certain area in Shanghai World Expo Park as an example. Figure 5 As shown, computing resources can be manually divided according to scale and equipment type. The whole system is divided into three cores in the figure. The SC_uipc console subsystem does not occupy the computing resources of the lower computer. It must include a thermal subsystem SM_thermal. SS_ can be selectively configured according to actual needs. The SS subsystem of this system is the electrical model SS_electric1 and SS_electric2, which are divided according to the A / B incoming cable topology of the energy center.

[0148] The meaning of each part in the figure is as follows: Ts=50us is the internal solution step of the subsystem; SSN:ON is the simulation start; Discrete5e-0.5s. is the step size of discrete simulation; powergui is the electrical simulation initialization module; opts is the thermal subsystem control instruction; toui is the thermal subsystem control result output; loadsig1 is the coupling parameter between the thermal subsystem and the power subsystem 1; loadsig2 is the coupling parameter between the thermal subsystem and the power subsystem 2; SM_thermal is the thermal subsystem module; uisc is the input of the thermal subsystem to the control calculation module; toop is the control calculation instruction of the control subsystem to the thermal subsystem; SC_uipc is the control calculation module; signaltrs2 is the coupling parameter between the thermal subsystem and the power subsystem 2; SS_electric2 is the power subsystem 2 module; signaltrs1 is the coupling parameter between the thermal subsystem and the power subsystem 1; SS_electric1 is the power subsystem 1 module.

[0149] Among them, for example, the topology structure within the SM subsystem is as follows Figure 6 As shown, the SM subsystem includes an electric refrigeration device, a flue gas absorption refrigeration device, a gas heating device, two energy collection devices, a cold power supply device, a hot power supply device, multiple loads, a data reading module and a data sending module, wherein the electric refrigeration device includes an electric refrigeration unit 1-6, the flue gas absorption refrigeration device includes an absorption refrigeration machine 1-2, and the gas heating device includes an electric boiler 1-3. The electric refrigeration device and the flue gas absorption refrigeration device are connected to the cold power supply device through the same energy collection device, and the energy collection device connected to the electric refrigeration device and the flue gas absorption refrigeration device is also connected to a cold water storage tank and a refrigeration unit; the gas heating device is connected to the hot power supply device through another energy collection device, and the energy collection device connected to the gas heating device is also connected to a hot water storage tank and a heating unit, and multiple loads 1-4 are respectively connected to the cold power supply device and the hot power supply device; the device model is networked according to the thermal model connection structure, and the parameter configuration can be performed by double-clicking the device model. The data reading module is used to read the real-time operation data of the SM subsystem, and the data sending module is used to upload the real-time operation data of the SM subsystem.

[0150] For example, the topology of the two SS subsystems is as follows: Figure 7 , Figure 8As shown, the two SS subsystems, namely the SS subsystem of the incoming cable of the energy center A and the SS subsystem of the incoming cable of the energy center B, have similar structures, both of which include multiple parallel loads, circuit breakers connected to the loads, 10kV / 400V transformers, isolation transformers, refrigerators 1-3 connected to the 10kV / 400V transformers and isolation transformers, diesel generators, 10kV power grids for powering the subsystems, electrical loads, data reading modules, and data sending modules. Among them, the number of loads in the SS subsystem of the incoming cable of the energy center A is 8, and the number of loads in the SS subsystem of the incoming cable of the energy center B is 6. The power consumption of the thermal system is used as a load and connected to the electrical topology of the SS subsystem. The data reading module is used to read the real-time operation data of the SS subsystem, and the data sending module is used to upload the real-time operation data of the SS subsystem. The diesel generator and the 10kV power grid power the electrical loads. After the model is built, the model can be loaded to the server for operation to obtain some intermediate data.

[0151] According to the IES model parameter verification steps combining operation and simulation data, the parameters of the energy center in a certain area of ​​Shanghai World Expo Park were verified. The acquisition equipment collected a point every hour, and selected one day of data to generate multiple operation curves. It is assumed here that the accuracy of the collected data is very high, almost close to the true value (because the true value cannot be obtained in practice), so that no new errors will be introduced, which is conducive to the error analysis of the verification results. The identification results using operation data, simulation data, and the combination of operation and simulation data are shown in Tables 1 and 2.

[0152] Table 1 Parameter identification results of different data sources

[0153]

[0154]

[0155] Table 2 Identification error statistics of different data sources

[0156] Data Source Operational data Simulation data Run and Simulation Data Maximum error 3.3187 3.1945 2.8829 Estimation error statistics 0.0529 0.0503 0.0492

[0157] As can be seen from the table, the present invention uses simulation analysis of different parameter values ​​to show that the parameter values ​​have a significant impact on the scheduling and operation of the system. The equipment is optimized and scheduled by combining the parameter identification results of the actual operation and simulation data. Compared with the optimized scheduling results obtained by using only the actual operation data, the system daily operating cost and carbon emissions results are more accurate, and the obtained scheduling plan is more in line with the actual situation of the system; therefore, the present invention combines the actual operation data and transient simulation data to perform parameter verification on the steady-state model. Compared with only using the actual operation data to verify the parameters, the maximum error and estimated error statistics are greatly reduced, that is, the accuracy of the system parameter verification is improved by combining the transient simulation data. By adopting a wider range of data sources, the error in parameter identification can be effectively reduced, and more accurate results can be obtained.

[0158] In general, the present invention uses an integrated energy simulation platform to construct a transient simulation model of an integrated energy system, simulates the steady-state operation of the system to obtain relevant simulation operation data, namely, full-link simulation operation data, analyzes and supplements the missing actual operation data, thereby effectively improving the data quality, and then identifies and verifies the model parameters in combination with the operation data.

[0159] Specifically, it is manifested in: (1) using the integrated energy simulation platform to perform transient simulation and effectively obtain data from the intermediate operation links of the integrated energy system, which will help improve the accuracy of parameter identification; (2) using transient simulation data to verify equipment parameters through parameter identification models, if the simulation results are reasonable, the simulation method is considered feasible, otherwise the simulation parameters are debugged to obtain reasonable results. (3) correcting the steady-state simulation results according to the operating data of the transient simulation model to improve the simulation accuracy.

[0160] In summary, the present invention can more effectively obtain data from the intermediate links of the integrated energy system through transient simulation, improve the accuracy of parameter identification, and provide high-precision data support for the next step of combining operation and simulation data to perform equipment model parameter verification; the present invention uses the collected operation data, and the missing equipment intermediate data is supplemented or fitted through simulation, and can eliminate some erroneous data through simulation to further improve the accuracy of parameter identification or verification. This provides guidance that is closer to the actual situation for the optimized operation of the integrated energy system.

[0161] Embodiment 2:

[0162] Based on the same inventive concept, the present invention also provides a comprehensive energy steady-state parameter configuration system, such as Fig. 9 As shown, including:

[0163] An operation data acquisition module is used to acquire historical actual power data and historical actual operation data of the integrated energy system in multiple historical periods;

[0164] The simulation data acquisition module is used to use the historical actual power data in each historical period as input, use the pre-built transient simulation model of the integrated energy system to simulate the entire operation process, and output the simulation operation data of the entire process of the integrated energy system;

[0165] A data fusion module is used to fuse the simulation operation data of all links in each historical period with the historical actual operation data in the same historical period to obtain multiple fused data;

[0166] The transient parameter determination module is used to construct a parameter identification model based on multiple fusion data, solve the parameter identification model using the interior point method, and obtain the optimal output of the transient simulation model and the optimal transient parameters of the model corresponding to the optimal output;

[0167] The steady-state parameter configuration module is used to derive the optimal steady-state parameters of the integrated energy system based on the optimal transient parameters and combined with the equipment operation mechanism of the integrated energy system, and complete the steady-state parameter configuration.

[0168] In this embodiment, the simulation data acquisition module is specifically used for:

[0169] Based on each historical period, the historical actual power data in the historical period is used as input, and a simulation of a set time length is performed through the transient simulation model. When the operation of the transient simulation model reaches a steady state, the simulation results of the transient simulation model are output as the simulation operation data of all links of the integrated energy system.

[0170] In this embodiment, the data fusion module is specifically used for:

[0171] Based on each historical period, the data deviation of the historical actual operation data in the same historical period is determined by taking the full-link simulation operation data in the historical period as the data benchmark, and the data in the historical actual operation data whose data deviation exceeds the set threshold is regarded as abnormal data, and the abnormal data is eliminated;

[0172] Extracting the intermediate link simulation operation data from the full link simulation operation data in the historical period;

[0173] The simulated operation data of the intermediate links are fused with the historical actual operation data after eliminating abnormal data to obtain the fused data for the historical period.

[0174] In this embodiment, the transient parameter determination module is specifically used for:

[0175] Based on each historical period, determine the difference between the fusion data in the historical period and the full-link simulation operation data output by the transient simulation model;

[0176] Based on the difference, an approximate evaluation function based on the voting method is used to determine the output deviation of the transient simulation model in the historical period;

[0177] The objective function is constructed with the goal of minimizing the sum of the output deviations of the transient simulation model in multiple historical periods;

[0178] According to the objective function, the constraints corresponding to each device in the integrated energy system are formulated and a parameter identification model is constructed.

[0179] In this embodiment, the expression corresponding to the objective function is as follows:

[0180]

[0181] Where N represents the number of measurement points, that is, the number of historical time periods. The data in each measurement point includes the historical actual power data in a historical time period and the fusion data corresponding to the historical actual power data. i (e i ) represents the approximate evaluation function of the measurement point i based on the voting method, e i represents the difference between the output of the transient simulation model at the measuring point i and the fusion data, satisfying f i (e i )≥0 and when e i The closer it is to 0, the i (e i ) is closer to 0; i and c represent the correlation coefficient, Z i represents the fused data at the measuring point i, x represents the transient parameter, h i (x) is the output of the transient simulation model under the transient parameter x, and θ represents the constraint condition.

[0182] In this embodiment, the constraint conditions include energy conservation constraints of each device in the integrated energy system and upper and lower limit constraints of transient parameters.

[0183] In this embodiment, the simulation data acquisition module is also used for:

[0184] Based on the mathematical models of each device in the integrated energy system, a transient simulation sub-model of each device is constructed;

[0185] Based on the transient simulation sub-model of each device and the topological connection relationship of each device in the integrated energy system, the structure of the transient simulation model is determined;

[0186] According to the actual operation data of the integrated energy system in a typical historical period, the initial transient parameters of the transient simulation model are determined, and combined with the structure of the transient simulation model, the transient simulation model is preliminarily constructed.

[0187] In this embodiment, each device in the integrated energy system includes: at least one of energy production equipment, energy conversion equipment and energy storage equipment.

[0188] Example 3

[0189] like Fig.10 As shown, the present invention also provides an electronic device, which may be a computer device, a single-chip device, an intelligent mobile device, etc. The electronic device in this embodiment may include a processor, a memory, a transceiver component, etc. The memory, the processor, and the transceiver component are connected via a bus; the memory may be used to store an execution program, and an exemplary execution program may include instructions; the processor is used to execute the instructions stored in the memory. The memory may also be used to store data, which may be called and / or modified when the instructions are executed.

[0190] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in a storage medium to implement the corresponding method flow or corresponding functions, so as to implement the steps of a comprehensive energy steady-state parameter configuration method in the above-mentioned embodiment.

[0191] Example 4

[0192] Based on the same inventive concept, the present invention also provides a readable storage medium, specifically an electronic device readable storage medium (Memory), which is a memory device in an electronic device for storing programs and data. It can be understood that the storage medium here can include both built-in storage media in electronic devices and, of course, extended storage media supported by electronic devices. The storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by a processor are also stored in the storage space, and these instructions can be one or more execution programs (including program codes). It should be noted that the storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk storage. The processor loads and executes one or more instructions stored in the storage medium, which can implement the steps of a comprehensive energy steady-state parameter configuration method in the above embodiment.

[0193] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0194] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0195] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0196] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0197] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit its protection scope. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that after reading the present invention, those skilled in the art can still make various changes, modifications or equivalent substitutions to the specific implementation methods of the application, but these changes, modifications or equivalent substitutions are all within the protection scope of the claims of the present invention.

Claims

1. A method for configuring comprehensive energy steady-state parameters, characterized in that: include: Obtain historical actual power data and historical actual operation data of the integrated energy system in multiple historical periods; Based on each of the historical time periods, the historical actual power data in the historical time period is used as input, a pre-built transient simulation model of the integrated energy system is used to simulate the entire operation process, and the simulation operation data of the entire operation process of the integrated energy system is output; The simulated operation data of all links in each of the historical time periods are merged with the historical actual operation data in the same historical time period to obtain a plurality of fused data; Building a parameter identification model based on the plurality of fused data, solving the parameter identification model using an interior point method, and obtaining an optimal output of the transient simulation model and an optimal transient parameter of the model corresponding to the optimal output; Based on the optimal transient parameters and in combination with the equipment operation mechanism of the integrated energy system, the optimal steady-state parameters of the integrated energy system are derived to complete the steady-state parameter configuration.

2. The method according to claim 1, characterized in that Based on each of the historical time periods, the historical actual power data in the historical time period is used as input, a pre-built transient simulation model of the integrated energy system is used to simulate the entire operation link, and the simulation operation data of the entire link of the integrated energy system is output, including: Based on each of the historical time periods, the historical actual power data in the historical time period is used as input, and simulation of a set time length is performed through the transient simulation model. When the operation of the transient simulation model reaches a steady state, the simulation result of the transient simulation model is output as the full-link simulation operation data of the integrated energy system.

3. The method according to claim 1 or 2, characterized in that The full-link simulation operation data in each of the historical time periods is fused with the historical actual operation data in the same historical time period to obtain a plurality of fused data, including: Based on each of the historical time periods, taking the simulated operation data of all links in the historical time period as the data benchmark, determining the data deviation of the historical actual operation data in the same historical time period, treating the data in the historical actual operation data whose data deviation exceeds the set threshold as abnormal data, and eliminating the abnormal data; Extracting the intermediate link simulation operation data from the full link simulation operation data in the historical period; The simulated operation data of the intermediate links are fused with the historical actual operation data after eliminating abnormal data to obtain fused data in the historical period.

4. The method according to claim 1, characterized in that The constructing a parameter identification model based on the plurality of fused data comprises: Based on each of the historical time periods, determining the difference between the fusion data in the historical time period and the full-link simulation operation data output by the transient simulation model; Based on the difference, an approximate evaluation function based on a voting method is used to determine an output deviation of the transient simulation model in the historical period; Constructing an objective function with the goal of minimizing the sum of the output deviations of the transient simulation model in the plurality of historical time periods; According to the objective function, the constraint conditions corresponding to each device in the integrated energy system are formulated and a parameter identification model is constructed.

5. The method according to claim 4, characterized in that The expression corresponding to the objective function is as follows: Wherein, N represents the number of measuring points, that is, the number of the historical time periods, and the data in each measuring point includes a historical actual power data in the historical time period and the fusion data corresponding to the historical actual power data, f i (e i ) represents the approximate evaluation function of the measurement point i based on the voting method, e i represents the difference between the output of the transient simulation model and the fusion data at the measuring point i, satisfying f i (e i )≥0 and when e i The closer it is to 0, the i (e i ) is closer to 0; i and c represent the correlation coefficient, Z i represents the fused data at the measuring point i, x represents the transient parameter, h i (x) is the output of the transient simulation model under the transient parameter x, and θ represents the constraint condition.

6. The method according to claim 4 or 5, characterized in that The constraint conditions include energy conservation constraints of each device in the integrated energy system and upper and lower limit constraints of transient parameters.

7. The method according to claim 1, characterized in that The transient simulation model is constructed by the following steps: Based on the mathematical model of each device in the integrated energy system, construct a transient simulation sub-model of each device; Based on the transient simulation sub-models of each of the devices, and according to the topological connection relationship of each device in the integrated energy system, determining the structure of the transient simulation model; According to the actual operation data of the integrated energy system in a typical historical period, the initial transient parameters of the transient simulation model are determined, and the transient simulation model is preliminarily constructed in combination with the structure of the transient simulation model.

8. The method according to claim 7, characterized in that Each device in the integrated energy system includes at least one of energy production equipment, energy conversion equipment and energy storage equipment.

9. A comprehensive energy steady-state parameter configuration system, characterized in that: include: An operation data acquisition module is used to acquire historical actual power data and historical actual operation data of the integrated energy system in multiple historical periods; A simulation data acquisition module is used to use the historical actual power data in each historical period as input, use a pre-built transient simulation model of the integrated energy system to simulate all operation links, and output the simulation operation data of all links of the integrated energy system; A data fusion module, used for fusing the simulation operation data of all links in each historical period with the historical actual operation data in the same historical period to obtain a plurality of fused data; A transient parameter determination module, used to construct a parameter identification model based on the plurality of fused data, solve the parameter identification model using an interior point method, and obtain an optimal output of the transient simulation model and an optimal transient parameter of the model corresponding to the optimal output; The steady-state parameter configuration module is used to derive the optimal steady-state parameters of the integrated energy system based on the optimal transient parameters and in combination with the equipment operation mechanism of the integrated energy system, and complete the steady-state parameter configuration.

10. The system according to claim 9, characterized in that The simulation data acquisition module is specifically used for: Based on each of the historical time periods, the historical actual power data in the historical time period is used as input, and simulation of a set time length is performed through the transient simulation model. When the operation of the transient simulation model reaches a steady state, the simulation result of the transient simulation model is output as the full-link simulation operation data of the integrated energy system.

11. The system according to claim 9 or 10, characterized in that The data fusion module is specifically used for: Based on each of the historical time periods, taking the simulated operation data of all links in the historical time period as the data benchmark, determining the data deviation of the historical actual operation data in the same historical time period, treating the data in the historical actual operation data whose data deviation exceeds the set threshold as abnormal data, and eliminating the abnormal data; Extracting the intermediate link simulation operation data from the full link simulation operation data in the historical period; The simulated operation data of the intermediate links are fused with the historical actual operation data after eliminating abnormal data to obtain fused data in the historical period.

12. The system according to claim 9, characterized in that The transient parameter determination module is specifically used for: Based on each of the historical time periods, determining the difference between the fusion data in the historical time period and the full-link simulation operation data output by the transient simulation model; Based on the difference, an approximate evaluation function based on a voting method is used to determine an output deviation of the transient simulation model in the historical period; Constructing an objective function with the goal of minimizing the sum of the output deviations of the transient simulation model in the plurality of historical time periods; According to the objective function, the constraint conditions corresponding to each device in the integrated energy system are formulated and a parameter identification model is constructed.

13. The system of claim 12, wherein: The expression corresponding to the objective function is as follows: Wherein, N represents the number of measuring points, that is, the number of the historical time periods, and the data in each measuring point includes a historical actual power data in the historical time period and the fusion data corresponding to the historical actual power data, f i (e i ) represents the approximate evaluation function of the measurement point i based on the voting method, e i represents the difference between the output of the transient simulation model and the fusion data at the measuring point i, satisfying f i (e i )≥0 and when e i The closer it is to 0, the i (e i ) is closer to 0; i and c represent the correlation coefficient, Z i represents the fused data at the measuring point i, x represents the transient parameter, h i (x) is the output of the transient simulation model under the transient parameter x, and θ represents the constraint condition.

14. The system according to claim 12 or 13, characterized in that The constraint conditions include energy conservation constraints of each device in the integrated energy system and upper and lower limit constraints of transient parameters.

15. The system of claim 9, wherein: The simulation data acquisition module is also used for: Based on the mathematical model of each device in the integrated energy system, construct a transient simulation sub-model of each device; Based on the transient simulation sub-models of each of the devices, and according to the topological connection relationship of each device in the integrated energy system, determining the structure of the transient simulation model; According to the actual operation data of the integrated energy system in a typical historical period, the initial transient parameters of the transient simulation model are determined, and combined with the structure of the transient simulation model, the transient simulation model is preliminarily constructed.

16. The system of claim 15, wherein: Each device in the integrated energy system includes at least one of energy production equipment, energy conversion equipment and energy storage equipment.

17. An electronic device, characterized in that: include: at least one processor and memory; The memory and the processor are connected via a bus; The memory is used to store one or more programs; When the one or more programs are executed by the at least one processor, the integrated energy steady-state parameter configuration method according to any one of claims 1 to 8 is implemented.

18. A readable storage medium, characterized in that: An execution program is stored thereon, and when the execution program is executed, the comprehensive energy steady-state parameter configuration method as described in any one of claims 1 to 8 is implemented.

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