CN115903549A - TwinCAT 3-based scheduling strategy screening method and device for comprehensive energy system - Google Patents
TwinCAT 3-based scheduling strategy screening method and device for comprehensive energy system Download PDFInfo
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Abstract
The embodiment of the application provides a TwinCAT 3-based scheduling strategy screening method and device for an integrated energy system, and the method comprises the steps of determining an operation mechanism of each energy device in the integrated energy system, and constructing a dual steady-state simulation model corresponding to each energy device based on the operation mechanism; combining all the double steady-state simulation models belonging to the comprehensive energy system to obtain a comprehensive energy system simulation model containing a scheduling strategy; and converting the comprehensive energy system simulation model containing the scheduling strategy into a TwinCAT3 model, independently compressing and accelerating the scheduling strategy and the dual steady-state simulation model in the TwinCAT3 model, and obtaining the optimal scheduling strategy based on the simulation result. And (3) converting the double steady-state simulation model into a TwinCAT3 model to perform accelerated simulation suitable for the TwinCAT3 model by constructing a double steady-state simulation model corresponding to the basic function and the complete function of each device in the comprehensive energy system, and obtaining an optimal scheduling strategy suitable for the comprehensive energy system from an accelerated simulation result.
Description
Technical Field
The application belongs to the field of energy control simulation, and particularly relates to a TwinCAT 3-based scheduling strategy screening method and device for an integrated energy system.
Background
An electric power department has widely adopted a mode of using a solver to solve after an optimized scheduling model is established to schedule a comprehensive energy system so as to improve the economic benefit and the energy utilization rate of energy supply. With the access of massive new energy to the integrated energy system, the parameter space of the integrated energy system model is multiplied, the calculation difficulty and uncertainty of the energy optimization scheduling of the integrated energy system model are increased continuously, the compiling of the optimization scheduling strategy is easy to cause problems, the problems can be caused when the optimization scheduling strategy is applied to an actual integrated energy system, economic losses are caused, and therefore the optimization scheduling strategy needs to be subjected to simulation verification before the actual application of the optimization scheduling strategy.
At present, researchers introduce various simulation software into the electrical field to build an optimized scheduling strategy platform, such as LabVIEW, HYPERSTIM, MATLAB/Simulink and the like. However, in the prior art, research results or more attention is paid to steady-state characteristics, equipment is often abstracted into conversion formulas among different energy forms without considering operation conditions such as grid connection, backwater and the like, and a comprehensive energy system cannot be truly described; or the simulation speed is slow, and the requirement of the optimized scheduling strategy verification platform on quick verification cannot be met.
Disclosure of Invention
In order to overcome the defects in the prior art, the embodiment provides a method and a device for screening a scheduling strategy of a TwinCAT 3-based comprehensive energy system.
Specifically, in a first aspect, the present embodiment provides a screening method for a scheduling policy of a TwinCAT 3-based integrated energy system, including:
determining an operation mechanism of each energy device in the comprehensive energy system, and constructing a double steady-state simulation model corresponding to each energy device based on the operation mechanism;
combining all the double steady-state simulation models belonging to the comprehensive energy system to obtain a comprehensive energy system simulation model containing a scheduling strategy;
and converting the comprehensive energy system simulation model containing the scheduling strategy into a TwinCAT3 model, independently compressing and accelerating the scheduling strategy and the dual steady-state simulation model in the TwinCAT3 model, and obtaining an optimal scheduling strategy based on a simulation result.
Optionally, the determining an operation mechanism of each energy device in the integrated energy system, and constructing a dual steady-state simulation model corresponding to each energy device based on the operation mechanism includes:
screening energy equipment belonging to a comprehensive energy system, and determining an operation mechanism of the energy equipment;
and constructing a double steady-state simulation model corresponding to each energy device based on the operation mechanism.
Optionally, the screening of the energy devices belonging to the integrated energy system and the determining of the operation mechanism of the energy devices include:
sorting the affiliation of the current energy equipment, and screening out the energy equipment belonging to the comprehensive energy system;
and analyzing the structure of the energy equipment, and determining the operation mechanism of the energy equipment according to the analysis result.
Optionally, the constructing a dual steady-state simulation model corresponding to each energy device based on the operation mechanism includes:
extracting basic parameters for realizing basic functions of the energy equipment from the operation mechanism, and constructing a basic steady-state simulation model corresponding to each energy equipment based on the basic parameters;
extracting complete parameters for realizing the complete functions of the energy equipment in the operation process, and constructing a complete steady-state simulation model corresponding to each energy equipment based on the complete parameters;
and obtaining a double steady-state simulation model comprising the basic steady-state simulation model and the complete steady-state simulation model.
Optionally, the extracting, from the operation mechanism, basic parameters for implementing basic functions of the energy devices, and constructing a basic steady-state simulation model corresponding to each energy device based on the basic parameters includes:
determining a basic function realized by the energy equipment, and extracting basic parameters for realizing the basic function from the operation mechanism;
and determining a basic scheduling strategy corresponding to the basic function, and constructing a basic steady-state simulation model corresponding to each energy device by combining the basic parameters.
Optionally, the extracting, from the operation mechanism, complete parameters for realizing complete functions of the energy devices, and constructing a complete steady-state simulation model corresponding to each energy device based on the complete parameters includes:
determining a complete function realized by the energy equipment, and extracting basic parameters for realizing the complete function from the operation mechanism;
and determining a complete scheduling strategy corresponding to the complete function, and constructing a complete steady-state simulation model corresponding to each energy device by combining the complete parameters.
Optionally, the combining all the double steady-state simulation models belonging to the integrated energy system to obtain the integrated energy system simulation model including the scheduling policy includes:
extracting all constraint conditions in the double steady-state simulation model, and integrating the constraint conditions to obtain a public constraint set suitable for the comprehensive energy system;
extracting a cost expression corresponding to each device from the double steady-state simulation model, and constructing an optimization objective function suitable for the comprehensive energy system based on the cost expressions;
and obtaining a comprehensive energy system simulation model containing a scheduling strategy based on the common constraint set and the optimization objective function.
Optionally, the converting the integrated energy system simulation model including the scheduling policy into a TwinCAT3 model, performing independent compression and accelerated simulation on the scheduling policy and the dual steady-state simulation model in the TwinCAT3 model, and obtaining an optimal scheduling policy based on a simulation result includes:
selecting a compiler suitable for a Simulink model, and calling the compiler to carry out Simulink model compilation on the comprehensive energy system simulation model containing the scheduling strategy;
extracting a result file output after compiling, classifying and compressing the result file to obtain a target file, and converting the target file into a TwinCAT3 model;
independently compressing the scheduling strategy and the dual steady-state simulation model in the TwinCAT3 model;
and performing accelerated simulation based on the TwinCAT3 model on the compressed scheduling strategy and the compressed dual steady-state simulation model, and obtaining an optimal scheduling strategy based on a simulation result.
In a second aspect, the present embodiment provides a scheduling policy screening apparatus for a TwinCAT 3-based integrated energy system, including:
the system comprises a construction unit, a simulation unit and a simulation unit, wherein the construction unit is used for determining the operation mechanism of each energy device in the comprehensive energy system and constructing a double steady-state simulation model corresponding to each energy device based on the operation mechanism;
the model unit is used for combining all the double steady-state simulation models belonging to the comprehensive energy system to obtain a comprehensive energy system simulation model containing a scheduling strategy;
and the scheduling strategy determining unit is used for converting the comprehensive energy system simulation model containing the scheduling strategy into a TwinCAT3 model, independently compressing and accelerating the scheduling strategy and the dual steady-state simulation model in the TwinCAT3 model, and obtaining an optimal scheduling strategy based on a simulation result.
Optionally, the building unit includes:
the mechanism confirming subunit is used for screening the energy equipment belonging to the comprehensive energy system and determining the operation mechanism of the energy equipment;
and the model construction subunit is used for constructing a double steady-state simulation model corresponding to each energy device based on the operation mechanism.
The beneficial effect that technical scheme that this application provided brought is:
and converting the dual steady-state simulation model into a TwinCAT3 model to perform accelerated simulation suitable for the TwinCAT3 model by constructing a dual steady-state simulation model corresponding to the basic function and the complete function of each device in the comprehensive energy system, and obtaining an optimal scheduling strategy suitable for the comprehensive energy system from an accelerated simulation result.
Drawings
In order to more clearly illustrate the technical solutions of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic flow chart of a scheduling policy screening method of a TwinCAT 3-based integrated energy system according to this embodiment;
fig. 2 is a schematic structural diagram of a scheduling policy screening apparatus of a TwinCAT 3-based integrated energy system according to this embodiment;
FIG. 3 is a schematic diagram of the electrical, thermal and cooling load curves of the park according to the present embodiment;
fig. 4 is a schematic diagram of a photovoltaic power curve of a park according to the present embodiment;
fig. 5 is a schematic diagram illustrating a change of an electrical energy storage output and an operation and maintenance cost according to the embodiment;
FIG. 6 is a schematic view of the operation cost of the park according to the present embodiment;
fig. 7 is a schematic structural diagram of a scheduling policy screening apparatus of a TwinCAT 3-based integrated energy system according to this embodiment.
Detailed Description
To make the structure and advantages of the present application clearer, the structure of the present application will be further described with reference to the accompanying drawings.
In a first aspect, the present embodiment provides a screening method for a scheduling policy of a TwinCAT 3-based integrated energy system, as shown in fig. 1, including:
and S10, determining the operation mechanism of each energy device in the comprehensive energy system, and constructing a double steady-state simulation model corresponding to each energy device based on the operation mechanism.
The method mainly realizes the technical scheme of constructing the dual steady-state simulation model based on the operation excitation of the energy equipment. Different from a common single steady-state simulation model, the double steady-state simulation model constructed here is a new model additionally established with a slight deviation on a standard model, and then the same subsequent processing is carried out on the two models, and the standard model is calibrated based on a preset deviation or used as a reference for detection.
And S20, combining all the double steady-state simulation models belonging to the comprehensive energy system to obtain a comprehensive energy system simulation model containing a scheduling strategy.
And combining the obtained double steady-state simulation models to obtain a comprehensive energy system simulation model containing a scheduling strategy, so that accelerated simulation processing can be conveniently carried out according to the comprehensive energy system simulation model in the subsequent steps.
And S30, converting the comprehensive energy system simulation model containing the scheduling strategy into a TwinCAT3 model, independently compressing and accelerating the scheduling strategy and the dual steady-state simulation model in the TwinCAT3 model, and obtaining an optimal scheduling strategy based on a simulation result.
Although the simulation speed can be increased by converting the simulation model into the twinCAT3 model, the data to be simulated is compressed before the simulation is performed, and the data size for the simulation can be increased by using the compressed data model for simulation, so that the simulation speed is further increased.
And (3) converting the double steady-state simulation model into a TwinCAT3 model to perform accelerated simulation suitable for the TwinCAT3 model by constructing a double steady-state simulation model corresponding to the basic function and the complete function of each device in the comprehensive energy system, and obtaining an optimal scheduling strategy suitable for the comprehensive energy system from an accelerated simulation result.
Optionally, determining an operation mechanism of each energy device in the integrated energy system, and constructing a dual steady-state simulation model corresponding to each energy device based on the operation mechanism, that is, step S10 includes:
s11, screening energy equipment belonging to the comprehensive energy system, and determining the operation mechanism of the energy equipment;
and S12, constructing a double steady-state simulation model corresponding to each energy device based on the operation mechanism.
In order to construct the dual steady-state simulation model used in the subsequent steps, energy devices requiring the construction of the dual steady-state simulation model need to be screened, and then the operation mechanism of the screened energy devices is determined.
Specifically, the energy devices belonging to the integrated energy system are screened, and the operation mechanism of the energy devices is determined, that is, step S11 includes:
s111, sorting the affiliation of the current energy equipment, and screening out the energy equipment belonging to the comprehensive energy system;
and step S112, analyzing the structure of the energy equipment, and determining the operation mechanism of the energy equipment according to the analysis result.
In the implementation, because the energy devices associated with the current integrated energy system are numerous, in order to accurately optimize the integrated energy system, the energy devices are firstly combed and the energy devices which do not belong to the integrated energy system are eliminated. Common energy equipment belonging to an integrated energy system comprises a gas turbine, an electric refrigerator, an absorption refrigerator, a photovoltaic, a gas boiler, an electric energy storage device and the like.
The method for carding the energy equipment in the step is simple, namely, the energy equipment is sorted according to the affiliation of the energy equipment, and if the affiliation is not in the comprehensive energy system, the subsequent operation mechanism acquisition step is not needed.
After the energy equipment which belongs to the comprehensive energy system is determined, the structure of the energy equipment can be analyzed, and the operation mechanism of the energy equipment is determined based on the analysis result.
Optionally, the constructing a dual steady-state simulation model corresponding to each energy device based on the operation mechanism, that is, step S12, includes:
step S121, extracting basic parameters for realizing basic functions of the energy equipment from an operation mechanism, and constructing a basic steady-state simulation model corresponding to each energy equipment based on the basic parameters;
step S122, extracting complete parameters for realizing the complete functions of the energy equipment from the operation mechanism, and constructing a complete steady-state simulation model corresponding to each energy equipment based on the complete parameters;
and S123, obtaining a double steady-state simulation model comprising a basic steady-state simulation model and a complete steady-state simulation model.
In implementation, the dual steady-state model of the corresponding energy device constructed in this step includes a basic steady-state simulation model constructed according to basic parameters of the energy device and a complete steady-state simulation model constructed according to complete parameters of the energy device.
The basic parameter refers to the minimum parameter which can be supported by the energy equipment to realize the expected function; the complete parameter refers to all parameters of the energy device capable of realizing all functions.
Specifically, the step of constructing the basic steady-state simulation model includes:
step S1211, determining a basic function realized by the energy equipment, and extracting basic parameters for realizing the basic function from an operation mechanism;
step S1212, determining a basic scheduling policy corresponding to the basic function, and building a basic steady-state simulation model corresponding to each energy device by combining the basic parameters.
Correspondingly, the step of constructing the complete steady-state simulation model comprises the following steps:
step S1221, determining the complete function realized by the energy equipment, and extracting basic parameters for realizing the complete function from the operation mechanism;
step S1222, determining a complete scheduling policy corresponding to the complete function, and constructing a complete steady-state simulation model corresponding to each energy device by combining the complete parameters.
In the implementation, the energy equipment is taken as an example of a gas turbine, and a gas turbine power generation system is composed of a micro gas turbine, a permanent magnet synchronous generator, a rectifier, an inverter and a filter.
The basic mathematical model of a gas turbine is:
in the formula (I), the compound is shown in the specification,P gt,e representing the power generated by the gas turbine;H gt,heat representing the heat production power of the gas turbine;P gt,gas representing the inlet power of the gas turbine;
、
the power generation efficiency and the waste heat utilization efficiency of the gas turbine are respectively shown.
On the basis of the basic mathematical model formed by the equations (1) and (2), it is also known that the relationship between the intake power and the intake rate of the gas turbine is as follows,
in the formula (I), the compound is shown in the specification,
represents the heating value of natural gas;
indicating the intake rate of natural gas.
In general, the mathematical models formed by the formulas (1), (2) and (3) are complete mathematical models. Furthermore, the gas turbine directly drives a built-in high-speed generator through the micro gas turbine, a high-frequency alternating current power supply is converted into a power-frequency alternating current power supply through an SPWM (sinusoidal pulse width modulation) rectifier and a frequency converter, and the power-frequency alternating current power supply is transmitted to a load or an alternating current power grid through frequency conversion speed regulation and PQ (Power quality control). Therefore, the calculation formulas of the SPWM modulation rectifier and the frequency converter can be properly added into the complete mathematical model.
Optionally, all the double steady-state simulation models belonging to the integrated energy system are combined to obtain the integrated energy system simulation model including the scheduling policy, and step S20 includes:
s21, extracting constraint conditions in all the double steady-state simulation models, and integrating the constraint conditions to obtain a common constraint set suitable for the comprehensive energy system;
s22, extracting a cost expression corresponding to each device from the double steady-state simulation model, and constructing an optimization objective function suitable for the comprehensive energy system based on the cost expressions;
and S23, obtaining a comprehensive energy system simulation model containing a scheduling strategy based on the common constraint set and the optimization objective function.
In the implementation, because the above-constructed dual steady-state simulation model has constraint conditions respectively corresponding to the basic steady-state simulation model and the complete steady-state simulation model, in order to complete the accelerated simulation operation in the subsequent steps, two sets of constraint conditions need to be integrated to obtain a common constraint set suitable for the integrated energy system.
FIG. 2 is a comprehensive energy system architecture of a certain actual park, wherein a class of industrial loads refers to industrial production lines requiring electric heat loads in the production process, and waste heat in a certain proportion is returned to a heat supply network after heat energy is used; the second type of industrial load refers to an industrial production line requiring only electrical load, and the cold load is mainly park refrigeration.
Establishing a park optimization scheduling model considering the least outsourcing energy cost and equipment operation and maintenance cost, wherein an optimization objective function can be expressed as
Wherein, the first and the second end of the pipe are connected with each other,C 1 representing the cost of outsourcing energy, including the cost of purchasing natural gas, heat and electricity from the outside, as
In the formula (I), the compound is shown in the specification,
and
respectively representing the price of natural gas, the price of heat energy and the price of external electricity purchase;
and
、
respectively representtThe time interval natural gas purchase amount, the heat energy purchase amount and the outsourcing electric purchase amount.
C 2 Represents the operating and maintenance cost of the equipment, and is represented as
In the formula (I), the compound is shown in the specification,
and
respectively represents the unit power operation and maintenance costs of photovoltaic, a gas boiler, a gas turbine, an electric refrigerator, an absorption refrigerator and electric energy storage,
、
、
、
、
and
respectively representing a photovoltaic system, a gas boiler, a gas turbine, an electric refrigerator, an absorption refrigerator and an electric energy storage systemtThe power of the time period.
The common constraint set is:
1) Energy storage operation restraint
By setting
And
the two 0-1 variables allow only three operating models for energy storage: charged, discharged and neither charged nor discharged when
Is 1, indicating electrical storage charging, when
A value of 1 indicates an electrical energy storage discharge. The specific constraints are expressed as:
in the formula (I), the compound is shown in the specification,
the rated charge-discharge power of the electrical energy storage is shown.
There are the following constraints on the electrical energy storage capacity:
in the formula (I), the compound is shown in the specification,
and
respectively representing the minimum and maximum capacity of the electrical energy storage.
2) Other plant operating constraints
The gas boiler, the gas turbine, the electric refrigerator, the absorption refrigerator and other equipment all work within an allowable range, and the output of the equipment can not exceed the maximum and minimum limit range and can be expressed as follows:
in the formula (I), the compound is shown in the specification,H gb,min 、H gt,min 、P ac,min andH ab,min respectively representing the minimum heat production power of a gas boiler, the minimum heat production power of a gas turbine, the minimum electric power consumption of an electric refrigerator and the minimum heat power consumption of an absorption refrigerator;H gb,max 、H gt,max 、P ac,max andH ab,max respectively representing the maximum heat production power of a gas boiler, the maximum heat production power of a gas turbine, and electric refrigerationThe maximum power consumption of the machine and the maximum heat consumption of the absorption refrigerator.
3) Restriction of purchased energy
For purchasing electricity, heat and natural gas from the outside, the following constraints are set:
in the formula (I), the compound is shown in the specification,P gas,min 、P heat,min andP grid,min respectively representing minimum power constraints for purchasing natural gas, thermal energy and electric energy from the outside;P gas,max 、P heat,max andP grid,max respectively representing the maximum power constraints for purchasing natural gas, thermal energy and electrical energy from the outside.
The research and research park is provided with photovoltaic, gas-fired boiler, gas turbine, electric refrigerator, absorption refrigerator and electric energy storage, the main loads are the electric, hot and cold loads required by industrial production, the load curve from 0 hour to 20 hours in a certain day park is shown in figure 3, and the photovoltaic power generation power curve is shown in figure 4
The results obtained by solving the established optimized scheduling model are shown in table 1:
TABLE 1 optimal scheduling model solution results
And constructing a simulation model of the comprehensive energy system equipment according to the framework of the electric heating and cooling system of the comprehensive energy system.
Optionally, the comprehensive energy system simulation model including the scheduling policy is converted into a TwinCAT3 model, the scheduling policy and the dual steady-state simulation model in the TwinCAT3 model are independently compressed and accelerated, and an optimal scheduling policy is obtained based on the simulation result, step S30 includes:
s31, selecting a compiler suitable for a Simulink model, and calling the compiler to carry out Simulink model compilation on a comprehensive energy system simulation model containing a scheduling strategy;
step S32, extracting the compiled and output result files, classifying and compressing the result files to obtain target files, and converting the target files into TwinCAT3 models;
s33, independently compressing a scheduling strategy and a dual steady-state simulation model in the TwinCAT3 model;
and S34, performing accelerated simulation based on the TwinCAT3 model on the compressed scheduling strategy and the compressed dual steady-state simulation model, and obtaining an optimal scheduling strategy based on a simulation result.
In implementation, before performing a specific operation of simulation based on the TwinCAT3 model in this step, a compiler needs to be invoked to perform Simulink model compilation on the integrated energy system simulation model including the scheduling policy.
Before calling the TwinCAT3 model for accelerated simulation, in order to further improve the effect of accelerated simulation, the result files output after compiling need to be extracted, the result files are classified and compressed to obtain target files, the target files are converted into the TwinCAT3 model, and then independent compression is performed on the scheduling strategy and the dual steady-state simulation model in the TwinCAT3 model.
The independent compression referred to here is to compress the scheduling policy and the dual steady-state simulation model separately. Considering that the number of inputs of the twinCAT3 model in unit time is limited, if the simulation speed is reduced according to the ordinary data transmission speed under the condition that the current simulation data volume is huge. Therefore, the present embodiment provides a data compression method, which respectively compresses a scheduling policy to be simulated and a dual steady-state simulation model, and performs accelerated simulation based on the compressed scheduling policy and the dual steady-state simulation model. Because the compressed data contains more contents on the premise of unchanged size, the simulation is carried out according to the compressed data, more simulation data can be processed in unit time, and the whole simulation time can be shortened compared with the simulation of the data before compression.
Specifically, the compression method herein can typically use the conventional data compression algorithm LZ77 algorithm and Huffman; and specific names and parameters in the scheduling strategy and the double steady-state simulation model can be replaced by short professional names aiming at the energy field affiliated to the embodiment, and the method can achieve the similar effect with a data compression algorithm.
The acceleration simulation technology based on the TwinCAT3 is adopted to perform acceleration simulation on the comprehensive energy system, and the TE1400 component carried by the TwinCAT3 can convert the model in Simulink into the TwinCAT3 model, so that the model is also visualized in the TwinCAT 3. And then, the input and output of the model are in one-to-one correspondence with the input and output of the controller by using a simple language, so that the closed-loop control can be realized, and the specific steps of converting the Simulink model into the TwinCAT3 model comprise the following steps:
301. selecting a compiler; running MATLAB with the identity of an administrator, modifying the path of the MATLAB into an installation folder of TwinCAT3 when the TE1400 is used for the first time, and running a SetupTwinCATTarget.p file in the TE1400 folder to enable the MATLAB to select a compiler for compiling a Simulink model;
302. setting a Simulink model; changing a solver into a fixed step length in Simulink model setting needing to be converted, and modifying a code generation file into 'TwinCAT.tlc'; inputting the name of a TcCom module generated in the Tc Build branch and selecting the derived module platform type; the corresponding parameters are modified in the Tc Advanced branch: the Task assignment item selects Manualconfig; the CallBy item selects Module; the Step size item selects UseTaskCycleTime;
the PLC Function Block item selects Module specific FB with properties for all parameters; through the setting, the module can automatically create a function block for calling the module by the PLC when being generated;
303. compiling a Simulink model; clicking the build to start compiling the model and waiting for the completion of compiling;
304. completing TwinCAT3 setting; finding a folder with the same name as the TcCom module generated in the step 303) in the TwinCAT3 folder, and selecting an xml file in the folder; newly building a PLC project in the TwinCAT3 project, clicking 'Import PLCopenXML' by a right button POUs, and selecting xml file Import; and completing variable declaration on the module interface functional block in the main function interface, and allocating the Task module as PlcTask.
And (4) simulating the system by taking the equipment output obtained by the CPLEX solution as input on a simulation platform, and verifying the control strategy. Firstly, the operation condition of the equipment is verified, as shown in fig. 5, a histogram of the electric energy storage output and an electric energy storage operation maintenance cost curve are shown, as shown in fig. 5, the rate of increase of the electric energy storage operation maintenance cost is in direct proportion to the absolute value of the electric energy storage output, and the model correctness is verified as the same as the actual condition.
Then, observing the operation cost curve of the park as shown in fig. 6, it can be seen that as the simulation progresses, the park cost gradually climbs to 374428 yuan, which is the same as the optimization solution result, and the correctness of the optimization scheduling strategy is verified.
Through comparison, the simulation speed of the strategy verification platform based on the TwinCAT3 is improved by more than 3 times compared with that of the strategy verification platform adopting MATLAB/Simulink, 1 hour and 7 minutes are needed when the MATLAB/Simulink platform is used, and the TwinCAT3 can be completed only by about 16 minutes and 12 seconds.
In a second aspect, the present embodiment provides a scheduling policy screening apparatus 4 of an integrated energy system based on TwinCAT3, as shown in fig. 7, including:
the building unit 41 is configured to determine an operation mechanism of each energy device in the integrated energy system, and build a dual steady-state simulation model corresponding to each energy device based on the operation mechanism.
The method mainly realizes the technical scheme of constructing the dual steady-state simulation model based on the operation excitation of the energy equipment. Unlike a common single steady-state simulation model, the double steady-state simulation model constructed here is a new model additionally constructed with a slight deviation for a standard model, and then the same subsequent processing is performed on the two models, and the standard model is calibrated based on a preset deviation or used as a reference for detection.
And the model unit 42 is used for combining all the double steady-state simulation models belonging to the comprehensive energy system to obtain a comprehensive energy system simulation model containing the scheduling strategy.
And combining the obtained double steady-state simulation models to obtain a comprehensive energy system simulation model containing a scheduling strategy, so that accelerated simulation processing can be conveniently carried out according to the comprehensive energy system simulation model in the subsequent steps.
And the scheduling policy determining unit 43 is configured to convert the integrated energy system simulation model including the scheduling policy into a TwinCAT3 model, perform independent compression and accelerated simulation on the scheduling policy and the dual steady-state simulation model in the TwinCAT3 model, and obtain an optimal scheduling policy based on a simulation result.
Although the simulation speed can be increased by converting the simulation model into the twinCAT3 model, the data to be simulated is compressed before the simulation is performed, and the data size for the simulation can be increased by using the compressed data model for simulation, so that the simulation speed is further increased.
And (3) converting the double steady-state simulation model into a TwinCAT3 model to perform accelerated simulation suitable for the TwinCAT3 model by constructing a double steady-state simulation model corresponding to the basic function and the complete function of each device in the comprehensive energy system, and obtaining an optimal scheduling strategy suitable for the comprehensive energy system from an accelerated simulation result.
Optionally, the constructing unit 41 includes:
the mechanism confirming subunit is used for screening the energy equipment belonging to the comprehensive energy system and determining the operation mechanism of the energy equipment;
and the model construction subunit is used for constructing a double steady-state simulation model corresponding to each energy device based on the operation mechanism.
In order to construct the dual steady-state simulation model used in the subsequent steps, energy devices requiring the construction of the dual steady-state simulation model need to be screened, and then the operation mechanism of the screened energy devices is determined.
Specifically, for energy equipment which is screened and belongs to the comprehensive energy system, the operation mechanism of the energy equipment is determined, that is, the mechanism confirmation subunit is specifically used for executing the following operations: sorting the affiliation of the current energy equipment, and screening out the energy equipment belonging to the comprehensive energy system; and analyzing the structure of the energy equipment, and determining the operation mechanism of the energy equipment according to the analysis result.
In the implementation, because the energy devices associated with the current integrated energy system are numerous, in order to accurately optimize the integrated energy system, the energy devices are firstly combed and the energy devices which do not belong to the integrated energy system are eliminated. Common energy equipment belonging to an integrated energy system comprises a gas turbine, an electric refrigerator, an absorption refrigerator, a photovoltaic, a gas boiler, an electric energy storage device and the like.
The method for carding the energy equipment in the step is simple, namely, the energy equipment is sorted according to the affiliation of the energy equipment, and if the affiliation is not in the comprehensive energy system, the subsequent operation mechanism acquisition step is not needed.
After the energy equipment belonging to the comprehensive energy system is determined, the structure of the energy equipment can be analyzed, and the operation mechanism of the energy equipment is determined based on the analysis result.
The sequence numbers in the above embodiments are merely for description, and do not represent the sequence of the assembly or the use of the components.
The above description is intended only to serve as examples of the present application and should not be construed as limiting the present application, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present application should be included in the scope of the present application.
Claims (10)
1. The TwinCAT 3-based scheduling strategy screening method for the comprehensive energy system is characterized by comprising the following steps of:
determining the operation mechanism of each energy device in the comprehensive energy system, and constructing a double steady-state simulation model corresponding to each energy device based on the operation mechanism;
combining all the double steady-state simulation models belonging to the comprehensive energy system to obtain a comprehensive energy system simulation model containing a scheduling strategy;
and converting the comprehensive energy system simulation model containing the scheduling strategy into a TwinCAT3 model, independently compressing and accelerating the scheduling strategy and the dual steady-state simulation model in the TwinCAT3 model, and obtaining an optimal scheduling strategy based on a simulation result.
2. The screening method of the scheduling strategy of the TwinCAT 3-based integrated energy system according to claim 1, wherein the determining of the operation mechanism of each energy device in the integrated energy system and the constructing of the dual steady-state simulation model corresponding to each energy device based on the operation mechanism comprises:
screening energy equipment belonging to a comprehensive energy system, and determining the operation mechanism of the energy equipment;
and constructing a double steady-state simulation model corresponding to each energy device based on the operation mechanism.
3. The method for screening the scheduling strategy of the TwinCAT 3-based integrated energy system according to claim 2, wherein the screening is performed on energy equipment belonging to the integrated energy system, and the determining of the operation mechanism of the energy equipment comprises the following steps:
sorting the affiliation of the current energy equipment, and screening out the energy equipment belonging to the comprehensive energy system;
and analyzing the structure of the energy equipment, and determining the operation mechanism of the energy equipment according to the analysis result.
4. The method of screening a scheduling strategy of a TwinCAT 3-based integrated energy system according to claim 2, wherein the constructing of the dual steady-state simulation model corresponding to each energy device based on the operation mechanism comprises:
extracting basic parameters for realizing basic functions of the energy equipment from the operation mechanism, and constructing a basic steady-state simulation model corresponding to each energy equipment based on the basic parameters;
extracting complete parameters for realizing the complete functions of the energy equipment in the operation process, and constructing a complete steady-state simulation model corresponding to each energy equipment based on the complete parameters;
and obtaining a double steady-state simulation model comprising the basic steady-state simulation model and the complete steady-state simulation model.
5. The screening method for scheduling strategies of TwinCAT 3-based integrated energy systems according to claim 4, wherein the extracting basic parameters for realizing the basic functions of the energy equipment from the operational mechanism and constructing a basic steady-state simulation model corresponding to each energy equipment based on the basic parameters comprises:
determining a basic function realized by the energy equipment, and extracting basic parameters for realizing the basic function from the operation mechanism;
and determining a basic scheduling strategy corresponding to the basic function, and constructing a basic steady-state simulation model corresponding to each energy device by combining the basic parameters.
6. The screening method of scheduling policy of twinCAT 3-based integrated energy system according to claim 4, wherein said extracting complete parameters for implementing the complete functions of said energy devices from said operational mechanism, and constructing a complete steady-state simulation model for each of said energy devices based on said complete parameters comprises:
determining a complete function realized by the energy equipment, and extracting basic parameters for realizing the complete function from the operation mechanism;
and determining a complete scheduling strategy corresponding to the complete function, and constructing a complete steady-state simulation model corresponding to each energy device by combining the complete parameters.
7. The screening method of the scheduling strategy of the TwinCAT 3-based integrated energy system according to claim 1, wherein the step of combining all the dual steady-state simulation models belonging to the integrated energy system to obtain the integrated energy system simulation model containing the scheduling strategy comprises the steps of:
extracting all constraint conditions in the double steady-state simulation model, and integrating the constraint conditions to obtain a common constraint set suitable for the comprehensive energy system;
extracting a cost expression corresponding to each device from the double steady-state simulation model, and constructing an optimization objective function suitable for the comprehensive energy system based on the cost expressions;
and obtaining a comprehensive energy system simulation model containing a scheduling strategy based on the common constraint set and the optimization objective function.
8. The screening method of the scheduling strategy of the TwinCAT 3-based integrated energy system according to claim 1, wherein the step of converting the integrated energy system simulation model containing the scheduling strategy into the TwinCAT3 model, the step of independently compressing and accelerating the scheduling strategy and the dual steady-state simulation model in the TwinCAT3 model, and the step of obtaining the optimal scheduling strategy based on the simulation result comprises the steps of:
selecting a compiler suitable for a Simulink model, and calling the compiler to carry out Simulink model compilation on the comprehensive energy system simulation model containing the scheduling strategy;
extracting a result file output after compiling, classifying and compressing the result file to obtain a target file, and converting the target file into a TwinCAT3 model;
independently compressing the scheduling strategy and the dual steady-state simulation model in the TwinCAT3 model;
and performing accelerated simulation based on the TwinCAT3 model on the compressed scheduling strategy and the compressed dual steady-state simulation model, and obtaining an optimal scheduling strategy based on a simulation result.
9. TwinCAT 3-based scheduling strategy screening device of an integrated energy system, which is characterized by comprising:
the system comprises a construction unit, a simulation unit and a simulation unit, wherein the construction unit is used for determining the operation mechanism of each energy device in the comprehensive energy system and constructing a double steady-state simulation model corresponding to each energy device based on the operation mechanism;
the model unit is used for combining all the double steady-state simulation models belonging to the comprehensive energy system to obtain a comprehensive energy system simulation model containing a scheduling strategy;
and the scheduling strategy determining unit is used for converting the comprehensive energy system simulation model containing the scheduling strategy into a TwinCAT3 model, independently compressing and accelerating the scheduling strategy and the dual steady-state simulation model in the TwinCAT3 model, and obtaining an optimal scheduling strategy based on a simulation result.
10. The TwinCAT 3-based scheduling policy screening device for integrated energy systems according to claim 9, wherein the constructing unit comprises:
the mechanism confirming subunit is used for screening the energy equipment belonging to the comprehensive energy system and determining the operation mechanism of the energy equipment;
and the model building subunit is used for building a double steady-state simulation model corresponding to each energy device based on the operation mechanism.
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