CN114610215A - Scheduling method and system of cogeneration system - Google Patents
Scheduling method and system of cogeneration system Download PDFInfo
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Abstract
The invention provides a scheduling method and a scheduling system of a cogeneration system, wherein the method comprises the following steps: acquiring the operation parameters of each device in the cogeneration system at the current moment; calculating to obtain real-time operation characteristic parameters representing the current operation state of each device based on the operation parameters; and inputting the real-time operation characteristic parameters into the optimized parameter prediction model to obtain the optimized operation parameter prediction value used for scheduling and/or controlling each device in the cogeneration system at the current moment. The invention is used for solving the defect that the overall power generation, heat supply and auxiliary service benefits of the cogeneration system cannot achieve better effects caused by coordinating the operation of each device in the cogeneration system by manual experience in the prior art, realizing the coordinated scheduling and accurate control of each device in the cogeneration system and optimizing the overall power generation, heat supply and auxiliary service benefits of the cogeneration system.
Description
Technical Field
The invention relates to the technical field of energy utilization, in particular to a scheduling method and system of a cogeneration system.
Background
The cogeneration is an energy-saving system which applies the energy cascade utilization principle and improves the energy utilization efficiency. In the system, high-temperature and high-pressure steam obtained by burning and heating fossil fuels such as coal and natural gas is firstly used for power generation, and the steam after power generation is then used for heat supply. Therefore, the cogeneration system has the advantages of saving energy, reducing atmospheric pollution, saving urban land and the like.
In the heat supply period, in order to ensure the heat supply amount, the minimum electric output exists in the cogeneration unit, and the adjusting capacity of the electric output of the unit is reduced. Meanwhile, under the scheduling mode of 'deciding power by heat', the cogeneration unit limits the adjustment flexibility of the power grid.
With the increasing demands on flexibility of power grids and energy conservation of power plants, various thermal power plants develop different forms of heat supply mode transformation on coal-fired, gas-fired, oil-fired cogeneration units governed by the thermal power plants so as to improve the operation efficiency and the adjustment capacity of the units, such as high back pressure transformation of the cogeneration units, low-cylinder near-zero output transformation, bypass steam extraction heat supply transformation, absorption/steam compression type heat pump installation, electric heating device installation and the like. The device and the equipment have different operation efficiency and adjustment capability, for example, the unit after high back pressure transformation has high operation efficiency but low adjustment capability, and the electric heating device has high adjustment capability but low operation efficiency.
After the transformation, the same thermal power plant can utilize a plurality of heat sources and other heat supply equipment contained in each unit in the cogeneration system of the plant to supply heat. However, in the operation of the conventional cogeneration system, for the coordinated operation among multiple units and multiple heat sources, a manual experience control mode is usually adopted, an automatic coordinated scheduling system for supplying heat to the multiple units and the multiple heat sources is lacked, and the coordinated scheduling with a power system is difficult. Meanwhile, in the deep peak shaving situation, the load of each cogeneration unit changes frequently, the units operate under the non-design working condition for a long time, and the operating energy efficiency is obviously reduced by adjusting the parameters depending on manual experience. In addition, the characteristic parameters of each device in the cogeneration system will also change due to the factors such as the change of working conditions and the long-term operation, and the difference exists between the nominal values of the characteristic parameters and the nominal values of the characteristic parameters. Therefore, the existing empirical control cannot optimize the overall power generation, heat supply and auxiliary service benefits of the cogeneration system.
Disclosure of Invention
The invention provides a scheduling method and a scheduling system of a cogeneration system, which are used for solving the defect that the overall power generation, heat supply and auxiliary service benefits of the cogeneration system cannot achieve better effects because the operation of each device in the cogeneration system is coordinated by manual experience in the prior art, realizing the coordinated scheduling and accurate control of each device in the cogeneration system and optimizing the overall power generation, heat supply and auxiliary service benefits of the cogeneration system.
The invention also provides a scheduling method of the cogeneration system, which comprises the following steps:
acquiring the operation parameters of each device in the cogeneration system at the current moment;
calculating to obtain real-time operation characteristic parameters representing the current operation state of each device based on the operation parameters;
inputting the real-time operation characteristic parameters into an optimized parameter prediction model to obtain an optimized operation parameter prediction value used for scheduling and/or controlling each device in the cogeneration system at the current moment;
the optimized parameter prediction model is constructed on the basis of historical operating characteristic parameters representing the equipment under different operating conditions and historical optimized operating parameters obtained on the basis of the historical operating characteristic parameters, and is updated on the basis of the real-time operating characteristic parameters and the calculated value of the optimized operating parameters at the current moment; the optimized operation parameter calculation value is calculated and obtained based on the real-time operation characteristic parameters and the historical operation characteristic parameters.
According to the scheduling method of the cogeneration system of the present invention, before calculating and obtaining the real-time operation characteristic parameters representing the current operation states of the respective devices based on the operation parameters, the scheduling method further includes:
preprocessing the operation parameters;
the pretreatment comprises the following steps: and the method comprises one or more of dead pixel elimination, linear interpolation, gross error elimination, noise elimination, steady-state working condition screening and standardized processing.
According to the scheduling method of the cogeneration system of the invention, the calculation value of the optimized operation parameter at the current moment is calculated based on the real-time operation characteristic parameter and the historical operation characteristic parameter, and the method comprises the following steps:
calling a physical model preset for the cogeneration system;
and on the basis of meeting the preset constraint condition of the cogeneration system, calculating to obtain the calculated value of the optimized operation parameter at the current moment by combining the real-time operation characteristic parameter and the historical operation characteristic parameter based on the physical model and aiming at achieving the preset optimization target of the cogeneration system.
According to the scheduling method of the cogeneration system of the present invention, the preset constraint condition includes: the overall power output of the cogeneration system meets the power load constraint, the thermal power output of the cogeneration system meets the heat load constraint, and the equipment meets the preset operation constraint;
the preset optimization target comprises: maximizing the overall power generation capacity of the cogeneration system, maximizing the overall heat supply capacity of the cogeneration system, and maximizing the ancillary service benefits of the cogeneration system.
According to the scheduling method of the cogeneration system, the historical operating characteristic parameters are operating characteristic parameters which are obtained by calculation and represent the operating state of each equipment at the current moment according to a preset period and based on the historical operating parameters of each equipment in the cogeneration system.
According to the scheduling method of the cogeneration system of the invention, the calculating and obtaining the real-time operation characteristic parameters representing the current operation states of the devices based on the operation parameters includes:
obtaining physical property associations between the operating parameters obtained at different nodes based on a pre-constructed system mathematical model characterizing heat transfer and flow process coupling of the cogeneration system;
obtaining the overall physical characteristics of the black box model based on the operation parameters obtained from the outwardly extended boundary measuring points; the boundary measuring points are measuring points positioned on the periphery of the nodes; the black box model is nodes with missing measuring points and/or inaccurate measuring points due to the missing and/or damage of the measuring points in the nodes;
obtaining the combined overall physical characteristics of the black box model based on the operation parameters obtained by the boundary measuring points positioned at different peripheries;
and based on the combination overall physical characteristic and the physical characteristic correlation, performing characteristic separation on the interior of the black box model to obtain real-time operation characteristic parameters representing the current operation state of each device.
According to the scheduling method of the cogeneration system of the invention, the calculating and obtaining the real-time operation characteristic parameters representing the current operation states of the devices based on the operation parameters includes:
establishing an equation set based on the inlet and outlet operation parameters of each device simultaneously;
and solving to obtain real-time operation characteristic parameters representing the current operation state of each device based on the equation set.
The scheduling method of the cogeneration system according to the present invention further includes:
and sending the optimized operation parameter predicted value to a distributed control system of the cogeneration system.
The present invention also provides a scheduling system of a cogeneration system, comprising:
the DCS communication module is used for acquiring the operation parameters of each device in the cogeneration system at the current moment;
the parameter identification module is used for calculating and obtaining real-time operation characteristic parameters representing the current operation state of each device based on the operation parameters;
the operation parameter optimization module is used for inputting the real-time operation characteristic parameters into an optimization parameter prediction model to obtain an optimization operation parameter prediction value used for scheduling and/or controlling each device in the cogeneration system at the current moment;
the optimized parameter prediction model is constructed on the basis of historical operating characteristic parameters representing the equipment under different operating conditions and historical optimized operating parameters obtained on the basis of the historical operating characteristic parameters, and is updated on the basis of the real-time operating characteristic parameters and the calculated value of the optimized operating parameters at the current moment; the optimized operation parameter calculation value is calculated and obtained based on the real-time operation characteristic parameters and the historical operation characteristic parameters.
The scheduling system of the cogeneration system according to the present invention further includes:
the user interface module is used for displaying the operation states of the parameter identification module and the DCS communication module, configuring the operation parameters and displaying the optimized parameters;
additionally, the optimized parametric prediction model includes: an optimization result generation layer, an update layer and an optimization result prediction layer;
the optimization result generation layer is used for calculating and obtaining the optimization results of the equipment under different operation conditions based on the preset physical model of the equipment and by combining the real-time operation characteristic parameters and the historical operation characteristic parameters obtained by the parameter identification module;
the updating layer is used for updating the optimized parameter prediction model based on the real-time operation characteristic parameters obtained by the parameter identification module and the optimized result obtained by the optimized result generation layer;
the optimization result prediction layer is used for predicting the optimized operation parameters of each device based on the real-time operation characteristic parameters obtained by the parameter identification module.
The invention provides a scheduling method and a scheduling system of a cogeneration system, which are characterized in that the operation parameters of each device in the cogeneration system are obtained in real time, the real-time operation characteristic parameters representing the current operation state of each device are obtained through calculation, the real-time operation characteristic parameters representing the current operation state of each device are input into a historical optimized operation parameter construction structure obtained based on the historical operation characteristic parameters and historical optimized operation parameters obtained based on the historical operation characteristic parameters, and the optimized operation parameter prediction value used for scheduling and/or controlling each device in the cogeneration system is obtained in an optimized parameter prediction model updated based on the real-time operation characteristic parameters and the optimized operation parameter calculation value at the current moment, so that the automatic coordinated scheduling and accurate control of multiple devices in the cogeneration system are realized, and the overall power generation, heat supply and auxiliary service benefits are optimized.
Drawings
In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a scheduling method of a cogeneration system according to the present invention;
fig. 2 is a schematic structural diagram of a scheduling system of a cogeneration system provided by the invention;
fig. 3 is a schematic structural view of a cogeneration system to which a scheduling system of the cogeneration system provided by the invention is applied;
fig. 4 is a schematic structural diagram of an electronic device provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The cogeneration is an energy-saving system which applies the energy cascade utilization principle and improves the energy utilization efficiency. In the system, high-temperature and high-pressure steam obtained by burning and heating fossil fuels such as coal and natural gas is firstly used for power generation, and the steam after power generation is then used for heat supply. Therefore, the cogeneration system has the advantages of saving energy, reducing atmospheric pollution, saving urban land and the like.
In the existing operation mode of the thermal power plant, for the coordination among a plurality of units with different heat supply modes and heat supply equipment in a combined heat and power generation system, a manual experience control mode is usually adopted, an automatic coordination scheduling system aiming at the situation of multiple units and multiple heat sources is lacked, and the coordinated scheduling with a power system is difficult. Meanwhile, in the peak shaving situation, the load of each cogeneration unit changes frequently and runs for a long time under a non-design working condition, and the parameter adjustment of the cogeneration units depends on manual experience, so that the high-efficiency running of the cogeneration units is difficult to ensure. In addition, the characteristic parameters of each device in the cogeneration system will also change due to the factors such as the change of working conditions and the long-term operation, and the difference exists between the nominal values of the characteristic parameters and the nominal values of the characteristic parameters. Therefore, the existing experience control can not optimize the overall power generation, heat supply and auxiliary service benefits of the power plant.
Based on the above, in the embodiment of the invention, when multiple units and multiple heating devices in a cogeneration system operate simultaneously, the real-time operation characteristic parameters of each unit/link are identified in real time by acquiring and analyzing the operation parameters of key measuring points of the units/links, the optimized parameter prediction model is utilized to calculate the optimized operation parameter prediction value, namely the optimized value of the operation parameter, each device in the cogeneration system is scheduled and/or controlled based on the optimized operation parameter prediction value, each unit and the heating device in the cogeneration system are enabled to be in the optimal operation state as much as possible, and the maximization of the overall power generation, heat supply and auxiliary service benefits of the cogeneration system is realized. The following will be described and explained with reference to specific embodiments.
An embodiment of the present invention provides a scheduling method for a cogeneration system, and the scheduling method for a cogeneration system of the present invention is described below with reference to fig. 1, where the scheduling method is executed on a computer or a combination of software and/or hardware thereof, as shown in fig. 1, and the method includes the following steps:
101. acquiring the operation parameters of each device in the cogeneration system at the current moment;
it can be understood that the heat exchanger unit and the heat supply equipment included in the cogeneration system may relate to a cogeneration unit that is not modified, a cogeneration unit that is modified with high back pressure, a cogeneration unit that is modified with low cylinder near zero output, a cogeneration unit that is modified with bypass extraction heat supply, an absorption/vapor compression heat pump, an electric heating equipment, and the like. For convenience of description, they will be collectively referred to as a device.
Specifically, the operation parameters of each equipment can directly reflect the operation state of each equipment, and the operation states of all the equipment in the cogeneration system can reflect the operation condition of the whole system, so that, in order to maximize the power generation, heat supply and auxiliary service benefits of the whole system, the operation of each equipment is firstly ensured to be under the optimal operation parameters, and therefore, the optimal operation parameters for scheduling and/or controlling each equipment are obtained based on the operation parameters of the equipment at the current moment.
More specifically, for a cogeneration system, the operating parameters it obtains include: the operation parameters can be specifically measured by arranging measuring points at corresponding positions of each device and then taking the measured parameters obtained by each measuring point as the operation parameters.
102. Calculating to obtain real-time operation characteristic parameters representing the current operation state of each device based on the operation parameters;
specifically, the definition of the real-time operation characteristic parameters is as follows: the minimum independent parameters for completely characterizing the current operation state of the equipment can be obtained by measuring the current operation parameters of the equipment and calculating through a mathematical model of the equipment.
103. Inputting the real-time operation characteristic parameters into an optimized parameter prediction model to obtain an optimized operation parameter prediction value used for scheduling and/or controlling each device in the cogeneration system at the current moment;
specifically, the optimized parameter prediction model is constructed based on historical operating characteristic parameters representing the equipment under different operating conditions and historical optimized operating parameters obtained based on the historical operating characteristic parameters, and is updated based on the real-time operating characteristic parameters and the calculated value of the optimized operating parameters at the current moment; the optimized operation parameter calculation value is calculated and obtained based on the real-time operation characteristic parameters and the historical operation characteristic parameters. The calculated value of the optimized operating parameter can be obtained by simultaneous equations of the real-time operating characteristic parameter and the historical operating characteristic parameter and then solving the equations, or can be obtained by calculation of a sequential module method, a simultaneous module method, a layering-dividing and dividing solution algorithm based on a heat flow method and the like.
For example: dividing all constraints (all equations representing a physical model of the cogeneration system) in the cogeneration system into linear constraints, nonlinear explicit constraints and nonlinear implicit constraints according to mathematical properties of the constraints, solving the linear constraints by using a linear equation solver, directly substituting an update strategy to solve the nonlinear explicit constraints, solving the remaining nonlinear implicit constraints by using a calculation process designed by taking the reduction of iteration times as a target, so as to calculate and obtain an optimized operation parameter calculation value on the basis of reducing the nonlinear iteration required by the system solution calculation to the minimum degree, and then updating the optimized parameter prediction model by combining the real-time operation characteristic parameters through algorithms such as a gradient descent method, a linear iteration method, a Newton method, a conjugate gradient method, a Levenberg-Marquardt algorithm, an Adam algorithm and the like.
The optimized operation parameter calculation value is obtained by calculating the real-time operation characteristic parameters and the historical operation characteristic parameters of each device, the accuracy is high, the optimized parameter prediction model is updated based on the optimized operation parameter calculation value and the real-time operation characteristic parameters, the prediction accuracy of the optimized parameter prediction model can be improved, the accuracy of the optimized operation parameter prediction value obtained by adopting the model is guaranteed, the automatic coordinated scheduling and the accurate control of multiple devices in the cogeneration system are realized, and the overall power generation, heat supply and auxiliary service benefits are optimized.
The optimized parameter prediction model may adopt a deterministic optimization algorithm or a heuristic algorithm as an operating parameter optimization algorithm to calculate the optimized operating parameter prediction value, specifically, such as: interior point method, sequence quadratic programming algorithm, genetic algorithm, simulated annealing algorithm and the like.
More specifically, the calculated value of the optimized operation parameter is more accurate than the predicted value of the optimized operation parameter, but the calculation time is longer, the predicted value of the optimized operation parameter obtained by the optimized parameter prediction model is used for scheduling and/or controlling each device in the cogeneration system at the current moment, and the scheduling and/or controlling real-time performance of each device is effectively ensured compared with the utilization of the predicted value of the optimized operation parameter.
Further, the optimized parameter prediction model may be in the form of various proxy models such as an analytical expression obtained by data fitting, a database, a Kriging model, and a neural network model, and is not limited in this regard.
As an embodiment of the present invention, before calculating and obtaining a real-time operation characteristic parameter representing a current operation state of each device based on the operation parameter, the method further includes:
preprocessing the operation parameters;
the pretreatment comprises the following steps: and the method comprises one or more of dead pixel elimination, linear interpolation, gross error elimination, noise elimination, steady-state working condition screening and standardized processing.
Specifically, the accuracy of the subsequently obtained real-time operation characteristic parameters can be further ensured by performing necessary preprocessing on the obtained operation parameters.
More specifically, the preprocessing operation performed on the obtained operation parameters may include dead pixel elimination, linear interpolation, gross error removal, noise removal, steady-state condition screening, normalization processing, and the like.
Further, for example: the adopted dead pixel elimination and gross error elimination method can be a 3 sigma criterion, the adopted noise elimination method can be a Gaussian filtering method based on a sliding window, and the adopted steady-state working condition screening method can be a Dickey-Fuller detection method and an amplified Dickey-Fuller method.
As an embodiment of the present invention, the calculation value of the optimized operating parameter at the current time is calculated based on the real-time operating characteristic parameter and the historical operating characteristic parameter, and includes:
calling a physical model preset for the cogeneration system;
and on the basis of meeting the preset constraint condition of the cogeneration system, calculating to obtain the calculated value of the optimized operation parameter at the current moment by combining the real-time operation characteristic parameter and the historical operation characteristic parameter based on the physical model and aiming at achieving the preset optimization target of the cogeneration system.
Specifically, calling a preset physical model of the cogeneration system is a basis for correctly calculating and obtaining the calculated value of the optimized operating parameter of each device. The physical model can be an overall model obtained by combining conventional physical models of all devices, an overall heat flow model based on a heat flow method and the like.
Furthermore, the construction method of the physical model is preferably a heat flow method based on a fire volume theory, namely, a heat flow model and a fluid flow model are established through the overall analysis of the system, the physical properties of the working medium are used as a ligament to connect two sub-models, and finally, an overall mathematical model of the system is obtained, so that the intermediate variables contained in the physical model are minimum.
More specifically, on the basis of meeting the preset constraint condition of the cogeneration system, with the aim of achieving the preset optimization target of the cogeneration system, based on the physical model, a mathematical model is obtained from the physical model, and then the real-time operation characteristic parameter and the historical operation characteristic parameter are combined to calculate the optimized operation parameter calculation value at the current moment, so that the calculated optimized operation parameter calculation value at the current moment meets the constraint condition and the optimization target of the cogeneration system at the same time, and therefore, the optimized operation parameter calculation value is the operation parameter meeting the requirements of the cogeneration system, and the optimized parameter prediction model is updated based on the operation parameter, so that the obtained optimized parameter prediction model meets the requirements of the corresponding cogeneration system.
As an embodiment of the present invention, the preset constraint condition includes: the overall power output of the cogeneration system meets the power load constraint, the thermal power output of the cogeneration system meets the heat load constraint, and the equipment meets the preset operation constraint;
the preset optimization target comprises: maximizing the overall power generation capacity of the cogeneration system, maximizing the overall heat supply capacity of the cogeneration system, and maximizing the ancillary service benefits of the cogeneration system.
Specifically, the electric output of the cogeneration system should satisfy the electric load constraint, the heat output should satisfy the heat load constraint, each equipment should satisfy the preset operation constraint, and meanwhile, in order to ensure that the optimal operation parameter prediction value of each equipment for scheduling and/or controlling the cogeneration system can achieve the optimal overall power generation, heat supply and auxiliary service benefits of the cogeneration system, the optimal operation parameter calculation value should be calculated with the optimization objectives of maximizing the overall power generation amount of the cogeneration system, maximizing the overall heat supply amount of the cogeneration system, and maximizing the auxiliary service benefits of the cogeneration system.
More specifically, the scheduling method of the cogeneration system provided by the embodiment of the invention can obtain the optimized operation parameters of each unit and equipment by taking the maximized overall power generation, heat supply and auxiliary service benefits of the power plant as the optimization target through the operation parameter optimization algorithm based on the real-time operation characteristic parameters representing the current operation state of each equipment when the overall power output of the cogeneration system meets the power load constraint and the heat output meets the heat load constraint and other constraints, so that the coordinated scheduling of multiple units and multiple heat sources in the cogeneration system and the accurate control of the units and the equipment are realized, and the overall power generation, heat supply and auxiliary service benefits of the power plant are optimized.
As an embodiment of the present invention, the historical operating characteristic parameter is an operating characteristic parameter that is obtained by calculation based on historical operating parameters of each device in the cogeneration system according to a predetermined period and represents an operating state of each device at the current moment.
Specifically, in consideration of the component aging problem of each equipment in long-term operation, historical operation parameters of each equipment in the cogeneration system are periodically called according to a predetermined period, and the operation characteristic parameters representing the operation state of each equipment at the current moment are obtained through calculation, that is, the operation characteristic parameters representing the operation state of each equipment at the current moment are periodically re-calibrated by using the historical operation parameters, so that the calculation efficiency of the calculation value of the optimized operation parameters can be effectively accelerated.
As an embodiment of the present invention, the calculating, based on the operation parameters, to obtain real-time operation characteristic parameters representing current operation states of the devices includes:
obtaining physical property associations between the operating parameters obtained at different nodes based on a pre-constructed system mathematical model characterizing heat transfer and flow process coupling of the cogeneration system;
obtaining the overall physical characteristics of the black box model based on the operation parameters obtained from the outwardly extended boundary measuring points; the boundary measuring points are measuring points positioned on the periphery of the nodes; the black box model is nodes with missing measuring points and/or inaccurate measuring points due to the missing and/or damage of the measuring points in the nodes;
obtaining the combined overall physical characteristics of the black box model based on the operation parameters obtained by the boundary measuring points positioned at different peripheries;
and based on the combination overall physical characteristic and the physical characteristic correlation, performing characteristic separation on the interior of the black box model to obtain real-time operation characteristic parameters representing the current operation state of each device.
It can be understood that the operation parameters of each device need to be obtained by acquiring measurement data of measurement points, such as sensors, arranged on each device, and in order to ensure the accuracy and richness of the measurement data, a plurality of nodes are generally arranged on one device, and each node includes a plurality of measurement points, it should be noted that, damage or deficiency inevitably occurs in the measurement points during the operation process, which may cause errors or lack of the obtained operation parameters, and at this time, it is necessary to ensure that accurate operation characteristic parameters are obtained based on the obtained operation parameters.
Specifically, in the embodiment of the invention, an integral identification method based on a heat flow model and a fluid dynamic-resistance balance equation is adopted.
More specifically, overall identification is based on overall analysis of the cogeneration system, a system mathematical model of heat transfer-flow process coupling is established, and physical characteristic correlation among different nodes is obtained; when a measuring point in the system is lost or damaged, a node lacking the measuring point or inaccurate measuring point is temporarily regarded as a 'black box model', the overall physical characteristics of the 'black box model' are obtained by adopting outwards extended boundary measuring point data, the overall physical characteristics of different boundary measuring point combinations are obtained by utilizing a plurality of groups of measuring point data, the interior of the 'black box model' is subjected to characteristic separation by utilizing the correlation among state parameters of each node described by a heat transfer-flow coupling model, and then the physical characteristics of each node under different working conditions, namely the real-time operation characteristic parameters representing the current operation state of each device are obtained. Therefore, the overall identification method realizes accurate identification of the characteristic parameters of the system by using the least possible measuring point data, thereby reducing the measuring point arrangement requirement of the cogeneration system, namely reducing the implementation difficulty and cost.
As an embodiment of the present invention, the calculating, based on the operation parameters, to obtain real-time operation characteristic parameters representing current operation states of the devices includes:
establishing an equation set based on the inlet and outlet operation parameters of each device simultaneously;
and solving to obtain real-time operation characteristic parameters representing the current operation state of each device based on the equation set.
Specifically, the calculation of the real-time operation characteristic parameters can also be realized by adopting analysis and identification based on multi-working-condition joint analysis, namely, an equation set is constructed by simultaneously establishing the inlet and outlet parameters of each device under the multi-working conditions, and the equation set is solved to obtain the operation characteristic parameters of each device.
More specifically, other methods may also be adopted to calculate and obtain the real-time operation characteristic parameter, such as: the overall identification method based on the artificial neural network comprises the following steps: the neural network is trained by the operation parameters obtained from the measuring points to obtain the thermal resistance of the heat exchange equipment, and then the parameters such as the heat exchange area, the heat exchange coefficient and the like are obtained from the thermal resistance, which are not elaborated herein.
As an embodiment of the present invention, the method further includes:
and sending the optimized operation parameter predicted value to a distributed control system of the cogeneration system.
Specifically, the optimized operation parameter prediction value is sent to a distributed control system DCS of the cogeneration system, wherein one cogeneration system may include a plurality of DCS units, each set of DCS is connected to and controls a plurality of sets of heat exchange units, heat supply equipment, and the like, and each set of DCS receives the optimized operation parameter prediction value and then uses the optimized operation parameter prediction value to realize scheduling and/or control of the heat exchange units, the heat supply equipment, and the like controlled by the DCS.
The scheduling method of the cogeneration system provided by the embodiment of the invention can calculate the real-time operation characteristic parameters of units, heating equipment and other equipment in the cogeneration system in real time, obtain the corresponding optimized operation parameter prediction values through the optimized parameter prediction model, realize the scheduling of various heating modes and the performance optimization of each heating equipment, optimize the overall power generation, heating and auxiliary service benefits of the cogeneration system, and ensure the real-time performance of optimized calculation; meanwhile, on the premise that the overall power output of the thermal power plant meets the power load constraint, the overall heat output of the thermal power plant meets the heat load constraint and other constraints, the optimized operation parameter calculation value of the heating equipment is calculated by taking the maximized overall power generation, heat supply and auxiliary service benefits of the thermal power plant as the optimization target based on the operation parameter optimization algorithm, and the optimized parameter prediction model is updated on line, so that the accuracy of the prediction result is ensured.
The following describes a scheduling system of a cogeneration system provided by the present invention with reference to fig. 2, and the scheduling system of the cogeneration system described below and the scheduling method of the cogeneration system described above may be referred to correspondingly.
As shown in fig. 2, the system includes a DCS communication module 210, a parameter identification module 220, and an operation parameter optimization module 230; wherein, the first and the second end of the pipe are connected with each other,
the DCS communication module 210 is configured to obtain operation parameters of each device in the cogeneration system at the current moment;
the parameter identification module 220 is configured to calculate and obtain a real-time operation characteristic parameter representing a current operation state of each device based on the operation parameter;
the operation parameter optimization module 230 is configured to input the real-time operation characteristic parameters into an optimized parameter prediction model, and obtain an optimized operation parameter prediction value used for scheduling and/or controlling each device in the cogeneration system at the current moment;
the optimized parameter prediction model is constructed on the basis of historical operating characteristic parameters representing the equipment under different operating conditions and historical optimized operating parameters obtained on the basis of the historical operating characteristic parameters, and is updated on the basis of the real-time operating characteristic parameters and the calculated value of the optimized operating parameters at the current moment; the optimized operation parameter calculation value is calculated and obtained based on the real-time operation characteristic parameters and the historical operation characteristic parameters.
According to the scheduling system of the cogeneration system provided by the embodiment of the invention, the operation parameters of each device in the cogeneration system are obtained in real time, the real-time operation characteristic parameters representing the current operation state of each device are obtained through calculation, the real-time operation characteristic parameters representing the current operation state of each device are input into the historical optimized operation parameter construction obtained based on the historical operation characteristic parameters representing the historical operation states of each device and the historical optimized operation parameter construction obtained based on the historical operation characteristic parameters, and the optimized operation parameter prediction value used for scheduling and/or controlling each device in the cogeneration system is obtained in the optimized parameter prediction model updated based on the real-time operation characteristic parameters and the optimized operation parameter calculation value at the current moment, so that the automatic coordinated scheduling and the accurate control of multiple devices in the cogeneration system are realized, and the overall power generation, heat supply and auxiliary service benefits are optimized.
As an embodiment of the present invention, the scheduling system of a cogeneration system further includes: a user interface module;
the user interface module is used for displaying the operation states of the parameter identification module and the DCS communication module, configuring the operation parameters and displaying the optimized parameters;
additionally, the optimized parametric prediction model includes: an optimization result generation layer, an update layer and an optimization result prediction layer;
the optimization result generation layer is used for calculating and obtaining the optimization results of the equipment under different operation conditions based on the preset physical model of the equipment and by combining the real-time operation characteristic parameters and the historical operation characteristic parameters obtained by the parameter identification module;
the updating layer is used for updating the optimized parameter prediction model based on the real-time operation characteristic parameters obtained by the parameter identification module and the optimized result obtained by the optimized result generation layer;
the optimization result prediction layer is used for predicting the optimized operation parameters of each device based on the real-time operation characteristic parameters obtained by the parameter identification module.
Specifically, the user interface module is respectively connected with the DCS communication module and the parameter identification module; the user interface module is used for displaying the operation states of the parameter identification module and the DCS communication module and configuring operation parameters; the user interface module also displays the optimization parameters for selection by an operator.
Preferably, the scheduling system of the cogeneration system further comprises a data processing module;
the data processing module is used for preprocessing the operation parameters;
the pretreatment comprises the following steps: and the method comprises one or more of dead pixel elimination, linear interpolation, gross error elimination, noise elimination, steady-state working condition screening and standardized processing.
Preferably, the calculation value of the optimized operating parameter at the current time for updating the optimized parameter prediction model is calculated based on the real-time operating characteristic parameter and the historical operating characteristic parameter, and includes:
calling a physical model preset for the cogeneration system;
and on the basis of meeting the preset constraint condition of the cogeneration system, calculating to obtain the calculated value of the optimized operation parameter at the current moment by combining the real-time operation characteristic parameter and the historical operation characteristic parameter based on the physical model and aiming at achieving the preset optimization target of the cogeneration system.
Preferably, the preset constraint condition includes: the overall electric output of the cogeneration system meets an electric load constraint, the thermal output of the cogeneration system meets a thermal load constraint, and each device meets a preset operation constraint;
the preset optimization target comprises: maximizing the overall power generation capacity of the cogeneration system, maximizing the overall heat supply capacity of the cogeneration system, and maximizing the ancillary service benefits of the cogeneration system.
Preferably, the parameter identification module is further configured to calculate, according to a predetermined period, an operation characteristic parameter representing an operation state of each device at the current time based on a historical operation parameter of each device in the cogeneration system.
Preferably, the parameter identification module is more specifically configured to obtain physical property correlations between the operating parameters obtained at different nodes based on a pre-constructed system mathematical model characterizing heat transfer and flow process coupling of the cogeneration system; obtaining the overall physical characteristics of the black box model based on the operation parameters obtained from the extended boundary measuring points; the boundary measuring points are measuring points positioned on the periphery of the nodes; the black box model is nodes with missing measuring points and/or inaccurate measuring points due to the missing and/or damage of the measuring points in the nodes; obtaining the combined overall physical characteristics of the black box model based on the operation parameters obtained by the boundary measuring points positioned at different peripheries; and separating the characteristics of the interior of the black box model based on the combination overall physical characteristics and the physical characteristic correlation to obtain real-time operation characteristic parameters representing the current operation state of each device.
Preferably, the parameter identification module is further specifically configured to construct an equation set based on the inlet/outlet operation parameters of each piece of equipment in a simultaneous manner; and solving and obtaining real-time operation characteristic parameters representing the current operation state of each device based on the equation set.
Preferably, the DCS communication module is further configured to send the predicted optimized operating parameter value to a distributed control system of the cogeneration system.
In summary, a schematic structural diagram of the scheduling system of the cogeneration system according to the embodiment of the present invention applied to the cogeneration system is shown in fig. 3, where the scheduling system of the cogeneration system includes: the system comprises a DCS communication module 1, a data processing module 2, a parameter identification module 3, an optimized parameter prediction model 4 and a user interface module 5; the optimization parameter prediction model 4 further comprises an optimization result generation layer 6, an update layer 7 and an optimization result prediction layer 8;
the cogeneration system comprises a multi-component distributed control system DCS9, and each group of DCS9 is connected with and controls a plurality of groups of heat exchange unit 10 and heat supply equipment 11; each group of DSC9 is respectively connected with a DCS communication module 1 of a scheduling system of the cogeneration system; the DCS communication module 1 is connected with the data processing module 2, and the DCS communication module 1 transmits measurement parameters (operation parameters) of relevant measuring points of a unit 10 and a heat supply device 11 in the managed cogeneration system to the data processing module 2; the data processing module 2 is connected with the parameter identification module 3, and the data processing module 2 transmits the preprocessed operation parameters to the parameter identification module 3; the parameter identification module 3 is connected with the optimization result prediction layer 8, and the parameter identification module 3 transmits operation characteristic parameters reflecting the operation states of the unit 10 and the heating equipment 11 in the cogeneration system governed by the scheduling system to the optimization result prediction layer 8; the optimization result prediction layer 8 is connected with the DCS communication module 1, and the optimization result prediction layer 8 transmits the optimized operation parameter prediction values of the unit 10 and the heating equipment 11 in the cogeneration system governed by the scheduling system to the DCS communication module 1; the DCS communication module 1 is connected with the existing DCS9 of the power plant to realize communication.
Meanwhile, the parameter identification module 3 is further connected to the optimization result generation layer 6, the parameter identification module 3 transmits operation characteristic parameters reflecting operation states of the unit 10 and the heating equipment 11 in the cogeneration system governed by the scheduling system to the optimization result generation layer 6, in addition, a historical operation database 12 is further built in the parameter identification module 3, historical operation characteristic parameters of each equipment are stored in the historical operation database 12, the historical operation characteristic parameters are also transmitted to the optimization result generation layer 6 by the historical operation database 12, the optimization result generation layer 6 calculates an optimized operation parameter calculation value at the current time based on the real-time operation characteristic parameters and the historical operation characteristic parameters, the optimization result generation layer 6 is connected to the update layer 7, and the optimization result generation layer 6 transmits the optimized operation parameter calculation value and the real-time operation characteristic parameters at the current time to the update layer 7, the updating layer 7 updates the optimized parameter prediction model 4 by using the calculated value of the optimized operation parameters and the real-time operation characteristic parameters at the current moment, and the updating layer 7 is connected with the optimized result prediction layer 8, so that the optimized result prediction layer 8 can obtain the predicted values of the optimized operation parameters of the unit 10 and the heat supply equipment 11 in the cogeneration system governed by the dispatching system at the next moment based on the updated optimized parameter prediction model 4.
Fig. 4 illustrates a physical structure diagram of an electronic device, which may include, as shown in fig. 4: a processor (processor)410, a communication Interface (Communications Interface)420, a memory (memory)430 and a communication bus 440, wherein the processor 410, the communication Interface 420 and the memory 430 are in communication with each other via the communication bus 440. The processor 410 may invoke logic instructions in the memory 430 to perform a scheduling method of a cogeneration system, the method comprising: acquiring the operation parameters of each device in the cogeneration system at the current moment; calculating to obtain real-time operation characteristic parameters representing the current operation state of each device based on the operation parameters; inputting the real-time operation characteristic parameters into an optimized parameter prediction model to obtain an optimized operation parameter prediction value used for scheduling and/or controlling each device in the cogeneration system at the current moment; the optimized parameter prediction model is constructed on the basis of historical operating characteristic parameters representing the equipment under different operating conditions and historical optimized operating parameters obtained on the basis of the historical operating characteristic parameters, and is updated on the basis of the real-time operating characteristic parameters and the calculated value of the optimized operating parameters at the current moment; the optimized operation parameter calculation value is calculated and obtained based on the real-time operation characteristic parameters and the historical operation characteristic parameters.
In addition, the logic instructions in the memory 430 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product, the computer program product including a computer program, the computer program being stored on a non-transitory computer readable storage medium, and when the computer program is executed by a processor, the computer being capable of executing the scheduling method of the cogeneration system provided by the above methods, the method including: acquiring the operation parameters of each device in the cogeneration system at the current moment; calculating to obtain real-time operation characteristic parameters representing the current operation state of each device based on the operation parameters; inputting the real-time operation characteristic parameters into an optimized parameter prediction model to obtain an optimized operation parameter prediction value used for scheduling and/or controlling each device in the cogeneration system at the current moment; the optimized parameter prediction model is constructed on the basis of historical operating characteristic parameters representing the equipment under different operating conditions and historical optimized operating parameters obtained on the basis of the historical operating characteristic parameters, and is updated on the basis of the real-time operating characteristic parameters and the calculated value of the optimized operating parameters at the current moment; the optimized operation parameter calculation value is calculated and obtained based on the real-time operation characteristic parameters and the historical operation characteristic parameters.
In yet another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored, the computer program, when being executed by a processor, implementing the scheduling method of the cogeneration system provided by the above methods, the method including: acquiring the operation parameters of each device in the cogeneration system at the current moment; calculating to obtain real-time operation characteristic parameters representing the current operation state of each device based on the operation parameters; inputting the real-time operation characteristic parameters into an optimized parameter prediction model to obtain an optimized operation parameter prediction value used for scheduling and/or controlling each device in the cogeneration system at the current moment; the optimized parameter prediction model is constructed on the basis of historical operating characteristic parameters representing the equipment under different operating conditions and historical optimized operating parameters obtained on the basis of the historical operating characteristic parameters, and is updated on the basis of the real-time operating characteristic parameters and the calculated value of the optimized operating parameters at the current moment; the optimized operation parameter calculation value is calculated and obtained based on the real-time operation characteristic parameters and the historical operation characteristic parameters.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A scheduling method of a cogeneration system, comprising:
acquiring the operation parameters of each device in the cogeneration system at the current moment;
calculating to obtain real-time operation characteristic parameters representing the current operation state of each device based on the operation parameters;
inputting the real-time operation characteristic parameters into an optimized parameter prediction model to obtain an optimized operation parameter prediction value used for scheduling and/or controlling each device in the cogeneration system at the current moment;
the optimized parameter prediction model is constructed on the basis of historical operating characteristic parameters representing the equipment under different operating conditions and historical optimized operating parameters obtained on the basis of the historical operating characteristic parameters, and is updated on the basis of the real-time operating characteristic parameters and the calculated value of the optimized operating parameters at the current moment; the optimized operation parameter calculation value is calculated and obtained based on the real-time operation characteristic parameters and the historical operation characteristic parameters.
2. The scheduling method of a cogeneration system according to claim 1, wherein before the calculating, based on the operation parameters, a real-time operation characteristic parameter representing a current operation state of each of the devices, the scheduling method further comprises:
preprocessing the operation parameters;
the pretreatment comprises the following steps: and the method comprises one or more of dead pixel elimination, linear interpolation, gross error elimination, noise elimination, steady-state working condition screening and standardized processing.
3. The scheduling method of a cogeneration system of claim 1, wherein said optimal operating parameter calculation value at the current time is calculated based on said real-time operating characteristic parameters and historical operating characteristic parameters, comprising:
calling a physical model preset for the cogeneration system;
and on the basis of meeting the preset constraint condition of the cogeneration system, calculating to obtain the calculated value of the optimized operation parameter at the current moment by combining the real-time operation characteristic parameter and the historical operation characteristic parameter based on the physical model and aiming at achieving the preset optimization target of the cogeneration system.
4. The scheduling method of a cogeneration system according to claim 3, wherein said preset constraints comprise: the overall power output of the cogeneration system meets the power load constraint, the thermal power output of the cogeneration system meets the heat load constraint, and the equipment meets the preset operation constraint;
the preset optimization target comprises: maximizing the overall power generation capacity of the cogeneration system, maximizing the overall heat supply capacity of the cogeneration system, and maximizing the ancillary service benefits of the cogeneration system.
5. The scheduling method of a cogeneration system according to claim 3, wherein the historical operating characteristic parameter is an operating characteristic parameter that is calculated to represent an operating state of each plant at the current time based on historical operating parameters of each plant in the cogeneration system according to a predetermined period.
6. The scheduling method of a cogeneration system according to claim 5, wherein said calculating, based on said operating parameters, real-time operating characteristic parameters characterizing the current operating status of said devices comprises:
obtaining physical property associations between the operating parameters obtained at different nodes based on a pre-constructed system mathematical model characterizing heat transfer and flow process coupling of the cogeneration system;
obtaining the overall physical characteristics of the black box model based on the operation parameters obtained from the extended boundary measuring points; the boundary measuring points are measuring points positioned on the periphery of the nodes; the black box model is nodes with missing measuring points and/or inaccurate measuring points due to the missing and/or damage of the measuring points in the nodes;
obtaining the combined overall physical characteristics of the black box model based on the operation parameters obtained by the boundary measuring points positioned at different peripheries;
and based on the combination overall physical characteristic and the physical characteristic correlation, performing characteristic separation on the interior of the black box model to obtain real-time operation characteristic parameters representing the current operation state of each device.
7. The scheduling method of a cogeneration system according to claim 5, wherein said calculating, based on said operating parameters, real-time operating characteristic parameters characterizing a current operating state of said each plant comprises:
establishing an equation set based on the inlet and outlet operation parameters of each device simultaneously;
and solving to obtain real-time operation characteristic parameters representing the current operation state of each device based on the equation set.
8. The scheduling method of a cogeneration system according to claim 1, further comprising:
and sending the optimized operation parameter predicted value to a distributed control system of the cogeneration system.
9. A scheduling system of a cogeneration system, comprising:
the DCS communication module is used for acquiring the operation parameters of each device in the cogeneration system at the current moment;
the parameter identification module is used for calculating and obtaining real-time operation characteristic parameters representing the current operation state of each device based on the operation parameters;
the operation parameter optimization module is used for inputting the real-time operation characteristic parameters into an optimization parameter prediction model to obtain an optimization operation parameter prediction value used for scheduling and/or controlling each device in the cogeneration system at the current moment;
the optimized parameter prediction model is constructed on the basis of historical operating characteristic parameters representing the equipment under different operating conditions and historical optimized operating parameters obtained on the basis of the historical operating characteristic parameters, and is updated on the basis of the real-time operating characteristic parameters and the calculated value of the optimized operating parameters at the current moment; the optimized operation parameter calculation value is calculated and obtained based on the real-time operation characteristic parameters and the historical operation characteristic parameters.
10. The scheduling system of a cogeneration system of claim 9, further comprising:
the user interface module is used for displaying the operation states of the parameter identification module and the DCS communication module, configuring the operation parameters and displaying the optimized parameters;
additionally, the optimized parametric prediction model includes: an optimization result generation layer, an update layer and an optimization result prediction layer;
the optimization result generation layer is used for calculating and obtaining the optimization results of the equipment under different operation conditions based on the preset physical model of the equipment and by combining the real-time operation characteristic parameters and the historical operation characteristic parameters obtained by the parameter identification module;
the updating layer is used for updating the optimized parameter prediction model based on the real-time operation characteristic parameters obtained by the parameter identification module and the optimized result obtained by the optimized result generation layer;
the optimization result prediction layer is used for predicting the optimized operation parameters of each device based on the real-time operation characteristic parameters obtained by the parameter identification module.
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