CN114493912A - Comprehensive energy optimal configuration method and device and storage medium - Google Patents
Comprehensive energy optimal configuration method and device and storage medium Download PDFInfo
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Abstract
The embodiment of the invention relates to the technical field of comprehensive energy optimization, and discloses a comprehensive energy optimization configuration method, which comprises the following steps: respectively acquiring performance curves of various devices in the integrated energy system, wherein the performance curves of the various devices at least comprise: a non-linear performance curve of a thermodynamic device; determining an objective function and solving parameters of the objective function; and iteratively solving the optimal solving parameters of the objective function for multiple times according to the performance curves of the various devices and preset constraint conditions. The comprehensive energy optimization configuration method, the comprehensive energy optimization configuration device and the storage medium have the advantage that the solving structure of the energy optimization problem in the comprehensive energy system is more accurate.
Description
Technical Field
The embodiment of the invention relates to the technical field of comprehensive energy optimization, in particular to a comprehensive energy optimization configuration method, a comprehensive energy optimization configuration device and a storage medium.
Background
The existing energy structure in China highly depends on fossil energy such as coal and the like, and the quit cost is huge.
The comprehensive energy system with the complementation of multiple energy sources can coordinate and cooperate different energy supply and energy utilization main bodies integrally, on one hand, the cascade utilization of energy sources is realized, on the other hand, the comprehensive management and the coordination complementation of multiple energy sources are realized by utilizing the coupling mechanism of each energy system on the time and space, and the comprehensive energy system has great effect on reducing the carbon emission and realizing the double-carbon target. However, the prior art has an inaccurate solution structure for the energy optimization problem in the integrated energy system.
Disclosure of Invention
The embodiment of the invention aims to provide a comprehensive energy optimization configuration method, a comprehensive energy optimization configuration device and a storage medium, which are more accurate in solving structure of an energy optimization problem in a comprehensive energy system.
In order to solve the above technical problem, an embodiment of the present invention provides a method for optimizing and configuring integrated energy, including: respectively obtaining performance curves of various devices in the integrated energy system, wherein the performance curves of the various devices at least comprise: a non-linear performance curve of a thermodynamic device; determining an objective function and solving parameters of the objective function; and iteratively solving the optimal solving parameters of the objective function for multiple times according to the performance curves of the various devices and preset constraint conditions.
In addition, the respectively obtaining performance curves of various devices in the integrated energy system includes: respectively acquiring parameters of the thermodynamic equipment and parameters of the electrical power equipment, and verifying the validity of the parameters; fitting a nonlinear performance curve of the thermodynamic device according to the verified parameters of the thermodynamic device; and fitting a linear performance curve or a nonlinear performance curve of the electromechanical device according to the verified parameters of the electromechanical device.
In addition, the fitting of the nonlinear performance curve of the thermodynamic device according to the verified parameters of the thermodynamic device includes: normalizing the parameters of the verified thermodynamic equipment; and fitting a nonlinear performance curve of the thermodynamic equipment according to the parameters after normalization processing.
In addition, the process of solving the optimal solution parameters of the objective function in each iteration comprises the following steps: solving a first optimization result according to the performance curves of the various devices and preset constraint conditions; performing secondary optimization on the primary optimization result to obtain an operation strategy distribution result of the equipment; and calculating the optimal solving parameter of the objective function according to the operation strategy distribution result.
In addition, the operation policy allocation of the device includes: an energy storage device operation strategy, a heat pump operation strategy and a water chilling unit operation strategy; in the step of performing secondary optimization on the primary optimization result to obtain an operation strategy distribution result of the equipment, the optimization target of the operation strategy of the energy storage equipment is to enable the battery to be deeply charged and deeply discharged, and the linear inequality constraint is an upper limit constraint and a lower limit constraint of energy storage; the optimization target of the heat pump operation strategy and the water chilling unit operation strategy is that the power consumption cost is the lowest, and the linear equality constraint is the cold and hot power balance constraint.
In addition, after performing secondary optimization on the primary optimization result to obtain an operation strategy allocation result of the device, the method further includes: calculating whether the power grid interaction power is balanced and whether the cold and heat balance error is within a preset error range in the operation process of the comprehensive energy system according to the operation strategy distribution result; and if the power grid interaction power is unbalanced or the cold and hot balance error is not in the preset error range, continuously and iteratively solving the optimal solving parameter of the objective function.
In addition, the iterative solution of the optimal solution parameter of the objective function for a plurality of times according to the performance curves of the various devices and the preset constraint conditions comprises the following steps: setting a plurality of groups of initial values; and carrying out multiple times of iteration on the multiple groups of initial values, the performance curves of various devices and preset constraint conditions to solve the optimal solving parameters of the objective function.
In addition, the solution parameters of the objective function include: the cost of the integrated energy system is the lowest or the carbon emission of the integrated energy system is the lowest.
The embodiment of the invention also provides a comprehensive energy optimization configuration device, which comprises: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of integrated energy optimization configuration described above.
The embodiment of the invention also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the comprehensive energy optimization configuration method.
The embodiment of the invention provides a comprehensive energy optimal configuration method, which is used for respectively obtaining performance curves of various devices in a comprehensive energy system, wherein the performance curves of the various devices at least comprise: determining a target function and solving parameters of the target function by using a nonlinear performance curve of thermodynamic equipment; and iteratively solving the optimal solving parameters of the objective function for multiple times according to the performance curves of various devices and preset constraint conditions. In the embodiment, the nonlinear performance curve is obtained for the thermodynamic equipment in the integrated energy system, the linear performance curve or the nonlinear performance curve is obtained for the electromechanical equipment, and the corresponding linear or nonlinear performance curve is correspondingly obtained according to the performance curve types of different equipment, so that the optimal solution parameters of the objective function obtained by multiple iterative solutions according to the performance curves of various equipment and preset constraint conditions are more accurate.
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One or more embodiments are illustrated by way of example in the accompanying drawings, which correspond to the figures in which like reference numerals refer to similar elements and which are not to scale unless otherwise specified.
FIG. 1 is a schematic flow diagram of an integrated energy optimization configuration method according to an embodiment of the invention;
FIG. 2 is a graphical illustration of a CCHP natural gas consumption linear fit according to an embodiment of the present invention;
FIG. 3 is a graph illustrating heat pump COP curve fitting results according to an embodiment of the present invention;
FIG. 4 is a diagram illustrating the distribution result of the operation strategy of the energy storage battery according to the embodiment of the invention;
FIG. 5 is a schematic illustration of the heat pump operating strategy distribution results according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of the distribution results of the operation strategy of the chiller according to the embodiment of the invention;
FIG. 7 is a schematic diagram of an integrated energy system interacting with power grid in accordance with an embodiment of the present invention;
FIG. 8 is a graphical illustration of thermal power balance error results according to an embodiment of the present invention;
FIG. 9 is a graphical illustration of cold power balance error results according to an embodiment of the invention;
FIG. 10 is a schematic diagram of a distribution of computed results for an optimal configuration of an integrated energy cost problem according to an embodiment of the present invention;
fig. 11 is a schematic structural diagram of an integrated energy optimization configuration apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, it will be appreciated by those of ordinary skill in the art that numerous technical details are set forth in order to provide a better understanding of the present application in various embodiments of the present invention. However, the technical solution claimed in the present application can be implemented without these technical details and various changes and modifications based on the following embodiments.
The first embodiment of the invention relates to an optimal configuration method of comprehensive energy, and the core of the embodiment lies in respectively obtaining performance curves of various devices in a comprehensive energy system, wherein the performance curves of the various devices at least comprise: determining a target function and solving parameters of the target function according to a nonlinear performance curve of thermodynamic equipment and a linear performance curve or a nonlinear performance curve of electrical equipment; and iteratively solving the optimal solving parameters of the objective function for multiple times according to the performance curves of various devices and preset constraint conditions. In the embodiment, the nonlinear performance curve is obtained for the thermodynamic equipment in the integrated energy system, the linear performance curve or the nonlinear performance curve is obtained for the electric power equipment, and the corresponding linear or nonlinear curve is correspondingly obtained according to the performance curve types of different equipment, so that the optimal solution parameters of the objective function obtained by multiple iterative solutions according to the performance curves of various equipment and preset constraint conditions are more accurate.
The following describes implementation details of the integrated energy optimization configuration method of the present embodiment in detail, and the following is only provided for easy understanding and is not necessary for implementing the present embodiment.
The flow diagram of the comprehensive energy optimization configuration method in this embodiment is shown in fig. 1:
step 101: and respectively acquiring performance curves of various devices in the comprehensive energy system.
Specifically, the integrated energy system includes various devices, such as: the Combined Cooling, Heating and Power (CCHP), fans, photovoltaic, heat pump, water chilling unit, energy storage and other devices, and the space-time coupling mechanism of a plurality of devices in the comprehensive energy system can realize the comprehensive management and coordination and complementation of various energy sources. These various devices can be broadly divided into two types of devices, thermodynamic devices and electrical devices, thermodynamic devices such as: heat pump, water chilling unit; the electric power equipment includes, for example: the cold, heat and electricity supply unit, the fan, the photovoltaic and the energy storage. For thermodynamic devices, the actual performance curve is a non-linear curve due to the presence of heat and cold exchanges, while for electrical devices, the actual performance curve is a linear or non-linear curve due to the presence of electrical energy interactions. In order to reduce the problem solving difficulty in the conventional comprehensive energy optimization configuration method, the performance curves of all equipment are linearized, and the difference between the performance curve of the thermodynamic equipment obtained in the way and the actual performance curve is large, so that the accuracy of the finally obtained optimal solving parameter is not high. In the embodiment, the nonlinear performance curve is obtained for the thermodynamic equipment in the comprehensive energy system, the linear performance curve or the nonlinear performance curve is obtained for the electromechanical equipment, and the corresponding linear or nonlinear curve is obtained correspondingly according to the performance curve types of different equipment, so that the accuracy of the finally obtained optimal solution parameter is high.
Optionally, separately obtaining performance curves of various devices in the integrated energy system includes: respectively acquiring parameters of thermodynamic equipment and parameters of electrical equipment, and verifying the validity of the parameters; fitting a nonlinear performance curve of the thermodynamic equipment according to the verified parameters of the thermodynamic equipment; and fitting a linear performance curve or a nonlinear performance curve of the electric power equipment according to the parameters of the electric power equipment passing the verification.
Specifically, in this embodiment, the integrated energy system device or the device model set in the integrated energy system is directly docked, so as to obtain parameters of the thermodynamic device and parameters of the electrical power device, where the parameters are introduced in a JavaScriptObject Notation (json) format, and a character string in the json format needs to be analyzed to obtain corresponding parameters, and then the validity of the obtained parameters is verified.
These parameters include at least operating parameters and equipment parameters including equipment ID, equipment power rating, etc. When verifying the validity of the parameter, determining the condition that the parameter is valid at least comprises: the ID numbers of the devices of the same type cannot be repeated, the rated power of the devices should be in a reasonable interval, and the different parameters of the devices cannot conflict. The conditions for validity of these verification parameters need to be preset, and the conditions for validity of the verification parameters given in this embodiment are only examples, and can be adjusted according to actual needs.
After the parameters of the thermodynamic device and the parameters of the electrical device are verified, the nonlinear performance curve of the thermodynamic device can be fitted according to the parameters of the verified thermodynamic device, and the linear performance curve or the nonlinear performance curve of the electrical device can be fitted according to the parameters of the verified electrical device.
Assuming that the thermodynamic device includes CCHP, the performance curve of CCHP is the natural gas consumption curve of CCHP. The CCHP is an electric power device, the natural gas consumption curve of the CCHP is a linear curve as shown in fig. 2, the horizontal axis in fig. 2 represents the load power of the CCHP, and the vertical axis represents the gas consumption.
Assuming that thermodynamic equipment comprises a heat pump and a water chilling unit, respectively fitting a Performance curve Of the heat pump and a Performance curve Of the water chilling unit, wherein the Performance curves Of the heat pump and the water chilling unit are both energy efficiency ratio (COP) curves, and the COP curve Of the heat pump refers to a ratio curve Of the heating capacity Of the heat pump to the consumed electric power; the COP curve of the water chilling unit refers to the ratio curve of the refrigerating capacity of the compressor to the consumed electric power. Since the heat pump is a thermodynamic device, the COP curve of the heat pump is a nonlinear curve as shown in fig. 3, in which the horizontal axis of fig. 3 represents consumed electric power and the vertical axis represents heating capacity of the heat pump. The COP curve of the chiller is substantially the same as that of the heat pump and is not shown in this embodiment.
In some examples, fitting a non-linear performance curve of a thermodynamic device according to parameters of a validated thermodynamic device includes: normalizing the parameters of the verified thermodynamic equipment; and fitting a nonlinear performance curve of the thermodynamic equipment according to the normalized parameters.
Aiming at the nonlinear performance curve of the thermodynamic equipment, firstly, the parameters of the thermodynamic equipment are normalized, and the nonlinear performance curve of the thermodynamic equipment is fitted according to the normalized parameters, so that the complexity in fitting is reduced. And when the parameters are insufficient in fitting, the curve can be complemented according to the parameter trend, such as: assuming that 8 groups of actual parameters form 8 anchor points, 2 groups of parameters can be complemented according to the 8 groups of parameters to form 10 anchor points, and then the 10 anchor points are used for fitting a smooth COP curve.
Step 102: and determining an objective function and solving parameters of the objective function.
In this embodiment, the objective function and the solving parameters of the objective function may be set according to the problem to be solved actually, for example: and if the problem to be solved actually is that the carbon emission of the comprehensive energy system is minimum or the cost of the comprehensive energy system is minimum.
When the problem to be solved is actually the lowest cost of the integrated energy system,
the objective function is shown in equation (1):
objective function＝Cgas+Cheating+Ccooling+Cgrid-Csell (1)
wherein, CgasFor CCHP Natural gas costs, CheatingFor the cost of heat pump power consumption, CcoolingFor the cost of water consumption of the chiller CgridTo purchase electricity costs from the grid, CsellThe profit obtained for selling electricity to the grid.
The solution parameter of the objective function is Min (objective function).
Optionally, the solution parameters of the objective function include: the cost of the comprehensive energy system is the lowest or the carbon emission of the comprehensive energy system is the lowest, and the comprehensive energy system can be set according to the problems to be solved actually.
Step 103: and solving a first optimization result according to the performance curves of various devices and preset constraint conditions.
The preset constraint conditions in this embodiment include inequality constraint conditions, such as SOC constraints of energy storage, and the finally solved operation strategy of the energy storage device must satisfy that the SOC is between the allowable maximum value and the allowable minimum value for each hour.
The preset constraints also include non-linear constraints such as a thermal power balance constraint, a cold power balance constraint, and an electrical power balance constraint.
The thermal power balance constraint is shown in equation (2) below:
HCCHP+HHeatPump-HLoad＝0 (2)
wherein HCCHPFor CCHP to produce heat power, HHeatPumpFor heat pump to produce heat power, HLoadIs the heat load.
The cold power balance constraint is shown in equation (3) below:
CCCHP+Cchiller-CLoad＝0 (2)
wherein, CCCHPRefrigeration capacity of CCHP, CChillerFor the refrigerating capacity of the refrigerating unit, CLoadIs a cold load.
The electric power balance constraint is shown in equation (4) below:
ECCHP+EWT+EPv+EGrid-ELoad-EHeatPump-EChiller-EBattery＝0 (4)
wherein E isCCHPGenerating power for CCHP, EWTFor power generation of the fan, EPVFor photovoltaic power generation, EGridFor the power of the whole system interacting with the power grid (positive value getting power from the power grid, negative value selling power to the power grid), ELoadTo an electrical load, EHeatPumpElectric power consumed for heat pumps, EChillerElectric power consumed by the refrigerating unit, EBatteryFor storing electrical power (positive values)Charged, negative is discharged).
In this embodiment, a solver is called to solve the first optimization result, and fmincon's default algorithm is used to solve the first optimization result.
Optionally, iteratively solving the optimal solution parameters of the objective function for multiple times according to the performance curves of various devices and preset constraint conditions includes: setting a plurality of groups of initial values; and carrying out multiple times of iteration on the multiple groups of initial values, performance curves of various devices and preset constraint conditions to solve the optimal solving parameters of the objective function.
In this embodiment, a plurality of sets of initial values are set for various devices in the integrated energy system, and in the solving process, the CPU is used to perform parallel computation from a plurality of initial points simultaneously, so as to effectively shorten the solving time, and the memory requirement for solving is related to the device for operating the algorithm, and the following rules are approximately applied:
memory＝0.9+0.5×NcoreGB
wherein, memory is the required memory size, NcoreTo run the number of CPU cores of an algorithmic device, for example, an 8-core 16-thread CPU requires approximately 4.9GB of memory.
Step 104: and performing secondary optimization on the primary optimization result to obtain an operation strategy distribution result of the equipment.
Optionally, the operation policy allocation of the device includes: an energy storage device operation strategy, a heat pump operation strategy and a water chilling unit operation strategy; in the step of performing secondary optimization on the primary optimization result to obtain an operation strategy distribution result of the equipment, the optimization target of the operation strategy of the energy storage equipment is to enable the battery to be deeply charged and deeply discharged, and the linear inequality constraint is an upper limit constraint and a lower limit constraint of energy storage; the optimization target of the heat pump operation strategy and the water chilling unit operation strategy is that the power consumption cost is the lowest, and the linear equality constraint is the cold and hot power balance constraint.
Specifically, the energy storage operation strategy allocation also uses a default solving algorithm of an fmincon function, the optimization goal is to enable the battery to be deeply charged and deeply discharged as far as possible, the linear inequality constraint is an SOC upper and lower limit constraint of the energy storage, and the final energy storage allocation result is shown in fig. 4. The strategy allocation of the heat pump and the water chilling unit adopts a patternsearch algorithm, the optimization target is that the power consumption cost is lowest, no linear inequality constraint exists, the linear equality constraint is a cold-hot power balance constraint, the final allocation result of the heat pump is shown in figure 5, and the final allocation result of the water chilling unit is shown in figure 6.
Step 105: and calculating the optimal solving parameters of the objective function according to the distribution result of the operation strategy.
In this embodiment, the optimal solution parameter of the objective function is calculated after the operation policy allocation result of the device is determined.
Optionally, after performing secondary optimization on the first optimization result to obtain an operation policy allocation result of the device, the method further includes: and calculating whether the power grid interaction power is balanced and whether the cold and hot balance error is in a preset error range in the operation process of the comprehensive energy system according to the operation strategy distribution result. And if the interactive power of the power grid is unbalanced or the cold and hot balance error is not within the preset error range, continuously and iteratively solving the optimal solving parameter of the objective function.
Specifically, after the operation strategy distribution result of the equipment is determined, data post-processing is required to be performed on the result, and the data post-processing at least comprises calculation of power grid interaction power and calculation of cold-heat balance errors. The grid interaction power is calculated after the output strategy of other devices is determined, so that the electric power can be ensured to be always balanced, the total operation cost can be further reduced after the power is distributed among the devices, and a graph of the grid interaction power is shown in fig. 7. Electric power is always balanced, but cold and hot power is not, cold and hot power balance is a constraint condition in two times of optimization, and the final cold and hot power is 10 due to the fact that the constraint has an error allowable range-3Balance error in kW magnitude, which is calculated and shown, can help us to evaluate the convergence condition of the algorithm, and the thermal power balance error of a certain optimization result is shown in figure 8, and the cold power balance error is shown in figure 9.
It should be noted that, if the solution parameter of the objective function is that the cost of the integrated energy system is the lowest, the power grid interaction power needs to be calculated first, and after the power of the integrated energy system interacting with the power grid is determined, the operation cost in the corresponding optimization time period can be calculated according to the natural gas price, the electricity purchasing price, the electricity selling price and the solved equipment operation strategy. In this embodiment, the solution parameters of the objective function are used as the lowest cost of the integrated energy system to perform iterative solution, and as shown in fig. 10, the result is 198 times of operation to obtain the minimum value of 62965, the result is distributed in the interval of the minimum value × 1+ 3%, and the minimum value of the optimization problem can be obtained by continuously operating for at most 30 times.
The result fluctuation of the comprehensive energy optimization configuration method in the embodiment is small, the results are distributed in an interval of 3% of the right side of the minimum value after 198 times of continuous operation, the error range is far smaller than that of an intelligent algorithm based on particle swarm and the like, and the probability is converged to the global optimal point. The algorithm adopts multi-starting-point parallel computation, the solving speed is accelerated, the probability of finding the global optimal solution is increased, and the probability of obtaining the global optimal solution after 30 times of operation reaches 100%.
The method for optimizing and configuring the comprehensive energy resource mainly aims to solve the problem of optimizing the comprehensive energy resource system, and particularly comprises the optimization of nonlinear parameter equipment. The comprehensive energy optimization algorithm considering the nonlinear factors of the equipment is provided, and can optimize a comprehensive energy system comprising CCHP (combined cooling heating and power supply unit), a fan, photovoltaic, a heat pump, a water chilling unit, energy storage and other equipment, wherein the CCHP has a linear fuel gas consumption curve, and the heat pump and the water chilling unit have nonlinear COP curves. The method has the characteristics of small result fluctuation, large probability convergence to the global optimum point and the like. The nonlinear parameters of the equipment in the system are firstly standardized, and then the standardized data anchor points are subjected to curve fitting, so that the parameters are continuous and the first derivative thereof is continuous, and the complexity of the algorithm is reduced; and when the solution is carried out, the multi-starting-point parallel computation is used, so that the solution speed is accelerated on one hand, and the probability that the algorithm converges to a local optimal point is reduced on the other hand.
The steps of the above methods are divided for clarity, and the implementation may be combined into one step or split some steps, and the steps are divided into multiple steps, so long as the same logical relationship is included, which are within the scope of the present patent; it is within the scope of the patent to add insignificant modifications to the algorithms or processes or to introduce insignificant design changes to the core design without changing the algorithms or processes.
The embodiment of the invention relates to a comprehensive energy optimization configuration method, as shown in fig. 11, comprising at least one processor 301; and a memory 302 communicatively coupled to the at least one processor 301; the memory 302 stores instructions executable by the at least one processor 301, and the instructions are executed by the at least one processor 301, so that the at least one processor 301 can perform the integrated energy optimization configuration method.
Where the memory 302 and the processor 301 are coupled in a bus, the bus may comprise any number of interconnected buses and bridges, the buses coupling one or more of the various circuits of the processor 301 and the memory 302. The bus may also connect various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface provides an interface between the bus and the transceiver. The transceiver may be one element or a plurality of elements, such as a plurality of receivers and transmitters, providing a means for communicating with various other apparatus over a transmission medium. The data processed by the processor 301 is transmitted over a wireless medium through an antenna, which further receives the data and transmits the data to the processor 301.
The processor 301 is responsible for managing the bus and general processing and may also provide various functions including timing, peripheral interfaces, voltage regulation, power management, and other control functions. And memory 302 may be used to store data used by processor 301 in performing operations.
The embodiment of the invention also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the comprehensive energy optimal configuration method.
That is, as can be understood by those skilled in the art, all or part of the steps in the method for implementing the embodiments described above may be implemented by a program instructing related hardware, where the program is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the method described in the embodiments of the present application. 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 various media capable of storing program codes.
It will be understood by those of ordinary skill in the art that the foregoing embodiments are specific examples for carrying out the invention, and that various changes in form and details may be made therein without departing from the spirit and scope of the invention in practice.
Claims (10)
1. An integrated energy optimization configuration method is characterized by comprising the following steps:
respectively obtaining performance curves of various devices in the integrated energy system, wherein the performance curves of the various devices at least comprise: a non-linear performance curve of a thermodynamic device, a linear performance curve of an electrical device, or a non-linear performance curve;
determining an objective function and solving parameters of the objective function;
and iteratively solving the optimal solving parameters of the objective function for multiple times according to the performance curves of the various devices and preset constraint conditions.
2. The method according to claim 1, wherein the separately obtaining the performance curves of the various devices in the integrated energy system comprises:
respectively acquiring parameters of the thermodynamic equipment and parameters of the electrical power equipment, and verifying the validity of the parameters;
fitting a nonlinear performance curve of the thermodynamic device according to the verified parameters of the thermodynamic device;
and fitting a linear performance curve or a nonlinear performance curve of the electromechanical device according to the verified parameters of the electromechanical device.
3. The method according to claim 2, wherein the fitting the non-linear performance curve of the thermodynamic device according to the verified parameters of the thermodynamic device comprises:
normalizing the parameters of the verified thermodynamic equipment;
and fitting a nonlinear performance curve of the thermodynamic equipment according to the parameters after normalization processing.
4. The method according to claim 1, wherein the process of solving the optimal solution parameters of the objective function for each iteration comprises:
solving a first optimization result according to the performance curves of the various devices and preset constraint conditions;
performing secondary optimization on the primary optimization result to obtain an operation strategy distribution result of the equipment;
and calculating the optimal solving parameter of the objective function according to the operation strategy distribution result.
5. The method according to claim 4, wherein the allocation of the operation strategy of the plant comprises: an energy storage device operation strategy, a heat pump operation strategy and a water chilling unit operation strategy;
in the step of performing secondary optimization on the primary optimization result to obtain an operation strategy distribution result of the equipment, the optimization target of the operation strategy of the energy storage equipment is to enable the battery to be deeply charged and deeply discharged, and the linear inequality constraint is an upper limit constraint and a lower limit constraint of energy storage;
the optimization target of the heat pump operation strategy and the water chilling unit operation strategy is that the power consumption cost is the lowest, and the linear equality constraint is the cold and hot power balance constraint.
6. The method according to claim 5, wherein after performing the second optimization on the first optimization result to obtain the operation policy distribution result of the device, the method further comprises:
calculating whether the power grid interaction power is balanced and whether the cold and heat balance error is within a preset error range in the operation process of the comprehensive energy system according to the operation strategy distribution result;
and if the power grid interaction power is unbalanced or the cold and hot balance error is not in the preset error range, continuously and iteratively solving the optimal solving parameter of the objective function.
7. The method for optimal configuration of integrated energy resources according to claim 1, wherein the iterative solution of the optimal solution parameters of the objective function for a plurality of times according to the performance curves of the various devices and preset constraint conditions comprises:
setting a plurality of groups of initial values;
and carrying out multiple times of iteration on the multiple groups of initial values, the performance curves of various devices and preset constraint conditions to solve the optimal solving parameters of the objective function.
8. The method according to claim 1, wherein the solution parameters of the objective function include: the cost of the integrated energy system is the lowest or the carbon emission of the integrated energy system is the lowest.
9. An integrated energy optimization configuration device, comprising:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of integrated energy optimization configuration according to any one of claims 1 to 8.
10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the integrated energy optimization configuration method according to any one of claims 1 to 8.
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