Energy operation modeling method and device for smart park

Abstract

The invention relates to an energy operation modeling method and device for a smart park, and belongs to the technical field of energy management.The energy operation modeling method for the smart park comprises the steps that a power generation model, an energy storage model and a water system power consumption model are built, and the power generation model comprises a photovoltaic power generation model and a wind power generation model; the energy storage model comprises an electrochemical energy storage model and a water cold storage performance model, and the water system power consumption model comprises a water chilling unit performance model, a water pump performance model and a cooling tower performance model; training a power generation model, an energy storage model and a water system power consumption model based on historical operation data of the target smart park, and determining model parameters of the power generation model, the energy storage model and the water system power consumption model; and based on the trained power generation model, the energy storage model and the water system power consumption model, modeling the energy operation state of the target smart park. According to the invention, the energy operation condition of the smart park can be accurately determined.

Description

Technical Field

[0001] The present invention relates to the field of energy management technology, and in particular to a method and device for energy operation modeling of a smart park. Background Art

[0002] The threat posed by global climate change to ecosystems and human life is becoming increasingly serious. Against the backdrop of the global economy's transition to a low-carbon economy, more and more industrial parks are responding to climate change by reducing greenhouse gas emissions.

[0003] As a major source of carbon emissions, optimizing energy scheduling in smart industrial parks has become a crucial step in the low-carbon transition. However, currently, each energy system in a smart park is relatively independent. Optimizing energy scheduling in a smart park requires access to performance data from each energy system. Existing energy management systems consume significant computing power and storage space for energy performance analysis, and it is difficult to accurately predict the future performance of energy systems. This hinders energy scheduling optimization in smart parks.

[0004] Therefore, how to accurately determine the energy operation status of a smart park has become a technical problem that needs to be solved urgently. Summary of the Invention

[0005] In view of this, it is necessary to provide an energy operation modeling method and device for a smart park to solve the current problems of high cost and insufficient accuracy in energy performance analysis of smart parks.

[0006] In order to solve the above problems, in a first aspect, the present invention provides an energy operation modeling method for a smart park, comprising: Constructing a power generation model, an energy storage model, and a water system power consumption model, wherein the power generation model includes a photovoltaic power generation model and a wind power generation model, the energy storage model includes an electrochemical energy storage model and a water cooling performance model, and the water system power consumption model includes a chiller performance model, a water pump performance model, and a cooling tower performance model; Based on historical operating data of the target smart park, the power generation model, the energy storage model, and the water system power consumption model are trained to determine model parameters of the power generation model, the energy storage model, and the water system power consumption model; Based on the trained power generation model, the energy storage model and the water system power consumption model, the energy operation status of the target smart park is modeled.

[0007] In one possible implementation, modeling the energy operation state of the target smart park based on the trained power generation model, the energy storage model, and the water system power consumption model includes: Based on the current operating data of the target smart park and the trained power generation model, energy storage model, and water system power consumption model, determine the power generation, energy storage, and water system power consumption of the target smart park within a preset time period in the future; Based on the power generation, energy storage and water system power consumption of the target smart park in the future preset period, the power purchase and / or power sales of the target smart park in the future preset period are determined.

[0008] In one possible implementation, the electrochemical energy storage model is used to determine the remaining capacity of the battery and is constructed based on the following formula:

[0009] in, express The remaining battery power at all times, express The remaining battery power at all times, Indicates the charging power of the battery. Indicates the discharge power of the battery. Indicates the loss coefficient of battery power, Indicates the battery's charge and discharge efficiency coefficient.

[0010] In one possible implementation, the water cooling performance model is used to determine the remaining cooling capacity of the water tank and is constructed based on the following formula:

[0011] in, express The remaining cold storage capacity of the water tank at all times, express The remaining cold storage capacity of the water tank at all times, Indicates the cold storage rate of the water tank, Indicates the cooling rate of the water tank. Indicates the loss coefficient of the cooling capacity of the water tank, Indicates the cold storage and cooling efficiency coefficient of the water tank.

[0012] In one possible implementation, the chiller performance model is used to determine the COP of the chiller and is constructed based on the following formula:

[0013] in, represents the COP of the chiller, Indicates the chilled water supply temperature. Indicates the cooling water supply temperature, Indicates the refrigeration side load, 、 、 and represents the regression coefficient.

[0014] In one possible implementation, the water pump performance model is used to determine the power consumption of the water pump and is constructed based on the following formula:

[0015] in, Indicates the power consumption of the water pump, Indicates the motor frequency of the water pump, 、 and represents the fitting coefficient.

[0016] In one possible implementation, the cooling tower performance model is used to determine the power consumption and approximation of the cooling tower and is constructed based on the following formula:

[0017]

[0018] in, represents the power consumption of the cooling tower, Indicates the motor frequency of the cooling tower, represents the degree of approach of the cooling tower, 、 、 、 、 and represents the fitting coefficient.

[0019] In one possible implementation, the photovoltaic power generation model is used to determine the photovoltaic power generation of the target smart park. The model parameters of the photovoltaic power generation model are obtained by training a random forest model based on preprocessed historical weather data and historical photovoltaic power generation. The preprocessing of the historical weather data includes fitting the historical weather data based on the K-nearest neighbor algorithm.

[0020] In one possible implementation, the wind power generation model is used to determine the wind power generation of the target smart park and is constructed based on the following formula:

[0021] in, represents the wind power generation, Indicates wind speed, and represents the fitting coefficient.

[0022] On the other hand, the present invention also provides an energy operation modeling device for a smart park, comprising: A construction module is used to construct a power generation model, an energy storage model, and a water system power consumption model. The power generation model includes a photovoltaic power generation model and a wind power generation model. The energy storage model includes an electrochemical energy storage model and a water cooling performance model. The water system power consumption model includes a chiller performance model, a water pump performance model, and a cooling tower performance model. a determination module, configured to train the power generation model, the energy storage model, and the water system power consumption model based on historical operation data of the target smart park, and determine model parameters of the power generation model, the energy storage model, and the water system power consumption model; A modeling module is used to model the energy operation status of the target smart park based on the trained power generation model, the energy storage model and the water system power consumption model.

[0023] In a second aspect, the present invention further provides a modeling device, comprising a memory and a processor, wherein: The memory is used to store programs; The processor is coupled to the memory and is used to execute the program stored in the memory to implement the steps in the energy operation modeling method of the smart park described in any of the above implementation methods.

[0024] In a third aspect, the present invention also provides a computer-readable storage medium for storing computer-readable programs or instructions, which, when executed by a processor, can implement the steps in the energy operation modeling method of a smart park described in any of the above-mentioned implementation methods.

[0025] The beneficial effects of the present invention are: the energy operation modeling method and device of the smart park provided by the present invention respectively model the specific systems corresponding to the source (power generation model), storage (energy storage model), and load (water system power consumption model), thereby providing a basis for the subsequent energy operation modeling of the smart park. Then, the model parameters of the power generation model, energy storage model, and water system power consumption model are determined through the historical operation data of the smart park, so that the power generation model, energy storage model, and water system power consumption model are more in line with the actual operation status of the smart park, thereby ensuring the accuracy of the subsequent determination of the energy operation status of the smart park. Finally, the energy operation status of the smart park is accurately modeled through the trained power generation model, energy storage model, and water system power consumption model, providing a basis for subsequent energy scheduling optimization. The present invention can accurately determine the energy operation status of the smart park. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A schematic flow chart of an embodiment of the energy operation modeling method for a smart park provided by the present invention; Figure 2 A schematic flow chart of an embodiment of the energy operation modeling process of a smart park provided by the present invention; Figure 3 A schematic structural diagram of an embodiment of the energy operation modeling device for a smart park provided by the present invention; Figure 4 This is a schematic structural diagram of an embodiment of the modeling device provided by the present invention. DETAILED DESCRIPTION

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0028] In the description of the embodiments of the present invention, unless otherwise specified, "plurality" means two or more. "And / or" describes the association relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can mean: A exists alone, A and B exist simultaneously, or B exists alone.

[0029] The terms "first," "second," and so on, used in the embodiments of the present invention are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, technical features designated as "first" or "second" may explicitly or implicitly include at least one such feature.

[0030] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0031] The present invention provides a method and device for energy operation modeling of a smart park, which are described below.

[0032] Figure 1 A flow chart of an embodiment of the energy operation modeling method of a smart park provided by the present invention is as follows: Figure 1 As shown in Figure 2, the energy operation modeling method for smart parks includes: S101. Construct a power generation model, an energy storage model, and a water system power consumption model. The power generation model includes a photovoltaic power generation model and a wind power generation model. The energy storage model includes an electrochemical energy storage model and a water cooling performance model. The water system power consumption model includes a chiller performance model, a water pump performance model, and a cooling tower performance model.

[0033] It should be noted that by constructing a power generation model that includes a photovoltaic power generation model and a wind power generation model, an energy storage model that includes an electrochemical energy storage model and a water cooling performance model, and a water system power consumption model that includes a chiller performance model, a water pump performance model, and a cooling tower performance model, the power generation, energy storage, and water system power consumption of the smart park can be determined, thereby providing a basis for the subsequent energy operation modeling of the smart park.

[0034] S102. Based on the historical operation data of the target smart park, the power generation model, the energy storage model and the water system power consumption model are trained to determine the model parameters of the power generation model, the energy storage model and the water system power consumption model.

[0035] It should be noted that: through the historical operating data of the target smart park, which mainly includes the historical operating parameters of the photovoltaic power generation system, wind power generation system, electrochemical energy storage system, water storage cooling performance system, chiller system, water pump system and cooling tower system, the power generation model, energy storage model and water system power consumption model are trained to determine the model parameters of the power generation model, energy storage model and water system power consumption model, so that the power generation model, energy storage model and water system power consumption model are more in line with the actual operating status of the target smart park, thereby ensuring the accuracy of the subsequent determination of the energy operation status of the target smart park.

[0036] S103. Model the energy operation status of the target smart park based on the trained power generation model, the energy storage model, and the water system power consumption model.

[0037] It should be noted that after completing the training of the power generation model, energy storage model and water system power consumption model, the trained power generation model, energy storage model and water system power consumption model can be used to accurately model the energy operation status of the target smart park, providing a basis for subsequent energy scheduling optimization.

[0038] To sum up, the energy operation modeling method of the smart park provided by the embodiment of the present invention provides a basis for the subsequent energy operation modeling of the smart park by modeling the specific systems corresponding to the source (power generation model), storage (energy storage model), and load (water system power consumption model). Then, the model parameters of the power generation model, energy storage model, and water system power consumption model are determined through the historical operation data of the smart park, so that the power generation model, energy storage model, and water system power consumption model are more in line with the actual operation status of the smart park, thereby ensuring the accuracy of the subsequent determination of the energy operation status of the smart park. Finally, the energy operation status of the smart park is accurately modeled through the trained power generation model, energy storage model, and water system power consumption model, providing a basis for subsequent energy scheduling optimization. The present invention can accurately determine the energy operation status of the smart park.

[0039] In some embodiments of the present invention, modeling the energy operation state of the target smart park based on the trained power generation model, the energy storage model, and the water system power consumption model includes: Based on the current operating data of the target smart park and the trained power generation model, energy storage model, and water system power consumption model, determine the power generation, energy storage, and water system power consumption of the target smart park within a preset time period in the future; Based on the power generation, energy storage and water system power consumption of the target smart park in the future preset period, the power purchase and / or power sales of the target smart park in the future preset period are determined.

[0040] It should be noted that when modeling the energy operation status of the target smart park based on the trained power generation model, energy storage model and water system power consumption model, the target smart park's power generation, energy storage and water system power consumption in the future preset period can be determined based on the current operating data of the target smart park and the trained power generation model, energy storage model and water system power consumption model. Then, based on the power generation, energy storage and water system power consumption of the target smart park in the future preset period, the target smart park's power purchase and / or power sales in the future preset period can be determined, thereby achieving accurate modeling of the energy operation status of the target smart park.

[0041] In some embodiments of the present invention, the electrochemical energy storage model is used to determine the remaining capacity of the battery and can be constructed based on the following formula:

[0042] in, express The remaining battery power at all times, express The remaining battery power at all times, Indicates the charging power of the battery. Indicates the discharge power of the battery. Indicates the loss coefficient of battery power, Indicates the battery's charge and discharge efficiency coefficient.

[0043] In some embodiments of the present invention, the water cooling performance model is used to determine the remaining cooling capacity of the water tank and can be constructed based on the following formula:

[0044] in, express The remaining cold storage capacity of the water tank at all times, express The remaining cold storage capacity of the water tank at all times, Indicates the cold storage rate of the water tank, Indicates the cooling rate of the water tank. Indicates the loss coefficient of the cooling capacity of the water tank, Indicates the cold storage and cooling efficiency coefficient of the water tank.

[0045] In some embodiments of the present invention, the chiller performance model is used to determine the COP of the chiller and can be constructed based on the following formula:

[0046] in, represents the COP of the chiller, Indicates the chilled water supply temperature. Indicates the cooling water supply temperature, Indicates the refrigeration side load, 、 、 and represents the regression coefficient.

[0047] In some embodiments of the present invention, the water pump performance model is used to determine the power consumption of the water pump and can be constructed based on the following formula:

[0048] in, Indicates the power consumption of the water pump, Indicates the motor frequency of the water pump, 、 and represents the fitting coefficient.

[0049] In some embodiments of the present invention, the cooling tower performance model is used to determine the power consumption and approximation of the cooling tower, and can be constructed based on the following formula:

[0050]

[0051] in, represents the power consumption of the cooling tower, Indicates the motor frequency of the cooling tower, represents the degree of approach of the cooling tower, 、 、 、 、 and represents the fitting coefficient.

[0052] In some embodiments of the present invention, the photovoltaic power generation model is used to determine the photovoltaic power generation of the target smart park. The model parameters of the photovoltaic power generation model are obtained by training a random forest model based on preprocessed historical weather data and historical photovoltaic power generation. The preprocessing of the historical weather data includes fitting the historical weather data based on the K-nearest neighbor algorithm.

[0053] It should be noted that fitting historical weather data using the K-nearest neighbor algorithm can extract similarities between meteorological conditions within the historical data, further improving the accuracy of the photovoltaic power generation model. Using a random forest model as the underlying structure of the photovoltaic power generation model can reduce overfitting, improve model accuracy and stability, and effectively capture the complex relationship between photovoltaic power generation and multiple meteorological factors.

[0054] In some embodiments of the present invention, the wind power generation model is used to determine the wind power generation of the target smart park and can be constructed based on the following formula:

[0055] in, represents the wind power generation, Indicates wind speed, and represents the fitting coefficient.

[0056] Combine Figure 2 From the perspective of the present invention, the specific systems corresponding to the source (power generation model), storage (energy storage model), and load (water system power consumption model) are modeled separately, and then the model parameters of the power generation model, energy storage model, and water system power consumption model are determined through the historical operation data of the smart park, so that the power generation model, energy storage model, and water system power consumption model are more in line with the actual operation status of the smart park. Finally, the energy operation status of the smart park is accurately modeled through the trained power generation model, energy storage model, and water system power consumption model, providing a basis for subsequent energy scheduling optimization. The present invention can accurately determine the energy operation status of the smart park.

[0057] In order to better implement the energy operation modeling method of the smart park in the embodiment of the present invention, based on the energy operation modeling method of the smart park, correspondingly, Figure 3 As shown, an embodiment of the present invention further provides an energy operation modeling device for a smart park. The energy operation modeling device 300 for a smart park includes: Construction module 301, for constructing a power generation model, an energy storage model, and a water system power consumption model, wherein the power generation model includes a photovoltaic power generation model and a wind power generation model, the energy storage model includes an electrochemical energy storage model and a water cooling performance model, and the water system power consumption model includes a chiller performance model, a water pump performance model, and a cooling tower performance model; A determination module 302 is configured to train the power generation model, the energy storage model, and the water system power consumption model based on historical operation data of the target smart park, and determine model parameters of the power generation model, the energy storage model, and the water system power consumption model; The modeling module 303 is used to model the energy operation status of the target smart park based on the trained power generation model, the energy storage model and the water system power consumption model.

[0058] The energy operation modeling device 300 for a smart park provided in the above embodiment can implement the technical solution described in the above embodiment of the energy operation modeling method for a smart park. The specific implementation principles of the above modules or units can refer to the corresponding contents in the above embodiment of the energy operation modeling method for a smart park, and will not be repeated here.

[0059] like Figure 4 As shown, the present invention also provides a modeling device 400. The modeling device 400 includes a processor 401, a memory 402 and a display 403. Figure 4 Only some of the components of the modeling device 400 are shown, but it should be understood that implementing all of the shown components is not a requirement, and more or fewer components may alternatively be implemented.

[0060] In some embodiments, the processor 401 may be a central processing unit (CPU), a microprocessor, or other data processing chip, configured to execute program codes or process data stored in the memory 402 , such as the magnetic resonance image optimization method of the present invention.

[0061] In some embodiments, processor 401 may be a single server or a server group. The server group may be centralized or distributed. In some embodiments, processor 401 may be local or remote. In some embodiments, processor 401 may be implemented on a cloud platform. In one embodiment, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, multiple clouds, or any combination thereof.

[0062] In some embodiments, the memory 402 may be an internal storage unit of the modeling device 400, such as a hard disk or memory of the modeling device 400. In other embodiments, the memory 402 may also be an external storage device of the modeling device 400, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc., equipped on the modeling device 400.

[0063] Furthermore, the memory 402 may include both an internal storage unit of the modeling device 400 and an external storage device. The memory 402 is used to store application software installed in the modeling device 400 and various data.

[0064] In some embodiments, display 403 can be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an organic light-emitting diode (OLED) touchscreen. Display 403 is used to display information on modeling device 400 and to display a visual user interface. Components 401-403 of modeling device 400 communicate with each other via a system bus.

[0065] In one embodiment, when the processor 401 executes the smart park energy operation modeling program in the memory 402, the following steps may be implemented: Constructing a power generation model, an energy storage model, and a water system power consumption model, wherein the power generation model includes a photovoltaic power generation model and a wind power generation model, the energy storage model includes an electrochemical energy storage model and a water cooling performance model, and the water system power consumption model includes a chiller performance model, a water pump performance model, and a cooling tower performance model; Based on historical operating data of the target smart park, the power generation model, the energy storage model, and the water system power consumption model are trained to determine model parameters of the power generation model, the energy storage model, and the water system power consumption model; Based on the trained power generation model, the energy storage model and the water system power consumption model, the energy operation status of the target smart park is modeled.

[0066] It should be understood that when the processor 401 executes the energy operation modeling program of the smart park in the memory 402, in addition to the above functions, it can also implement other functions. For details, please refer to the description of the corresponding method embodiment above.

[0067] Furthermore, the embodiments of the present invention do not specifically limit the type of modeling device 400 mentioned. Modeling device 400 may be a portable electronic device such as a mobile phone, tablet computer, personal digital assistant (PDA), wearable device, or laptop computer. Exemplary portable electronic devices include, but are not limited to, portable electronic devices running iOS, Android, Microsoft, or other operating systems. The aforementioned portable electronic devices may also be other portable electronic devices, such as a laptop computer with a touch-sensitive surface (e.g., a touch panel). It should also be understood that in other embodiments of the present invention, modeling device 400 may not be a portable electronic device, but rather a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0068] Accordingly, an embodiment of the present application also provides a computer-readable storage medium, which is used to store computer-readable programs or instructions. When the program or instructions are executed by a processor, it can implement the steps or functions in the energy operation modeling method of the smart park provided by the above-mentioned method embodiments.

[0069] Those skilled in the art will appreciate that all or part of the process flow of the above-described method embodiment can be implemented by instructing related hardware (such as a processor, controller, etc.) through a computer program, and the computer program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a magnetic disk, an optical disk, a read-only memory, or a random access memory.

[0070] The above is a detailed introduction to the energy operation modeling method and device for the smart park provided by the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core ideas. At the same time, for those skilled in the art, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for modeling energy operation of a smart park, characterized in that: include: Constructing a power generation model, an energy storage model, and a water system power consumption model, wherein the power generation model includes a photovoltaic power generation model and a wind power generation model, the energy storage model includes an electrochemical energy storage model and a water cooling performance model, and the water system power consumption model includes a chiller performance model, a water pump performance model, and a cooling tower performance model; Based on historical operating data of the target smart park, the power generation model, the energy storage model, and the water system power consumption model are trained to determine model parameters of the power generation model, the energy storage model, and the water system power consumption model; Based on the trained power generation model, the energy storage model and the water system power consumption model, the energy operation status of the target smart park is modeled.

2. The energy operation modeling method of a smart park according to claim 1 is characterized in that: Modeling the energy operation state of the target smart park based on the trained power generation model, the energy storage model, and the water system power consumption model includes: Based on the current operating data of the target smart park and the trained power generation model, energy storage model, and water system power consumption model, determine the power generation, energy storage, and water system power consumption of the target smart park within a preset time period in the future; Based on the power generation, energy storage and water system power consumption of the target smart park in the future preset period, the power purchase and / or power sales of the target smart park in the future preset period are determined.

3. The energy operation modeling method of a smart park according to claim 1 is characterized in that: The electrochemical energy storage model is used to determine the remaining capacity of the battery and is constructed based on the following formula: in, express The remaining battery power at all times, express The remaining battery power at all times, Indicates the charging power of the battery. Indicates the discharge power of the battery. Indicates the loss coefficient of battery power, Indicates the battery's charge and discharge efficiency coefficient.

4. The energy operation modeling method of a smart park according to claim 1 is characterized in that: The water cooling performance model is used to determine the remaining cooling capacity of the water tank and is constructed based on the following formula: in, express The remaining cold storage capacity of the water tank at all times, express The remaining cold storage capacity of the water tank at all times, Indicates the cold storage rate of the water tank, Indicates the cooling rate of the water tank. Indicates the loss coefficient of the cooling capacity of the water tank, Indicates the cold storage and cooling efficiency coefficient of the water tank.

5. The energy operation modeling method of a smart park according to claim 1 is characterized in that: The chiller performance model is used to determine the COP of the chiller and is constructed based on the following formula: in, Indicates the COP of the chiller, Indicates the chilled water supply temperature. Indicates the cooling water supply temperature, Indicates the refrigeration side load, 、 、 and represents the regression coefficient.

6. The energy operation modeling method of a smart park according to claim 1 is characterized in that: The water pump performance model is used to determine the power consumption of the water pump and is constructed based on the following formula: in, Indicates the power consumption of the water pump, Indicates the motor frequency of the water pump, 、 and represents the fitting coefficient.

7. The energy operation modeling method of a smart park according to claim 1 is characterized in that: The cooling tower performance model is used to determine the power consumption and approximation of the cooling tower and is constructed based on the following formula: in, represents the power consumption of the cooling tower, Indicates the motor frequency of the cooling tower, represents the degree of approach of the cooling tower, 、 、 、 、 and represents the fitting coefficient.

8. The energy operation modeling method of a smart park according to claim 1 is characterized in that: The photovoltaic power generation model is used to determine the photovoltaic power generation of the target smart park. The model parameters of the photovoltaic power generation model are obtained by training a random forest model based on preprocessed historical weather data and historical photovoltaic power generation. The preprocessing of the historical weather data includes fitting the historical weather data based on the K-nearest neighbor algorithm.

9. The energy operation modeling method of a smart park according to claim 1 is characterized in that: The wind power generation model is used to determine the wind power generation of the target smart park and is constructed based on the following formula: in, represents the wind power generation, Indicates wind speed, and represents the fitting coefficient.

10. An energy operation modeling device for a smart park, characterized in that: include: A construction module is used to construct a power generation model, an energy storage model, and a water system power consumption model. The power generation model includes a photovoltaic power generation model and a wind power generation model. The energy storage model includes an electrochemical energy storage model and a water cooling performance model. The water system power consumption model includes a chiller performance model, a water pump performance model, and a cooling tower performance model. a determination module, configured to train the power generation model, the energy storage model, and the water system power consumption model based on historical operation data of the target smart park, and determine model parameters of the power generation model, the energy storage model, and the water system power consumption model; A modeling module is used to model the energy operation status of the target smart park based on the trained power generation model, the energy storage model and the water system power consumption model.

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