Energy panoramic visualization dynamic control method based on multi-source data fusion

Abstract

The invention relates to the technical field of multi-dimensional energy dynamic regulation and control, in particular to an energy panoramic visual dynamic control method based on multi-source data fusion, and the method comprises the steps: needed electricity consumption judgment, power station information extraction, predicted generating capacity calculation, clean energy generating capacity judgment, clean energy power station confirmation and combustion energy power station confirmation. According to the invention, through centralized multi-energy coupled electric energy monitoring, when the power supply quantity of the power grid does not meet the power demand, the electric quantity generated by other energy sources of the power grid is dispatched; and the clean energy power station or the combustion energy power station for supplementary power supply is confirmed by combining the electric energy transmission loss condition of the clean energy power station and the power generation efficiency condition of the power generation equipment in the combustion energy power station, so that low energy utilization efficiency is avoided, the power supply reliability is improved, and multi-energy coupling scheduling is realized. And complementarity among different energy sources is reflected, and limitation on flexibility and activeness of the energy market is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-dimensional energy dynamic regulation and control, and in particular to a method for dynamic control of energy panoramic visualization based on multi-source data fusion. Background Art

[0002] With the diversification of energy structures, power grids no longer rely solely on a single source of electricity; instead, they couple multiple energy sources to form complex energy systems. However, existing power grid monitoring methods primarily focus on single-energy monitoring. For systems with multiple coupled energy sources, they lack effective operational monitoring tools, making it difficult to accurately assess the interrelationships and coordinated operational status of multiple energy sources. This makes it difficult to meet the requirements for safe, efficient, and stable operation of multi-energy coupled power grids. Therefore, a new monitoring method is needed to enable comprehensive, systematic, and real-time monitoring and management of multi-energy coupled power grids.

[0003] For example, the Chinese patent publication number CN119448283A discloses a regional power peak-shaving cloud service system and method for multi-energy collaborative optimization, including: collecting regional electricity consumption time series data, collecting key data of photovoltaic power stations and key data of wind power stations per unit time; preprocessing the key data of photovoltaic power stations and key data of wind power stations to obtain preprocessed key data of photovoltaic power stations and preprocessed key data of wind power stations; inputting the preprocessed key data of photovoltaic power stations into a photovoltaic power generation prediction model, and inputting the preprocessed key data of wind power stations into a wind power generation prediction model to obtain predicted photovoltaic power generation and predicted wind power generation respectively; inputting regional electricity consumption time series data into a regional electricity consumption prediction model to obtain future regional electricity consumption per unit time; the present invention improves the prediction accuracy of regional predicted electricity consumption and predicted power generation of distributed energy power stations.

[0004] The following problems still exist in the existing technology: 1. In the analysis of multi-energy projected power generation, in the analysis of the projected power generation of wind power stations, the wind speed corresponding to the height of the wind turbine is not actually analyzed, which reduces the power generation effect of the wind turbine, thereby reducing the credibility of the confirmation of the total power generation of the wind turbine, and cannot provide effective data support for the subsequent clean energy power scheduling.

[0005] 2. When multiple energy sources are needed for power dispatch, if the clean energy power station or the combustion power station for supplementary power supply is not determined based on the power transmission loss of the clean energy power station and the power generation efficiency of the power generation equipment in the combustion power station, a large amount of electricity may be lost during the transmission process, wasting clean energy. At the same time, in order to compensate for the transmission loss, the power generation capacity may need to be increased, which will increase the loss and operating costs of the power generation equipment, reduce the stability of the power grid operation, and may also hinder the optimization of the energy structure. Summary of the Invention

[0006] In view of this, in order to solve the problems raised in the above background technology, an energy panoramic visualization dynamic control method based on multi-source data fusion is proposed.

[0007] The purpose of the present invention can be achieved through the following technical solutions: The present invention provides a dynamic control method for energy panoramic visualization based on multi-source data fusion, including the following steps: S1, required power consumption judgment: the dedicated power supply network of the target park is recorded as the target power grid, and the expected required power consumption of the target park in the current monitoring period and the expected power supply of the target power grid in the current monitoring period are extracted to judge whether the required power consumption of the target park in the current monitoring period is in short supply. If not, there is no need to supplement the power supply. If there is a shortage, execute step S2.

[0008] S2. Power station information extraction: Extract the expected climate information corresponding to each monitoring day in the current monitoring cycle for the area of the target park, extract the installation angle of each photovoltaic panel in each solar power station corresponding to the target power grid, and extract the height and model of each wind turbine in each wind power station.

[0009] S3. Calculation of expected power generation: Calculate the expected power generation of each solar power station and each wind power station corresponding to the target power grid within the current monitoring period.

[0010] S4. Determination of clean energy power generation: Extract the power transmission distances of each solar power station and each wind power station corresponding to the target power grid respectively, and determine whether the clean energy power station corresponding to the target power grid can meet the power demand of the target park within the current monitoring period. If it can be met, execute step S5; if not, execute step S6.

[0011] S5. Confirmation of clean energy power stations: Confirm that the target park’s electricity demand during the current monitoring period corresponds to the clean energy power stations that require supplementary power supply.

[0012] S6. Confirmation of combustion-energy power stations: extract the actual output electric power and total heat input of the power generation equipment in each combustion-energy power station corresponding to the target power grid in each power generation, calculate the power generation efficiency of the power generation equipment in each combustion-energy power station corresponding to the target power grid, and confirm that the power demand of the target park in the current monitoring period corresponds to the combustion-energy power station that needs to provide additional power.

[0013] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention monitors the power of centralized multi-energy coupling, that is, when the power supply of the power grid does not meet the power demand, the power generated by other energy sources of the power grid is dispatched to avoid low energy utilization efficiency, thereby improving power supply reliability, and having multi-energy coupling scheduling, which reflects the complementarity between different energy sources and avoids restrictions on the flexibility and activity of the energy market.

[0014] (2) The present invention improves the power generation effect of the wind turbine by performing an actual analysis of the wind speed corresponding to the height of the wind turbine in the analysis of the expected power generation of the wind power station, thereby improving the credibility of the confirmation of the total power generation of the wind turbine and providing an effective data support basis for the subsequent clean energy power scheduling.

[0015] (3) The present invention identifies the clean energy power station or the combustion energy power station for supplementary power supply by combining the power transmission loss of the clean energy power station and the power generation efficiency of the power generation equipment in the combustion energy power station, thereby avoiding the loss of a large amount of power during the transmission process, saving clean energy, reducing the loss and operating costs of the power generation equipment, improving the stability of the power grid operation, and avoiding the obstruction of energy structure optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 Schematic diagram of the process steps of the present invention.

[0018] Figure 2 This is a flow chart for determining whether the power consumption required by the present invention is insufficient.

[0019] Figure 3 This is a flow chart for determining whether the electricity demand of the present invention can be met. DETAILED DESCRIPTION

[0020] 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 part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0021] See also Figure 1As shown, the present invention provides a dynamic control method for energy panoramic visualization based on multi-source data fusion, including: Figure 2 As shown, S1, required power consumption judgment: record the dedicated power supply network of the target park as the target power grid, extract the expected required power consumption of the target park in the current monitoring period and the expected power supply of the target power grid in the current monitoring period, and judge whether the power consumption required by the target park in the current monitoring period is insufficient. If not, there is no need to supplement the power supply. If there is a shortage, execute step S2.

[0022] It should be noted that the expected power consumption of the target park during the current monitoring period and the expected power supply of the target power grid during the current monitoring period are extracted from the prediction systems of the energy management department of the target park and the power company corresponding to the target power grid respectively.

[0023] In a specific embodiment of the present invention, the method for judging whether the target park's required electricity consumption in the current monitoring period is short of is: comparing the target park's estimated required electricity consumption in the current monitoring period with the target power grid's estimated power supply in the current monitoring period. If the target park's estimated required electricity consumption in the current monitoring period is greater than the target power grid's estimated power supply in the current monitoring period, it indicates that the target park's required electricity consumption in the current monitoring period is short of; otherwise, it indicates that the target park's required electricity consumption in the current monitoring period is not short of.

[0024] S2. Power station information extraction: Extract the expected climate information corresponding to each monitoring day in the current monitoring cycle for the area of the target park, extract the installation angle of each photovoltaic panel in each solar power station corresponding to the target power grid, and extract the height and model of each wind turbine in each wind power station.

[0025] In a specific embodiment of the present invention, the climate information includes light intensity, light duration, wind direction, wind speed duration and wind speed at each altitude layer.

[0026] It should be noted that the light intensity, light duration, wind direction, wind speed duration and wind speed at each altitude layer are all extracted from the weather forecast platform corresponding to each monitoring day in the current monitoring period in the area where the target park belongs.

[0027] It should also be noted that the installation angle of each photovoltaic panel in each solar power station corresponding to the target power grid and the height and model of each wind turbine in each wind power station are extracted from the photovoltaic panel management system of each solar power station and the wind turbine management system of each wind power station respectively.

[0028] S3. Calculation of expected power generation: Calculate the expected power generation of each solar power station and each wind power station corresponding to the target power grid within the current monitoring period.

[0029] In a specific embodiment of the present invention, the specific process of calculating the expected power generation of each photovoltaic power station corresponding to the target power grid during the current monitoring period is as follows: A1, extracting the light intensity and light duration from the expected climate information corresponding to each monitoring day in the target park area during the current monitoring period, and setting the power generation impact factor of each photovoltaic panel in each photovoltaic power station corresponding to the meteorological level on each monitoring day according to the installation angle of each photovoltaic panel in each photovoltaic power station corresponding to the target power grid. ,in, Indicates the number of the monitoring day, , Indicates the number of the solar power station. , Indicates the number of the photovoltaic panel, .

[0030] It should be noted that the specific process of setting the power generation influencing factor of each photovoltaic panel in each photovoltaic power station at the corresponding meteorological level on each monitoring day is as follows: according to the installation angle of each photovoltaic panel in each photovoltaic power station corresponding to the target power grid, the reference light intensity and reference light duration of the installation angle of each photovoltaic panel in each photovoltaic power station are located from the database and recorded as and .

[0031] The expected light intensity and light duration of the target park area on each monitoring day during the current monitoring period are recorded as and .

[0032] Set the power generation impact factor of each photovoltaic panel in each solar power station at the corresponding meteorological level on each monitoring day , .

[0033] A2. Extract the daily benchmark power generation of each photovoltaic panel at each solar power station from the database, and record it as .

[0034] A3. Calculate the expected power generation of each solar power station corresponding to the target grid during the current monitoring period. , ,in, Indicates the number of photovoltaic panels, Indicates the number of monitoring days.

[0035] In a specific embodiment of the present invention, the specific process of calculating the expected power generation of each wind power station corresponding to the target power grid in the current monitoring period is as follows: B1, extracting the wind direction, wind speed duration and wind speed at each altitude layer from the expected climate information corresponding to each monitoring day in the current monitoring period in the area to which the target park belongs, and setting the power generation impact factor of each wind turbine in each wind power station at the corresponding meteorological level on each monitoring day according to the height and model of each wind turbine in each wind power station corresponding to the target power grid. ,in, Indicates the number of the wind power station, , Indicates the number of the wind turbine. .

[0036] In a specific embodiment of the present invention, the specific process of setting the power generation impact factor of each wind turbine in each wind power station at the meteorological level corresponding to each monitoring day is as follows: C1, record the expected wind speed duration corresponding to each monitoring day in the target park area during the current monitoring period as .

[0037] C2. Based on the height of each wind turbine in each wind power station corresponding to the target grid, the predicted wind speed of each wind turbine in each wind power station at each monitoring day is located from the wind speed of each height layer in the target park area during the current monitoring period, and recorded as .

[0038] C3. According to the model of each wind turbine in each wind power station, locate the appropriate bearing wind speed of each wind turbine model in each wind power station from the database, and record it as .

[0039] C4, will and The relative deviation and and The sum of the relative deviation values of is taken as the power generation influencing factor of each wind turbine in each wind power station at the corresponding wind level on each monitoring day. , Indicates the duration of the reference wind speed under the set benchmark wind power generation condition.

[0040] The embodiment of the present invention improves the power generation effect of the wind turbine by performing actual analysis of the wind speed corresponding to the height of the wind turbine in the analysis of the expected power generation of the wind power station, thereby improving the credibility of the confirmation of the total power generation of the wind turbine and providing effective data support for subsequent clean energy power scheduling.

[0041] C5. According to the expected wind direction of the target park area on each monitoring day during the current monitoring period, set the power generation impact factor of each wind turbine in each wind power station at the corresponding wind direction level on each monitoring day. .

[0042] It should be noted that the specific process of setting the power generation impact factor of each wind turbine in each wind power station at the wind direction level corresponding to each monitoring day is as follows: if the expected wind direction corresponding to a monitoring day in the target park area during the current monitoring period is the same as the rotation direction of a wind turbine in a wind power station, then the power generation impact factor of the wind turbine in the wind power station at the wind direction level corresponding to the monitoring day is recorded as .

[0043] If the expected wind direction corresponding to a certain monitoring day in the target park area during the current monitoring period is opposite to the rotation direction of a certain wind turbine in a certain wind power station, the power generation impact factor of the wind turbine in the wind power station at the wind direction level corresponding to the monitoring day is recorded as .

[0044] If the expected wind direction corresponding to a certain monitoring day in the current monitoring period in the target park area and the rotation direction of a certain wind turbine in a certain wind power station are other than the case, then the power generation impact factor of the wind turbine in the wind power station at the corresponding wind direction level on the monitoring day is recorded as , thus obtaining the power generation impact factor of each wind turbine in each wind power station at the corresponding wind direction level on each monitoring day , The value of or or , .

[0045] It should be noted that the other situations mentioned above refer to the situation where the wind direction is expected to have an angle between 0 and 180 degrees with the rotation direction of a wind turbine under a certain wind speed, and the greater the deviation of the installation angle from the wind direction, the greater the reduction in power generation.

[0046] C6. Set the power generation impact factor of each wind turbine in each wind power station at the corresponding meteorological level on each monitoring day , , Represents a natural constant.

[0047] B2. According to the model of each wind turbine in each wind power station, locate the daily benchmark power generation of each wind turbine model in each wind power station from the database, and record it as .

[0048] B3. Calculate the expected power generation of each wind power station corresponding to the target grid during the current monitoring period , ,in, Indicates the number of wind turbines.

[0049] See also Figure 3 As shown, S4, clean energy power generation judgment: extract the power transmission distances of each solar power station and each wind power station corresponding to the target power grid respectively, and judge whether the clean energy power station corresponding to the target power grid can meet the power demand of the target park within the current monitoring period. If it can be met, execute step S5; if not, execute step S6.

[0050] It should be noted that the power transmission distances of the solar power stations and wind power stations corresponding to the target power grid are extracted from the power transmission management system of the target power grid.

[0051] In a specific embodiment of the present invention, both the solar power station and the wind power station are clean energy power stations.

[0052] In a specific embodiment of the present invention, the specific process of determining whether the clean energy power station corresponding to the target grid can meet the electricity demand of the target park within the current monitoring period is as follows: D1, the power transmission distances of each solar power station and each wind power station corresponding to the target grid are recorded as and .

[0053] D2. Extract the power loss per unit transmission distance of each solar power station and each wind power station corresponding to the target grid from the database, and record them as and .

[0054] D3. The target park's expected power consumption in the current monitoring period and the target grid's expected power supply in the current monitoring period are recorded as and .

[0055] D4. Calculate the expected power generation of the clean energy power station corresponding to the target grid during the current monitoring period , ,in, Indicates the number of solar power stations, Indicates the number of wind power stations.

[0056] D5. If , it indicates that the clean energy power station corresponding to the target grid can meet the electricity demand of the target park within the current monitoring period. , it indicates that the clean energy power station corresponding to the target power grid cannot meet the electricity demand of the target park within the current monitoring period.

[0057] S5. Confirmation of clean energy power stations: Confirm that the target park’s electricity demand during the current monitoring period corresponds to the clean energy power stations that require supplementary power supply.

[0058] In a specific embodiment of the present invention, the specific process of confirming the clean energy power station that needs to supplement the power supply corresponding to the electricity demand of the target park in the current monitoring period is as follows: E1, sorting the total power transmission losses of each solar power station and each wind power station corresponding to the target power grid from small to large, obtaining the total power transmission loss ranking of each clean energy power station corresponding to the target power grid, and recording the expected power generation of each clean energy power station in the current monitoring period as ,in, Indicates the number of the clean energy power station, .

[0059] It should be noted that the total power transmission loss of each solar power station corresponding to the target grid is The total power transmission loss of each wind power station corresponding to the target grid is .

[0060] E2. and For comparison, if , the first clean energy power station after sorting will be used as the clean energy power station that needs to supplement the power supply corresponding to the electricity demand of the target park in the current monitoring period. , then and For comparison, if , then the first two clean energy power stations after sorting will be used as the clean energy power stations that need to supplement the power supply corresponding to the electricity demand of the target park in the current monitoring period. , then and Compare and so on until the target park's electricity demand in the current monitoring period corresponds to the clean energy power station that needs to supplement the power supply, where: 、 and They respectively represent the expected power generation of the first, second and third clean energy power stations after sorting in the current monitoring period.

[0061] S6. Confirmation of combustion-energy power stations: extract the actual output electric power and total heat input of the power generation equipment in each combustion-energy power station corresponding to the target power grid in each power generation, calculate the power generation efficiency of the power generation equipment in each combustion-energy power station corresponding to the target power grid, and confirm that the power demand of the target park in the current monitoring period corresponds to the combustion-energy power station that needs to provide additional power.

[0062] It should be noted that the actual output electric power of the power generation equipment in each combustion power station corresponding to the target power grid in each power generation is collected by a power meter installed at the output end of the generator.

[0063] It should also be noted that if the fuel of a combustion-powered power station is solid fuel, the total heat input of the fuel = solid fuel mass * solid calorific value, where the solid fuel mass is measured by a belt scale and the solid calorific value is determined by laboratory analysis, usually using an oxygen bomb calorimeter. If the fuel of a combustion-powered power station is liquid fuel, the total heat input of the fuel = liquid fuel volume * liquid fuel density * liquid calorific value, where the liquid fuel volume is measured by a flow meter, the liquid fuel density is measured by a density meter, and the liquid calorific value also needs to be determined by laboratory analysis, which can be measured using equipment such as a bomb calorimeter. If the fuel of a combustion-powered power station is gas fuel, the total heat input of the fuel = gas volume * gas calorific value, where the gas volume is measured by a gas flow meter and the gas calorific value is measured using a calorimeter.

[0064] In a specific embodiment of the present invention, the specific process of calculating the power generation efficiency of the power generation equipment in each combustion energy power station corresponding to the target power grid is as follows: F1, the actual output power and the total heat input of the power generation equipment in each combustion energy power station corresponding to the target power grid in each power generation are recorded as and ,in, Indicates the number of the combustion power station, , Indicates the number of each power generation. .

[0065] F2, extract the fuel conversion rate of each combustion power station corresponding to the target grid from the database and record it as .

[0066] F3. Calculate the power generation efficiency of the power generation equipment in each combustion power station corresponding to the target power grid. , ,in, Indicates the number of times power is generated.

[0067] The embodiment of the present invention determines the clean energy power station or the combustion energy power station for supplementary power supply by combining the power transmission loss of the clean energy power station and the power generation efficiency of the power generation equipment in the combustion energy power station, thereby avoiding the loss of a large amount of electricity during the transmission process, saving clean energy, reducing the loss and operating costs of the power generation equipment, improving the stability of the power grid operation, and avoiding the obstruction of energy structure optimization.

[0068] In a specific embodiment of the present invention, the method for confirming that the target park's electricity demand in the current monitoring period corresponds to the combustion energy power station that needs to supplement the power supply is as follows: G1. Confirming the target park's electricity generation capacity that needs to be supplemented by the combustion energy power station in the current monitoring period , .

[0069] G2. Extract the basic power generation of each combustion power station corresponding to the target power grid on a single monitoring day from the database, thereby obtaining the basic power generation of each combustion power station in the current monitoring period and recording it as .

[0070] G3. Evaluate the expected power generation of each combustion power station during the current monitoring period .

[0071] G4. Sort the power generation efficiency of the power generation equipment in each combustion power station from large to small to obtain the power generation efficiency ranking of the power generation equipment in each combustion power station, and record the expected power generation of each combustion power station in the current monitoring period as ,in, Indicates the number of the sorted combustion power station, .

[0072] G5, will and For comparison, if , then the first combustion-energy power station after sorting will be used as the combustion-energy power station that needs to be supplemented with power according to the electricity demand of the target park in the current monitoring period. , then and For comparison, if , then the first two combustion-based power stations after sorting will be used as the combustion-based power stations that need to provide additional power to the target park in response to its electricity demand during the current monitoring period. , then and Compare and so on until the target park's electricity demand in the current monitoring period corresponds to the required supplementary power supply of the combustion energy power station, where: 、 and They respectively represent the expected power generation of the first, second and third combustion power stations after sorting in the current monitoring period.

[0073] The embodiment of the present invention centrally monitors the power of multiple energy couplings, that is, when the power supply of the power grid does not meet the power demand, the power generated by other energy sources of the power grid is dispatched to avoid low energy utilization efficiency and improve power supply reliability. The multi-energy coupling dispatch reflects the complementarity between different energy sources and avoids restrictions on the flexibility and activity of the energy market.

[0074] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should all fall within the scope of protection of the present invention.

Claims

1. An energy panoramic visualization dynamic control method based on multi-source data fusion, characterized by: include: S1. Extract the expected power consumption of the target park and the expected power supply of the target power grid, and determine whether the required power consumption is insufficient. If not, no power supply supplement is required. If so, execute step S2. S2. Extract the expected climate information corresponding to the target park area, and extract the installation angle of each photovoltaic panel and the height and model of each wind turbine corresponding to the target power grid; S3. Calculate the expected power generation of each solar power station and each wind power station; S4. Extract the power transmission distance of each solar power station and each wind power station, and determine whether the corresponding clean energy power station meets the power demand of the target park. If yes, execute step S5; if not, execute step S6; S5. Confirm that the target park's electricity demand corresponds to the clean energy power station that needs to provide supplementary power; S6. Extract the actual output power of the power generation equipment and the total heat input of the fuel in each combustion energy power station, calculate the power generation efficiency of the power generation equipment, and confirm the combustion energy power station that needs to supplement the power supply corresponding to the electricity demand of the target park.

2. The method for dynamic control of energy panorama visualization based on multi-source data fusion according to claim 1 is characterized by: The method for determining whether the required electricity consumption is in short supply is as follows: comparing the expected electricity consumption required by the target park in the current monitoring period with the expected power supply of the target power grid in the current monitoring period. If the expected electricity consumption required by the target park in the current monitoring period is greater than the expected power supply of the target power grid in the current monitoring period, it indicates that the target park is in short supply of electricity in the current monitoring period. Otherwise, it indicates that the target park is not in short supply of electricity in the current monitoring period.

3. The method for dynamic control of energy panorama visualization based on multi-source data fusion according to claim 1 is characterized by: The climate information includes light intensity, light duration, wind direction, wind speed duration and wind speed at each altitude.

4. The method for dynamic control of energy panorama visualization based on multi-source data fusion according to claim 3 is characterized by: The specific process of calculating the expected power generation of each solar power station is as follows: A1. Extract the sunlight intensity and duration from the predicted climate information for each monitoring day in the target park's area during the current monitoring cycle. Then, based on the installation angles of the photovoltaic panels in each photovoltaic power station corresponding to the target grid, set the meteorological power generation impact factor for each photovoltaic panel in each photovoltaic power station on each monitoring day. A2. Extracting from the database the daily benchmark power generation of each photovoltaic panel at each solar power station at the corresponding installation angle; A3. Calculate the expected power generation of each photovoltaic power station corresponding to the target grid during the current monitoring period based on a fusion analysis of the power generation impact factors of each photovoltaic panel at the corresponding meteorological level on each monitoring day and the single-day benchmark power generation of each photovoltaic panel's installation angle.

5. The method for dynamic control of energy panorama visualization based on multi-source data fusion according to claim 4 is characterized by: The specific process of calculating the expected power generation of each wind power station is as follows: B1. Extract the wind direction, wind speed duration, and wind speed at each altitude layer from the expected climate information corresponding to each monitoring day in the current monitoring cycle for the target park area. And set the power generation impact factor of each wind turbine in each wind power station corresponding to the meteorological level on each monitoring day based on the height and model of each wind turbine in each wind power station corresponding to the target power grid. B2. Locating the daily benchmark power generation of each wind turbine model in each wind power station from the database according to the model of each wind turbine in each wind power station; B3. Calculate the expected power generation of each wind power station corresponding to the target grid during the current monitoring period based on a comprehensive analysis of the power generation impact factors of each wind turbine at the corresponding meteorological level on each monitoring day and the single-day benchmark power generation of each wind turbine model.

6. The method for dynamic control of energy panorama visualization based on multi-source data fusion according to claim 4 is characterized by: The specific process of setting the power generation impact factor of each wind turbine in each wind power station at the corresponding meteorological level on each monitoring day is as follows: C1. Obtain the expected duration of wind speed in the target park area for each monitoring day during the current monitoring cycle; C2. Based on the heights of the wind turbines in the wind power stations corresponding to the target grid, locate the predicted wind speeds at the corresponding heights of the wind turbines in each wind power station on each monitoring day from the predicted wind speeds at each height level in the target park area on each monitoring day during the current monitoring cycle; C3. Locating the appropriate wind speed for each wind turbine model in each wind power station from a database based on the model of each wind turbine in each wind power station; C4. Calculate the power generation impact factor of each wind turbine in each wind power station at the corresponding wind level on each monitoring day; C5. According to the expected wind direction of the target park area on each monitoring day during the current monitoring period, set the power generation impact factor of each wind turbine in each wind power station at the corresponding wind direction level on each monitoring day; C6. Calculate and set the power generation impact factor of each wind turbine in each wind power station at the corresponding meteorological level on each monitoring day.

7. The method for dynamic control of energy panorama visualization based on multi-source data fusion according to claim 5 is characterized by: The specific process of determining whether the corresponding clean energy power station meets the electricity demand of the target park is as follows: D1. Obtain the power transmission distances of each solar power station and each wind power station corresponding to the target power grid; D2. Extract the power loss per unit transmission distance of each solar power station and each wind power station corresponding to the target grid from the database, and record them as and ; D3. The target park's expected power consumption in the current monitoring period and the target grid's expected power supply in the current monitoring period are recorded as and ; D4. Calculate the expected power generation of the clean energy power station corresponding to the target grid during the current monitoring period ; D5. If , it indicates that the clean energy power station corresponding to the target grid can meet the electricity demand of the target park within the current monitoring period. , it indicates that the clean energy power station corresponding to the target power grid cannot meet the electricity demand of the target park within the current monitoring period.

8. The method for dynamic control of energy panorama visualization based on multi-source data fusion according to claim 7 is characterized by: The specific process of confirming the target park's electricity demand corresponding to the clean energy power station that needs to provide supplementary power is as follows: E1. Sort the total power transmission losses of each solar power station and each wind power station corresponding to the target grid from small to large, and obtain the total power transmission loss ranking of each clean energy power station corresponding to the target grid. The estimated power generation of each clean energy power station in the current monitoring period after sorting is recorded as ,in, Indicates the number of the clean energy power station, ; E2. and For comparison, if , the first clean energy power station after sorting will be used as the clean energy power station that needs to supplement the power supply corresponding to the electricity demand of the target park in the current monitoring period. , then and For comparison, if , then the first two clean energy power stations after sorting will be used as the clean energy power stations that need to supplement the power supply corresponding to the electricity demand of the target park in the current monitoring period. , then and Compare and so on until the target park's electricity demand in the current monitoring period corresponds to the clean energy power station that needs to supplement the power supply, where: 、 and They respectively represent the expected power generation of the first, second and third clean energy power stations after sorting in the current monitoring period.

9. The method for dynamic control of energy panorama visualization based on multi-source data fusion according to claim 7 is characterized by: The specific process of calculating the power generation efficiency of the power generation equipment is as follows: F1. The actual output power and total heat input of fuel in each power generation of the power generation equipment in each combustion power station corresponding to the target grid are recorded as and ,in, Indicates the number of the combustion power station, , Indicates the number of each power generation. ; F2, extract the fuel conversion rate of each combustion power station corresponding to the target grid from the database and record it as ; F3. Calculate the power generation efficiency of the power generation equipment in each combustion power station corresponding to the target power grid. , ,in, Indicates the number of times power is generated.

10. The method for dynamic control of energy panorama visualization based on multi-source data fusion according to claim 9 is characterized in that: The method for confirming the target park's electricity demand corresponding to the combustion energy power station that needs to provide supplementary power is: G1. Confirm the target park's need for additional power generation from combustion-based power plants during the current monitoring period. , ; G2. Extract the basic power generation of each combustion power station corresponding to the target power grid on a single monitoring day from the database, thereby obtaining the basic power generation of each combustion power station in the current monitoring period and recording it as ; G3. Evaluate the expected power generation of each combustion power station during the current monitoring period ; G4. Sort the power generation efficiency of the power generation equipment in each combustion power station from large to small to obtain the power generation efficiency ranking of the power generation equipment in each combustion power station, and record the expected power generation of each combustion power station in the current monitoring period as ,in, Indicates the number of the sorted combustion power station, ; G5, will and For comparison, if , then the first combustion-energy power station after sorting will be used as the combustion-energy power station that needs to be supplemented with power according to the electricity demand of the target park in the current monitoring period. , then and For comparison, if , then the first two combustion-based power stations after sorting will be used as the combustion-based power stations that need to provide additional power to the target park in response to its electricity demand during the current monitoring period. , then and Compare and so on until the target park's electricity demand in the current monitoring period corresponds to the required supplementary power supply of the combustion energy power station, where: 、 and They respectively represent the expected power generation of the first, second and third combustion power stations after sorting in the current monitoring period.

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