Photovoltaic power generation prediction method, and power dispatching command interaction system and method based on block chain

Abstract

The invention discloses a photovoltaic power generation prediction method, and the method comprises the following steps: S1, building a photovoltaic power generation model: S11, obtaining an air water vapor reference content Hs according to the saturated vapor pressure and atmospheric pressure of an area where a photovoltaic power station is located; s12, according to the obtained air water vapor reference content Hs, the air water vapor content Hs1 under the wind dilution effect and the air water vapor content Hs4 under the light evaporation effect and the haze shielding effect are obtained at the same time; s13, the actual air water content Hs0 is obtained; s14, obtaining a photovoltaic power generation attenuation coefficient K according to the actual air water content Hs0; s15, according to the photovoltaic power generation attenuation coefficient K, the actual photovoltaic power generation capacity is obtained; s2, predicting the generating capacity: obtaining a saturated vapor pressure curve, a wind power curve, an illumination intensity curve and a haze concentration curve of the area where the photovoltaic power station is located, and obtaining an actual generating capacity curve of the photovoltaic power station by adopting a photovoltaic power generation model. The invention further discloses a power dispatching command interaction system and method based on the block chain.

Description

Technical Field

[0001] The present invention belongs to the technical field of power dispatching, and specifically provides a photovoltaic power generation prediction method, and a blockchain-based power dispatching command interaction system and method. Background Art

[0002] Power dispatching is an effective management method used to ensure the safe and stable operation of the power grid, reliable external power supply, and orderly progress of various power production tasks. The power dispatching command interaction system can efficiently and accurately complete various dispatching tasks to ensure the stable operation of the power system.

[0003] When using the power dispatching and command interactive system for power dispatching, it is necessary to collect equipment load status information. In particular, for power grids connected to photovoltaic power stations, during the photovoltaic power generation process, due to the PID effect, water vapor will have a serious impact on the photovoltaic power generation, resulting in the inability to accurately judge the power generation of the photovoltaic power station during power dispatching. Specifically, the PID effect refers to water vapor entering the solar panel through the backplane, resulting in a high bias voltage between the internal circuit and the frame, which in turn causes electrical performance degradation and a sharp drop in power generation. The PID effect is particularly evident during long-term outdoor operation, and current power dispatching technology is unable to accurately judge this aspect, resulting in inaccurate subsequent power dispatching, which has become a problem that needs to be solved urgently by people in this field. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a photovoltaic power generation prediction method, a blockchain-based power dispatching and command interaction system and method, which can accurately predict photovoltaic power generation, thereby improving the accuracy, efficiency and automation level of power dispatching to ensure the stable operation of the power system and the reliability of power supply.

[0005] In order to achieve the above object, the present invention provides the following technical solutions:

[0006] The present invention first proposes a photovoltaic power generation prediction method, which includes the following steps:

[0007] S1: Build a photovoltaic power generation model

[0008] S11: Obtaining a baseline water vapor content Hs in the air based on the saturated vapor pressure and atmospheric pressure of the area where the photovoltaic power station is located;

[0009] S12: Based on the obtained air water vapor baseline content Hs, obtain the air water vapor content Hs1 under the effect of wind dilution and the air water vapor content Hs4 under the effect of light evaporation and haze obstruction;

[0010] S13: Obtain the actual air moisture content Hs0 in the area where the photovoltaic power station is located;

[0011] S14: Calculate the photovoltaic power generation attenuation coefficient K based on the actual air moisture content Hs0;

[0012] S15: Obtaining actual photovoltaic power generation according to the photovoltaic power generation attenuation coefficient K;

[0013] S2: Predicting power generation: Obtain the saturated vapor pressure curve, wind force curve, light intensity curve, and haze concentration curve of the area where the photovoltaic power station is located, and use the photovoltaic power generation model to obtain the actual power generation curve of the photovoltaic power station.

[0014] Furthermore, in step S11, the air water vapor baseline content Hs is:

[0015]

[0016] Where: Ps is the saturated vapor pressure; P is the atmospheric pressure.

[0017] Furthermore, in step S12, the water vapor content Hs1 of the air under the effect of wind dilution is:

[0018]

[0019] Where: Q is the wind force; Q max is the maximum wind speed;

[0020] The air water vapor content Hs4 considering both the evaporation effect of light and the obstruction effect of haze is:

[0021] Hs4=Hs2-Hs3

[0022]

[0023] Where: Hs2 is the air water vapor content under the effect of light evaporation; M is the light intensity; M max is the maximum light intensity; Hs3 is the air water vapor content under the effect of haze; G is the haze concentration; G max The maximum haze concentration.

[0024] Furthermore, in step S13, the actual air moisture content Hs0 is:

[0025] Hs0=Hs-Hs1-Hs4+Hs5-Hs6

[0026] Wherein: Hs5 is the increased air water vapor content in a wetland environment; Hs6 is the decreased air water vapor content in a dry environment; and: when the photovoltaic power station is located in a wetland environment, Hs6 = 0; when the photovoltaic power station is located in a dry environment, Hs5 = 0.

[0027] Furthermore, in step S14, the photovoltaic power generation attenuation coefficient K is:

[0028]

[0029] Among them: Hs max is the maximum water vapor content in the air; K max It is the highest power generation attenuation coefficient.

[0030] Furthermore, in step S15, the actual power generation of the photovoltaic power station is:

[0031] Qs0=Qs(1-K)

[0032] Among them: Qs0 is the actual power generation of the photovoltaic power station; Qs is the theoretical power generation obtained by the photovoltaic power station based on sunlight.

[0033] Furthermore, in step S2, the photovoltaic power station power generation curve is:

[0034] Qs0(t)=Qs(t)(1-K(t))

[0035] Where: Qs0(t) is the curve of the actual power generation of the photovoltaic power station changing with time t; Qs(t) is the curve of the theoretical power generation of the photovoltaic power station changing with time t; K(t) is the curve of the photovoltaic power generation attenuation coefficient changing with time t.

[0036] The present invention also proposes a blockchain-based power dispatching and command interactive system, which includes a blockchain module, a preparation module, an inspection module, an operation command module, an operation issuing module, a monitoring and control module, and a data acquisition and transmission module, which are electrically connected in sequence;

[0037] The blockchain module is used to collect and store power grid operation status information in real time through blockchain technology; the power grid operation status information includes the saturated vapor pressure curve, wind speed curve, light intensity curve and haze concentration curve of the photovoltaic power station area;

[0038] The preparation module is used to collect the grid operation status information in the blockchain module and organize and analyze the grid operation status information; the preparation module is provided with a photovoltaic power generation model, and uses the photovoltaic power generation prediction method according to any one of claims 1 to 7 to obtain the actual power generation curve of the photovoltaic power station;

[0039] The review work module is used to review the work plan and conduct on-site verification of facilities that require power outages, while considering the impact on the power system and taking corresponding measures;

[0040] The operation order module is used to fill in the operation order ticket according to the work plan and review it according to the mobilization plan, work content and safety measures requirements;

[0041] The operation issuing module is used to notify relevant units to prepare before the operation and issue the operation order using mobilization terminology; the content of the notice issued by the operation issuing module is the same as the content of the operation ticket;

[0042] The monitoring and control module is used to monitor the power system in real time and to remotely control the power system;

[0043] The data acquisition and transmission module is used to collect data from various power equipment through remote control equipment and transmit the data back to the main station or data center; the power equipment includes a photovoltaic power station, and the data collected from the photovoltaic power station includes a saturated vapor pressure curve, wind curve, light curve and haze concentration curve of the area where the photovoltaic power station is located.

[0044] The present invention also proposes a blockchain-based power dispatching and command interaction method, which includes the following steps:

[0045] Step 1: Before carrying out power dispatch and command work, the preparatory work module comprehensively collects the power grid operation status information in the blockchain; the power grid operation status information includes the saturated vapor pressure curve, wind force curve, light intensity curve, and haze concentration curve of the area where the photovoltaic power station is located; the preparatory work module organizes and analyzes the power grid operation status information, and uses the photovoltaic power generation model set in the preparatory work module to obtain the actual power generation curve of the photovoltaic power station using the photovoltaic power generation prediction method according to any one of claims 1 to 7;

[0046] Step 2: Before deciding on a power switching operation, review the work plan and conduct on-site verification of the facilities that require power outages. Consider the impact on the power system and take countermeasures in advance.

[0047] Step 3: Fill out the operation order ticket according to the work plan, ensuring that the operation purpose is clear and the content of the operation order ticket is consistent with the planned work requirements. The operation numbers in the operation order ticket are filled in ascending order, and operations with the same number are carried out simultaneously. The operation order tickets are cross-examined and reviewed based on the mobilization plan, work content and safety measures.

[0048] Step 4: Issue a notice before the operation to inform relevant units to prepare. The notice content is the same as the operation ticket content. When issuing operation orders using mobilization terms, issue them item by item according to the operation ticket. Once confirmation of the completion of the previous order is obtained, issue the next order.

[0049] Step 5: Real-time monitoring and control of the power system, providing real-time monitoring of the grid operation status and power equipment status, and remote control of the power system through control functions;

[0050] Step 6: Collect data from various power equipment through telecontrol equipment, transmit the data back to the main station or data center, and process and store the collected data; the power equipment includes photovoltaic power stations, and the data collected from the photovoltaic power stations include the saturated vapor pressure curve, wind curve, light curve and haze concentration curve of the area where the photovoltaic power station is located.

[0051] The beneficial effects of the present invention are:

[0052] The photovoltaic power generation prediction method of the present invention can obtain the attenuation coefficient of photovoltaic power generation and then obtain the actual photovoltaic power generation through environmental data such as wind speed, light intensity, haze concentration, atmospheric pressure, and saturated vapor pressure in the area where the photovoltaic power station is located, and thus obtain the actual photovoltaic power generation, and construct a photovoltaic power generation model. Specifically, since water vapor enters the photovoltaic cell panel through the photovoltaic backplane, the voltage between the internal circuit and the frame is relatively high, which in turn causes electrical performance degradation and a sharp drop in power generation. The present invention obtains the saturated vapor pressure curve, wind speed curve, light intensity curve and haze concentration curve of the area where the photovoltaic power station is located, and can obtain the actual power generation curve of the photovoltaic power station through the photovoltaic power generation model, that is, it can improve the prediction accuracy of photovoltaic power generation, thereby improving the accuracy of power dispatching, and improving the efficiency and quality of power dispatching. Moreover, by comprehensively considering the evaporation of water vapor due to light intensity and haze obstruction, the data accuracy is further improved. At the same time, considering the impact of two different environments, dry and wet, on the water content of the air, the accuracy of the actual power generation prediction data of the photovoltaic power station can be guaranteed to the greatest extent.

[0053] This invention presents a blockchain-based power dispatch and command interactive system. The decentralized and tamper-proof nature of blockchain can improve the transmission efficiency and security of power dispatch instructions, reducing human intervention and errors. The openness and transparency of blockchain can enhance the transparency of the power dispatch process, facilitating oversight by regulators and users. Blockchain can record power transaction data, helping power systems achieve more accurate load forecasting and optimize resource allocation. Blockchain's encryption technology and consensus mechanism can improve power system security, preventing data leaks and system attacks. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to make the purpose, technical solutions and beneficial effects of the present invention more clear, the present invention provides the following drawings for illustration:

[0055] Figure 1 This is a flow chart of the photovoltaic power generation prediction method of the present invention;

[0056] Figure 2 This is a principle block diagram of the blockchain-based power dispatching and command interactive system of the present invention. DETAILED DESCRIPTION

[0057] The present invention will be further described below with reference to the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it. However, the embodiments are not intended to limit the present invention.

[0058] Example 1

[0059] like Figure 1 As shown, the photovoltaic power generation prediction method of this embodiment includes the following steps.

[0060] S1: Construct a photovoltaic power generation model.

[0061] S11: Obtain a baseline water vapor content Hs in the air based on the saturated vapor pressure and atmospheric pressure of the area where the photovoltaic power station is located.

[0062] Specifically, in this embodiment, the air water vapor baseline content Hs is:

[0063]

[0064] Where: Ps is the saturated vapor pressure; P is the atmospheric pressure.

[0065] S12: Based on the obtained air water vapor baseline content Hs, obtain the air water vapor content Hs1 under the effect of wind dilution and the air water vapor content Hs4 under the effect of light evaporation and haze shielding.

[0066] Specifically, in this embodiment, the air water vapor content Hs1 under the effect of wind dilution is:

[0067]

[0068] Where: Q is the wind force; Q max The maximum wind speed.

[0069] The air water vapor content Hs4 considering both the evaporation effect of light and the obstruction effect of haze is:

[0070] Hs4=Hs2-Hs3

[0071]

[0072] Where: Hs2 is the air water vapor content under the effect of light evaporation; M is the light intensity; M max is the maximum light intensity; Hs3 is the air water vapor content under the effect of haze; G is the haze concentration; G max The maximum haze concentration.

[0073] S13: Obtain the actual air moisture content Hs0 in the area where the photovoltaic power station is located.

[0074] In this embodiment, the actual air moisture content Hs0 is:

[0075] Hs0=Hs-Hs1-Hs4+Hs5-Hs6

[0076] Wherein: Hs5 is the increased air water vapor content in a wetland environment; Hs6 is the decreased air water vapor content in a dry environment; and: when the photovoltaic power station is located in a wetland environment, Hs6 = 0; when the photovoltaic power station is located in a dry environment, Hs5 = 0.

[0077] S14: Obtain the photovoltaic power generation attenuation coefficient K based on the actual air moisture content Hs0.

[0078] In this embodiment, the photovoltaic power generation attenuation coefficient K is:

[0079]

[0080] Among them: Hs max is the maximum water vapor content in the air; K max It is the highest power generation attenuation coefficient.

[0081] S15: According to the photovoltaic power generation attenuation coefficient K, the actual photovoltaic power generation is obtained.

[0082] In this embodiment, the actual power generation of the photovoltaic power station is:

[0083] Qs0=Qs(1-K)

[0084] Among them: Qs0 is the actual power generation of the photovoltaic power station; Qs is the theoretical power generation obtained by the photovoltaic power station based on sunlight.

[0085] S2: Predicting power generation: Obtain the saturated vapor pressure curve, wind force curve, light intensity curve, and haze concentration curve of the area where the photovoltaic power station is located, and use the photovoltaic power generation model to obtain the actual power generation curve of the photovoltaic power station.

[0086] Specifically, the power generation curve of the photovoltaic power station is:

[0087] Qs0(t)=Qs(t)(1-K(t))

[0088] Where: Qs0(t) is the curve of the actual power generation of the photovoltaic power station changing with time t; Qs(t) is the curve of the theoretical power generation of the photovoltaic power station changing with time t; K(t) is the curve of the photovoltaic power generation attenuation coefficient changing with time t.

[0089] The photovoltaic power generation prediction method of this embodiment uses environmental data such as wind speed, light intensity, haze concentration, atmospheric pressure, and saturated vapor pressure in the area where the photovoltaic power station is located to obtain the photovoltaic power generation attenuation coefficient, thereby obtaining the actual photovoltaic power generation and constructing a photovoltaic power generation model. Specifically, because water vapor enters the photovoltaic cell panel through the photovoltaic backsheet, the voltage between the internal circuit and the frame is relatively high, which in turn causes electrical performance degradation and a sharp drop in power generation. By obtaining the saturated vapor pressure curve, wind speed curve, light intensity curve, and haze concentration curve of the area where the photovoltaic power station is located, this embodiment can obtain the actual power generation curve of the photovoltaic power station through the photovoltaic power generation model. This can improve the prediction accuracy of photovoltaic power generation, thereby improving the accuracy of power dispatch and improving the efficiency and quality of power dispatch. By comprehensively considering the effect of light intensity and haze on water vapor evaporation, data accuracy is further improved. At the same time, considering the impact of dry and wet environments on air moisture content, the accuracy of the actual power generation prediction data of the photovoltaic power station can be guaranteed to the greatest extent.

[0090] Example 2

[0091] like Figure 2 As shown, the blockchain-based power dispatching and command interaction system of this embodiment includes a blockchain module, a preparation module, an inspection module, an operation command module, an operation issuance module, a monitoring and control module, and a data acquisition and transmission module that are electrically connected in sequence.

[0092] In this embodiment, the blockchain module is used to collect and store real-time grid operating status information using blockchain technology. This grid operating status information includes equipment status and load conditions. Specifically, in this embodiment, the grid is connected to a photovoltaic power station. The grid operating status information includes the saturated vapor pressure curve, wind speed curve, light intensity curve, and haze concentration curve for the area where the photovoltaic power station is located.

[0093] In this embodiment, the preparation module is used to collect, organize, and analyze the grid operation status information from the blockchain module. In this embodiment, the preparation module includes a photovoltaic power generation model. The preparation module uses the photovoltaic power generation prediction method described in Example 1 to obtain the actual power generation curve of the photovoltaic power station.

[0094] In this embodiment, the review work module is used to review the work plan and conduct on-site verification of facilities that require power outages, while considering the impact on the power system including flow, stability, frequency and voltage, and taking corresponding measures.

[0095] In this embodiment, the operation command module is used to fill in the operation command ticket according to the work plan, and review it according to the mobilization plan, work content and safety measures requirements.

[0096] In this embodiment, the operation issuing module is used to notify relevant units to prepare before the operation and issue the operation command using mobilization terminology; the notice content issued by the operation issuing module is the same as the content of the operation ticket.

[0097] In this embodiment, the monitoring and control module is used to monitor and control the power system in real time. Specifically, the monitoring and control module is used to monitor the power grid operation status and power equipment status in real time, and remotely control the power system through control functions.

[0098] In this embodiment, the data acquisition and transmission module is used to collect data from various power equipment via telecontrol equipment and transmit the data back to a master station or data center. In this embodiment, the power equipment includes a photovoltaic power station. The data collected from the photovoltaic power station includes the saturated vapor pressure curve, wind speed curve, light intensity curve, and haze concentration curve for the area where the photovoltaic power station is located. The saturated vapor pressure curve, wind speed curve, light intensity curve, and haze concentration curve can be obtained by the meteorological department in the area where the photovoltaic power station is located, or they can be measured by sensor elements deployed in the area where the photovoltaic power station is located.

[0099] Example 3

[0100] The power dispatching and command interaction method based on blockchain in this embodiment includes the following steps:

[0101] Step 1: Before commencing power dispatch and command work, thorough preparation is required. This embodiment uses the preparatory work module to comprehensively collect grid operation status information from the blockchain; grid operation status information includes equipment status and load conditions. Specifically, in this embodiment, grid operation status information includes the saturated vapor pressure curve, wind speed curve, light intensity curve, and haze concentration curve for the region where the photovoltaic power station is located. The preparatory work module organizes and analyzes this grid operation status information and uses the photovoltaic power generation prediction method described in Example 1 to obtain the actual power generation curve of the photovoltaic power station.

[0102] Step 2: Before deciding on a power switching operation, review the work plan and conduct on-site verification of the facilities that require power outages. At the same time, consider the impact on the power system, including flow, stability, frequency, and voltage, and take countermeasures in advance.

[0103] Step 3: Fill out the operation order ticket according to the work plan, ensure that the purpose of the operation is clear, the content of the issued operation ticket is consistent with the planned work requirements, the operation numbers in the operation ticket are filled in in ascending order, and operations with the same number are carried out at the same time; the operation order tickets are subject to mutual review and are reviewed based on the mobilization plan, work content and safety measures.

[0104] Step 4: Issue a notice before the operation to inform relevant units to prepare. The content of the notice is the same as that of the operation ticket. When issuing operation orders using mobilization terms, issue them item by item according to the operation ticket. After receiving confirmation that the previous order has been completed, issue the next order.

[0105] Step 5: Real-time monitoring and control of the power system, providing real-time monitoring of the grid operation status and power equipment status, and remote control of the power system through control functions, such as adjusting the output of generators, switching lines, etc.

[0106] Step 6: Data is collected from various power equipment using telecontrol equipment and transmitted back to the master station or data center for processing and storage. In this embodiment, the power equipment includes a photovoltaic power station. The data collected from the photovoltaic power station includes the saturated vapor pressure curve, wind speed curve, light intensity curve, and haze concentration curve for the area where the photovoltaic power station is located. The saturated vapor pressure curve, wind speed curve, light intensity curve, and haze concentration curve can be obtained from the meteorological department in the area where the photovoltaic power station is located. Alternatively, they can be measured using sensors deployed in the area where the photovoltaic power station is located.

[0107] The above embodiments are merely preferred embodiments for the purpose of fully illustrating the present invention, and the scope of protection of the present invention is not limited thereto. Equivalent substitutions or modifications made by those skilled in the art based on the present invention are within the scope of protection of the present invention. The scope of protection of the present invention shall be subject to the claims.

Claims

1. A photovoltaic power generation prediction method, characterized by: The steps include: S1: Build a photovoltaic power generation model S11: Obtaining a baseline water vapor content Hs in the air based on the saturated vapor pressure and atmospheric pressure of the area where the photovoltaic power station is located; S12: Based on the obtained air water vapor baseline content Hs, obtain the air water vapor content Hs1 under the effect of wind dilution and the air water vapor content Hs4 under the effect of light evaporation and haze obstruction; S13: Obtain the actual air moisture content Hs0 in the area where the photovoltaic power station is located; S14: Calculate the photovoltaic power generation attenuation coefficient K based on the actual air moisture content Hs0; S15: Obtaining actual photovoltaic power generation according to the photovoltaic power generation attenuation coefficient K; S2: Predicting power generation: Obtain the saturated vapor pressure curve, wind force curve, light intensity curve, and haze concentration curve of the area where the photovoltaic power station is located, and use the photovoltaic power generation model to obtain the actual power generation curve of the photovoltaic power station.

2. The photovoltaic power generation prediction method according to claim 1, characterized in that: In step S11, the air water vapor baseline content Hs is: Where: Ps is the saturated vapor pressure; P is the atmospheric pressure.

3. The photovoltaic power generation prediction method according to claim 1, wherein: In step S12, the water vapor content Hs1 of the air under the effect of wind dilution is: Where: Q is the wind force; Q max is the maximum wind speed; The air water vapor content Hs4 considering both the evaporation effect of light and the obstruction effect of haze is: Hs4=Hs2-Hs3 Where: Hs2 is the air water vapor content under the effect of light evaporation; M is the light intensity; M max is the maximum light intensity; Hs3 is the air water vapor content under the effect of haze; G is the haze concentration; G max The maximum haze concentration.

4. The photovoltaic power generation prediction method according to claim 1, characterized in that: In step S13, the actual air moisture content Hs0 is: Hs0=Hs-Hs1-Hs4+Hs5-Hs6 Wherein: Hs5 is the increased air water vapor content in a wetland environment; Hs6 is the decreased air water vapor content in a dry environment; and: when the photovoltaic power station is located in a wetland environment, Hs6 = 0; when the photovoltaic power station is located in a dry environment, Hs5 = 0.

5. The photovoltaic power generation prediction method according to claim 1, characterized in that: In step S14, the photovoltaic power generation attenuation coefficient K is: Among them: Hs max is the maximum water vapor content in the air; K max It is the highest power generation attenuation coefficient.

6. The photovoltaic power generation prediction method according to claim 1, characterized in that: In step S15, the actual power generation of the photovoltaic power station is: Qs0=Qs(1-K) Among them: Qs0 is the actual power generation of the photovoltaic power station; Qs is the theoretical power generation obtained by the photovoltaic power station based on sunlight.

7. The photovoltaic power generation prediction method according to claim 1, characterized in that: In step S2, the photovoltaic power station power generation curve is: Qs0(t)=Qs(t)(1-K(t)) Where: Qs0(t) is the curve of the actual power generation of the photovoltaic power station changing with time t; Qs(t) is the curve of the theoretical power generation of the photovoltaic power station changing with time t; K(t) is the curve of the photovoltaic power generation attenuation coefficient changing with time t.

8. A blockchain-based power dispatching and command interactive system, characterized by: It includes a blockchain module, a preparation module, an inspection module, an operation command module, an operation issuing module, a monitoring and control module, and a data acquisition and transmission module that are electrically connected in sequence; The blockchain module is used to collect and store power grid operation status information in real time through blockchain technology; the power grid operation status information includes the saturated vapor pressure curve, wind speed curve, light intensity curve and haze concentration curve of the photovoltaic power station area; The preparation module is used to collect the grid operation status information in the blockchain module and organize and analyze the grid operation status information; the preparation module is provided with a photovoltaic power generation model, and uses the photovoltaic power generation prediction method according to any one of claims 1 to 7 to obtain the actual power generation curve of the photovoltaic power station; The review work module is used to review the work plan and conduct on-site verification of facilities that require power outages, while considering the impact on the power system and taking corresponding measures; The operation order module is used to fill in the operation order ticket according to the work plan and review it according to the mobilization plan, work content and safety measures requirements; The operation issuing module is used to notify relevant units to prepare before the operation and issue operation orders using mobilization terms; The content of the notice issued by the operation issuing module is the same as the content of the operation ticket; The monitoring and control module is used to monitor the power system in real time and to remotely control the power system; The data acquisition and transmission module is used to collect data from various power equipment through remote control equipment and transmit the data back to the main station or data center; the power equipment includes a photovoltaic power station, and the data collected from the photovoltaic power station includes a saturated vapor pressure curve, wind curve, light curve and haze concentration curve of the area where the photovoltaic power station is located.

9. A blockchain-based power dispatching and command interaction method, characterized by: The steps include: Step 1: Before carrying out power dispatch and command work, the preparatory work module comprehensively collects the power grid operation status information in the blockchain; the power grid operation status information includes the saturated vapor pressure curve, wind force curve, light intensity curve, and haze concentration curve of the area where the photovoltaic power station is located; the preparatory work module organizes and analyzes the power grid operation status information, and uses the photovoltaic power generation model set in the preparatory work module to obtain the actual power generation curve of the photovoltaic power station using the photovoltaic power generation prediction method according to any one of claims 1 to 7; Step 2: Before deciding on a power switching operation, review the work plan and conduct on-site verification of the facilities that require power outages. Consider the impact on the power system and take countermeasures in advance. Step 3: Fill out the operation order ticket according to the work plan, ensuring that the operation purpose is clear and the content of the operation order ticket is consistent with the planned work requirements. The operation numbers in the operation order ticket are filled in ascending order, and operations with the same number are carried out simultaneously. The operation order tickets are cross-examined and reviewed based on the mobilization plan, work content and safety measures. Step 4: Issue a notice before the operation to inform relevant units to prepare. The notice content is the same as the operation ticket content. When issuing operation orders using mobilization terms, issue them item by item according to the operation ticket. Once confirmation of the completion of the previous order is obtained, issue the next order. Step 5: Real-time monitoring and control of the power system, providing real-time monitoring of the grid operation status and power equipment status, and remote control of the power system through control functions; Step 6: Collect data from various power equipment through telecontrol equipment, transmit the data back to the main station or data center, and process and store the collected data; the power equipment includes photovoltaic power stations, and the data collected from the photovoltaic power stations include the saturated vapor pressure curve, wind curve, light curve and haze concentration curve of the area where the photovoltaic power station is located.

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