CN115965199A - Virtual power plant optimal scheduling method based on distributed energy - Google Patents

Abstract

The invention provides a virtual power plant optimal scheduling method based on distributed energy, which belongs to the technical field of power plant energy scheduling and comprises the steps of obtaining the electric quantity generated by each renewable energy power generation unit in a preset area within preset time and the electric quantity generated by a non-renewable energy power generation unit within preset time; acquiring the power consumption of each power consumption unit in the preset area within the preset time; establishing a virtual power plant optimization model, analyzing the generated electric quantity and the electricity consumption, and determining an average value of the generated electric quantity and an average value of the electricity consumption; constraining the average value established by the optimization model through the parameters of the virtual power plant; setting a numerical value formed after the power consumption is restrained on the optimization model, and adjusting the power supply quantity of the power consumption unit according to the average value of the power generated by the power generation unit; the distributed energy resource optimizing and dispatching system can optimize and dispatch distributed energy resources through a virtual power plant based on distributed renewable energy resources and non-renewable energy resources, meet the flexibility requirement of a power grid, and achieve the technical effect of reasonable management of the distributed energy resources.

Description

A Distributed Energy Based Virtual Power Plant Optimal Scheduling Method

technical field

The invention belongs to the technical field of power plant energy scheduling, and more specifically relates to a distributed energy-based virtual power plant optimal scheduling method.

Background technique

This year, many countries are exploring an energy development model that combines Internet technology with renewable energy technology, using the smart grid as the resource allocation center to build a multi-energy coupling system with horizontal multi-source complementarity and vertical source-grid-load-storage coordination. Under the emerging energy Internet architecture, the energy supply and demand system is a "source-network-load-storage" complex, and multiple energy sources such as electricity, heat, cold, and gas are coupled and interconnected from the demand side to the supply side.

In this context, distributed energy includes not only distributed power generation resources such as wind, light, and biomass, but also distribution-side and demand-side resources such as energy storage, electric vehicles, and controllable loads, as well as multiple energy coupling devices. As an effective means of aggregating distributed energy, virtual power plants can realize energy gathering, energy storage, energy supply and energy consumption without changing the grid connection mode and geographical location of individual resources by means of advanced communication, metering, control and other technologies , effectively connect distributed energy and power systems, and realize resource integration and distribution. The scale of distributed renewable energy and distributed non-renewable energy is large, and it also presents high complexity and uncertainty. In order to meet the flexibility requirements of the power grid, distributed energy needs to be managed reasonably and optimally dispatched. Therefore There is an urgent need to study an optimal scheduling method for virtual power plants based on distributed energy.

Contents of the invention

The purpose of the present invention is to provide a method for optimal scheduling of virtual power plants based on distributed energy, aiming to solve the technical problem that based on distributed renewable energy and non-renewable energy, virtual power plants are unfavorable to optimal scheduling of distributed energy.

In order to achieve the above purpose, the technical solution adopted by the present invention is to provide a distributed energy-based virtual power plant optimal scheduling method, including:

Obtain the electricity generated by each renewable energy generating unit within the preset area and the electricity generated by the non-renewable energy generating unit within the preset time;

Obtaining the power consumption of each power consumption unit in the preset area within the preset time;

Establish a virtual power plant optimization model, analyze the electricity generated by the renewable energy generation unit, the electricity generated by the non-renewable energy generation unit, and the electricity consumption of the power consumption unit, and establish the average value of the generated electricity and the average electricity consumption;

The average value established by the optimization model is constrained by the parameters of the virtual power plant;

The value formed after setting the power consumption constraint on the optimization model is used to adjust the power supply of the power consumption unit according to the average power generated by the power generation unit.

In a possible implementation manner, the virtual power plant includes a regulator, and the regulator can adjust the power supply to the power consumption unit within its preset range, so as to restrict the power consumption of the power consumption unit, so The regulator includes an input unit, a regulation model and an output unit, the input unit is used to input the average value of power consumption of the power consumption unit, the regulation model is used to constrain the average power consumption of the power consumption unit, and the output unit It is used to calculate the output constrained power consumption value, and the virtual power plant optimizes the power supply to the power consumption unit according to the constrained power consumption value.

In a possible implementation, the distributed energy-based virtual power plant optimization scheduling method also includes setting a first electricity collection module, and installing it on the power supply end of the renewable energy power generation unit and the power supply end of the non-renewable energy power generation unit, the The first power collection module is used to collect power generation. The virtual power plant establishes a power generation model of a renewable energy power generation unit and a power generation model of a non-renewable energy power generation unit according to the obtained power generation, and optimizes the two models.

In a possible implementation, the distributed energy-based virtual power plant optimal scheduling method also includes setting a second power collection module and installing it on the power supply end of the power unit, and the second power collection module is used for collection. The power consumption of the power unit, the virtual power plant establishes the power consumption model of the power unit according to the obtained power consumption, and optimizes the model.

In a possible implementation manner, the first electricity collection module is wirelessly connected to a power generation monitor, and the power generation monitor is detachably connected to a drone, and the drone carries the power generation monitor to monitor the power generation The power supply end of the unit is monitored, and the drone is connected with a camera, which is used to collect image information of the power supply end and transmit the information to the power generation monitor.

In a possible implementation manner, the power generation monitor is connected to a mobile terminal through wireless communication, and the mobile terminal is used to synchronously display the information collected and received by the power generation monitor, and the mobile terminal and the UAV The wireless remote communication is connected and used to control the flight of the drone, and the mobile terminal has a control module suitable for controlling the operation of the drone.

In a possible implementation manner, the power supply terminals of the plurality of power consumption units are electrically connected to a transmission line, and the transmission line is connected to a leakage detector, and the leakage detector is used to detect the leakage of the transmission line, The leakage detector has an alarm, and the alarm sends out an alarm signal when the transmission line leaks, and the leakage detector sends a leakage signal to the virtual power plant, and the virtual power plant controls power supply to the power consumption unit according to the leakage signal.

In a possible implementation, the distributed energy-based virtual power plant optimal scheduling method also includes a cost controller for measuring the power generation cost of the non-renewable energy generating unit, a cost controller for measuring the total power generation output of the non-renewable energy generating unit The total price controller of the price, the virtual power plant establishes an input-output model according to the cost of power generation and the total price of power generation, and regulates to make the cost of power generation less than the total price of power generation, and the total price of power generation is less than the total cost of electricity consumption of multiple power-consuming units.

In a possible implementation, the distributed energy-based virtual power plant optimization scheduling method also includes setting a mobile image acquisition machine for image acquisition of the transmission line appearance quality information, the mobile image acquisition machine includes a mobile car body, an electric control cabinet connected to the upper end of the mobile car body, and an image collector, a machine vision detection device is installed inside the electric control cabinet, and the image collector is used to collect appearance images toward the power transmission line and transmit image information For the machine vision detection device, the machine vision detection device has built-in machine vision detection software, and can obtain the transmission line quality detection result according to the comparison and analysis of the collected images.

In a possible implementation, the distributed energy-based virtual power plant optimal scheduling method also includes setting a controller, which is electrically connected to the power supply end of each power consumption unit and used to control the power supply end to turn on or off, when the power generation cost When it is greater than the total power generation price, or when the total power generation price is greater than the total power consumption cost of the multiple power consumption units, the controller cuts off the power supply to the multiple power consumption units.

The beneficial effect of the distributed energy-based virtual power plant optimal dispatching method provided by the present invention is that compared with the prior art, the distributed energy-based virtual power plant optimal dispatching method of the present invention includes: obtaining each The electricity generated by each renewable energy generating unit within the preset time and the electricity generated by the non-renewable energy generating unit within the preset time; obtain the electricity consumption of each power consumption unit in the preset area within the preset time Quantity; establish a virtual power plant optimization model, analyze the electricity generated by the renewable energy generation unit, the electricity generated by the non-renewable energy generation unit, and the electricity consumption of the power consumption unit, and establish the average value of the generated electricity and the average electricity consumption; through The parameters of the virtual power plant constrain the average value established by the optimization model; the value formed after setting the power consumption constraint on the optimization model is used to adjust the power supply of the power consumption unit according to the average power generated by the power generation unit; it can be based on distributed Renewable energy and non-renewable energy, through the virtual power plant to optimize the dispatch of distributed energy, respond to the flexibility needs of the power grid, and achieve the technical effect of reasonable management of distributed energy.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings that need to be used in the descriptions of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only of the present invention. For some embodiments, those of ordinary skill in the art can also obtain other drawings based on these drawings without any creative effort.

Fig. 1 is a control block diagram of a distributed energy-based virtual power plant optimal dispatching method provided by an embodiment of the present invention;

Fig. 2 is a controller control block diagram of a distributed energy-based virtual power plant optimal scheduling method provided by an embodiment of the present invention;

Fig. 3 is a control block diagram of a power generation unit of a distributed energy-based virtual power plant optimal dispatching method provided by an embodiment of the present invention;

Fig. 4 is a control block diagram of a power consumption unit of a distributed energy-based virtual power plant optimal dispatching method provided by an embodiment of the present invention;

Fig. 5 is a control block diagram of a mobile image acquisition machine of a distributed energy-based virtual power plant optimal scheduling method provided by an embodiment of the present invention.

Detailed ways

In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

Please refer to FIG. 1 to FIG. 5 together. Now, a distributed energy-based virtual power plant optimal scheduling method provided by the present invention will be described. The distributed energy-based virtual power plant optimal scheduling method includes: obtaining the electricity generated by each renewable energy generating unit within a preset time and the electricity generated by a non-renewable energy generating unit within a preset time in a preset area ;Obtain the power consumption of each power consumption unit in the preset area within a preset time; establish a virtual power plant optimization model, and analyze the power generated by renewable energy power generation units, the power generated by non-renewable energy power generation units, and the power consumption of power consumption units The average value of electricity generated and the average value of electricity consumption are established; the average value established by the optimization model is constrained by the parameters of the virtual power plant; the value formed after setting the electricity consumption constraint on the optimization model, according to the power generation The average value of power generated by the unit is used to adjust the power supply of the power consumption unit.

The present invention provides an optimal dispatching method for a virtual power plant based on distributed energy. Compared with the prior art, the present invention provides an optimal dispatching method for a virtual power plant based on distributed energy. The electricity generated by the unit within the preset time and the electricity generated by the non-renewable energy generating unit within the preset time; obtain the electricity consumption of each power consumption unit in the preset area within the preset time; establish a virtual power plant optimization model, Analyze the electricity generated by the renewable energy generation unit, the electricity generated by the non-renewable energy generation unit, and the electricity consumption of the power consumption unit, and establish the average value of the generated electricity and the average electricity consumption; establish the optimization model through the parameters of the virtual power plant Constrain the average value of the power consumption; the value formed after setting the power consumption constraint on the optimization model is used to adjust the power supply of the power consumption unit according to the average power generated by the power generation unit; it can be based on distributed renewable energy and non-renewable energy, through The virtual power plant optimizes the dispatch of distributed energy, responds to the flexibility requirements of the power grid, and realizes the technical effect of reasonable management of distributed energy.

The preset area referred to in this embodiment refers to the area where distributed energy needs to be optimally dispatched to the area. It can be understood that if the virtual power plant in this area needs to be optimally dispatched, then the area is designated as the preset area. The area, that is, the area can be pre-set, and the distributed energy is optimized and dispatched for this area. In practical applications, the preset area can be an area or a geographical area, in which the power generation of renewable energy generation units and non-renewable energy generation units and the power consumption of power consumption units are optimized and regulated to achieve The distributed energy virtual power plant optimizes scheduling to realize the rational distribution and efficient utilization of energy. The virtual power plant optimization model is a model based on power generation and power consumption. This model can be a functional relationship or a formula, etc., and can analyze the peak value and ground peak value of the generated power, and the peak value and low value of power consumption. peak etc. The model is also able to calculate the average value of the electricity produced by the output and the average value of the electricity used.

The renewable energy power generation units in this application refer to units or enterprises or institutions that generate power based on renewable energy resources, such as units that rely on wind, light, biomass, etc. to generate power, such as wind power plants, solar power plants, etc. Non-renewable energy power generation units refer to units or enterprises or institutions that generate power based on non-renewable energy resources, such as units that rely on coal and other resources to generate power, such as typical thermal power plants.

The power consumption unit in this area refers to the units or users or enterprises that need to use electric energy. Because it is based on the preset area, preferably the electric energy generated by these power generating units is supplied to multiple power consumption units. The virtual power plant optimization model is a model established based on the analysis of power generation and power consumption. It can be understood as an optimization formula or equation, which can analyze the power generation and power consumption and obtain the average value. After obtaining the average value of power generation and power consumption, the average value is then constrained. The parameters of the virtual power plant can use the parameters in the existing technology, and the average value is constrained by this parameter, that is, the average value is usually lowered by one level, the power consumption of the electric unit is less than the average value, and the virtual power plant generates electricity through the power generation unit The average value adjusts the power supply of the power consumption unit. If the power generation of the power generation unit is small, the power supply to the power consumption unit is adjusted through the virtual power plant. The technical effect of rationally allocating power supply, ensuring the reasonable power consumption of power consumption units, and optimizing dispatching of virtual power plants.

In some embodiments, please refer to FIG. 1 to FIG. 5 , the virtual power plant includes a regulator, and the regulator can adjust the power supply to the power consumption unit within its preset range, so as to constrain the power consumption of the power consumption unit, The controller includes an input unit, a regulation model and an output unit. The input unit is used to input the average power consumption of the power consumption unit, the regulation model is used to constrain the average power consumption of the power consumption unit, and the output unit is used to calculate the output constraint. The power consumption value, the virtual power plant optimizes the power supply to the power consumption unit according to the constrained power consumption value.

The power supply to the power consumption unit can be adjusted through the regulator. When the production capacity (the power generated by the power generation unit) is small, the optimally regulated power supply should also be small. In short, through the optimal scheduling and reasonable distribution of power of the virtual power plant, It realizes the reasonable power consumption of the power consumption unit without affecting the normal operation of the load of the power consumption unit.

Specifically, the controller is like a regulator or a calculator, which can calculate the output power consumption value according to the input power consumption average value of the power consumption unit. Usually, the power consumption value is smaller than the power consumption average value. It can ensure the normal and reasonable power consumption of the power consumption unit and avoid the phenomenon of overload operation. The control model is a formula or an equation, and the output power supply to be supplied to the power consumption unit can be calculated through the input quantity.

In some embodiments, referring to Fig. 1 to Fig. 5, the distributed energy-based virtual power plant optimal dispatching method also includes setting a first power collection module, which is installed on the power supply end of the renewable energy power generation unit and the non-renewable energy power generation unit At the power supply end, the first electricity collection module is used to collect power generation, and the virtual power plant establishes a power generation model of a renewable energy power generation unit and a power generation model of a non-renewable energy power generation unit according to the obtained power generation, and optimizes the two models.

In some embodiments, please refer to FIG. 1 to FIG. 5 , the distributed energy-based virtual power plant optimal dispatching method also includes setting a second power collection module, installing it on the power supply end of the power unit, and using the second power collection module To collect the power consumption of the power consumption unit, the virtual power plant establishes the power consumption model of the power consumption unit according to the acquired power consumption, and optimizes the model. The above-mentioned first power acquisition module and second power acquisition module both use the power collector in the prior art, which can collect power parameters such as power, voltage and current, and install them on the power supply end to collect the corresponding power information. Through the virtual power plant, the collected power information can be optimized and dispatched, so as to facilitate the reasonable power consumption of the power consumption unit and the reasonable power supply of the power generation unit.

Specifically, the power supply terminal of the power consumption unit refers to the supply terminal of electric energy used by multiple users, that is, the power supply terminal can supply power to the power consumption unit. The power supply end of the power generation unit refers to the output end of the generated electric energy, that is, the electric energy is provided to the user through the output end.

In some embodiments, please refer to FIG. 1 to FIG. 5 , the first power collection module is connected to a power generation monitor through wireless communication, and the power generation monitor is detachably connected to a drone, and the drone carries the power generation monitor to supply power to the power generation unit The UAV is connected to a camera, and the camera is used to collect image information of the power supply end and transmit the information to the power generation monitor. The UAV can fly to any location, so as to monitor the power supply end with a power generation monitor, and judge whether the power supply end is in a reasonable and normal power supply state. Monitoring can be done towards the opposite side, or towards other directions or positions. The camera can be installed on the UAV in the later stage. It can take and collect photos or images, which can be transmitted to the power generation monitor. The power generation monitor has a memory that can store a large number of images or photos or video information. Control its running direction or position, etc.

In some embodiments, please refer to FIG. 1 to FIG. 5 , the power generation monitor is connected with a mobile terminal through wireless communication, and the mobile terminal is used to synchronously display the information collected and received by the power generation monitor, and the mobile terminal is connected with the drone through wireless remote communication and used To control the flight of the UAV, the mobile terminal has a control module suitable for controlling the operation of the UAV. The flight of the UAV is controlled by the mobile terminal, and there is a display screen on the mobile terminal to view the information of the power supply end of each power generation unit, so as to provide a reference for judging whether the power supply end is operating normally. Through the control module, wireless communication with the UAV can be realized, and its operation can be reasonably controlled. The mobile terminal is similar to a remote control that can be held in hand, and the operation of the drone can be controlled through the remote control.

In some embodiments, please refer to FIG. 1 to FIG. 5 , the power supply terminals of multiple power consumption units are electrically connected to the transmission line, and the transmission line is connected with a leakage detector. The leakage detector is used to detect the leakage of the transmission line. The leakage detector An alarm is provided. When the transmission line leaks, the alarm sends out an alarm signal. The leakage detector sends the leakage signal to the virtual power plant, and the virtual power plant controls the power supply to the power consumption unit according to the leakage signal. The leakage detector used in this embodiment can collect the power information or parameters of the transmission line in real time online, so as to provide reference for whether the virtual power plant supplies power to the power consumption unit. If leakage occurs on the transmission line, the leakage information will be sent to the virtual The power plant sends out an alarm signal at the same time, and the virtual power plant cuts off the power supply to one or more of the power consumption units, realizing the technical effect that the leakage can cut off the power supply in time to prevent excessive leakage.

In order to be able to increase the power supply to power consumption units while controlling the cost of power generation, in some embodiments, please refer to Figures 1 to 5, the optimal scheduling method for virtual power plants based on distributed energy The cost controller of the power generation cost of the energy generation unit, the total price controller used to measure the total price of the power generation output of the non-renewable energy power generation unit, the virtual power plant establishes an input-output model according to the power generation cost and the total power generation The cost is less than the total price of power generation, and the total price of power generation is less than the total power consumption cost of multiple power consumption units. First of all, it is necessary to analyze according to the cost of power generation and the total price of power generation, so that the total price of power generation (electricity price multiplied by the amount of power generated) is less than the total cost of electricity consumption of the power consumption unit, so that the power generation unit can be in a profitable state, and at the same time It can supply normal and reasonable power to the power consumption unit.

Specifically, the total cost of electricity consumption is the sum of the costs generated by the electricity used by multiple power consumption units. If the sum of the costs of the power consumption units is greater than the total price of power generation, it means that the normal power generation of the power generation unit is in a profitable state.

The cost controller can store the cost required for metered power generation, and the total price controller can store the total price or output value created by the output of metered power generation. The input-output model can be established through the cost and the total price, and a reasonable judgment can be made on whether to supply power to the power-consuming unit based on the model (that is, when the power-consuming unit is in an unprofitable state, the power supply to the power-consuming unit is cut off).

In some embodiments, referring to Fig. 1 to Fig. 5, the distributed energy-based virtual power plant optimal scheduling method also includes setting a mobile image acquisition machine, which is used for image acquisition of the transmission line appearance quality information, the mobile image acquisition The machine includes a mobile car body, an electric control cabinet connected to the upper end of the mobile car body, and an image collector. A machine vision detection device is installed inside the electric control cabinet. The image collector is used to collect appearance images toward the transmission line and transmit the image information to the machine vision Inspection device, machine vision inspection device has built-in machine vision inspection software, and can obtain the quality inspection results of transmission lines according to the comparison and analysis of the collected images. The mobile car body can move along the extension direction of the power transmission line, so as to provide support for the operation of the image collector, so that it can operate safely and normally. In addition, the mobile car body has a driver, which can drive the mobile car body to move, and the driver It is connected to the mobile terminal through wireless communication. By controlling the driver on the mobile terminal, the moving distance of the moving car body can be controlled, so that the image collector can move and collect along the transmission line, and stop when it needs to stop. Collect at a certain location. The electric control cabinet has built-in power supply, etc., which can provide electric energy for the driver.

Specifically, the image collector is an industrial CCD camera, which can accurately and clearly collect the image information of the appearance quality of the transmission line, so that it can be compared and analyzed with the machine vision inspection software to determine whether the part of the transmission line is damaged or incomplete, etc. Phenomenon, so that the construction personnel can carry out maintenance and other operations in the later stage.

In some embodiments, please refer to FIG. 1 to FIG. 5 , the distributed energy-based virtual power plant optimal dispatching method further includes setting a controller, which is electrically connected to the power supply end of each power consumption unit and used to control the power supply end to turn on or Closed, when the cost of power generation is greater than the total price of power generation, or the total price of power generation is greater than the total cost of electricity consumption of multiple power consumption units, the controller cuts off the power supply to multiple power consumption units. The controller can control the power on and off of the power supply end, and when there is leakage or other emergencies, the power supply to the power supply end of the power consumption unit can be cut off through the controller.

Specifically, the controller is connected with the mobile terminal through wireless communication, and the control of the controller can be realized through manipulation on the mobile terminal, so as to realize wireless remote control on and off of power supply to the power consumption unit. The controller can adopt switches in the prior art, etc., and can realize the on-off control of electric energy.

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present invention should be included in the protection of the present invention. within range.

Claims (10)

1. A virtual power plant optimal scheduling method based on distributed energy is characterized by comprising the following steps:

acquiring the electric quantity generated by each renewable energy power generation unit in a preset area within a preset time and the electric quantity generated by each non-renewable energy power generation unit within the preset time; acquiring the power consumption of each power consumption unit in the preset area within the preset time;

establishing a virtual power plant optimization model, analyzing the electric quantity generated by the renewable energy power generation unit, the electric quantity generated by the non-renewable energy power generation unit and the electricity consumption of the electricity consumption unit, and determining an average value of the generated electric quantity and an average value of the electricity consumption; constraining the average value established by the optimization model through the parameters of the virtual power plant; and setting a numerical value formed after the restriction of the electricity consumption on the optimization model, and adjusting the electricity supply quantity of the electricity consumption unit according to the average value of the electricity quantity generated by the electricity generation unit.

2. The method as claimed in claim 1, wherein the virtual power plant comprises a controller, the controller can adjust the power supply amount to the power consumption units within a preset range of the controller to constrain the power consumption of the power consumption units, the controller comprises an input unit, a control model and an output unit, the input unit is used for inputting the average value of the power consumption units, the control model is used for constraining the average value of the power consumption units, the output unit is used for calculating the power consumption value after constraint, and the virtual power plant optimizes the power supply amount to the power consumption units according to the constrained power consumption value.

3. The method according to claim 1, wherein the method further comprises a first electric quantity acquisition module, which is installed at a power supply end of the renewable energy power generation unit and a power supply end of the non-renewable energy power generation unit, and is used for acquiring electric energy, and the virtual power plant establishes an electric energy generation model of the renewable energy power generation unit and an electric energy generation model of the non-renewable energy power generation unit according to the acquired electric energy, and optimizes the two models.

4. The method as claimed in claim 1, wherein the method further comprises setting a second power collection module to be installed at a power supply end of the power consumption unit, the second power collection module being used for collecting power consumption of the power consumption unit, and the virtual power plant building a power consumption model of the power consumption unit according to the obtained power consumption and optimizing the model.

5. The distributed energy resource-based virtual power plant optimized scheduling method according to claim 3, wherein the first electricity quantity collection module is wirelessly connected with a power generation monitor, the power generation monitor is detachably connected with an unmanned aerial vehicle, the unmanned aerial vehicle carries the power generation monitor to monitor the power supply terminals of the power generation units, and the unmanned aerial vehicle is connected with a camera for collecting image information of the power supply terminals and transmitting the information to the power generation monitor.

6. The distributed energy resource-based virtual power plant optimal scheduling method according to claim 5, wherein the power generation monitor is wirelessly and communicatively connected with a mobile terminal, the mobile terminal is used for synchronously displaying the information collected and received by the power generation monitor, the mobile terminal is wirelessly and remotely communicatively connected with the unmanned aerial vehicle and is used for controlling the unmanned aerial vehicle to fly, and the mobile terminal is provided with a control module adapted to control the unmanned aerial vehicle to operate.

7. The distributed energy based virtual power plant optimized scheduling method of claim 1, wherein power supply terminals of the plurality of power utilization units are electrically connected with a power transmission line, the power transmission line is connected with a leakage detector, the leakage detector is used for detecting leakage of the power transmission line, the leakage detector is provided with an alarm, when the power transmission line leaks electricity, the alarm sends an alarm signal, the leakage detector delivers a leakage signal to the virtual power plant, and the virtual power plant controls power supply to the power utilization units according to the leakage signal.

8. The method as claimed in claim 1, wherein the method further includes a cost controller for measuring the generating cost of the non-renewable energy generating unit, and a total price controller for measuring the total price of the generating output of the non-renewable energy generating unit, the virtual power plant establishes an input-output model according to the generating cost and the total price of the generating output, and regulates and controls the generating cost to be less than the total price of the generating output, and the total price of the generating output is less than the total cost of the generating output.

9. The method as claimed in claim 7, wherein the method further comprises setting a mobile image collector for collecting images of the appearance quality information of the power transmission line, the mobile image collector comprises a mobile vehicle body, an electric control cabinet connected to the upper end of the mobile vehicle body, and an image collector, the electric control cabinet is internally provided with a machine vision detection device for collecting appearance images towards the power transmission line and transmitting the image information to the machine vision detection device, the machine vision detection device is internally provided with machine vision detection software, and the machine vision detection software can analyze the images according to the ratio of the collected images to obtain the quality detection result of the power transmission line.

10. The method as claimed in claim 8, wherein the method further comprises setting a controller, electrically connected to the power supply terminal of each power consumption unit, for controlling the power supply terminal to be turned on or off, and when the power generation cost is greater than the total power generation cost or the total power generation cost is greater than the total power consumption cost of the plurality of power consumption units, the controller cuts off power supply to the plurality of power consumption units.

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