CN114421803A

CN114421803A - Self-adaptive micro-grid control method and device with stable self-generating energy supply

Info

Publication number: CN114421803A
Application number: CN202111550470.1A
Authority: CN
Inventors: 赖大坤; 茶兴增
Original assignee: University of Electronic Science and Technology of China
Current assignee: University of Electronic Science and Technology of China
Priority date: 2021-12-17
Filing date: 2021-12-17
Publication date: 2022-04-29

Abstract

The invention relates to a self-adaptive micro-grid control method and device with stable self-generating energy supply. The device is by nanometer textile printing technique, with adaptive control module 1, from the weaving printing of power generation module 2 and energy storage module 3 on ordinary fabric, adaptive control module includes microprocessor 4, voltage detector 5, current detector 6, digital analog converter 7, memory 8, wireless bluetooth 9, boost circuit 10 and voltage stabilizing circuit 11, from power generation module including nanometer friction power generation district 12, solar energy power generation district 13, body temperature thermoelectric power generation district 14 and biofuel power generation district 15, energy storage module comprises super capacitor array 16 and coulometric detector 17. And a real-time adaptive algorithm and a long-time neural network model form an adaptive micro-grid control algorithm to realize adaptive micro-grid control. The self-adaptive micro-grid technology effectively utilizes multiple self-generating modes and the self-adaptive micro-grid technology to realize self-adaptive self-generation of multiple modules and multiple biological energies, the generated electric energy can be used for detecting human vital signs, the evaluation of the human vital signs is realized through the intelligent cloud and the mobile terminal, and the self-adaptive micro-grid technology has the functions of automatic diagnosis and treatment and auxiliary treatment.

Description

Self-adaptive micro-grid control method and device with stable self-generating energy supply

Technical Field

The invention belongs to the technical field of wearable electronics, and particularly relates to a self-adaptive micro-grid control method and device with stable self-generating energy supply.

Background

The self-generating technology is a novel power generating technology, and various energies in the surrounding environment are converted into electric energy so as to drive low-power-consumption electronic equipment to operate. Currently, common self-generating technologies include friction generators, solar power generation, body temperature thermoelectricity, and biofuel cells. Meanwhile, the nano textile printing technology, the micro-grid technology and the energy storage technology are combined, and multiple self-generating modes are optimized and controlled.

The micro-grid energy control system is a set of energy control system with the functions of optimal power generation scheduling, load management, real-time monitoring, automatic micro-grid energy management and the like. The energy control system is mainly used for providing monitoring and control functions for a micro-grid system comprising distributed power supplies and energy storage units such as friction power generation, solar power generation, body temperature thermoelectricity and biological fuel cells. The intelligent microgrid energy management system is designed based on a cloud platform, and intelligent microgrid energy control is achieved through energy management.

At present, the reported wearable self-generating device has the following problems: 1) the power generation mode is single, only the energy of the single form on the body surface of the human body is utilized, various energies are not utilized, and the energy utilization rate is not high; 2) the power generation value is low, the power capacity is small, and the power generation device can only be applied to the power supply of load equipment with lower power consumption and cannot continuously supply power to equipment with higher power consumption.

At present, the reported microgrid technology has the following problems: 1) the research field of the existing microgrid control method is limited to the control between the traditional alternating current main grid and the distributed grid, such as a 'distributed adaptive control method of an alternating current microgrid under non-ideal communication' with the patent number of CN 113708419A, a 'microgrid optimization scheduling method based on a particle swarm optimization algorithm' with the patent number of CN 108695903B, an 'island microgrid adaptive synchronous frequency control method based on a consistency strategy' with the patent number of CN 109066765B and a 'microgrid optimization scheduling method based on an improved bat algorithm' with the patent number of CN 113488990A, which aim at the adaptive energy control between the traditional alternating current main grid and the distributed grid, but are not the adaptive energy control of the wearable microgrid applied to a human body; 2) the existing micro-grid control method cannot detect human body states such as human body motion states, human body environment and human body external temperature at the same time.

Disclosure of Invention

The invention provides a self-adaptive microgrid control method and device with stable self-generating energy supply, aiming at the problems of the existing wearable self-generating device and microgrid technology, the device adopts a nano textile printing technology to print a self-adaptive control module, a self-generating module and an energy storage module on a common fabric in a textile manner, the self-adaptive control module comprises a microprocessor, a voltage detector, a current detector, a transformer, a voltage stabilizer, a digital-to-analog converter, a memory and wireless Bluetooth, the self-generating module comprises a nano friction power generation area, a solar power generation area, a body temperature power generation area and a biofuel power generation area, and the energy storage module comprises an electric quantity detector and a super capacitor array.

The invention provides a self-adaptive microgrid control method and device with stable self-generating energy supply aiming at the problems of the existing wearable self-generating device and microgrid technology, wherein the method is a self-adaptive microgrid control method, an adaptive control module monitors output voltage and current of 4 self-generating areas, an analog signal is converted into a digital signal through a digital-to-analog converter, a self-generating area working state matrix is formed, and the working state of each generating area is determined; calculating a human body state matrix according to the working state of each self-generating area, and determining the human body state; meanwhile, the self-adaptive control module monitors the electric quantity of the super capacitor array of the energy storage module to form a super capacitor electric quantity matrix; the three matrix data are stored by the data storage device, the data are transmitted to the mobile terminal through the wireless Bluetooth, the mobile terminal transmits the data to the server to form long-term data, the mobile terminal analyzes the data to form a real-time adaptive algorithm, the server analyzes the long-term data to form long-term neural network model prediction, the long-term data and the long-term neural network model prediction form an adaptive micro-grid control algorithm, and the adaptive micro-grid control algorithm reminds people to change the human body state, so that the working state of each self-generating area is changed, and the adaptive micro-grid control is realized.

The self-generating module comprises a nanometer friction generating area, a solar generating area, a body temperature thermoelectric generating area and a human body biofuel generating area. The nanometer friction power generation area is arranged at the position of the left arm and the right arm close to the armpit, consists of a negative propeller based on polytetrafluoroethylene and a positive stator based on ethyl cellulose-polyurethane, and obtains energy through sliding motion. The solar power generation region is arranged on the back of the left shoulder and the back of the right shoulder and consists of an N-type layer, a PN junction and a P-type layer. The body temperature thermoelectric generation area is arranged at the lower part of the chest clavicle and consists of P-type thermoelectric crystal grains and N-type thermoelectric crystal grains which are assembled on the flexible polyimide substrate, and energy is provided through the body temperature thermoelectric effect. The human body biofuel power generation area is arranged in the middle of the chest, and biochemical energy is continuously collected from human body surface secretions through enzymatic reaction by biological enzyme based on carbon nano tubes. The energy storage module consists of a super capacitor, is arranged in the middle of the chest and is formed by silk-screen printing of a carbon nano tube and polystyrene sulfate mixed capacitor and is used for storing energy. The self-adaptive control module is composed of a silicon-based micro printed circuit, is arranged in the middle of the chest and is used for self-adaptively reminding a human body to change the state of the human body so as to change the working state of each power generation area and realize self-adaptive micro-grid control.

Drawings

Fig. 1 is a schematic diagram of an adaptive microgrid control device with stable self-generating energy supply according to the present invention.

Fig. 2 is a schematic diagram of a control method of an adaptive microgrid with stable self-generating energy supply according to the present invention.

Fig. 3 is a flow chart of the real-time adaptive algorithm proposed by the present invention.

Fig. 4 is a long-term neural network hierarchy diagram according to the present invention.

Fig. 5 is a schematic structural diagram of a nano-friction power generation region according to the present invention.

Fig. 6 is a schematic structural diagram of a solar power generation region according to the present invention.

Fig. 7 is a schematic structural view of a human body temperature thermoelectric generation region according to the present invention.

FIG. 8 is a schematic structural diagram of a human body biofuel generation area provided by the present invention.

Fig. 9 is a schematic structural diagram of a super capacitor according to the present invention.

Fig. 10 shows an embodiment of the present invention, which is implemented on a flexible textile garment by a nano textile printing technology.

Detailed Description

The invention relates to a self-adaptive micro-grid control method and a device with stable self-generating energy supply, as shown in figure 1, the device adopts a nano textile printing technology to print a self-adaptive control module 1, a self-generating module 2 and an energy storage module 3 on a common fabric in a textile manner, the self-adaptive control module comprises a microprocessor 4, a voltage detector 5, a current detector 6, a digital-to-analog converter 7, a memory 8, a wireless Bluetooth 9, a booster circuit 10 and a voltage stabilizing circuit 11, the self-generating module comprises a nano friction power generation area 12, a solar power generation area 13, a body temperature thermoelectric power generation area 14 and a biofuel power generation area 15, and the energy storage module comprises a super capacitor array 16 and an electric quantity detector 17.

The invention relates to a self-adaptive microgrid control method and a device with stable self-generating energy supply, the method is a self-adaptive microgrid control method, the self-adaptive control module monitors the electric quantity of a super capacitor of an energy storage module and the output voltage and current of 4 self-generating areas, the working state and the human body state of each generating area are determined, data are formed through a digital-to-analog converter and stored, the data are transmitted to a mobile terminal and a server through wireless Bluetooth, the data are analyzed by the mobile terminal to form a real-time self-adaptive algorithm, the data are analyzed by the server to form long-time neural network model prediction, the self-adaptive microgrid control algorithm and the mobile terminal form a self-adaptive microgrid control algorithm, the human body state is changed through the algorithm, and self-adaptive microgrid control is realized. As shown in fig. 2, a block diagram is implemented for the method, a specific embodiment of the method:

step 1: the monitoring parameters include 4 spontaneous power generation regions and a super capacitor array, as shown in 18 in fig. 2, wherein a nanometer friction power generation region is marked as a spontaneous power generation region a, a solar power generation region is marked as a spontaneous power generation region B, a body temperature thermoelectric power generation region is marked as a spontaneous power generation region C, and a biofuel power generation region is marked as a spontaneous power generation region D.

Step 2: the output voltage and current of the 4 self-generating regions A, B, C, D are monitored by the voltage detector and current detector of 19 in fig. 2, and the charge of the super capacitor array is monitored by the charge detector.

And step 3: from the output voltages and currents of the 4 self-power-generation regions A, B, C, D, the self-power-generation-region operating state matrix of 20 in fig. 2 is formed; the theoretical working state of each power generation area is divided into 1 (in working state) and 0 (in non-working state), so that the following working state matrix can be obtained:

(1111)	(1011)	(0111)	(0011)
				(1110)	(1010)	(0110)	(0010)
(1101)	(1001)	(0101)	(0001)
				(1100)	(1000)	(0100)	(0000)

wherein, the internal ordering mode of each element is (ABCD). Since the body temperature thermoelectric is generally in an operating state in practical conditions, two

rows

3 and 4 in the table above generally do not exist, and if and only if the body temperature thermoelectric generation area is damaged, the body temperature thermoelectric generation area is damaged. In addition, when the nanometer friction power generation area works, the biofuel power generation area inevitably works, so the second row in the above table does not exist generally unless the special human body has almost no body surface secretion during the movement process. Therefore, the operating state of the self-generating region is usually the 1 st row in the table above, and there are 4 operating states as follows:

(1111)

(1011)

(0111)

(0011)

the human body state matrix as shown in fig. 2 can be obtained from the working state matrix of the self-generating region, that is, when the first number of elements of the working state matrix of the self-generating region is "1", it represents that the nano friction generating region is in a working state, at this time, the human body motion state is "dynamic", otherwise, it is "static"; when the second number of the matrix elements of the working state of the self-generating area is '1', the solar generating area is in the working state, the environment where the human body is located is 'strong illumination', and the environment where the human body is located is 'weak illumination' otherwise; as described above, the third number of the elements of the working state matrix of the self-generating area is generally "1", which represents that the body temperature thermoelectric generating area is in a working state, and at this time, the external temperature of the human body can be calculated by the output voltage and current of the area, otherwise, the area fails; when the fourth number of the matrix elements of the working state of the self-generating area is '1', the matrix elements represent that the biofuel generating area is in the working state, the motion state of the human body is 'dynamic', the secretion amount of the secretion on the surface of the human body can be calculated by the output voltage and current of the area, and the secretion amount is 'static' otherwise. The following human state matrix is then obtained:

wherein, the internal ordering mode of each element is (ABCD), the first number is '1' to indicate that the human motion state is 'dynamic', otherwise, the human motion state is 'static'; the second number is '1' which indicates that the environment of the human body is 'strong illumination', and conversely 'weak illumination'; alpha is alpha_iAnd beta_i(i-1, 2,3,4) respectively represents the external temperature of the human body and the secretion amount of the secretion on the surface of the human body.

From the charge detector, the super capacitor charge matrix 20 in fig. 2 can be obtained as follows:

wherein the content of the first and second substances,

taking "1" to represent that the super capacitor electric quantity is higher than the critical residual electric quantity, and taking "0" to represent that the super capacitor electric quantity is lower than the critical residual electric quantity. Taking a 1 × 5 super capacitor array as an example, a possible super capacitor electric quantity array is as follows:

1

0

1

0

and 4, step 4: the three matrixes are stored in a data memory 21 in fig. 2, the data are uploaded to a mobile terminal 22 in fig. 2 through wireless transceiving Bluetooth 21 in fig. 2, and the mobile terminal uploads the data to a server to form long-term data;

and 5: the mobile terminal quickly analyzes the data to form a real-time adaptive algorithm of 23 in fig. 2, and the server forms a long-time neural network of 23 in fig. 2 by training the long-time data. The real-time adaptive algorithm is given by a flow chart shown in fig. 3, and the specific flow is as follows:

scheme 1: loading a self-generating area working state matrix, a human body state matrix and a super capacitor electric quantity matrix;

and (2) a flow scheme: judging whether the electric quantity of the super capacitor is lower than the critical electric quantity, if so, determining the number of the super capacitor;

and (3) a flow path: for the situation that the electric quantity in the super capacitor array is lower than the critical electric quantity, first, whether the second number of elements in the working state matrix of the self power generation region or the human body state matrix has "1" is judged? If yes, the personnel is in a strong illumination environment at the moment and can go to an area with stronger illumination intensity; if no, it indicates that the person is in a "weak light" environment, and needs to be reminded of starting to move, and then it is determined whether the fourth number of elements in the working state matrix of the self-power-generation region or the human body state matrix has "1"? If yes, reminding the person to keep the exercise intensity, and if not, reminding the person to increase the exercise intensity;

and (4) a flow chart: if the human body is in the illumination area, determine whether there is "1" from the working state matrix of the power generation area or the first number of elements in the human body state matrix or not? If yes, reminding the person to keep the exercise intensity; if not, indicating that the person does not move, reminding the person to start moving; then, whether the fourth number of elements in the working state matrix of the self-generating area or the human body state matrix has '1'? If yes, reminding the person to keep the exercise intensity, and if not, reminding the person to increase the exercise intensity;

and (5) a flow chart: after the process, the voltage detector, the current detector and the electric quantity detector are used for monitoring the output voltage, the output current and the electric quantity of the super capacitor array of the 4 self power generation areas again to form a self power generation area working state matrix, a human body state matrix and a super capacitor electric quantity matrix of the process 1, and iterative optimization is achieved.

The long-term neural network structure is composed of an input layer 24, a convolutional layer 25, a pooling layer 26, a convolutional layer 27, a pooling layer 28, and a full-link layer 29, as shown in fig. 4. The long-term neural network construction process is as follows:

step 1: and constructing a database. Uploading the data segments of each power generation area to a mobile terminal through Bluetooth by a data memory in the device in a time-sharing manner to form a long-term database corresponding to each power generation area;

step 2: and (5) building a model. Building a convolutional neural network based on tensoflow, and extracting the characteristics of input voltage and current data to form human body power generation characteristics;

and step 3: and (6) testing the model. Based on the trained neural network model, testing by using a test data set to evaluate the performance of the model;

and 4, step 4: and (5) model prediction. And (3) predicting the recent power generation state of the human body by applying the trained model, and forming power generation intervention to realize self-adaptive micro-grid control.

The invention relates to a self-adaptive microgrid control method and device with stable self-generating energy supply. (ii) a

(1) As shown in fig. 5, it is a schematic structural diagram of the nano friction power generation region.

Step 1: weaving a waterproof, hydrophobic insulating layer 30 on the inside of the fabric;

step 2: a positive stator layer 31 based on ethyl cellulose-polyurethane is woven on the insulating layer from the inner side of the fabric to the direction of human skin;

and step 3: placing a polytetrafluoroethylene-based negative thruster 32 on the surface of the positive stator layer 31;

and 4, step 4: placing a positive stator layer 33 based on ethylcellulose-polyurethane on the surface of the negative thruster;

and 5: a waterproof, hydrophobic insulating layer 30 is woven on the surface of the positive stator 33.

(2) Fig. 6 is a schematic structural diagram of a solar power generation region.

Step 1: weaving a waterproof, hydrophobic insulating layer 34 on the outside of the fabric;

step 2: printing a substrate electrode 35 on the outer side surface of the insulating layer;

and step 3: printing a P-type semiconductor layer 36 on the outer surface of the substrate electrode;

and 4, step 4: printing an N-type semiconductor layer 37 on the outer side surface of the P-type semiconductor layer;

and 5: printing a sparse electrode 38 on the outer side surface of the N-type semiconductor layer;

step 6: a flexible transparent plastic protective film 39 is arranged on the outer side surface of the sparse electrode;

(3) fig. 7 is a schematic structural view of the body temperature thermoelectric generation region.

Step 1: weaving a waterproof, hydrophobic insulating layer 40 on the inside of the fabric;

step 2: weaving a flexible conductive silver wire layer 41 on the surface of the insulating layer;

and step 3: weaving P-type thermoelectric particle layer 42 and N-type thermoelectric particle layer 43 on the surface of the conductive silver wire layer

And 4, step 4: an anode interface 44 is led out from the surface of the P-type thermoelectric particle layer, and a cathode interface 45 is led out from the surface of the N-type thermoelectric particle layer;

(4) as shown in fig. 8, is a schematic structural view of a biofuel power generation region.

Step 1: weaving a waterproof, hydrophobic insulating layer 46 on the inside of the fabric;

step 2: printing a carbon nanotube layer 47 on the surface of the insulating layer;

and step 3: printing a naphthoquinone layer 48 on the surface of the carbon nano tube layer, and printing a lactic acid oxidase layer 49 on the surface of the naphthoquinone layer;

and 4, step 4: the cathode prints a silver oxide layer 50 on the surface of the carbon nano tube;

the invention relates to a self-adaptive micro-grid control method and a device with stable self-generating energy supply, wherein an energy storage module of the device is used for spinning a planar micro super capacitor based on a fabric on a common fabric by a nano-spinning technology, and as shown in figure 9, the structure of the device is schematically shown.

Step 1: weaving a waterproof, hydrophobic insulating layer 51 on the outside of the fabric;

step 2: printing a carbon nanotube and polystyrene sulfonate mixed interdigital layer 52 on the surface of the insulating layer;

and step 3: printing a polyvinyl alcohol electrolyte anode 53 and a polyvinyl alcohol electrolyte cathode 54 on two sides of the carbon nanotube and polystyrene sulfonate mixed interdigital layer;

and 4, step 4: the surfaces of the carbon nano tube and polystyrene sulfonate mixed interdigital layer and the anode and the cathode of the polyvinyl alcohol electrolyte are printed with a textile waterproof and hydrophobic insulating layer 51;

the invention relates to a self-adaptive micro-grid control method and a device with stable self-generating energy supply, which can be realized on flexible textile clothes by a nano textile printing technology, and as shown in figure 10, the method and the device are composed of a self-adaptive control module 55, an energy storage module 56, a nano friction power generation area 57, a solar power generation area 58, a body temperature thermoelectric power generation area 59 and a biofuel power generation area 60. The self-adaptive control module is located at the middle lower part of the chest, the energy storage module is located at the middle part of the chest, the nanometer friction power generation area is located at two sides of the chest and close to arm positions of armpits, the solar power generation area is located at two shoulders and back parts, the body temperature thermoelectric power generation layer is located at the lower side of a clavicle of the chest, and the biofuel power generation area is located at the middle upper part of the chest.

Claims

1. A self-adaptive micro-grid control method and a device with stable self-generating energy supply are characterized in that 1) the device prints a self-adaptive control module, a self-generating module and an energy storage module on a common fabric in a spinning mode through a nano textile printing technology, the self-adaptive control module comprises a microprocessor, a voltage detector, a current detector, a transformer, a voltage stabilizer, a digital-to-analog converter, a memory and wireless Bluetooth, the self-generating module comprises a nano friction generating area, a solar generating area, a body temperature generating area and a biofuel generating area, and the energy storage module comprises a super capacitor array and an electric quantity detector. 2) The method is a self-adaptive microgrid control method, the self-adaptive control module monitors the electric quantity of a super capacitor of an energy storage module and the output voltage and current of 4 self-generating areas, the working state and the human body state of each generating area are determined, data are formed through a digital-to-analog converter and stored, the data are transmitted to a mobile terminal and a server through wireless Bluetooth, the mobile terminal analyzes the data to form a real-time self-adaptive algorithm, the server analyzes the data to form long-time neural network model prediction, the server analyzes the data to form a self-adaptive microgrid control algorithm, and the self-adaptive microgrid control algorithm guides people to change the human body state, so that the self-adaptive microgrid control is realized.

2. The self-adaptive microgrid control method and device with stable self-generating energy supply function according to claim 1 is characterized in that the method and device can determine the working states and human body states of 4 self-generating areas, wherein the working states of the 4 self-generating areas are respectively determined by monitoring the output voltage and current change conditions of each area by 4 voltage detectors and current detectors, the working state of each generating area is simplified into two states of working and non-working, and the 4 generating areas are combined to have 16 working states; the human body state comprises the human body motion state (dynamic or static), the environment (strong light or weak light), the external temperature of the human body and the secretion amount of human skin secretion, and is determined by the working states of 4 power generation areas.

3. The method and the device for controlling the self-adaptive microgrid with stable self-generating energy supply of claim 1 are characterized in that the method and the device can form a self-adaptive microgrid control algorithm to change the human body state according to the working states and the human body states of 4 self-generating areas, so as to realize the self-adaptive microgrid control. The working states and the human body states of the 4 self-power-generation areas are converted into digital signals by a digital-to-analog converter, the digital signals are stored, the data are transmitted to the mobile terminal and the server by the wireless Bluetooth, and the mobile terminal forms a real-time self-adaptive algorithm based on real-time data and is used for changing the human body state in real time; the server trains a neural network model based on the long-term data for predicting the human body state; the real-time adaptive algorithm and the long-term neural network model jointly form an adaptive microgrid control method, and the working states of 4 self-generating areas are changed by the method, so that adaptive microgrid control is realized.

4. The method and the device for controlling the self-adaptive microgrid capable of stably supplying the self-generating energy are characterized in that the method and the device can be applied to common fabrics by a nano textile printing technology, and simultaneously form a wearable device for monitoring the vital signs of the human body with the self-adaptive self-generating energy supply control function together with a dry electrode with a bioelectricity detection function, so that the wearable device is used for detecting the heart rate, the breathing rate and the body temperature of the human body.