Intelligent photovoltaic power generation device and control method thereof

文档序号:588587 发布日期:2021-05-25 浏览:12次 中文

阅读说明:本技术 一种智能光伏发电装置及其控制方法 (Intelligent photovoltaic power generation device and control method thereof ) 是由 姚屏 何剑朋 唐贺清 宾坤 陈晔 于 2021-01-08 设计创作,主要内容包括:本发明涉及光伏发电技术领域,具体涉及一种智能光伏发电装置及其控制方法。本发明有效地将光伏发电与氢燃料电池结合在一起;采用电解水触发机制,电解池,氢气储能装置,氧气储能装置,氢气进气口,氧气进气口,氢燃料电池进行电化学反应产生电能;运用最大功率点跟踪原理,追踪光伏阵列输出电压和电流,调整占空比进行阻抗匹配,同时通过计算最佳的光照方位,使光伏阵列始终处于最大照度状态,提高了光伏发电电能转化效率,进一步地,还可利用物联网平台获取云服务中天气数据,实现手机APP远程监控系统电能数据以及控制光伏电池阵列转向。(The invention relates to the technical field of photovoltaic power generation, in particular to an intelligent photovoltaic power generation device and a control method thereof. The invention effectively combines photovoltaic power generation and a hydrogen fuel cell; an electrolyzed water triggering mechanism, an electrolytic cell, a hydrogen energy storage device, an oxygen energy storage device, a hydrogen gas inlet, an oxygen gas inlet and a hydrogen fuel cell are adopted to carry out electrochemical reaction to generate electric energy; the photovoltaic array output voltage and current are tracked by applying the maximum power point tracking principle, the duty ratio is adjusted to carry out impedance matching, meanwhile, the photovoltaic array is always in the maximum illumination state by calculating the optimal illumination direction, the photovoltaic power generation electric energy conversion efficiency is improved, furthermore, the weather data in cloud service can be acquired by utilizing the platform of the Internet of things, and the electric energy data of the mobile phone APP remote monitoring system and the steering of the photovoltaic cell array are realized.)

1. An intelligent photovoltaic power generation device and a control method thereof comprise a photovoltaic cell array, a photovoltaic energy storage device, a driving assembly, a sensor assembly, a control system, an Internet of things platform, a communication module, an electrolyzed water triggering mechanism, a cooling water inlet, an electrolytic cell, a hydrogen energy storage device, a hydrogen gas inlet, an oxygen energy storage device, an oxygen gas inlet, a hydrogen fuel cell, an inverter, an alternating current load and a direct current load, and are characterized in that: the system comprises a driving assembly, a sensor assembly, a control system, an electrolytic water triggering mechanism, an electrolytic cell, a cooling water inlet, a hydrogen and oxygen energy storage device, a hydrogen inlet and an oxygen inlet, wherein the driving assembly can realize the rotation and the movement of two degrees of freedom of a photovoltaic cell array, the sensor assembly transmits sensed environmental data to the control system, the control system receives and transmits data with an Internet of things platform through a WiFi communication module, the electrolytic water triggering mechanism is connected with the electrolytic cell, the electrolytic cell is a water electrolysis generation place, water required for electrolysis is introduced into the cooling water inlet, the electrolytic cell is connected with the hydrogen and oxygen energy storage device, the two devices are respectively connected with the hydrogen inlet and the oxygen inlet, two gases are introduced into a hydrogen fuel cell to perform electrochemical reaction; the photovoltaic cell array absorbs radiant heat energy and light energy from solar illumination and converts the radiant heat energy and the light energy into direct current electric energy through a photovoltaic effect, and the control system controls and adjusts the electric energy; one part of electric energy is used for driving a direct current load and an alternating current load, the other part of electric energy is used for transmitting the rest electric energy to a hydrogen fuel cell for storage according to the use condition of the electric energy so as to be used for an alternating current load or a direct current load or used at night, and the control system determines whether the hydrogen fuel cell generates electric energy through chemical reaction by consuming the electric energy in the photovoltaic energy storage device to operate an electrolytic water triggering mechanism or is directly connected to a load end to supply power to the load by comparing the power synthesis value of the photovoltaic cell array and the power consumption value of the load.

2. The intelligent photovoltaic power generation device and the control method thereof according to claim 1, wherein: the control system also functions to protect the hydrogen fuel cell, i.e., to control the cell from over-discharge.

3. The intelligent photovoltaic power generation device and the control method thereof according to claim 1, wherein: the carrier of the Internet of things platform is an upper computer, electric power of the photovoltaic cell array and the electric power of the hydrogen fuel cell can be checked in the upper computer, the driving assembly can be controlled to adjust the orientation of the photovoltaic cell array on two degrees of freedom, the photovoltaic cell array is enabled to be always at the maximum illuminance azimuth angle, and further the Internet of things platform can send future weather and temperature information and historical weather data to the control system, so that a control instruction is sent.

4. The intelligent photovoltaic power generation device and the control method thereof according to claim 1, wherein: the control system adopts an industrial controller, a WiFi communication module is used as a medium for information communication between the industrial controller and the Internet of things platform, and the stability and the output power of the power generation system are improved by adopting a Maximum Power Point Tracking (MPPT) method according to the change rule of the output of the photovoltaic array.

5. The intelligent photovoltaic power generation device and the control method thereof according to claim 1, wherein: the industrial-grade controller serial bus module collects photovoltaic array output voltage at regular intervals, observes the trend of system output power change after interference, and then judges whether the adjustment direction of the voltage is appropriate, so as to adjust the direction of the interference. When weather is sunny, a uniform illumination tracking method, namely a mixed ant colony algorithm, is used, and when weather is cloudy or cloudy, a local shadow tracking method, namely a particle swarm algorithm is improved.

Technical Field

The invention relates to the technical field of photovoltaic power generation, in particular to an intelligent photovoltaic power generation device and a control method thereof.

Background

In the past decades, the economy of China has developed at a high speed, and particularly the development of the coal and steel industry is mature, but because raw coal, petroleum, natural gas and the like are continuously exploited, the non-renewable energy in China is rapidly reduced, and the ecological environment is damaged, so that the development of green renewable energy is a necessary measure for ensuring the sustainable development of human beings. The most abundant electric energy source in nature is solar energy, while the prisons in China are vast, the solar illumination resources are very abundant, and according to statistics, the total amount of sunlight radiation in all parts of the country is about 4KWh/m on average2Even up to 6kWh/m in Tibet regions2. The method combines the geographical advantages of China, greatly promotes the photovoltaic solar power generation technology, continuously improves the intelligent level and the conversion efficiency of the photovoltaic power generation system, and solves more power utilization problems. The existing photovoltaic power generation system is low in electric energy conversion efficiency and high in system cost, so that the photovoltaic power generation industry of all countries in the world depends on government financial subsidies to support the operation of the photovoltaic power generation system, and the large-scale application of the photovoltaic power generation system is very difficult.

Disclosure of Invention

Aiming at the defects in photovoltaic power generation, the control algorithm of the solar photovoltaic power generation system is improved, the generated power of the photovoltaic power generation system is effectively tracked in real time, the system can be ensured to work near the maximum power point all the time, and the aim of improving the photoelectric conversion rate is fulfilled.

In order to realize the purpose, the following technical scheme is adopted:

an intelligent photovoltaic power generation device and a control method thereof comprise a photovoltaic cell array, a photovoltaic energy storage device, a driving assembly, a sensor assembly, a control system, an Internet of things platform, a communication module, an electrolyzed water triggering mechanism, a cooling water inlet, an electrolytic cell, a hydrogen energy storage device, a hydrogen gas inlet, an oxygen energy storage device, an oxygen gas inlet, a hydrogen fuel cell, an inverter, an alternating current load and a direct current load, wherein the driving assembly can realize the rotary movement of two degrees of freedom for the photovoltaic cell array, the sensor assembly transmits sensed environmental data to the control system, the control system carries out data receiving and transmitting with the Internet of things platform through a wifi communication module, the electrolyzed water triggering mechanism is connected with the electrolytic cell, the electrolytic cell is a water electrolysis place, the cooling water inlet is filled with water required for electrolysis, and the electrolytic cell is connected with the hydrogen and oxygen energy storage device, the two devices are respectively connected with the hydrogen gas inlet and the oxygen gas inlet, so that the two gases are introduced into the hydrogen fuel cell to perform electrochemical reaction to generate electric energy, the alternating current load and the direct current load are distributed with electric energy by the control system, and the inverter is used for converting direct current into alternating current. The photovoltaic cell array absorbs radiation heat energy and light energy from solar illumination and converts the radiation heat energy and the light energy into direct current electric energy through a photovoltaic effect, and the control system controls and adjusts the electric energy. One part of electric energy is used for driving a direct current load and an alternating current load, the other part of electric energy is used for transmitting the rest electric energy to a photovoltaic energy storage device for storage according to the use condition of the electric energy for use in preparation for an alternating current/direct current load or at night, the control system determines whether to operate an electrolytic water triggering mechanism or not by comparing the power synthesis value of a photovoltaic cell array and the load power consumption value, and hydrogen generated by water electrolysis is used for carrying out electrochemical reaction with a hydrogen fuel cell to generate electric energy to be supplied to a load end. The control system also functions to protect the hydrogen fuel cell, i.e., to control the cell from over-discharge. The control system realizes data receiving and sending through the WiFi communication module and the Internet of things platform, the carrier of the Internet of things platform is an upper computer, electric power of the photovoltaic cell array and the hydrogen fuel cell can be checked in the upper computer, the driving assembly can also be controlled to adjust the position of the photovoltaic cell array in two degrees of freedom, the photovoltaic cell array is enabled to be always at the maximum illuminance azimuth angle, and further the Internet of things platform can send future weather and temperature information and historical weather data to the control system so as to send a control instruction. In order to realize performance optimization, the method further comprises the following steps:

the control system adopts an industrial controller and a WiFi communication module, the WiFi is used as a medium for receiving and transmitting data between the controller and an Internet of things platform, and a Maximum Power Point Tracking (MPPT) method is adopted according to a change rule of photovoltaic array output, so that the stability and the output power of the power generation system are improved. The maximum power point tracking principle is that the output voltage and current of a photovoltaic array are detected in real time, the duty ratio of a DC/DC circuit is self-optimally adjusted through an MPPT algorithm to adjust the current impedance, the equivalent impedance is matched with the impedance of the photovoltaic array, the change of the output power and the change of the temperature and illumination keep synchronous, and the system can still work in the best state of the current situation.

The industrial-grade controller serial port bus collects photovoltaic array output electric signals at regular intervals, observes the trend of system output power change after interference, and then judges whether the adjustment direction of the photovoltaic array is proper or not, so as to adjust the direction of the interference. When weather is sunny, a uniform illumination tracking method, namely a mixed ant colony algorithm, is used, and when weather is cloudy or cloudy, a local shadow tracking method, namely a particle swarm algorithm is improved.

The control system controller controls the set parameters through a serial port bus, and acquires a photovoltaic array power generation parameter C and a load power consumption parameter H through a master control chip A/D interface, wherein C is the power provided by the photovoltaic array power generation system, and H is the power consumed by the load. If the C is larger than H, namely the power provided by the photovoltaic array power generation system is larger than the power consumed by the load, the WiFi module sends a message to the upper computer, and the upper computer judges the electric energy transmitted to the photovoltaic energy storage device by calling future weather condition prediction data in the cloud large data platform database; if the detected C is H, namely the power provided by the photovoltaic array power generation system is equal to the power consumed by the load, the whole system is in a balanced state, the control system enters a dormant state, the electrolytic cell stops electrolysis, and the system waits for the next detection signal to wake up; if C is less than H, namely the power provided by the photovoltaic array power generation system is less than the power consumed by a load, the upper computer receives a signal of insufficient energy supply, a normally open contact in the photovoltaic energy storage device is closed, the water electrolysis device is triggered to electrolyze to generate hydrogen and oxygen, the hydrogen and oxygen are stored in the hydrogen and oxygen energy storage devices respectively, when the control system detects that the storage amounts of the two gases reach the minimum value, a hydrogen gas inlet and an oxygen gas inlet are opened, the hydrogen gas inlet and the oxygen gas inlet are connected into a hydrogen fuel cell to perform electrochemical reaction to generate electric energy for supplementing the insufficiency of the power supply of the photovoltaic system, when the control system detects that the storage amounts of the two gases reach the maximum value, the information that the gas storage is full is sent; the control system continuously detects the gas threshold values of the hydrogen energy storage device and the oxygen energy storage device, when the detection values are smaller than the gas threshold values, the system starts a protection mode, and the hydrogen fuel cell does not provide electric energy for the load any more.

The invention has the beneficial effects that: the present invention effectively combines photovoltaic power generation with a hydrogen fuel cell. The electrochemical reaction is carried out by adopting an electrolyzed water triggering mechanism, an electrolytic cell, a hydrogen energy storage device, an oxygen energy storage device, a hydrogen gas inlet, an oxygen gas inlet and a hydrogen fuel cell to generate electric energy. The photovoltaic array output voltage and current are tracked by applying the maximum power point tracking principle, the duty ratio is adjusted to carry out impedance matching, meanwhile, the photovoltaic array is always in the maximum illumination state by calculating the optimal illumination direction, the photovoltaic power generation electric energy conversion efficiency is improved, furthermore, the weather data in cloud service can be acquired by utilizing the Internet of things platform, and the electric energy data of the mobile phone APP remote monitoring system, the photovoltaic cell array steering control and the operation switch of the whole system are realized.

Drawings

FIG. 1 is a block diagram of the system of the present invention;

FIG. 2 is a schematic diagram of data message delivery according to the present invention;

FIG. 3 is a schematic diagram of the disturbance observation optimization method of the present invention;

FIG. 4 is a flow chart of the hybrid ant colony algorithm design of the present invention;

fig. 5 is a flow chart of the particle swarm tracking algorithm of the present invention.

Detailed Description

The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic views illustrating only the basic structure of the present invention in a schematic manner, and thus show only the constitution related to the present invention.

As shown in figure 1, the intelligent photovoltaic power generation device comprises a photovoltaic cell array, a driving assembly, a sensor assembly, a control system, an Internet of things platform, a communication module, an electrolyzed water triggering mechanism, a cooling water inlet, an electrolytic cell, a hydrogen energy storage device, a hydrogen gas inlet, an oxygen energy storage device, an oxygen gas inlet, a hydrogen fuel cell, an inverter, an alternating current load and a direct current load, wherein the driving assembly can realize the rotary movement of two degrees of freedom for the photovoltaic cell array, the sensor assembly transmits sensed environmental data to the control system, the control system carries out data transceiving with the Internet of things platform through a wifi communication module, the electrolyzed water triggering mechanism is connected with the electrolytic cell, the electrolytic cell is a water electrolysis generation place, water required for electrolysis is introduced into the cooling water inlet, and the electrolytic cell is connected with the hydrogen and the oxygen energy storage device, the two devices are respectively connected with the hydrogen gas inlet and the oxygen gas inlet, so that the two gases are introduced into the hydrogen fuel cell to perform electrochemical reaction to generate electric energy, the alternating current load and the direct current load are distributed with electric energy by the control system, and the inverter is used for converting direct current into alternating current. The photovoltaic cell array absorbs radiation heat energy and light energy from solar illumination and converts the radiation heat energy and the light energy into direct current electric energy through a photovoltaic effect, and the control system controls and adjusts the electric energy. One part of electric energy is used for driving a direct current load and an alternating current load, the other part of electric energy is used for transmitting the rest electric energy to a photovoltaic energy storage device for storage according to the use condition of the electric energy so as to supplement the electric energy for the alternating current and direct current load or be used at night, and the control system determines whether to operate an electrolytic water triggering mechanism to enable hydrogen fuel to carry out chemical reaction to generate electric energy to supply power for the load or not by comparing the power synthesis value of a photovoltaic cell array and the power consumption value of the load. The control system also functions to protect the hydrogen fuel cell, i.e., to control the cell from over-discharge. Control system passes through communication module and thing networking platform and realizes the receiving and dispatching of data, thing networking platform carrier is cell-phone APP, can look over photovoltaic cell array and hydrogen fuel cell's voltage value on APP software, also can control drive assembly and adjust photovoltaic cell array on two degrees of freedom, makes it be in the biggest illuminance azimuth all the time, and further, thing networking platform can send control system with future weather and temperature information, historical weather data.

As shown in fig. 2, the sensor assembly of the present invention includes an illumination sensor and a temperature sensor, and output signals of the sensors are sent to different channels of the main control chip through the isolation conversion interface circuit, and then are converted into digital values after being sampled by the a/D conversion module, and the digital values are used as entry parameters of the control program. The power calculation module is used for calculating a value of the photovoltaic array power changing along with the change of temperature and illumination, feeding the value back to the control system, and adjusting the working point of the photovoltaic cell in real time to enable the photovoltaic cell to continuously work near the maximum power point. The industrial controller is communicated with the WiFi chip through a serial port, the WiFi chip receives the generated voltage and power of the photovoltaic array and the voltage of the hydrogen fuel cell, and the WiFi chip can upload and download data to a port of the Internet of things in a station mode, so that the corresponding voltage and power values can be displayed on APP software; the WiFi chip can also receive weather forecast and historical weather data information transmitted from the Internet of things end, and then transmits the weather forecast and historical weather data information to the industrial controller to make a control decision, and the driving assembly is adjusted to rotate the photovoltaic cell array left and right or up and down to ensure sufficient solar radiation. The industrial controller controls the set parameters through a serial port bus, and acquires a photovoltaic array power generation parameter C and a load power consumption parameter H through a master control chip serial port bus interface, wherein the C is the power provided by the photovoltaic array power generation system, and the H is the power consumed by the load. If the C is detected to be larger than H, namely the power provided by the photovoltaic array power generation system is larger than the power consumed by the load, the water electrolysis triggering mechanism is enabled, the rest power is provided for the electrolytic cell, the electrolyzed water generates hydrogen and oxygen which are respectively stored in the hydrogen and oxygen energy storage devices, and when the two gas quantities are enough, the hydrogen gas inlet and the oxygen gas inlet are opened and connected into the hydrogen fuel cell to carry out electrochemical reaction to generate electric energy. When the control system detects that the electric energy is larger than the storage threshold value of the battery, the control system loses the energy to electrolyze the water triggering mechanism, and the electrolytic cell stops electrolyzing; if the detected C is H, namely the power provided by the photovoltaic array power generation system is equal to the power consumed by the load, the whole system is in a balanced state, and the control system enters a dormant state; and if C is detected to be less than H, namely the power provided by the photovoltaic array power generation system is less than the power consumed by the load, the control system starts the hydrogen fuel cell to generate power to supplement the shortage of the photovoltaic system, the control system continuously detects the gas threshold values of the hydrogen energy storage device and the oxygen energy storage device, and when the detected value is less than the gas threshold value, the system starts a protection mode, and the hydrogen fuel cell does not provide electric energy for the load any more.

As shown in fig. 3, the maximum power point tracking algorithm uses a disturbance observation method, and in an uphill direction from a zero point, when the reference voltage increases, the output power also approaches to the vicinity of the maximum power point, and when the reference voltage continuously increases, the maximum power point is crossed, and at this time, the power starts to decrease with the increase of the voltage so as to be far away from the maximum power point, as shown in a process B; when the optimization algorithm monitors that the power is reduced, the voltage disturbance direction is changed, as shown in the process D; after the maximum power point is crossed again, the power begins to decrease, as shown in the process C, the voltage disturbance direction is changed again, and the steps are repeated in a circulating mode.

As shown in fig. 4, when the weather is clear, a uniform illumination tracking method, i.e., a hybrid ant colony algorithm, is used. The ant colony algorithm is a method for solving the optimization problem, the foraging path of each ant represents a solution of the corresponding optimization problem, the foraging paths of all ants form a solution space of the optimization problem, and the optimal path is the optimal solution of the optimization problem. And regarding the ant position as the duty ratio in the photovoltaic power generation system, regarding the pheromone content as the power of the photovoltaic power generation system, and comparing to obtain a maximum value point which is the maximum power point. Firstly, the number n of ants is required to be set, the ants are randomly placed, and an initial pheromone value is set; updating the tabu list requires adding the current position of each ant into the tabu list; determining the direction is to select a location to go to according to a formula of transition probability; calculating the increment of the pheromone, namely calculating the content of the pheromone on each boundary when each ant returns to the starting point from the starting point; and finally, adding a 2-opt ant colony algorithm in the optimization process to prevent the extreme value state from being trapped.

As shown in FIG. 5, when the weather is cloudy or cloudy, the target function is analogized to the required total output power X by using the local shadow tracking method and adopting the improved particle swarm optimizationLocation of particlesThen is the required UValue of voltage. Firstly, setting initialization parameters, determining the number of particles, the number of iterations, the search space dimension, the weight w, the learning factors c1 and c2, and the maximum velocity value Vmax(ii) a Calculating a particle adaptive value and particle evaluation, determining an individual and global new-stage optimal value, comparing the experienced optimal position adaptive values, if the current adaptive value is large, taking the current adaptive value as a new individual optimal value, then comparing the adaptive value of each particle with a group optimal adaptive value, taking the largest as a group optimal value, then updating the position and the speed of the particle, and if the speed and the position of the particle exceed the upper limit and the lower limit, resetting the upper limit and the lower limit; and then, updating the optimal value, calculating the fitness value again, comparing the current value with the previous value, updating the individual and global optimal values, terminating and obtaining the optimal solution when the iteration times are reached, and otherwise, calculating the fitness value again.

In light of the foregoing description of the preferred embodiment of the present invention, many modifications and variations will be apparent to those skilled in the art without departing from the spirit and scope of the invention. The technical scope of the present invention is not limited to the content of the specification, and must be determined according to the scope of the claims.

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