57 results about "Mppt algorithm" patented technology

The invention provides a photovoltaic module maintenance method, medium and system, and belongs to the technical field of photovoltaic module maintenance, and the method comprises the steps: obtaining the multi-dimensional data of a module through infrared thermal image scanning, IV curve testing, electroluminescent imaging, PID attenuation measurement, mechanical load testing and other technologies, and predicting the performance attenuation trend through a deep learning degradation prediction model. The core innovation lies in that a PVDefectNet model is utilized to carry out automatic defect identification on an electroluminescent image, traditional manual interpretation is replaced, health indexes are calculated and health levels are divided through an MPEvalue multi-parameter comprehensive evaluation function, a differentiated overhaul scheme is made based on an objective evaluation result, a repair effect is verified through an MPPT algorithm, and the repair efficiency is improved. The technical problem that the accuracy is not high enough due to the fact that photovoltaic module defect detection often depends on artificial experience is solved.

The invention relates to the technical field of hybrid energy, and particularly provides a self-adaptive power distribution multi-source parallel mobile power supply system which comprises a multi-source input interface, a multi-channel input adjusting module, an energy storage module, an energy storage bidirectional adjusting module, a self-adaptive power distribution module and a power output interface. The method is characterized in that an MPPT algorithm is independently executed for each heterogeneous power supply through a multi-channel input adjusting module, and energy extraction is maximized; based on load detection and a multi-stage feedback mechanism, dynamic self-adaptive power distribution is realized; a multi-channel input end is adjusted into a unified standard bus voltage, and an output end dynamically adjusts the voltage according to a load, so that the energy conversion efficiency is improved while the use convenience is ensured; and the standard lithium battery units spliced without tools and the modular circuit design are adopted, so that the flexible combination and disassembly of the system are realized. According to the invention, the complexity of the hybrid energy system is greatly reduced, the system stability is improved, and efficient and lightweight hybrid energy mobile power supply is realized.

The invention discloses a system for improving multi-series parallel power generation of photovoltaic cells, and relates to the technical field of photovoltaic power supply, the system comprises photovoltaic panels, photovoltaic optimizers, a photovoltaic gateway and an inverter, the power output of a photovoltaic array is optimized through a multi-stage cooperative control strategy, each photovoltaic panel is connected with an independent photovoltaic optimizer, and the photovoltaic panels are connected with the photovoltaic gateways. A working point is dynamically adjusted by adopting an MPPT algorithm, real-time data interaction with a photovoltaic gateway is carried out in a wireless or wired communication mode, the photovoltaic gateway automatically detects open-circuit voltage differences of parallel strings, dynamically adjusts the MPPT voltage range of each string and ensures the overlapping proportion of output voltages, the photovoltaic gateway monitors the duty ratio change of the strings, and when shielding is detected, the photovoltaic gateway is switched on and switched off. The MPPT parameters of the affected string are automatically adjusted, and the generating capacity of the system is improved.

The invention discloses a multi-energy coupling intelligent power generation device integrating wind power, photovoltaic energy and wave energy, and belongs to the technical field of distributed energy systems. Aiming at the problems of high intermittency, low coupling efficiency, structural redundancy and the like of a traditional system, three power generation units are integrated through a rack: a wave power generation unit adopts a multi-directional articulated shaft-connecting rod-bevel gear pair and spur gear-rack transmission to construct a double-cooperative power generation path, and is matched with a guide rail sliding block and a reset spring; wave multi-degree-of-freedom energy is efficiently captured, and the transmission precision is ensured; the wind power generation unit decelerates and increases torque by using a box-type planetary reducer; and the photovoltaic power generation unit dynamically follows light through the double-shaft holder and the photoresistor array in combination with an MPPT (maximum power point tracking) algorithm. According to the invention, wave energy is mainly used, wind / light is coordinated and complementary, when wind power or photovoltaic power is influenced, the wave energy continuously supplies power, the traditional bottleneck is broken through, stable and efficient energy supply in water areas such as islands and oceans is realized, and compared with a traditional scheme, the wave energy utilization rate and the power supply stability are remarkably improved.

The invention relates to the technical field of photovoltaic gateways, and provides a management method and system of a photovoltaic four-function gateway, and the management method comprises the steps: constructing a photovoltaic power generation power prediction model based on electrical parameters, equipment state parameters and environmental parameters, and outputting a photovoltaic power generation power prediction value of a future time period; calculating the fluctuation degree of the photovoltaic power generation power prediction value according to the photovoltaic power generation power prediction value in the future time period, and adaptively adjusting the disturbance step length of the MPPT algorithm based on the fluctuation degree to track the maximum power point of the photovoltaic module; constructing a photovoltaic power generation power fitting model based on the environmental parameters and the electrical parameters, judging the dust accumulation state of the photovoltaic panel by comparing the deviation between the real-time power generation power and the fitting power, and generating a cleaning suggestion based on future weather forecast; and based on the electrical parameters, the equipment state parameters and the environmental parameters, constructing a fault diagnosis model, and performing real-time evaluation and fault early warning on the state of the photovoltaic panel.

The invention provides a dynamic power matching method of a photovoltaic hydrogen production system, which comprises the following steps: acquiring load demand data from an electrolytic tank in the hydrogen production system, combining stable power output, finely adjusting a power adjusting range by utilizing a proportional-integral control method, and judging a real-time power matching state when the electrolytic tank runs; after continuous operation parameters are obtained, through conjoint analysis of real-time power data and gas supply parameters, a self-adaptive filtering algorithm is adopted to optimize a dynamic matching process, and the long-term stability of the system under illumination fluctuation is judged; and extracting abnormal characteristics of power instability and gas supply fluctuation from a long-term stability judgment result, updating control parameters of an MPPT algorithm through historical operation data, and determining an optimized topological structure and a gas supply support scheme. According to the invention, the long-term stability of the system under illumination fluctuation is improved, and efficient and stable operation of the photovoltaic hydrogen production system is realized.

The invention discloses a 2000W photovoltaic intelligent MPPT (maximum power point tracking) power supply control method and a 2000W photovoltaic intelligent MPPT power supply control system, which are used for an energy storage battery. Detecting whether the photovoltaic input voltage is within a preset voltage range; if the photovoltaic input voltage is in the preset voltage range, performing forward disturbance or reverse disturbance processing on the photovoltaic input voltage by adopting an MPPT algorithm to obtain a photovoltaic output voltage corresponding to the photovoltaic maximum output power; the energy storage battery is charged according to the photovoltaic output voltage, and the photovoltaic output voltage is the photovoltaic output voltage corresponding to the photovoltaic maximum output power. The photovoltaic input voltage is processed through the MPPT algorithm to obtain the photovoltaic output voltage corresponding to the photovoltaic maximum output power, and then the photovoltaic output voltage corresponding to the photovoltaic maximum output power is used for charging the energy storage battery, so that the charging efficiency of the energy storage battery is improved, and the maximum efficiency of photovoltaic power generation is fully exerted.

A five-level inverter model prediction control method capable of enhancing the bus utilization rate comprises the steps that at the sampling k moment, the output voltage, the output current and the load voltage of an inverter are measured, and physical quantities under a dq coordinate system are obtained through the coordinate transformation principle; constructing a prediction model, and calculating the predicted current of the inverter under the dq coordinate system; according to the photovoltaic MPPT algorithm, the photovoltaic voltage vpv and the photovoltaic current ipv are used as input quantities, the deviation value of the output of the DC voltage reference # imgabs0 # photovoltaic MPPT algorithm and the actual DC side voltage is used as the input of a PI controller, and therefore a d-axis current reference value is obtained; on-line calculation and evaluation of a cost function J are carried out in combination with six switching states of the inverter, the switching state enabling the cost function value to be minimum is found, and the cost function J acts on the inverter in the next switching period. According to the invention, fast dynamic response can be realized, and robustness to power grid fluctuation and load fluctuation is stronger; the structure is simpler, the bus voltage utilization rate is maximized, and the voltage stress between the direct current side capacitor and the switching device is lower.

The invention relates to the technical field of power systems, in particular to a photovoltaic wind power cluster and power distribution network coordinated intelligent regulation and control power supply system, which comprises a photovoltaic wind power cluster, a power distribution network and an intelligent regulation and control device in communication connection with the photovoltaic wind power cluster and the power distribution network, and comprises a data acquisition module, a cluster division module, a coordinated control module and an energy management module, an energy storage system and a fault diagnosis module are also arranged; the coordination control module stabilizes power grid parameters by matching an MPC unit optimization instruction with a reactive power coordination strategy; the energy management module uses an improved MPPT algorithm to improve the power generation efficiency, and combines with prediction to optimize a power generation plan; the energy storage system stabilizes power fluctuation, and the fault diagnosis module quickly locates and disposes faults based on wavelet transform and CNN-LSTM. The method can adapt to conventional, high-photovoltaic-permeability and high-load-rate scenes, guarantees that the frequency deviation is smaller than or equal to + / -0.2 Hz and the voltage fluctuation is smaller than or equal to + / -5%, remarkably improves the renewable energy consumption rate and the power supply reliability, and is suitable for various power distribution networks containing distributed new energy.

The invention discloses a zero-carbon energy storage building comprehensive illumination energy load optimization scheduling method, and relates to the technical field of power grid coupling scheduling, and the method comprises the steps: recognizing a reflected light path through a light path random sampling simulation method based on a building photo-thermal environment feature matrix, and constructing a building surface light intensity distribution thermodynamic diagram; according to the building surface light intensity distribution thermodynamic diagram, the deflection angle of the building reflector array is dynamically adjusted, and a building light guide performance parameter set is generated through a dynamic light field efficiency quantification method; according to the building light guide performance parameter set, a hybrid MPPT algorithm is adopted to obtain a photovoltaic operation state data set; building energy hierarchical scheduling is carried out based on the photovoltaic operation state data set, and an energy scheduling instruction set and a cross-domain energy scheduling collaborative log are obtained; according to the method, the photovoltaic operation state data set and the power grid hierarchical framework are fused through the building energy hierarchical scheduling model, cross-space-time collaborative optimization of the illumination energy and the power grid load is realized, and the target of zero-carbon building light-storage-network full-link efficient scheduling is achieved.

The embodiment of the invention provides a photovoltaic charging control method and device, a storage medium and a charging system. The method is used for controlling a charging system, and the charging system comprises a PV panel, a PV boost converter and a battery system. The method comprises the steps that before a charging system is started, a first switching tube and a third switching tube are closed, and if it is judged that the short-circuit current of a PV panel is larger than a set current threshold value, the PV panel is controlled to be connected to and activate a battery system; when the charging system enters the working stage, acquiring the voltage of the PV panel and the power supply current of the battery system; power supply current and PV panel voltage are calculated through an improved MPPT algorithm, voltage single-loop given voltage is generated, and the improved MPPT algorithm starts to search the maximum power point when the PV panel voltage is zero; calculating the given voltage of the voltage single loop and the voltage of the PV panel based on a proportional-integral algorithm, and generating switch-on time of a switch tube; and the second switch tube and the third switch tube are controlled according to the switch tube conduction time, so that the hardware cost and the control cost of the charging system are reduced.

The invention relates to the technical field of heating systems, and particularly discloses a heating system adopting a photovoltaic direct drive and mains supply coupled double-source heating technology, comprising a photovoltaic direct drive module which is composed of a photovoltaic array and a high-frequency isolation type direct drive converter, the direct drive converter adopts a three-level ANPC topological structure, and a deep learning-based MPPT algorithm is built in the direct drive converter; the commercial power coupling module is used for connecting commercial power with photovoltaic direct drive output in parallel through a bidirectional coupler based on a magnetic integration technology; the intelligent energy management unit comprises a sensor group and a coupling controller, and the sensor group collects photovoltaic array output power, mains supply voltage, heating load requirements and environment temperature signals in real time; and the waste energy recovery module is connected with the photovoltaic direct drive module and the heating terminal in parallel, comprises an excess electric energy recovery unit and is composed of a DC-DC converter and a phase change heat storage device, photovoltaic power generation, mains supply complementation and energy recovery technologies are combined, and efficient and intelligent clean energy heating is achieved.

The application provides a photovoltaic heating adapter device, which comprises a power module, a driving circuit, a signal acquisition circuit, a power tracking circuit, a temperature control circuit, an interface control circuit, a button control circuit, a liquid crystal display circuit, a control unit and a control power input circuit. The control unit analyzes the voltage, current and power of the photovoltaic and load, controls the output of the power device through the driving circuit according to the MPPT algorithm, directly drives the heating body, and changes the load to track the power change of the photovoltaic cell, so that the photovoltaic cell always works at the maximum power point. The interface control circuit can be connected to the upper controller, and the photovoltaic heating adapter device is complementary matched with the mains driving heating, directly heated and stored energy. The photovoltaic heating adapter device has high practicability, high safety, stable operation balance and the like, utilizes the photovoltaic to heat the heating body, saves a large amount of energy, and is applied to a heat circulation system to improve the heat energy efficiency.

The present application belongs to the technical field of energy, and specifically discloses a greenhouse power supply system light storage capacity configuration method, device, equipment and medium; the present application is based on typical daily load distribution data, establishes a photovoltaic capacity configuration model and an energy storage capacity configuration model; the photovoltaic capacity configuration model is solved through the MPPT algorithm, the energy storage capacity configuration model is solved through the improved particle swarm algorithm, and the optimal solution is obtained; according to the optimal solution, the light storage capacity of the greenhouse power supply system is configured; based on the MPPT algorithm and the improved particle swarm algorithm, the optimal photovoltaic capacity configuration result and the energy storage capacity configuration result are obtained, the operation speed is fast, the reliability is high, and the problems of slow late convergence speed, premature convergence and falling into a local optimal solution of the existing algorithm itself are overcome.

The application discloses a kind of photovoltaic module intelligent control method based on TinyML, specifically related to photovoltaic system control technical field, pre-training under model quantization control based on original collection data to TinyML framework, according to the spatial distribution of photovoltaic module array surface temperature, the generalization ability of model is evaluated by k-fold cross validation, and the model is optimized by hyperparameter search, for obtaining illumination intensity threshold and temperature threshold, MCU reads the environmental data when photovoltaic module is used, according to different environmental data, MCU adjusts photovoltaic module voltage through dynamic control strategy, and carries out fault diagnosis to photovoltaic module through the time series data of sensor and TinyML algorithm. Through adaptive MPPT algorithm, the energy conversion efficiency of photovoltaic system is significantly improved, and the stability and reliability of the system are improved according to the dynamic adjustment of control strategy.

The invention provides an optical storage system output power control method and an optical storage system. The method comprises the following steps: calculating the output power of a photovoltaic system according to the measured inverter output current and inverter output voltage; based on a maximum power point tracking (MPPT) algorithm and a first proportion-integration-differentiation (PID) control algorithm, controlling the output power of the photovoltaic system at the maximum power point; controlling the working mode of the energy storage system according to the output power of the photovoltaic system and a preset grid-connected power target value; and controlling the output power of the energy storage system based on a second PID control algorithm, so as to control the output power of the optical storage system at a grid-connected power target value. According to the technical scheme provided by the embodiment of the invention, the fluctuation of the output power of the photovoltaic system can be quickly responded, the output power of the photovoltaic system is relatively stable by adjusting the working mode and the output power of the energy storage system, the operation efficiency of the photovoltaic system is ensured, and the stability of a power grid is improved.

The invention discloses a photovoltaic module maximum power point tracking and grid-connected control method, in a photovoltaic system, the input of a series converter SLC is connected to an equivalent direct current bus, each photovoltaic string is connected to the equivalent direct current bus through a cascade converter, and the cascade converter adopts a cascade structure of a DAB converter and a BL converter. A DAB converter is used as a first stage, and a BL converter is used as a second stage; the method comprises the following steps: acquiring a real-time main bus voltage, if the main bus voltage is in a normal grid-connected interval, acquiring a real-time equivalent direct current bus voltage by using a central converter, and adjusting the equivalent direct current bus voltage through PI closed-loop control; independently operating an MPPT algorithm for each photovoltaic string by using a BL converter so as to realize maximum power point tracking; a DAB converter is utilized to obtain a real-time intermediate bus voltage, the intermediate bus voltage is kept stable through SPS modulation, and stable power support is provided for a BL converter.

The invention discloses a vehicle-mounted MPPT (maximum power point tracking) photovoltaic charging method, which relates to the technical field of vehicle-mounted photovoltaic charging and comprises the following steps: constructing a Buck-Boost circuit topology, acquiring an analog output signal of a vehicle-mounted photovoltaic module in real time through a sampling circuit, and converting the analog output signal into a corresponding digital signal; the obtained digital signals are analyzed, and whether a protection program is executed or not is judged according to the analysis result; simulating the output power of the vehicle-mounted photovoltaic module based on an MPPT algorithm so as to obtain corresponding reference voltage and reference current; the actual output of the vehicle-mounted photovoltaic module is compared with the reference voltage and the reference current, the actual output of the vehicle-mounted photovoltaic module is compensated according to the obtained error value, and then a corresponding PWM signal is generated; and adjusting the direct current output by the vehicle-mounted photovoltaic module according to the PWM signal, and collecting the output to a direct current bus to complete the charging of the battery.

According to the power coordination control method for the two-stage grid-forming photovoltaic converter, the two-stage grid-forming photovoltaic converter comprises a Boost module and a three-phase converter, the input side of the Boost module is connected to a photovoltaic array, the output side of the Boost module is connected to the input side of the three-phase converter, and the output side of the three-phase converter is connected to a power grid. The coordination control method is characterized by comprising the following steps: S1, acquiring an actual voltage value of a DC bus of a Boost module, and controlling the Boost module to work by adopting an MPPT algorithm based on the actual voltage value; and S2, the three-phase converter is controlled by VSG, and the difference value between the actual voltage value and the reference voltage value of the DC bus of the Boost module is used as the correction of an active loop controlled by VSG.

The application provides a wind, light, hydrogen and storage direct-current micro-grid distributed control method and system, and belongs to the technical field of micro-grid distributed control, wherein the method comprises the following steps: adopting an EPP-MPPT algorithm based on a Newton-Raphson method to perform maximum power output control on a photovoltaic generator set in a photovoltaic power generation unit, adopting an IMPPT algorithm to perform maximum power output control on a wind power generator in a wind power generation unit, adopting a distributed power supply control strategy to adjust power imbalance among distributed power generation units, load demand and energy storage equipment, and dividing the whole power balance control process into an active part and a passive part. The application can effectively solve the current overshoot or undershoot problem of the traditional bus voltage signal control under the system power mutation of the distributed energy storage equipment.

This invention discloses a control method for multi-model photovoltaic module arrays, belonging to the field of intelligent photovoltaic technology. The method includes: S1, acquiring current electrical parameters; S2, electrical parameter difference and threshold comparison analysis: calculating the difference between the current electrical parameters and the predicted electrical parameters, and determining whether the difference is greater than a preset threshold. If it is greater, proceed to step S3; otherwise, proceed to step S4; S3, adjusting the power supply control quantity and time series array values, then proceeding to step S5; S4, rearranging the time series array; S5, predicting the next time series electrical parameters; S6, two-dimensional FFT: performing a two-dimensional Fourier transform on the time series matrix to obtain the time-spectrum array; S7, predicting the electrical parameter increment; S8, MPPT algorithm control. By integrating frequency domain analysis, probabilistic prediction, and distributed parallel control, environmental abrupt changes and module differences are transformed into computable time-series spectral features, achieving "predictive" tracking of MPPT, which can significantly improve power generation efficiency under complex illumination and module difference scenarios.

The invention relates to the technical field of photovoltaic power generation control, and particularly discloses an inter-group power balancing method and system of a photovoltaic power generation system, and the method comprises the steps: obtaining environment parameters according to environment monitoring points, carrying out the recognition of the environment parameters, and carrying out the clustering of photovoltaic modules according to a recognition result; for each type of photovoltaic modules, working parameters of the photovoltaic modules are obtained based on a wireless communication module, and a clustering result is adjusted according to the working parameters; and selecting a photovoltaic module from the adjusted clustering result, calculating the voltage and current corresponding to the maximum power point of the photovoltaic module by using an MPPT algorithm, and synchronously generating an adjustment instruction pointing to the same kind of photovoltaic modules. According to the method, the photovoltaic modules are clustered according to the environmental parameters and the working parameters of the photovoltaic modules, only one photovoltaic module is analyzed for each type of photovoltaic modules, the control instruction of one type of photovoltaic modules is synchronously determined, and the data acquisition and analysis cost is greatly reduced on the basis that the adjustment effect is only reduced to some extent.

The invention discloses a photovoltaic MPPT (Maximum Power Point Tracking) control algorithm, which relates to the technical field of photovoltaic control algorithms, utilizes the characteristics of simple structure, high convergence speed, high global optimization capability, wide applicability and the like of a gradient optimization algorithm, and improves the defects of premature convergence and sensitivity to control parameters of the gradient optimization algorithm. Meanwhile, the photovoltaic output energy efficiency and the stability of the photovoltaic output energy efficiency serve as the evaluation basis, an MPPT algorithm performance evaluation model is constructed through an analytic hierarchy process, photovoltaic MPPT performance is evaluated, and GTO performance is verified and improved.

The application discloses a kind of based on reinforcement learning's light storage fills integrated system and power distribution control method, it is related to light storage fills technical field, it is difficult to take into account dynamic response speed, operating stability and energy management efficiency under complex working condition technical problem.The method comprises: based on maximum power point tracking MPPT algorithm determines the maximum power point of photovoltaic power generation unit for electric energy output;Real-time acquisition is carried out to multiple operating parameters by reinforcement learning power compensation agent, the power deviation between total output power and reference power is calculated, and proportioning treatment is carried out, and state vector is inputted jointly;Based on multiple input state vectors, multiple target weighted comprehensive reward function, obtain power compensation deep neural network;Based on real-time operating parameter, power compensation deep neural network carries out inference processing, obtains the power regulation amount of energy storage unit, enters preset working mode.The application realizes the flexible, accurate and safe distribution of power between photovoltaic, energy storage and power grid.

The application discloses a power supply management system based on distributed power grid energy storage equipment, and relates to the technical field of power supply management. The system collects and pre-processes light intensity and temperature data in a fixed time period, then reconstructs a phase space, obtains a maximum Lyapunov exponent through a small data amount method, compares the maximum Lyapunov exponent with a threshold value, selects an MPPT algorithm or an LSTM-MPPT algorithm to track the maximum output power of solar energy, and effectively improves the accuracy of maximum output power tracking. The maximum output power is sorted by time, and the slope k between the two points is obtained. Whether to start the standby energy storage equipment is determined by the size of k, and the charging and discharging conditions of the standby energy storage equipment are determined by the positive and negative of k. After starting the standby energy storage equipment, the loss of electric energy transmission between solar energy and the standby energy storage equipment is compared with the electric energy consumed by moving the standby energy storage equipment to solar energy, so as to select wire transmission or move the standby energy storage equipment, thereby avoiding electric energy loss.

The present invention discloses a 2000W photovoltaic intelligent MPPT power supply control method and system for an energy storage battery. The method comprises: obtaining a photovoltaic input voltage; detecting whether the photovoltaic input voltage is within a preset voltage range; if the photovoltaic input voltage is within the preset voltage range, performing forward or reverse perturbation processing on the photovoltaic input voltage using an MPPT algorithm to obtain a photovoltaic output voltage corresponding to the maximum photovoltaic output power; and charging the energy storage battery based on the photovoltaic output voltage, wherein the photovoltaic output voltage is the photovoltaic output voltage corresponding to the maximum photovoltaic output power. The present invention processes the photovoltaic input voltage using the MPPT algorithm to obtain a photovoltaic output voltage corresponding to the maximum photovoltaic output power, and then uses the photovoltaic output voltage corresponding to the maximum photovoltaic output power to charge the energy storage battery, thereby improving the charging efficiency of the energy storage battery and fully realizing the maximum efficiency of photovoltaic power generation.

The present invention proposes a novel DC energy collection and management chip and its operating method, wherein the chip includes: a low-voltage cold start loop, a novel MPPT algorithm energy collection circuit, and an energy management circuit; the low-voltage cold start loop is used to stimulate the internal voltage conversion circuit at a low voltage level, so that the circuit transitions to a normal working state; the novel MPPT algorithm energy collection circuit is used to collect energy, convert the collected ambient energy into electrical energy, and achieve maximum power tracking through a transient enhanced MPPT algorithm circuit; the energy management circuit is used to judge the state of CSTOR, input the judgment result into a control module to generate different enable signals UV and EN, and activate the corresponding management modes Q1 and Q2. The present invention activates the charging management circuit to store excess energy in a secondary energy storage element, a supercapacitor or lithium-ion battery, and activates the DC-DC buck converter to output a stable voltage for the system load, thereby achieving high-efficiency management of DC environmental energy such as photovoltaic and thermoelectric energy.

The present application relates to photovoltaic gateway technical field, propose a kind of photovoltaic four can gateway management method and system, the management method includes: based on electrical parameter, equipment state parameter and environmental parameter, construct photovoltaic power generation power prediction model, and output future time period's photovoltaic power generation power prediction value;According to the fluctuation degree of photovoltaic power generation power prediction value, the fluctuation degree of photovoltaic power generation power prediction value is calculated, and based on fluctuation degree self-adapting adjustment MPPT algorithm's perturbation step length to track the maximum power point of photovoltaic module;Based on environmental parameter and electrical parameter, construct photovoltaic power generation power fitting model, by comparing the deviation of real-time power generation power and fitting power, determine photovoltaic panel dust accumulation state, and generate cleaning suggestion based on future weather forecast;Based on electrical parameter, equipment state parameter and environmental parameter, construct fault diagnosis model, and carry out real-time evaluation and fault early warning to photovoltaic panel state.

The invention provides an MPPT (Maximum Power Point Tracking) control method and device for a two-stage flyback micro inverter, relates to the photovoltaic field, and solves the technical problem of insufficient efficiency and adaptability under complex working conditions due to the fact that an existing MPPT algorithm cannot give consideration to dynamic tracking speed and steady-state control precision in the two-stage flyback micro inverter. The method comprises the following steps: collecting direct current side voltage and direct current side current of a photovoltaic module, and calculating current input power; updating the maximum power based on the current input power and the maximum power; determining to enter an MPPT mode or a constant power mode based on the currently obtained maximum power and the set power; calculating an expected voltage reference in an MPPT mode or a constant power mode; according to the deviation between the expected voltage reference and the output voltage, the PWM duty ratio is analyzed through a PI controller. The MPPT control method and the MPPT control device are used in the MPPT control process of the two-stage flyback micro inverter.

The invention provides a photovoltaic air conditioning system bus voltage dynamic adjusting method, a photovoltaic air conditioning system and a photovoltaic air conditioner, and belongs to the technical field of household appliances. The method comprises the steps that the air conditioner electricity demand is solved according to the compressor operation frequency, and the system state of the photovoltaic air conditioner is judged in combination with photovoltaic power generation power; when it is judged that the system state of the photovoltaic air conditioner is in an inversion mode, the bus voltage value is adjusted to the maximum power output point through an MPPT algorithm; and when it is judged that the state of the photovoltaic air conditioning system is a rectification mode, a reinforcement learning algorithm is adopted to set a bus voltage initial value, and the bus voltage is optimized to a bus voltage target value through a PID control algorithm. According to the method, the bus voltage is adjusted to the optimal value in real time according to the electricity demand of the air conditioner, it is ensured that the system can stably operate under different operation conditions, the overall stability and reliability of the system are improved, and the method is suitable for the photovoltaic air conditioner system under various complex working conditions.