1082 results about "Photovoltaic power plants" patented technology

A solar photovoltaic plant is disclosed where a number of distributed DC-to-DC converters are used in conjunction with a central DC-to-AC converter. Each DC-to-DC converter is dedicated to a portion of the photovoltaic array and tracks the maximum power point voltage thereof. The DC-to-DC converters also boost the photovoltaic voltage and regulate a DC output current for transmission to the central DC-to-AC converter. Five distinct advantages are had over the prior art. First, efficiencies in intra-field power collection are greatly improved by transferring power at higher DC voltages. Second, the number of independent photovoltaic maximum power point trackers in the power plant can be increased, in a cost effective manner, to optimize the overall photovoltaic array energy harvest. Third, each DC-to-DC converter output “looks” like a current source at the input of the DC-to-AC converter and therefore can be easily paralleled. Fourth, the current source nature of the DC-to-DC converter outputs enables the DC-to-AC converter to operate with a minimum, fixed DC bus voltage to provide maximum DC-to-AC power conversion efficiencies. And fifth, each distributed DC-to-DC converter can isolate a faulted portion of the photovoltaic array while the remainder of the array continues producing power.

A method for forecasting reduction in sunlight intensity due to cloud cover at a photovoltaic power plant is described. The method comprises determining characteristics of one or more clouds from sensors surrounding the photovoltaic power plant. The cloud characteristics are used to create a 3D map of the clouds. The 3D map in combination with information on the angle of the sun is used to create a 3D projection on the surface of the earth, resulting in a 2D surface irradiance map. The 2D surface irradiance map may be taken in successive projections or used in combination with wind speed data to forecast fluctuation in irradiance at the photovoltaic power plant. The forecasted reductions in power may be used to enact measures at the plant such as reducing the power output of inverters to prevent sudden fluctuations in the power output of the photovoltaic plant feeding the utility.

The subject matter of the invention is an inverter (3), more specifically for use in a photovoltaic plant (1) with a direct voltage input (connection terminals 4; 5) for connection to a generator (2) and an alternating voltage output (connection terminals 7; 8) for feeding into an energy supply network (6) as well as with a DC-AC converter (12) with semiconductor switch elements (15) and an intermediate circuit (11), at least one short-circuit switch element (18) being connected in parallel to the generator (2), so that the voltage will not exceed a maximum voltage value neither at the connection terminals (4; 5) of the generator (2) nor between the connection terminals (9; 10) of the inverter. This is achieved in that the inverter (3) comprises, in the intermediate circuit (12), a buffer capacitor (14) that is connected to the generator (2) through a protection diode (17) so that said buffer capacitor (14) will not be discharged upon actuation of the short-circuit switch element (18), the generator (2) working according to a clock rate in the short-circuit mode of operation.

The invention discloses a method and a system for intelligent centralized monitoring and management of a photovoltaic power station. The method includes the steps: acquiring and analyzing meteorological data of the photovoltaic power station; acquiring signals of an inverter, a circuit breaker and a transformer of the photovoltaic power station and receiving remote control signals to control related modules; acquiring voltage, current and component temperature data of each sub-module of the photovoltaic power station; converting the data into proper protocols, transmitting the protocols to a network switch through a network and finally transmitting the protocols to a monitoring computer and a server; displaying the data. Operation, maintenance and management of the distributed power station are realized by the centralized monitoring and management method, the data of the photovoltaic power station are deeply analyzed, the problem of shortage of data statistics of the photovoltaic power station is solved, and the operation and maintenance management mode of the photovoltaic power station is optimized.

The invention relates to a system for monitoring a photovoltaic battery pack string and belongs to the field of running and management of a photovoltaic power generation system. In a photovoltaic power station, photovoltaic battery packs are connected in series and then are connected with a header box according to specific conditions, photovoltaic battery pack strings are connected in parallel, and the header box is connected with a grid-connected inverter. When the typical problems of connection, dust accumulation, component obsolescence difference and the like in a photovoltaic battery occur, the efficiency of the photovoltaic power generation system is influenced, and a monitoring system is needed to be arranged in the header box to monitor the photovoltaic battery pack string. The monitoring system can effectively manage the photovoltaic power station by acquiring photovoltaic pack string parameters, and combining other system parameters of the power station to realize autodiagnosis and effectively identify the problem of the power station. The system comprises a singlechip system, a power supply circuit, a voltage detection circuit, a current detection circuit, an intelligent communication interface circuit, an electrical meter chip and the like. In the system, a large-scale integrated circuit is used, and the system has a small volume, is low in energy consumption, has high reliability, and realizes the capacity of continuously monitoring the photovoltaic pack string in the life of the photovoltaic power generation system when assembled in the photovoltaic header box.

The invention discloses a wind and photovoltaic generation power prediction system with multiple prediction modes. The system is characterized by comprising a numerical value weather prediction data acquisition module for inputting numerical value weather forecast data serving as basic data of a prediction algorithm, a prediction mode selection module used for selecting a proper prediction algorithm to predict the power of a wind power plant or a photovoltaic power plant, a prediction algorithm module used for predicting the power of the wind power plant or the photovoltaic power plant and comprising a physical model, an adaptive logic network algorithm model and a BP neural network model, and a prediction result storage module for storing result data predicted by the prediction algorithm module. According to the method, the numerical value weather forecast data is used as input data of the prediction algorithm, the most proper prediction method is selected through the mode selection module, and a power prediction result is obtained.

A system is disclosed for extracting a medium DC voltage from a plurality of PV modules arranged in an array and supplying the medium DC voltage to inverters located outside the array near a point of interconnection with a utility grid.

The invention provides a photovoltaic power station intelligent monitoring analysis platform and a method thereof. The intelligent monitoring analysis platform comprises an equipment operation state monitoring module, an equipment operation state evaluation module and a statistical analysis module, the equipment operation state monitoring module collects equipment operation state data in the photovoltaic power station, screens and stores the data, and analyzes the screened data to obtain equipment operation state data; the equipment operation state evaluation module evaluates the equipment operation state according to the equipment operation state data, performs fault early warning and fault diagnosis, and outputs a fault diagnosis result; and a statistical analysis module performs analysis and calculation based on the equipment operation state data and the fault diagnosis result, and displays a statistical analysis result. The multiple functions of photovoltaic power generation powerprediction, equipment operation monitoring, fault early warning, fault diagnosis, operation management, statistical analysis and the like are integrated, and the problems of lack of operation and maintenance means, many accidental fault damage events, easy interference of power generation efficiency and the like of the current photovoltaic power station are solved.

The invention discloses a photovoltaic power station mobile operation method based on a dynamic adaptive task scheduling strategy. According to the method, matching is performed in multiple dimensions through the dynamic adaptive task scheduling strategy; an operation task is distributed to assigned operation personnel, wherein comprehensive consideration in multiple dimensions of task finishing deadline, task predicated duration time, task type, task complexity, task priority, task operation location, operation skill requirement and operation role requirement for finishing the task is performed. The operation personnel perform comprehensive consideration in dimensions of operation skill, distributed operation task, role set and current location. After the task is distributed, each operation task is dispensed to the distributed operation personnel in real time. After the operation task is finished, real-time tracking and evaluation are performed on a work result of the operation personnel according to operation personnel feedback information. The photovoltaic power station mobile operation method has advantages of improving operation automatic degree of an intelligent photovoltaic power station, improving operation efficiency and reducing operation cost.

The invention discloses photovoltaic panel cleaning equipment for a photovoltaic power plant. The photovoltaic panel cleaning equipment comprises a track fixedly installed on the ground and a supporting arm, two pairs of supporting columns are fixedly installed on the bottom surface of the supporting arm in a bilaterally symmetrical manner, a wheel rotationally arranged on the bottom surface of each supporting column, and the wheels can roll on the track. When a cleaning motor is started, the cleaning motor drives a cleaning shaft to rotate, the cleaning shaft rotates to drive a cleaning brushto rotate to clean a photovoltaic panel, working can be conducted in the photovoltaic power plant, and cleaning work can be efficiently completed. When cleaning is conducted, the cleaning angle of the cleaning equipment can be adjusted through the inclination angle of the photovoltaic panel, the cleaned photovoltaic panel can be wiped again, and therefore the photovoltaic panel can be rapidly cleaned; and water in the cleaning process can be directly recycled, not only can the photovoltaic panel be cleaned thoroughly, but also the waste of water resources can be reduced.

The invention relates to a short-term power prediction method of a photovoltaic power plant based on density peak hierarchical clustering. The method comprises the following steps: (A) obtaining prediction day meteorological data, an SVM identification model for weather type identification, and power prediction models corresponding to different weather types; (B) according to the prediction day meteorological data, using the SVM identification model to carry out layer-by-layer identification, and determining the weather type of a prediction day; and (C) using the prediction day meteorological data as the input of the power prediction model of the corresponding weather type, and outputting a power predicted value corresponding to the prediction day; wherein the SVM identification model and the power prediction models are obtained in the following way: carrying out hierarchical clustering of historical day meteorological data to form K cluster sets each corresponding to a weather type, further establishing the SVM identification model for identifying weather types, and establishing the power prediction model based on the weather type at the same time. Compared with the prior art, the method has advantages such as high prediction precision.

The invention relates to a photovoltaic power plant output power prediction method based on a weighted FCM clustering algorithm. The method provided by the invention comprises the steps that a weather data sample which matches a meteorological data sample to be predicted and the corresponding photovoltaic power plant output power are selected from the existing photovoltaic power plant operation database and are used as a reference sample; through knowledge evaluation, a typical data matrix is selected and is combined with the meteorological data sample to be predicted; after normalization, a final standard sample matrix is formed and is used as an input variable of the algorithm; and after property-weighted FCM clustering algorithm iteration, output power corresponding to the meteorological data sample to be predicted is acquired. According to the invention, the shortcomings of complex meteorological factors, unbalanced influence on the output power, meteorological data randomness and uncertainty and the like are overcome; the method has the advantages of fast prediction and high accuracy; a prediction result provides a data support for rational resource dispatching and scientific overall planning of the power industry; and good economic and social benefits are acquired.

The invention discloses a method for photovoltaic power station group region power prediction on the basis of an improved RBF neural network. The method comprises the steps of dividing a whole region into a plurality of sub-regions, performing data quality control, and removing data points remarkably not conforming to practice; calculating relative coefficients between photovoltaic power station measured power in every sub-region and sub-region total measured power, and selecting a plurality of standard photovoltaic power stations for every sub-region; utilizing a method of combining physics and statics to achieve short-term power prediction of the standard photovoltaic power stations; establishing a particle swarm optimization RBF neural network model based on a genetic operator, and predicting short-term power of every sub-region; and accumulating power prediction results of every sub-region to obtain prediction total power of a region photovoltaic power station group. The method aims to help a power scheduling department to formulate next day generation schedules according to the region power prediction results, real-time scheduling adjustment is optimized, spinning reserve capacity of a power system is reduced, system running costs are reduced, and the system photovoltaic acceptance capability is further improved.

The invention relates to a photovoltaic array fault diagnosis method and device based on spatiotemporal distribution characteristics. A photovoltaic output time component and a spatial component are calculated and obtained by a time and spatial distribution function for the photovoltaic array output starting from the historical operation data and the historical environment data of a photovoltaic power plant, the components are used as a training data set, a probabilistic neural network is trained by the training data set, a photovoltaic array fault diagnosis model is obtained, a time functionand a spatial function for photovoltaic branch output are established to effectively describe the distribution law of string current under different fault conditions, the photovoltaic power station DCside array fault diagnosis method established based on the probabilistic neural network is high in diagnosis precision, and finally, branch current data are inputted to the photovoltaic array fault diagnosis model to realize diagnosis of multiple types of fault, and the existing data of the actual project can be fully utilized effectively.

The invention discloses a horizontal single axis sun-tracking support apparatus. The apparatus comprises at least two groups of photovoltaic panel assemblies, wherein the photovoltaic panel assemblies each consist of a photovoltaic panel and a fastener that is used for fixing the photovoltaic panel. The photovoltaic panel assembly is fixed on a drive tube that can drive the photovoltaic panel assembly to rotate. The photovoltaic panel assembly and the drive tube are symmetrically arranged on both sides of a rotary reducer, and the drive tube is connected to an output end of the rotary reducer. The rotary reducer is mounted on a main supporting pillar, and is connected to a motor that supplies a power source to the rotary reducer. An aligning structure with a self-lubricating bearing disposed inside is arranged on the drive tube that is on a side end of each photovoltaic panel assembly away from the rotary reducer. Each aligning structure is correspondingly disposed on a subordinate supporting pillar. The apparatus has the advantages that a ''0'' eccentric design is implemented by adding the aligning structure, so as to achieve a self-balancing effect; functions of autonomous drive and control and self-cleaning and the like are implemented; and no external power supply is required to supply power, so that cables are less used, and the apparatus is applicable to different sizes of photovoltaic power plants.

A distributed photovoltaic (PV) power plant includes a plurality of distributed dc-dc converters. The dc-dc converters are configured to switch in coordination with one another such that at least one dc-dc converter transfers power to a common dc-bus based upon the total system power available from one or more corresponding strings of PV modules. Due to the coordinated switching of the dc-dc converters, each dc-dc converter transferring power to the common dc-bus continues to operate within its optimal efficiency range as well as to optimize the maximum power point tracking in order to increase the energy yield of the PV power plant.

The invention belongs to power systems, and relates to an electromechanical transient modeling method based on a VSC (Voltage Source Converter) grid-connection photovoltaic power station and a battery energy-storage power station. For the development form of increasing new-energy generating equipment based on the VSC grid-connection, based on the consideration to computation characteristics of electromechanical transient simulation of large power systems, a method for modeling by combination of various devices is used, and a high-expandability and strong-practicability modeling method of the new-energy generating equipment based on the VSC grid-connection is realized by combining with the own operating characteristics of the VSC, thus, the aim of quick and accurate modeling in simulation calculation of the large power systems can be realized.

The present invention discloses a photovoltaic power station monitoring and operation integration system. The technical scheme of the invention concretely comprises the steps of: detecting generationcurrents and voltages of photovoltaic cells through a Hall sensor in photovoltaic combiner boxes and transmitting the generation currents and voltages to a processor; connecting and gathering detection modules of the plurality of combiner boxes in a RS485 communication mode to perform transmission through a wireless module; determining a photovoltaic panel fault condition through a photovoltaic panel fault rapid detection location system based on an unmanned aerial vehicle; monitoring and cleaning a photovoltaic panel through a cleaning robot carrying a dust detection sensor; locating actual positions of faults through the photovoltaic panel fault rapid detection location system based on the unmanned aerial vehicle, and sending fault information through a wireless communication module; andapplying the wireless communication network to connect each system of a power station to allow operation and maintenance work to be integrated and intelligent.

The invention provides a random production analog method of an electric system with a large-scale photovoltaic power station. The method includes the following steps that conventional unit data, light resource data and time sequence load data are acquired; the equivalent effective capacity cumulant of all orders of a system unit without the photovoltaic power station is determined; time sequence effective capacity probability distribution Beta models and parameters of photovoltaic power generation at corresponding time frames are sequentially acquired; equivalent effective capacity distribution probability models and parameters of the system unit with the photovoltaic power station at corresponding time frames and reliability indexes under the corresponding load levels are sequentially obtained; and the reliability indexes of the system under the total load level are obtained in a hop-by-hop accumulation mode. The method relates to correlation on the time sequence between photovoltaic power station output and the load change, random fluctuation of the photovoltaic power station output is contained in system equivalent effective capacity probability distribution through cumulant correction, and the method is used for acquiring the reliability indexes of the system under the corresponding running modes.

The invention discloses a photovoltaic power station intelligent inspection method and a system based on an unmanned aerial vehicle image. The system comprises an unmanned aerial vehicle data import module, an inspection data analysis module, a deep learning algorithm module, a digital photovoltaic power station module, an inspection result management module and an inspection playback module. According to the invention, a deep learning algorithm is introduced into multi-modal inspection image data, so that more accurate photovoltaic defect detection is realized; by establishing a digital photovoltaic power station, the expression of the overall layout of the photovoltaic power station and the playback of the inspection process are realized; through registration of a virtual scene image and a real acquired image, the position and the number of a photovoltaic panel in a real scene are acquired; a single-batch inspection process and a single-batch inspection result are visually displayed through a playback function, so that accurate detection of defects of the photovoltaic panel is realized; and an inspection playback function is constructed, and the inspection process is visualized, so that intuitive debugging and inspection management of operation and maintenance personnel are facilitated, the automatic operation and maintenance level of the photovoltaic power station is greatly improved, and the inspection efficiency of the photovoltaic power station is effectively improved.

The invention discloses a multi-factor based photovoltaic power station middle-and-long-term generating capacity prediction method including the following steps of A) based on the data of an environment detector and a weather station, acquiring the power station dimensions, inclination angles, and historical daily level radiation quantities, and selecting the number of days in the month, the date sequence number in a year, solar constants, and the ground reflectivity; B) calculating the annual inclined plane total radiation quantity I; C) calculating the comprehensive efficiency of a photovoltaic power plant; D) calculating the annual effective hour number of the photovoltaic power plant; E) calculating the generating capacity of the first year; and F) calculating the generating capacity value of the nth year and the total generating capacity for many years of the photovoltaic power plant. The prediction method is simple in calculation, efficient, and stable, and has good prediction benefits and good application prospects.

The invention discloses a photovoltaic power station hot spot detection and positioning method based on a thermal infrared image. Pictures shot by a thermal imager carried by an unmanned aerial vehicle are infrared pictures, the resolution ratio is very low, the form of hot spots is usually very small, the accuracy of hot spot recognition is very low, and accurate positioning is difficult. Aimingat hot spot identification, the invention provides a UAV-YOLO model, a neural network residual error unit is added for fusion, characteristics of a front network are utilized to a greater extent, andhot spot characteristics of a far visual angle are learned; a YOLOv3 backbone network architecture is improved, and more hot spot appearance feature information can be learned in a front-end network.Aiming at hot spot positioning, the invention provides a geometric positioning algorithm, and the longitude and latitude of a hot spot are calculated through the longitude and latitude of an image center point, a yaw angle, the shooting height of an unmanned aerial vehicle and other information. According to the invention, the hot spot positioning precision is improved on the premise of ensuring the hot spot identification accuracy.

On an inverter (1) for converting an electric direct voltage, in particular of a photovoltaic direct voltage source into an alternating voltage with a direct voltage input with two terminals (DC+, DC−) and one alternating voltage output with two terminals (AC1, AC2) and with one bridge circuit including semiconductor switching elements (S1-S6), said bridge circuit comprising one first bridge branch (Z1) including four switching elements (S1-S4) and one second bridge branch (Z2) including two additional switching elements (S5, S6) as well as a freewheeling circuit provided with additional diodes (D7, D8), the efficiency is further increased without high frequency interferences and capacitive leakage currents having the possibility to occur on the generator side. This is achieved in that a respective one of the freewheeling diodes (D7, D8) forms a freewheeling branch together with a respective one of the switching elements (S2, S3) located in the first bridge branch (Z1), said freewheeling branch carrying a freewheeling current in a condition decoupled from the direct voltage.

The invention discloses a photovoltaic power station unmanned aerial vehicle inspection system. The system comprises: an inspection unmanned aerial vehicle provided with a flight control module and apower module, a wireless communication module, a visible light camera and an infrared thermal imaging camera which are electrically connected with the flight control module; an unmanned aerial vehiclehangar provided with an inner cavity capable of accommodating the inspection unmanned aerial vehicle and a data transmission module, wherein the data transmission module can be in wireless communication with the wireless communication module; and an unmanned aerial vehicle management center comprising a data processing server and a terminal device, wherein the data processing server can communicate with the data transmission module, and the terminal equipment is provided with a display module. The photovoltaic power station unmanned aerial vehicle inspection system can know whether a photovoltaic panel breaks down or is damaged and can know the position of the photovoltaic panel according to the image information shot by the unmanned aerial vehicle and the corresponding flight information, so that maintainers can complete an inspection task without on-site control, and the inspection efficiency is improved.

The invention relates to a parameter identification-based photovoltaic power generation system fault diagnosis method and a parameter identification-based photovoltaic power generation system fault diagnosis system. The parameter identification-based photovoltaic power generation system fault diagnosis method includes the following steps that: the fault diagnosis model of a photovoltaic power generation system is built, and the optimal solutions of the fault diagnosis model are obtained; the fault diagnosis model is trained; and fault diagnosis is carried out on the photovoltaic power system based on the trained fault diagnosis model. According to the parameter identification-based photovoltaic power generation system fault diagnosis method of the invention, according to problems which easily appear in the photovoltaic power generation system, namely, open-circuiting and short-circuiting of a photovoltaic battery assembly, the overload of an inverter and the failure of a control system, the parameter identification-based photovoltaic power generation system fault diagnosis model under a mismatch condition is built; an I-U curve is obtained according to the data of a photovoltaic power plant in different working conditions; analog simulation is carried out on the actually-measured I-U curve, so that the optimal solutions of the parameters of the model are obtained; an RBF neural network is utilized to train the model, so that the trained fault diagnosis model is obtained; and test samples or real-time samples of the photovoltaic power plant are inputted to the model, so that fault diagnosis can be carried out.

A computer-implemented method for dynamically controlling a plurality of photovoltaic (PV) inverters is provided. The method is implemented by a dynamic photovoltaic (DP) controller in communication with a user interface. The method includes receiving, from an electrical meter, an electrical value of a plurality of electrical values associated with an inverter of the plurality of PV inverters, where the electrical meter is associated with point of interconnection between the plurality of inverters and an electrical grid, calculating, an electrical metric based on the electrical value, generating, a command signal for the inverter based on the calculated electrical metric, transmitting the command signal to the inverter, the command signal configured to change an output power level of the inverter, and causing the inverter to change the power level via the command signal.

Arc flash mitigation devices are employed to protect personnel during maintenance of photovoltaic inverters. During normal operation, an alternating current (AC) output of a photovoltaic inverter is coupled to a low voltage winding of a step up transformer through a bus-bar (e.g., an electrically conductive interconnect), which has higher current rating than a fuse. During maintenance, the bus-bar is replaced with the fuse. The fuse may be employed in conjunction with a switch. The switch may be a disconnect switch that places the bus-bar in parallel with the fuse during normal operation, and decouples the bus-bar from the fuse during maintenance. The switch may also be a transfer switch that places either the bus-bar or the fuse in series with the AC output of the photovoltaic inverter and the low voltage winding of the step up transformer.

The present invention relates to a rock anchor foundation structure suitable for a mountain photovoltaic module and a construction method of the rock anchor foundation structure. A technical solution of the present invention is as follows: the rock anchor foundation structure comprises a drill hole drilled in a rock slope, an anchor rod module arranged in the drill hole and a photovoltaic power station module. The photovoltaic power station module is connected with the anchor rod module through a hollow connecting steel pipe; the photovoltaic power station module comprises a bracket welded on the top of the hollow connecting steel pipe, a beam mutually hinged with the top of the bracket and a photovoltaic cell panel arranged at the upper part of the beam. The rock anchor foundation structure of the present invention is suitable for the technical fields of around treatment and foundation engineering design.

The invention particularly discloses an industrial GPRS monitoring terminal. The industrial GPRS monitoring terminal comprises a hardware circuit and a software system operating in hardware, wherein the hardware circuit comprises an embedded microcontroller, a GPRS wireless communication module, a power module, a GPRS power management module, a storage module, an input and output module, a hardware watchdog and an indicator lamp; the embedded microcontroller starts or stops the supplying of power to the GPRS wireless communication module by controlling the GPRS power management module; the software system is composed of a bottom-layer hardware driving program, an embedded operating system and a multi-task application program. The high-reliability GPRS monitoring terminal provided by the invention can normally operate in severe application environments such as photovoltaic power stations and wind power plants.