1280 results about "Photovoltaic system" patented technology

The invention discloses a micro-grid power control method, system and device based on fuzzy modulation and a storage medium, and relates to the technical field of intelligent grid integration of a photovoltaic system and a micro-grid, and the method comprises the steps: firstly obtaining the real-time power data of a photovoltaic system, carrying out the control processing through fuzzy logic, and calculating a reference instruction; according to the reference instruction, hysteresis time is dynamically adjusted through modulation hysteresis control, and an inverter switching signal is generated; converting direct current into alternating current based on the switching signal and a power switching device, injecting the alternating current into the micro-grid, calculating active and reactive power reference values, ensuring that the system operates according to a unit power factor, and giving active power to the reference value; according to the method, the power control precision and adaptability of the micro-grid are improved, excessive switching of the inverter is avoided, loss is reduced, the service life is prolonged, power matching and stable transmission are achieved, reactive loss is reduced, bus voltage is stabilized, harmonic waves can be reduced, the electric energy quality is improved, and efficient and stable operation of the micro-grid is guaranteed.

The invention provides an intelligent fault diagnosis method and system for a photovoltaic system. The method comprises the following steps: collecting multi-source heterogeneous operation parameter data of the photovoltaic system based on an intelligent sensor network and carrying out standardized preprocessing; local feature extraction is carried out on edge nodes, a frequency moment is calculated, data summary aggregation is carried out through a frequency moment optimization algorithm, and a fusion key feature vector set is constructed by using a multi-modal data fusion model; performing anomaly detection based on the normal behavior mode baseline, and generating an abnormal state alarm signal and a preliminary anomaly type indication; constructing a weighted graph model based on a system topological structure, constructing a fault association sub-graph by using an approximate spanning tree algorithm, accurately positioning a fault unit and diagnosing a fault type; and generating and executing a self-healing operation scheme according to the fault diagnosis conclusion. Through the distributed multi-modal data fusion and approximate spanning tree fault positioning technology, rapid and accurate diagnosis and autonomous recovery of the photovoltaic system fault are realized, and the system reliability and the operation efficiency are improved.

The invention provides a photovoltaic system and an insulation resistance detection method thereof, the photovoltaic system comprises a plurality of photovoltaic modules, a plurality of low-voltage switches, a plurality of high-voltage switches and a detection control circuit, the low-voltage switches are connected with one or more photovoltaic modules to form a second photovoltaic module, and the high-voltage switches are connected with the detection control circuit. The high-voltage switches are connected with one or more second photovoltaic modules which are connected in parallel, and the detection control circuit is connected with the low-voltage switches and the high-voltage switches, controls the high-voltage switches to be turned off in sequence, controls the corresponding low-voltage switches to be switched to a second switch state, determines the faulted first photovoltaic module according to the insulation resistance of the photovoltaic system, and ends the operation. The method does not need to employ a mode of manually plugging and unplugging the string or changing the voltage of the string, can achieve the detection of all fault assemblies, improves the detection precision, and improves the detection range.

The invention provides a key node identification-based distributed photovoltaic system energy storage configuration double-layer optimization method. The method comprises the following steps of establishing a power generation probability density model and a power utilization probability density model of a distributed photovoltaic system; determining an energy storage key node in the distributed photovoltaic system; a double-layer optimization target and constraint conditions of an energy storage configuration scheme are established, the energy storage configuration scheme comprises position and capacity schemes of a plurality of energy storage units arranged in the distributed photovoltaic system and time-phased operation schemes of each energy storage unit, and the double-layer optimization target comprises position and capacity optimization targets of the energy storage units on the outer layer; and the energy storage unit of the inner layer operates the optimization target in different time periods. And based on the energy storage key node, the double-layer optimization target and the constraint condition, determining an optimal energy storage configuration scheme of the distributed photovoltaic system through a double-layer search mode. According to the technical scheme, the optimal energy storage configuration scheme of the distributed photovoltaic system can be efficiently and accurately obtained.

The invention relates to the technical field of photovoltaic support monitoring, and discloses a photovoltaic support displacement safety monitoring method. The method comprises the steps that sensors are installed at different nodes of a photovoltaic support based on a stay wire displacement monitoring system, and horizontal displacement and vertical displacement are collected in real time; correcting the displacement data through multi-dimensional data fusion in combination with environmental factors; and calculating the vibration frequency of the bracket, monitoring the frequency change in real time, and generating a bracket health assessment report and an early warning signal. In the prior art, accurate monitoring of support displacement is difficult to realize under a complex environment condition, and especially under the condition of non-uniform support stress or foundation settlement, accurate displacement monitoring and early warning cannot be provided. According to the invention, through multi-node sensor data acquisition, environmental factor correction and dynamic vibration frequency calculation, accurate monitoring and early warning of the displacement of the photovoltaic support are realized, and the operation safety and reliability of a photovoltaic system are improved.

The invention discloses a cooperative control method and system for a charging pile and a photovoltaic energy storage system, and the method comprises the following steps: obtaining data of different sources, inputting the data into a fusion neural network model, carrying out the prediction of time series data through a deep learning model, carrying out the intelligent decision, and optimizing the electric energy dispatching; constructing an energy scheduling model of quantum calculation, processing a plurality of variables based on quantum calculation, calculating in a multi-target environment by using a quantum annealing algorithm, and solving a multi-target globally optimal solution; edge computing equipment is deployed, data processing and computing capabilities are transferred from a central server to local nodes of the charging pile, the energy storage system and the photovoltaic system, local data processing and real-time optimization are carried out, the multi-objective optimization problem is solved through quantum annealing and a quantum approximate optimization algorithm, the computing efficiency of the scheduling system can be greatly improved, and the scheduling efficiency is improved. And the calculation bottleneck faced by the traditional method is avoided. Data from different sources are integrated, intelligent decision making is carried out through deep learning, and the self-adaptive capacity of the system is enhanced.

The invention discloses a light storage integrated power station coordination control method, device and equipment and a storage medium, and belongs to the technical field of power coordination and management. The method is applied to a control system of a light storage integrated power station, the light storage integrated power station further comprises a load side, a photovoltaic side and an energy storage side, real-time load information of the load side and real-time load information of the photovoltaic side are collected respectively, and real-time meteorological information of the position where the photovoltaic side is located is collected; according to the real-time load information and the real-time meteorological information, respectively predicting load change trends of the load side and the photovoltaic side, and generating an optimal collaborative scheduling strategy according to the load change trends and the electric energy reserves of the energy storage side through a preset light storage integrated coordination model; and performing dynamic coordination control on the load side, the energy storage side and the photovoltaic side according to the optimal coordination scheduling strategy, thereby realizing coordination between the energy storage system and the photovoltaic system, and improving the utilization efficiency of the overall energy.

The invention discloses a maximum correlation entropy adaptive dynamic estimation method containing a distributed photovoltaic power distribution network, and belongs to the technical field of power systems. The invention discloses a maximum correlation entropy adaptive dynamic estimation method for a distributed photovoltaic power distribution network, and the method comprises the steps: building a two-stage three-phase distributed photovoltaic physical model containing a feedback control link, and forming a photovoltaic system state equation containing a differential link; establishing a power distribution network state equation based on a Holt's two-parameter exponential smoothing method; the kernel width parameter of the maximum correlation entropy is adjusted in real time according to the measurement error statistical characteristics; a maximum correlation entropy criterion is adopted as a target function, and a robust Kalman gain updating formula is obtained in combination with a Gaussian kernel function and an adaptive weight matrix; and integrating the robust Kalman gain updating formula into the integral framework of the volume Kalman filtering to complete the dynamic state estimation of the power distribution network. By adopting the maximum correlation entropy adaptive dynamic estimation method containing the distributed photovoltaic power distribution network, the problem that an existing dynamic state estimation method is insufficient in estimation precision in the distributed photovoltaic and non-Gaussian noise power distribution network can be solved.

The invention belongs to the technical field of photovoltaic modules, and relates to a photovoltaic module, a preparation method thereof and a photovoltaic system, and the photovoltaic module comprises a battery piece layer which comprises a plurality of battery pieces which are connected with one another; the back surface of the battery piece layer comprises a coating layer, a grid line, a first adhesive film layer and a first cover plate which are stacked in sequence; a hollow reflective material layer is also arranged between the coating layer and the first adhesive film layer, the average reflectivity of the reflective material layer in a visible light wave band is greater than or equal to 30%, and the coverage area of the reflective material layer in the back surface of the battery piece layer is less than or equal to 70%. The reflective material layer is additionally arranged on the back of the photovoltaic module, so that the double-sided power generation capability is considered while the back color difference is effectively eliminated, and the photovoltaic module is particularly suitable for distributed application scenes.

The invention discloses a source network load storage comprehensive management and control method based on an improved particle swarm algorithm, and the method comprises the following steps: 1, building a source network load storage interaction model in a power distribution network, 2, analyzing the network loss influence factors of the power distribution network, and 3, improving the particle swarm algorithm, and solving a bilevel programming problem. And step 4, based on a double-layer optimization result, the goal of the upper-layer model is to minimize the total cost by determining the position and the capacity of the energy storage station, and the key points of the lower-layer model are to minimize load fluctuation, optimize node voltage and maximize photovoltaic energy consumption so as to obtain an energy storage and photovoltaic system output needing to be executed and a charging strategy of the electric vehicle. The efficiency and the practical value of the optimization strategy in the aspect of reducing the energy consumption of the power grid are fully embodied.

The invention relates to the technical field of photovoltaic, in particular to a photovoltaic module, which comprises a first battery string group, a second battery string group and a third battery string group, the first battery string group is formed by connecting four first battery strings in series, and each first battery string is formed by connecting a plurality of battery pieces in series; the second battery string group is formed by connecting four second battery strings in parallel, and each second battery string is formed by connecting a plurality of battery pieces in series; the first battery string group and the second battery string group are arranged side by side, and the whole first battery string group and the whole second battery string group are connected in series; four parallel first battery strings form a first battery string group, four parallel second battery strings form a second battery string group, and then the first battery string group and the second battery string group are connected in series to form a four-parallel two-string circuit; therefore, the total output current and a conventional assembly using a complete or half battery are ensured to be at the same level, the compatibility of the assembly and an existing photovoltaic system is ensured, and the output power is effectively improved.

The invention is suitable for the technical field of solar cells, and provides a solar cell and a preparation method thereof, a photovoltaic module and a photovoltaic system, and the solar cell comprises a silicon substrate which comprises a first surface and a second surface which are opposite to each other; the doping layer is arranged on at least one of the first surface and the second surface; the passivation layer is arranged on one side, deviating from the silicon substrate, of the doping layer and comprises a through hole; the seed layer penetrates through the through hole and is connected with the doping layer; the passivation layer comprises a first injection part, and the first injection part is at least partially contacted with the seed layer; an injection material corresponding to the first injection part comprises a main preparation material of the seed layer; the main preparation material is the preparation material with the maximum mass ratio.

A photovoltaic module and a photovoltaic system. The photovoltaic module includes a panel, a back plate, a cell sheet layer, and a first encapsulation adhesive film layer, wherein the back plate and the panel are stacked, the cell sheet layer is located between the panel and the back plate, the first encapsulation adhesive film layer is located between the cell sheet layer and the panel, a color layer is provided between the panel and the first encapsulation adhesive film layer, the color layer is a light-transmitting layer, and a relief structure is provided on the side of the panel facing away from the first encapsulation adhesive film layer. The relief structure can reduce the reflection of sunlight on the panel, thereby increasing the incident amount of sunlight and increasing the power generation of solar energy.

The invention relates to the technical field of power system automation, and discloses a distributed photovoltaic spatio-temporal data recovery and unsupervised clustering method and system.The distributed photovoltaic spatio-temporal data recovery and unsupervised clustering method comprises the steps that observation data of a distributed photovoltaic system are collected, and the observation data comprise historical distributed photovoltaic output time sequences; the collected historical distributed photovoltaic output time sequence is used as an input signal to be transmitted to each module of the GRAIL framework so as to drive a network to jointly learn time sequence dynamic characteristics and a clustering structure; wherein the GRAIL framework is a closed-loop iterative structure, and comprises a clustering sensing data generation module, a latent feature representation module and a self-adaptive clustering and refining module. The method can be widely applied to distributed photovoltaic station operation monitoring and abnormity identification scenes, and intelligent regional state recovery and mode grouping are realized.

The invention relates to the technical field of buck-boost switching control, and discloses a buck-boost seamless switching MPPT control method which has remarkable advantages. The single-side boost-buck function can stably control the output voltage in a full-voltage range, and the problem that the efficiency and stability of the system are affected due to the fact that the traditional topology cannot accurately regulate and control the power under the photovoltaic high-voltage working condition is effectively solved. A buck-boost mode is seamlessly switched, the response speed and reliability are improved, and faults caused by improper mode switching are avoided; when the method is applied to an energy storage product, the PV high voltage condition does not exist, the additional control logic can be reduced, the system complexity is reduced, the reliability is improved, meanwhile, the development cost and the maintenance difficulty are reduced, and powerful support is provided for photovoltaic system performance improvement and energy storage product optimization.

The invention provides a thin film battery and a preparation method thereof, a photovoltaic system, a power utilization device and a power generation device, the thin film battery comprises a substrate, a bottom electrode layer, a semiconductor layer and a top electrode layer which are stacked in sequence, and the thin film battery further comprises a first scribing groove group, a second scribing groove group and a third scribing groove group, the semiconductor layer comprises a first semiconductor layer and a second semiconductor layer; the bottom electrode layer, the first semiconductor layer and the top electrode layer form a plurality of sub-cells arranged along a second direction, and the plurality of sub-cells are structurally separated and connected in series through a scribing groove group; the bottom electrode layer, the second semiconductor layer and the top electrode layer form a plurality of diodes arranged in the second direction, the plurality of diodes are structurally separated through the lineation groove group, and the lineation groove group also enables one diode to be connected with a plurality of sub-cells in parallel, so that the sub-cells and bypass diodes can be prepared simultaneously in the process, and the production efficiency is improved. And the sub-battery damage caused by the hot spot effect is avoided.

The invention discloses a large-duration double-source combined supply emergency security vehicle and a control method thereof.The emergency security vehicle comprises a photovoltaic system, a lithium battery system, a hydrogen production system and a hydrogen storage system, the photovoltaic system is connected with the lithium battery system and the hydrogen production system, and the hydrogen production system is connected with the hydrogen storage system; the lithium battery system comprises a fuel cell and a power lithium battery, and the fuel cell is electrically connected with the power lithium battery; the hydrogen production system comprises a PEM electrolytic bath; the hydrogen storage system comprises a modularized hydrogen cylinder group, the power lithium battery is connected with the PEM electrolytic bath through a DC / DC converter, and the PEM electrolytic bath is connected with the modularized hydrogen cylinder group through a high-pressure hydrogen pipeline; the external hydrogen charging interface is communicated with the modularized hydrogen cylinder group, and the modularized hydrogen cylinder group is communicated with a hydrogen inlet of the fuel cell; the method has the advantages that the power and the cruising ability are improved.

The invention discloses an intelligent monitoring, early warning and operation and maintenance management method for a photovoltaic system. The method comprises the following steps: S1, dynamic fusion and edge collaborative acquisition of multi-source heterogeneous data: constructing a full-dimensional data acquisition system covering a photovoltaic module, an inverter, a combiner box, a meteorological environment and a power grid side; a framework of'edge preprocessing + cloud fine fusion 'is adopted, edge nodes realize second-level data synchronization through a lightweight time sequence alignment algorithm, and sensor noise is eliminated by adopting an improved density-based abnormal value filtering algorithm; and the cloud end allocates dynamic weights to data of different frequencies and different types based on a multi-modal data fusion model of an attention mechanism, so that high-precision data fusion is realized. By constructing a full-dimensional data acquisition system and an innovative fusion framework, the problem of data fragmentation of traditional photovoltaic monitoring is solved, the data fusion precision is improved, and a high-quality data basis is provided for subsequent analysis and diagnosis.

The invention discloses an insulation fault detection method, an inverter and a photovoltaic system, and the method comprises the steps: detecting an MPPT unit with an insulation fault, controlling the switching tube of the MPPT unit with the insulation fault to be switched off, and controlling the switching tubes of other normal MPPT units to be switched on; and a turn-off device corresponding to the MPPT unit with the insulation fault is controlled, so that the m photovoltaic strings corresponding to the MPPT unit with the insulation fault independently charge the direct current bus capacitor in sequence, and the photovoltaic string with the insulation fault is detected. According to the invention, the photovoltaic string with the insulation fault can be accurately positioned, and the manpower, time and economic cost for manually checking the position of the fault string for the second time can be saved.

The invention discloses an intelligent greenhouse irrigation system taking water from air, which belongs to the field of agricultural engineering and intelligent control and comprises a greenhouse main body, a flow guide device, a photovoltaic module, a storage battery, a multi-source sensor, a digital twinborn module, an irrigation decision module, an intelligent execution module, a visual management platform and an ecological collaboration module. The greenhouse main body realizes cooling and condensed water collection by utilizing a surface functional coating, and water is guided into the water cellar through the flow guide device; the photovoltaic system cooperates with the phase-change material to realize power generation, heat storage and temperature compensation; the digital twinborn module is fused with multi-source data to construct a virtual model, and crop water demand and environment change are predicted; the irrigation decision module formulates an optimization strategy according to the water volume, the electric quantity and the prediction result; the intelligent execution module accurately controls irrigation and feeds back and adjusts in real time; and the ecological cooperation module is linked with regional environment data to realize overall management of greenhouse water consumption and ecological protection. According to the system, cooperative utilization of water resources and energy is achieved, and irrigation intellectualization is improved.

The invention provides an insulation detection method and device of a photovoltaic system, a controller and the photovoltaic system. The method comprises the following steps: detecting whether the photovoltaic system has an insulation fault; if the photovoltaic system has the insulation fault, determining the position of the insulation fault in the fault photovoltaic string according to the ratio of the voltage to ground of the first pole of the photovoltaic system to the open-circuit voltage of the photovoltaic string; the first electrode is any one of a direct-current bus positive electrode and a direct-current bus negative electrode; and respectively and independently controlling the positive and negative electrodes of the input end of each direct current conversion circuit to be short-circuited, and for each MPPT module, determining whether the insulation fault position is located in the MPPT module based on the change of the voltage to ground of the first electrode before and after the short circuit of the MPPT module. According to the photovoltaic system insulation fault detection method and the photovoltaic system insulation fault detection device, insulation faults from a system level to a component level can be spanned, additional devices are not needed, manpower, time and economic cost required by field troubleshooting is reduced, and the detection efficiency of the photovoltaic system insulation faults is improved.

The invention relates to the field of circuit breaker grid-connected and off-grid conversion, in particular to a system for realizing grid-connected and off-grid conversion based on a residual current protection circuit breaker, which is characterized in that a data sensing module acquires data through a Modbus-RTU protocol, processes the data through a linear active disturbance rejection control algorithm and outputs a pure data sequence; the power-off state analysis module predicts the power-off probability in combination with an echo state network algorithm, judges the island state through an improved island detection algorithm, fuses multi-source information by utilizing a D-S evidence theory, and judges whether the mains supply is powered off or not to generate a control instruction; the cooperative verification module carries out priority ranking on PCS based on an analytic hierarchy process and a fuzzy evaluation method and carries out cooperative control on off-grid mode switching by confirming the state of the commercial power, and the commercial power recovery module calculates the maximum recoverable power according to the rated power of the PCS and the SOC of a battery through load priority scheduling and a greedy algorithm, and gradually recovers load power supply; the system significantly improves the anti-interference capability of grid-connected and off-grid conversion, and is suitable for regions with unstable power grids. Customers feed back that the system is charged depending on an original photovoltaic system under the condition that the mains supply is in long-term power failure, so that the power utilization condition is greatly improved, and the power utilization difficulty is relieved.

The invention discloses a distributed photovoltaic multi-agent resource allocation method, system and device based on the game theory and a medium, and relates to the technical field of resource allocation, and the method comprises the steps: determining each agent participating in contribution in a distributed photovoltaic system, and defining a revenue function according to the revenue factor of each agent; constructing a non-cooperative game model by taking each main body as a decision maker and taking own income maximization as a target, and solving a corresponding Nash equilibrium strategy combination; on the basis of the non-cooperative game model, allowing the subjects to form an alliance, constructing a cooperative game model, and calculating the Sharpley value of each subject; and performing income distribution on each main body in the alliance according to the Shapley value, and adding a dynamic adjustment and incentive mechanism on the basis of an income distribution result to adapt to market condition changes. According to the method, the non-cooperation and cooperation combined multi-agent game model is constructed, and the Sharpley value is combined to carry out income distribution, so that efficient cooperation and fair distribution of the participants in the distributed photovoltaic system are realized.

The invention discloses a photovoltaic access power distribution network fault diagnosis method based on fault identification, and particularly relates to the technical field of power grid fault diagnosis, and the method comprises the steps: synchronously obtaining multi-point electrical quantity monitoring data, photovoltaic system inverter operation data and environment data of a power distribution network side, and carrying out the abnormality elimination and delay compensation preprocessing; based on the switching frequency of the photovoltaic inverter and the line parameters of the power distribution network, adaptively selecting a wavelet basis function and a decomposition scale, and extracting a fusion fault feature vector; inputting the feature vectors into a two-channel hybrid neural network model for intelligent diagnosis, and outputting fault section positioning, type classification, severity level and occurrence time information; and finally generating a fault processing instruction according to the diagnosis result. According to the method, the problems of low diagnosis precision, slow response and the like caused by single data source, poor feature extraction self-adaption and simple model structure of the existing method are effectively solved, the accuracy and reliability of complex fault recognition are remarkably improved, and closed-loop automation of fault diagnosis and processing is realized.

The utility model relates to the technical field of back contact, and particularly discloses a back contact cell and a photovoltaic system, the back contact cell comprises a silicon substrate, and the backlight surface of the silicon substrate is provided with a plurality of first areas and second areas which are alternately arranged; the first semiconductor composite layer is arranged in the first region and comprises a tunneling passivation layer and a first doping layer which are sequentially arranged in the direction away from the silicon substrate; the second semiconductor composite layer is at least partially arranged in the second area and comprises a passivation contact layer and a second doping layer which are sequentially arranged in the direction away from the silicon substrate, and the polarity of the second doping layer is opposite to that of the first doping layer; the composite TCO layer is arranged in at least partial areas of the sides, back to the silicon substrate, of the first doping layer and the second doping layer, the composite TCO layer comprises a first TCO layer and a second TCO layer which are sequentially arranged in the direction away from the silicon substrate, and the refractive index of the first TCO layer is larger than that of the second TCO layer. And the cell conversion efficiency can be effectively improved.

The invention discloses a grid line protection structure, a battery piece, a photovoltaic module and a photovoltaic system, the grid line protection structure is arranged on the battery piece, the battery piece comprises a first surface, a second surface and a cutting surface, the cutting surface intersects with the first surface and the second surface, the first surface is provided with a first grid line, the cutting surface is covered with a passivation layer, and the passivation layer is provided with a second grid line. The first surface is provided with a first cutting edge, and the grid line protection structure comprises a first isolation layer which at least covers a first grid line adjacent to the first cutting edge. The first isolation layer is arranged in the area, adjacent to the cutting face, in the battery piece, and the first isolation layer covers the first grid line in the area, so that the first grid line can be effectively isolated from the passivation solution forming the passivation layer, corrosion of the passivation solution to the first grid line is prevented, and the service life of the battery piece is prolonged. Therefore, the phenomenon of edge passivation failure or micro electric leakage caused by the fact that metal ions generated by corrosion of the first grid line migrate to the area of the passivation layer is prevented.

A system implements a weather-based irradiance forecasting algorithm that can aid in planning PV array operations. The system implements a cascaded temporal convolutional network (TCN) neural architecture that uses nine weather characteristics in a time-bound window to predict future solar irradiance. The system achieves a significant performance improvement with as little as a single day prior of weather data compared to baseline results.

A distributed photovoltaic ultra-short-term power prediction method based on VMD-BiLSTM-XGBoost comprises the following steps: S1, data preprocessing and correlation analysis are carried out, historical meteorological data and historical power data of a distributed photovoltaic system are acquired, and missing value processing, abnormal value processing and normalization processing are carried out on the data in sequence; on the basis of the Pearson's correlation coefficient, meteorological characteristic quantities having significant correlation with the photovoltaic power are screened; classifying the sites according to the attributes of the distributed photovoltaic sites by adopting a classification prediction method based on virtual acquisition; s2, self-adaptive VMD signal decomposition is carried out; s3, constructing and training a combined prediction model; and S4, ultra-short-term power prediction. The technical problem to be solved by the invention is to provide a distributed photovoltaic ultra-short-term power prediction method based on VMD-BiLSTM-XGBoost. The problems of modal aliasing, high data acquisition cost, low prediction precision in extreme weather and poor calculation efficiency of a complex model in an existing photovoltaic power prediction method are solved.

The utility model discloses a back contact solar cell, a back contact cell string, a photovoltaic assembly and a photovoltaic system, the back contact solar cell comprises a plurality of first doping units, and each first doping unit comprises a first doping conductive layer, a second doping conductive layer and a first isolation area which are arranged on the back surface of a silicon substrate; the first doped conductive layers and the second doped conductive layers are alternately arranged, and the doping types of the first doped conductive layers and the second doped conductive layers are opposite; the first isolation region is arranged between the first doped conductive layer and the second doped conductive layer, and the surface of the first isolation region is recessed towards the silicon substrate relative to the surface of the first doped conductive layer; the surface of the first doped conductive layer is recessed towards the silicon substrate relative to the surface of the second doped conductive layer; the first doped conductive layer is provided with a first grid line, the second doped conductive layer is provided with a second grid line, and the height of the first grid line is smaller than the height of the adjacent second grid line. The back contact solar cell provided by the utility model is high in double-sided rate and yield.

The utility model discloses a steel structure sunlight room with a photovoltaic system, which is characterized in that a steel structure glass wall is fixed on the ground and is used for supporting a sectional material piece; the steel structure glass wall comprises a front vertical wall; the profile pieces and the heat insulation glass are sequentially arranged at intervals and used for blocking the top of the steel structure sunlight room. The plurality of photovoltaic modules are respectively mounted on the upper surface of the profile piece to form a photovoltaic array for converting light energy into electric energy; the profile piece is provided with a mounting part and a first containing part, and the mounting part and the first containing part are arranged on the two sides of the profile piece; the mounting part is used for fixing the heat insulation glass, and the first accommodating part is used for accommodating and limiting the heat insulation glass adjacent to the first accommodating part; the execution assembly is used for being connected with the profile pieces close to the front vertical wall so as to drive the profile pieces to move in the direction away from the front vertical wall, and therefore the top of the steel structure sunlight room can be ventilated. The utility model aims to provide the steel structure sunlight room, and aims to design a reasonable ventilation system, prevent the internal temperature from being too high, and improve the user experience.