CN115589187A - Photovoltaic power generation system and method for improving power generation efficiency of solar cell - Google Patents

Abstract

The invention discloses a photovoltaic power generation system and method for improving the power generation efficiency of solar cells, and specifically relates to the field of photovoltaic power generation, including a monitoring module, a power generation prediction module, a central control module, a control module, and a display module. The monitoring module is mainly used for collecting Photovoltaic power generation related information, and transmit the collected information to the central control module and the power generation prediction module. Judging the information transmitted by the monitoring module, obtaining the power generation efficiency of the solar panel and the optimal tilt angle of the support through the calculation of the central control module, and transmitting the information to the control module and the display module, the control module is used to adjust the angle of the photovoltaic panel, Controlling the replacement of power generation components, the display module is used to receive the information of the control module and display the power generation information on the display screen.

Description

Photovoltaic power generation system and method for improving power generation efficiency of solar cells

technical field

The present invention relates to the technical field of photovoltaic power generation, and more specifically, the present invention relates to a photovoltaic power generation system and method for improving the power generation efficiency of solar cells.

Background technique

Photovoltaic power generation refers to the power generation method that directly converts solar radiation into electrical energy. It is the mainstream of solar power generation today. Distributed photovoltaic power generation refers to construction near the user's site. The photovoltaic power generation facility characterized by system balance adjustment is a new type of power generation and energy comprehensive utilization method with broad development prospects. It advocates the principles of nearby power generation, nearby grid connection, nearby conversion, and nearby use. At the same time, it effectively solves the problem of power loss in boosting and long-distance transportation.

The development of distributed photovoltaic power generation is of great significance to optimize the energy structure, realize the "double carbon target", promote energy conservation and emission reduction, and achieve sustainable economic development. Installing a 1 kilowatt photovoltaic power generation system under the average sunshine conditions in my country can generate 1,200 electricity a year, reduce coal consumption by about 400 grams, and reduce carbon dioxide emissions by about 1 ton.

The basic configuration of distributed photovoltaic power generation equipment is: solar panels, inverters, bracket cables, installation accessories, monitoring systems, etc. Large-scale power stations also need transformers, power distribution cabinets and other auxiliary equipment. Distributed photovoltaic power generation systems are divided into strings Both type and centralized type.

Solar cell power generation efficiency affects the effectiveness of distributed photovoltaic power generation systems. Solar panels naturally produce less electricity over time. This reduced power output is called degradation rate. The median degradation rate of solar panels is about 0.5%, which means that the power generation of solar panels will decrease at a rate of 0.5% per year. At present, the main factors affecting the power generation efficiency of solar cells are the intensity of sunlight, the quality of the battery, and the material of the solar panel. Therefore, the following methods can be used to improve the power generation efficiency of solar panels and prolong their service life. The methods include: 1. Keep the surface of solar panels clean and tidy, and reduce hot spots on the surface of solar panels; 2. Regularly monitor and maintain solar panels to maintain solar energy systems. Optimal panel performance, electricity meters, inverters and other components operate at maximum efficiency.

Contents of the invention

In order to overcome the above-mentioned defects of the prior art, the present invention provides a photovoltaic power generation system and method for improving the power generation efficiency of solar cells, by monitoring the surface of solar panels and taking timely measures to remove foreign matter on the surface of solar panels, and promptly replace solar cells with serious hot spots , by adjusting the angle of the solar panel to ensure that the sun shines directly on the solar panel, improve the power generation efficiency of the solar cell, and ensure the operating efficiency of the important components through monitoring and maintenance of the important components of photovoltaic power generation, so as to solve the problems raised in the above background technology.

Technical solutions

In order to achieve the above purpose, the present invention provides the following technical solutions: including a monitoring module, a power generation prediction module, a central control module, a control module, and a display module, the monitoring module is mainly used to collect temperature, average illumination range, illumination angle, illumination Duration, solar panel hot spots, battery panel information, power generation voltage, power generation current, daily power generation, and transmit the collected information to the central control module and power generation prediction module, the power generation prediction module is used to predict the value of power generation, Provide a basis for the comparison and judgment of the central control module. The central control module is used to judge the information transmitted by the monitoring module. Through the calculation of the central control module, the power generation efficiency of the solar panel and the optimal tilt angle of the support are obtained, and the information is transmitted to the control module. and a display module, the control module is used to adjust the angle of the photovoltaic battery panel and control the replacement of power generation components, the control module is connected with the DC combiner box, the DC power distribution cabinet, the grid-connected inverter, the storage battery, and the battery panel bracket, the said The display module is used to receive the information of the control module, and display the power generation information on the display screen.

In a preferred embodiment, the power generation forecasting module builds a photovoltaic power generation forecasting model through a fruit fly algorithm combined with a neural network hybrid algorithm. The forecasting model is divided into an input layer, a hidden layer, and an output layer. The input layer, The input variable is the average temperature and average illumination of each period of the photovoltaic power generation system; the hidden layer, the neural network excitation function adopts a unipolar sigmods excitation function, the neural network structure is a double hidden layer, and the number of neurons in the hidden layer is 25. The hidden layer is composed of neurons, which determine the weight of each input variable and the weight of each output variable, and predict the average temperature and average illumination of each time period of the sample through the hidden layer; the output layer outputs the weight of each time period of the day The photovoltaic power generation capacity, the photovoltaic power generation prediction model is divided into 24 hours / day, each hour is a calculation unit, each node in the input layer is used as an excitation signal to form the input signal of the next layer, and the output signal of this layer It is also used as the input signal of the lower layer, and so on.

In a preferred embodiment, the mixed algorithm process of the fruit fly algorithm combined with the neural network is as follows:

Step A1, initialize, initialize the population size S, the maximum number of iterations iter, randomly generate the position, moving direction, moving step size and neuron weight of each fruit fly;

Step A2, read the data, read the training sample data of the photovoltaic power generation system, including the average temperature, average light intensity and photovoltaic power generation amount of each time period, and normalize the sample data;

Step A3, train the neural network samples to obtain the corresponding weights, and use the fruit fly algorithm to correct and optimize the weights. The fruit flies move a certain step in the predetermined direction and calculate the concentration. At this time, the concentration is the predicted value , if the predicted value best is better, keep it and continue to iterate until the prediction accuracy is reached;

Step A4, output the position where the concentration of fruit flies in the population is the highest, that is, the optimal weight value of the neural network, and output the prediction result.

In a preferred embodiment, the monitoring module includes a hot spot detection unit, and the hot spot detection unit detects through an unmanned aerial vehicle, by carrying a high-definition camera, an infrared camera, and a communication device on the unmanned aerial vehicle, and using hot spot positioning, Photovoltaic panels are photographed and inspected from multiple angles to obtain hot spot information. The specific process of UAV infrared hot spot detection is as follows: plan the detection range and path, then carry out flight shooting, then implement monitoring operations on hot spots, and finally The image is fully analyzed and abnormal areas are marked.

In a preferred embodiment, the monitoring module first collects photovoltaic power generation related information, and then predicts the photovoltaic power generation amount according to the collected information, then the central control module compares and judges according to the collected data, forms an operation instruction, and finally executes the operation instruction, And monitor the implementation results in time to ensure the implementation effect, specifically including the following steps:

Step 101, data collection, collect photovoltaic power generation weather information, solar panel surface information, and power generation component performance information at a certain frequency through the monitoring module, and collect average temperature, average illumination amplitude, illumination angle, illumination duration, and solar panel hot spots in each period , the loss rate of power generation components, and the daily power generation;

Step 102, building a forecasting model of photovoltaic power generation, predicting the photovoltaic power generation of each time period of the day by inputting the average temperature and average light of each time period of the photovoltaic power generation system, and setting the predicted photovoltaic power generation as a reference value;

Step 103, generate operation instructions and early warnings, calculate the optimal tilt angle of the solar panel through the calculation unit in the central control module, calculate the daily power generation efficiency of the solar panel, and the power consumed by the power generation components, and then pass the central control module The comparison and judgment unit in the system compares the predicted photovoltaic power generation with the actual power generation. If the actual power generation is abnormally lower than the predicted power generation, a self-inspection instruction is formed to check the placement angle of the distributed photovoltaic power generation panels and the power generation components. Check one by one. The monitoring of the power generation components includes the hot spot monitoring of the solar panel. The actual thermal image obtained by the hot spot detection unit is compared with the standard thermal image. If the actual thermal image has a large color difference, a replacement and cleaning battery If the power consumption of the power generation components exceeds the warning value, start the warning unit in the central control module, and form an operation instruction and transmit it to the control module;

Step 104, execute the central control instruction, and execute the generated operation instruction through the control module, including an automatic control execution module and a manual execution module. The automatic control execution module is used to automatically control the tilt angle of the solar panel, and the execution method is that the control module passes the The motor controls the tilt angle of the solar panel, controls the rotation of the motor to adjust the angle of the photovoltaic solar panel, and the manual execution module is used to execute instructions for replacing solar panels and power generation components;

Step 105: Feedback the execution result. After the execution is completed, manually start the monitoring module through the human-computer interaction unit of the central control module to verify the execution effect. After the verification is passed, the warning is released.

In a preferred embodiment, the data collection is obtained by analyzing IV curves with large data, including evaluation-steps or depressions, low current, and low voltage.

Technical effects and advantages of the present invention: the present invention takes measures to remove foreign matter on the surface of the solar panel in time by monitoring the surface of the solar panel, replaces solar cells with serious hot spots in time, and ensures that the sun directly shines on the solar panel by adjusting the angle of the solar panel, thereby improving Solar cell power generation efficiency, through the monitoring and maintenance of important components of photovoltaic power generation, to ensure the operating efficiency of important components.

Description of drawings

Fig. 1 is a schematic diagram of the system structure of the present invention.

Fig. 2 is a structural schematic diagram of the systematic method of the present invention.

detailed description

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure, and to fully convey the scope of the present disclosure to those skilled in the art.

At the same time, it should be understood that, for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

The following description of at least one exemplary embodiment is merely illustrative in nature and in no way serves as any limitation of the application, its application or uses.

Techniques, methods and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, such techniques, methods and devices should be considered part of the description.

It should be noted that like numerals and letters denote like items in the following figures, therefore, once an item is defined in one figure, it does not require further discussion in subsequent figures.

Embodiments of the present application may be applied to computer systems/servers that are operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well-known computing systems, environments and/or configurations suitable for use with computer systems/servers include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, Microprocessor-based systems, set-top boxes, programmable consumer electronics, networked personal computers, minicomputer systems, mainframe computer systems, and distributed cloud computing technology environments including any of the above, etc.

Computer systems/servers may be described in the general context of computer system-executable instructions, such as program modules, being executed by the computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, etc., that perform particular tasks or implement particular abstract data types. The computer system/server can be practiced in distributed cloud computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computing system storage media including storage devices.

This embodiment is based on a distributed photovoltaic power generation device, which is basically configured as: photovoltaic cell components, a DC combiner box, a DC power distribution cabinet, a grid-connected inverter, installation accessories, a charge and discharge controller, and a storage battery. Photovoltaic battery modules are arranged in parallel or in series according to the array method to convert solar energy into electrical energy, and then send it to the DC power distribution cabinet through the DC combiner box, or send it to the AC power distribution cabinet through the grid-connected inverter. Inside, the photovoltaic cell assembly is electrically connected to the DC power distribution cabinet through the positive DC bus bar and the negative DC bus bar. The photovoltaic cell assembly is fixedly connected to the support, and the support is controlled by a motor to change the inclination angle.

The present invention provides a photovoltaic power generation system and method for improving the power generation efficiency of solar cells as shown in Figure 1, including a monitoring module, a power generation prediction module, a central control module, a control module, and a display module. Temperature, average illumination range, illumination angle, illumination duration, solar panel hot spots, battery panel information, power generation voltage, power generation current, daily power generation, and transmit the collected information to the central control module and power generation prediction module. The quantity prediction module is used to predict the value of power generation, and provides a basis for the comparison and judgment of the central control module. Tilt angle, and transmit the information to the control module and display module, the control module is used to adjust the angle of photovoltaic panels, control the replacement of power generation components, the control module and DC combiner box, DC power distribution cabinet, grid-connected inverter , storage battery and battery board bracket are connected, and the display module is used to receive the information of the control module and display the power generation information on the display screen.

The power generation forecasting module builds a photovoltaic power generation forecasting model through a fruit fly algorithm combined with a neural network hybrid algorithm. The forecasting model is divided into an input layer, a hidden layer, and an output layer. In the input layer, the input variable is each time period of the photovoltaic power generation system The average temperature, the average illumination; the hidden layer, neural network activation function adopts unipolar sigmods activation function is:, the neural network structure is a double hidden layer, the number of neurons in the hidden layer is 25, and the hidden layer consists of The neuron is composed of neurons, which determine the weight of each input variable and the weight of each output variable, and predict the average temperature and average illumination of the sample at each time period through the hidden layer; the output layer outputs the photovoltaic power generation at each time period of the day, and will The photovoltaic power generation prediction model is divided into 24 hours/day, and each hour is a calculation unit. Each node in the input layer is used as an excitation signal to form the input signal of the next layer, and the output signal of this layer is used as the input signal of the lower layer. , and so on, the hybrid algorithm flow of fruit fly algorithm combined with neural network is as follows:

Step A1, initialize, initialize the population size S, the maximum number of iterations iter, randomly generate the position, moving direction, moving step size and neuron weight of each fruit fly;

Step A2, read the data, read the training sample data of the photovoltaic power generation system, including the average temperature, average light intensity and photovoltaic power generation amount of each time period, and normalize the sample data;

Step A3, train the neural network samples to obtain the corresponding weights, and use the fruit fly algorithm to correct and optimize the weights. The fruit flies move a certain step in the predetermined direction and calculate the concentration. At this time, the concentration is the predicted value , if the predicted value best is better, keep it and continue to iterate until the prediction accuracy is reached;

Step A4, output the position where the concentration of fruit flies in the population is the highest, that is, the optimal weight of the neural network. Output prediction results.

The output side of the grid-connected inverter is connected to the public distribution network in parallel, and the synchronization point is set at the AC output end of the grid-connected inverter. The grid-connected inverter automatically detects the grid voltage, phase and frequency, and the voltage at the synchronization point When the phase and frequency are consistent with the voltage, phase and frequency of the power grid, the grid-connected inverter transmits the AC power to the low-voltage end of the transformer, and after being boosted by the three-phase transformer, it is sent to the public distribution network for power supply by the transmission line to ensure When the inverter is connected to the grid, there is no impact or disturbance on the public distribution network.

The present invention provides a method for using a photovoltaic power generation system and method for improving the power generation efficiency of solar cells as shown in Figure 2. First, the monitoring module collects photovoltaic power generation related information, and then predicts the photovoltaic power generation amount according to the collected information, and then the central control module Comparing and judging based on the collected data, forming operation instructions, and finally executing the operation instructions, and monitoring the execution results in time to ensure the execution effect, specifically including the following steps:

Step 101, data collection, collect photovoltaic power generation weather information, solar panel surface information, and power generation component performance information at a certain frequency through the monitoring module, and collect average temperature, average illumination amplitude, illumination angle, illumination duration, and solar panel hot spots in each period , the loss rate of power generation components, and the daily power generation;

Step 102, building a forecasting model of photovoltaic power generation, predicting the photovoltaic power generation of each time period of the day by inputting the average temperature and average light of each time period of the photovoltaic power generation system, and setting the predicted photovoltaic power generation as a reference value;

Step 103, generate operation instructions and early warnings, calculate the optimal tilt angle of the solar panel through the calculation unit in the central control module, calculate the daily power generation efficiency of the solar panel, and the power consumed by the power generation components, and then pass the central control module The comparison and judgment unit in the system compares the predicted photovoltaic power generation with the actual power generation. If the actual power generation is abnormally lower than the predicted power generation, a self-inspection instruction is formed to check the placement angle of the distributed photovoltaic power generation panels and the power generation components. Check one by one. The monitoring of the power generation components includes the hot spot monitoring of the solar panel. The actual thermal image obtained by the hot spot detection unit is compared with the standard thermal image. If the actual thermal image has a large color difference, a replacement and cleaning battery If the power consumption of the power generation components exceeds the warning value, start the warning unit in the central control module, and form an operation instruction and transmit it to the control module;

Step 104, execute the central control instruction, and execute the generated operation instruction through the control module, including an automatic control execution module and a manual execution module. The automatic control execution module is used to automatically control the tilt angle of the solar panel, and the execution method is that the control module passes the The motor controls the tilt angle of the solar panel, controls the rotation of the motor to adjust the angle of the photovoltaic solar panel, and the manual execution module is used to execute instructions for replacing solar panels and power generation components;

Step 105: Feedback the execution result. After the execution is completed, manually start the monitoring module through the human-computer interaction unit of the central control module to verify the execution effect. After the verification is passed, the warning is released.

In this embodiment, it needs to be specifically explained that the monitoring module includes a hot spot detection unit, and the hot spot detection unit detects through the drone, and by installing a high-definition camera, an infrared camera, and a communication device on the drone, and using the hot spot location , photograph and inspect photovoltaic panels from multiple angles to obtain hot spot information. The specific process of UAV infrared hot spot detection is as follows: plan the detection range and path, then carry out flight shooting, then implement monitoring operations on hot spots, and finally The image is fully analyzed and abnormal areas are marked.

In this embodiment, it needs to be specifically explained that: the illumination angle, illumination duration, and temperature can be obtained from the meteorological data in the weather forecast.

In this embodiment, it needs to be specifically explained that: the data collection is obtained by analyzing IV curves with big data, including evaluation-steps or depressions, low current, and low voltage.

Finally: the above is only a preferred embodiment of the present invention, and is not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the present invention within the scope of protection.

Claims (7)

1. Improve solar cell generating efficiency's photovoltaic power generation system, its characterized in that: the solar photovoltaic power generation system comprises a monitoring module, a power generation predicting module, a central control module, a control module and a display module, wherein the monitoring module is mainly used for collecting temperature, average illumination amplitude, illumination angle, illumination duration, solar panel hot spots, panel information, power generation voltage, power generation current and daily power generation amount, transmitting the collected information to the central control module and the power generation predicting module, the power generation predicting module is used for predicting power generation amount values and providing basis for comparison and judgment of the central control module, the central control module is used for judging the transmitted information of the monitoring module, the solar panel power generation efficiency and the optimal support inclination angle are obtained through calculation of the central control module, the information is transmitted to the control module and the display module, the control module is used for adjusting the angle of a photovoltaic panel and controlling the replacement of a power generation component, the control module is connected with a direct current combiner box, a direct current power distribution cabinet, a grid-connected inverter, a storage battery and a panel support, and the display module is used for receiving the information of the control module and displaying the power generation information in a display screen.

2. The photovoltaic power generation system for improving the power generation efficiency of a solar cell according to claim 1, characterized in that: the photovoltaic power generation prediction model is built by combining a drosophila algorithm with a neural network hybrid algorithm and is divided into an input layer, a hidden layer and an output layer, and input variables of the input layer are the average temperature and the average illumination of the photovoltaic power generation system in each time period; the neural network excitation function adopts a unipolar sigmods excitation function, the neural network structure is a double hidden layer, the number of neurons in the hidden layer is 25, the hidden layer consists of neurons, the neurons determine the weight values of all input variables and all output variables, and the average temperature and the average illumination of the sample in all time periods are predicted through the hidden layer; the output layer outputs the photovoltaic power generation amount of each time period on the day, the photovoltaic power generation prediction model is divided into 24 hours/day, each hour is a calculation unit, each node in the input layer serves as an excitation signal to form an input signal of the next layer, the output signal of the layer serves as an input signal of the next layer, and the like.

3. The photovoltaic power generation system for improving the power generation efficiency of a solar cell according to claim 2, characterized in that: the mixed algorithm flow of the drosophila algorithm combined with the neural network is as follows:

a1, initializing population scale S, maximum iteration number iter, and randomly generating the position, moving direction, moving step length and neuron weight of each drosophila;

a2, reading data, reading training sample data of the photovoltaic power generation system, wherein the training sample data comprises average temperature, average illumination intensity and photovoltaic power generation amount of each time period, and performing normalization processing on the sample data;

step A3, training through a neural network sample to obtain a corresponding weight, correcting and optimizing the weight by using a drosophila algorithm, moving the drosophila individual to a preset direction for a certain step length, calculating concentration, namely a predicted value, and if the predicted value best is better, retaining and continuously iterating until the prediction precision is reached;

and A4, outputting the position with the highest concentration of the fruit flies in the population, namely the optimal weight of the neural network, and outputting a prediction result.

4. The photovoltaic power generation system for improving the power generation efficiency of a solar cell according to claim 1, characterized in that: the monitoring module includes hot spot detecting element, and hot spot detecting element detects through unmanned aerial vehicle, through carrying on high definition camera, infrared camera, communication device on unmanned aerial vehicle to use the hot spot location, shoot and patrol and examine the photovoltaic board from many angles, obtain hot spot information, the infrared hot spot of unmanned aerial vehicle detects concrete flow as follows: planning a detection range and a detection path, then carrying out flight shooting, carrying out monitoring operation on the hot spots, and finally carrying out comprehensive analysis on the image and marking an abnormal area.

5. The method of photovoltaic power generation system for improving power generation efficiency of solar cells according to any one of claims 1 to 4, wherein: the method comprises the steps of firstly collecting relevant information of photovoltaic power generation through a monitoring module, then predicting photovoltaic power generation capacity according to the collected information, then comparing and judging the collected data through a central control module to form an operation instruction, finally executing the operation instruction, monitoring an execution result in time and ensuring an execution effect, and specifically comprises the following steps:

step 101, data acquisition, namely acquiring photovoltaic power generation weather information, solar panel surface information and power generation component performance information according to a certain frequency through a monitoring module, and acquiring average temperature, average illumination amplitude, illumination angle, illumination duration, solar panel hot spot condition, loss rate of a power generation component and daily generated energy in each period;

102, building a photovoltaic power generation amount prediction model, predicting the photovoltaic power generation amount of each time period of the current day by inputting the average temperature and the average illumination of each time period of the photovoltaic power generation system, and setting the predicted photovoltaic power generation amount as a reference value;

103, generating an operation instruction and early warning, calculating the optimal inclination angle of the solar panel through an operation unit in the central control module, calculating the generation efficiency of the solar panel and the power consumed by a power generation component every day, comparing the predicted photovoltaic power generation with the actual power generation through a comparison and judgment unit in the central control module, forming a self-checking instruction if the actual power generation is abnormally lower than the predicted power generation, checking the arrangement angle of the distributed photovoltaic power generation panels and the power generation component one by one, monitoring the power generation component, including hot spot monitoring of the solar panel, comparing an actual hot image obtained by a hot spot detection unit with a standard hot image, sending an instruction for replacing and cleaning the panels if the color difference of the actual hot image is large, starting an early warning unit in the central control module if the power consumption of the power generation component exceeds the early warning value, and forming an operation instruction to be transmitted to the control module;

104, executing a central control instruction, and executing the generated operation instruction through a control module, wherein the operation instruction comprises an automatic control execution module and a manual execution module, the automatic control execution module is used for automatically controlling the inclination angle of the solar panel, the execution mode is that the control module controls the inclination angle of the solar panel through a motor on a control support and controls the motor to rotate so as to adjust the angle of the photovoltaic solar panel, and the manual execution module is used for executing instructions for replacing the solar panel and replacing a power generation component;

and 105, feeding back an execution result, after the execution is finished, manually starting the monitoring module through a human-computer interaction unit of the central control module, verifying the execution effect, and after the verification is passed, canceling the early warning.

6. The method of photovoltaic power generation system for improving the power generation efficiency of solar cells according to claim 5, wherein: the data acquisition is obtained by analyzing an IV curve by using big data, and comprises evaluation, step or recess, low current and low voltage.

7. The method of photovoltaic power generation system for improving the power generation efficiency of solar cells according to claim 5, wherein: the illumination angle, the illumination duration and the temperature can be obtained through meteorological data in weather forecast.

Images