The article presents the results of predicting the power at the output of the solar panel by polynomials of different degrees. The article indicates the need for solar power forecast. The article describes what factors affect the forecast of solar power at the output of the solar panel. Forecasting the amount of electricity generated by a solar power plant is primarily a prediction of the amount of solar radiation received by the solar panel, which in turn depends on environmental conditions and parameters. Data were taken from 04.05.2019 - 05.05.2019 with a discreteness of 1 minute. In order to calculate the forecast, the values of solar insolation were converted to power. The hourly curve of change of solar power with a discreteness in 1 minute is presented. A two-hour curve of the change in solar power with a resolution of 10 minutes is presented. The daily curve of change of solar power with a discreteness in 1 hour is presented. The horizon at 1 hour and 1 day was chosen for forecasting. Approximation of data by means of polynomials of various degrees is checked. The article shows graphs of changes in real and predicted values of solar power at the output of the solar panel. The graphs clearly show which method of forecasting is more accurate. The accuracy of the predicted values was assessed using the average relative error. Of all the considered methods of calculating the predicted value of the power of the solar panel, the smallest error is obtained when the data are selected for 2 hours, differ by no more than 2 times and have a discreteness of 10 minutes. The benefit of using the correction of the predicted data by the Hoyne method is checked. To predict the power of the solar panel by approximation, it is advisable to adjust the predicted data. To correct the data, it is advisable to use the method of predictor-corrector. Predictor - is the predicted value, and the corrector - is the adjusted value After calculating the power forecast at the output of solar power, an algorithm was developed with which you can calculate the predicted value of power. The developed algorithm for calculating the forecast uses the following parameters: data discreteness, the period for which the data are taken for analysis, the degree of the polynomial. First, the algorithm selects data for the selected period, selects discreteness. If you want to increase the discreteness, it averages the value. But on the basis of the selected values calculates the polynomial of the selected degree. Then, based on the calculated equation, the forecast is calculated and the predicted values are displayed in the form of a graph.

The article is devoted to the development of an automated device for plant care at home. The main factors influencing plant development are considered. A comparative analysis of existing devices was made. The growth of plants is influenced by many factors: the level of light, soil moisture, room temperature, carbon dioxide level. When plants are growing indoors, the most important thing is timely watering and access to light. The required amount of light for most plants is 12-18 hours per day. Our country is in the temperate climate zone, so we have 15 hours of light in summer, 13 hours in autumn and spring, and 9 hours in winter. The amount of light in summer is normal, in autumn and spring - within normal limits, but in winter there is a certain lack of light. The lack of natural insolation in winter leads to light starvation of houseplants and reduced intensity of photosynthesis. Therefore, the decrease of the amount of natural light is compensated by artificial light sources. Analysis of the devices on the market has shown that devices that can solve such problems exist, but there is no device with all functions simultaneously. Lighting devices illuminate on a timer, regardless of natural light. Irrigation devices are intended for industrial, not for domestic use. Existing technological solutions for home cultivation have only a warning function: sound or light, which can bring some inconvenience. Looking on these problems, a device is created to maintain the required soil moisture and the required amount of light. The control unit is based on a microcontroller that analyses the data obtained from the sensors and sends the appropriate signals to the climate control devices. The device is equipped with a soil moisture sensor, a light sensor, a real - time sensor, an LED lamp, a water pump, an LED lamp driver, and a control key of water pump. To control soil moisture, a capacitive humidity sensor is used, the advantages of it is the absence of corrosion of metal parts of the sensors that touch the ground. A light meter based on the BH1750 chip is used as a light sensor. This sensor has a wide measuring range, measuring accuracy - 1 lux, small dimensions and the ability to connect to a microcontroller via I2C interface. The DS3231 chip is used as a real-time clock that required to maintain a circadian rhythm close to the natural one for a given plant. An LED strip with red and blue LEDs is used for lighting. The ratio of blue / red LEDs depends on the stage of growth and the type of plant, but it is usually from 1/3 to 1/5. The key that controls the LED strip and the water pump are the MOS transistors. They are silent and allow you to adjust the brightness of the LED strip.