scholarly journals Very-short term solar power generation forecasting based on trend-additive and seasonal-multiplicative smoothing methodology

2018 ◽  
Vol 51 ◽  
pp. 02003
Author(s):  
Stanislav Eroshenko ◽  
Alexandra Khalyasmaa ◽  
Rustam Valiev
Keyword(s):  
Solar Power ◽  
Forecast Error ◽  
Renewable Energy Sources ◽  
Power Station ◽  
Short Term ◽  
Operating Modes ◽  
Power Stations ◽  
Operational Forecasting ◽  
Solar Power Station ◽  
System Operating

In conditions of development of generating facilities on renewable energy sources, the technology runs up to uncertainty in the operational and short-term planning of the power system operating modes. To date, reliable tools for forecasting the generation of solar power stations are required. This paper considers the methodology of operational forecasting of solar power stations output based on the mathematical apparatus of cubic exponential smoothing with trend and seasonal components. The presented methodology was tested based on the measuring data of a real solar power station. The average forecast error was not more than 10% for days with variable clouds and not more than 3% for clear days, which indicates the effectiveness of the proposed approach.

scholarly journals Very-short term solar power generation forecasting based on trend-additive and seasonal-multiplicative smoothing methodology

2018 ◽  
Vol 51 ◽  
pp. 02003
Author(s):  
Stanislav Eroshenko ◽  
Alexandra Khalyasmaa ◽  
Rustam Valiev
Keyword(s):  
Solar Power ◽  
Forecast Error ◽  
Renewable Energy Sources ◽  
Power Station ◽  
Short Term ◽  
Operating Modes ◽  
Power Stations ◽  
Operational Forecasting ◽  
Solar Power Station ◽  
System Operating

In conditions of development of generating facilities on renewable energy sources, the technology runs up to uncertainty in the operational and short-term planning of the power system operating modes. To date, reliable tools for forecasting the generation of solar power stations are required. This paper considers the methodology of operational forecasting of solar power stations output based on the mathematical apparatus of cubic exponential smoothing with trend and seasonal components. The presented methodology was tested based on the measuring data of a real solar power station. The average forecast error was not more than 10% for days with variable clouds and not more than 3% for clear days, which indicates the effectiveness of the proposed approach.

scholarly journals Machine learning techniques for short-term solar power stations operational mode planning

2018 ◽  
Vol 51 ◽  
pp. 02004 ◽  
Author(s):  
Stanislav Eroshenko ◽  
Alexandra Khalyasmaa ◽  
Denis Snegirev
Keyword(s):  
Decision Trees ◽  
Solar Power ◽  
Machine Learning Techniques ◽  
Gradient Boosting ◽  
Operational Mode ◽  
Mathematical Methods ◽  
Short Term ◽  
Advantages And Disadvantages ◽  
Power Stations ◽  
Operational Forecasting

The paper presents the operational model of very-short term solar power stations (SPS) generation forecasting developed by the authors, based on weather information and built into the existing software product as a separate module for SPS operational forecasting. It was revealed that one of the optimal mathematical methods for SPS generation operational forecasting is gradient boosting on decision trees. The paper describes the basic principles of operational forecasting based on the boosting of decision trees, the main advantages and disadvantages of implementing this algorithm. Moreover, this paper presents an example of this algorithm implementation being analyzed using the example of data analysis and forecasting the generation of the existing SPS.

scholarly journals Machine learning techniques for short-term solar power stations operational mode planning

2018 ◽  
Vol 51 ◽  
pp. 02004
Author(s):  
Stanislav Eroshenko ◽  
Alexandra Khalyasmaa ◽  
Denis Snegirev
Keyword(s):  
Decision Trees ◽  
Solar Power ◽  
Machine Learning Techniques ◽  
Gradient Boosting ◽  
Operational Mode ◽  
Mathematical Methods ◽  
Short Term ◽  
Advantages And Disadvantages ◽  
Power Stations ◽  
Operational Forecasting

The paper presents the operational model of very-short term solar power stations (SPS) generation forecasting developed by the authors, based on weather information and built into the existing software product as a separate module for SPS operational forecasting. It was revealed that one of the optimal mathematical methods for SPS generation operational forecasting is gradient boosting on decision trees. The paper describes the basic principles of operational forecasting based on the boosting of decision trees, the main advantages and disadvantages of implementing this algorithm. Moreover, this paper presents an example of this algorithm implementation being analyzed using the example of data analysis and forecasting the generation of the existing SPS.

scholarly journals Exploring the effectiveness of using devices that follow the Sun

2019 ◽  
Vol 302 ◽  
pp. 01017
Author(s):  
Janusz Musiał ◽  
Joanna Wilczarska ◽  
Oleg Polishchuk ◽  
Andrii Ramskyi
Keyword(s):  
Solar Power ◽  
Electric Energy ◽  
The Sun ◽  
Solar Panels ◽  
Power Station ◽  
Power Stations ◽  
Automatic Mode ◽  
Manual Adjustment ◽  
Cloudy Weather ◽  
Solar Power Station

The article is devoted to the study of the effectiveness of devices that follow the Sun. For this purpose, the construction of a two-axes tracker with an automatic system of steering the solar panels on azimuth during the light period of the day and with the possibility of manually adjusting the angle of rotation of the solar panels on the zenith, depending on the season is designed. For the proposed construction, the calculation of the angles of the zenith is made and the optimal angles are selected for manual adjustment of the seasonal positions of the system. The photo modules, which are installed stationary on the developed tracker system, are selected. Structural and electrical principle diagram of the stand was developed for determining the efficiency of solar power station, equipment was selected and its manufacture made. A solar power station monitoring system has been developed, which enables to automatically visualize parameters, perform data processing in real time, create databases and perform a comparative analysis of their operational efficiency in an automatic mode. Experimental researches have been carried out on determination of the generated electric energy by static and dynamic solar power stations, on the basis of which the efficiency of tracker systems of rotation of solar panels is confirmed. The use of dynamic systems compared to static allows to increase the production of electricity by 33% under the same conditions. But with poor illumination of the panels (rain, fog, cloudy weather), the tracker's effectiveness decreases and it does not exaggerate 5% when fully covered with the sky. Therefore, the use of tracking systems in the absence of direct sunlight on the surface of photo modules is not feasible.

scholarly journals Evaluation of Work Efficiency of the Solar Power Plant Installed on the Roof of a House in Hanoi City

2020 ◽  
Vol 63 (1) ◽  
pp. 30-41 ◽  
Author(s):  
T. N. Nguyen ◽  
V. D. Sizov ◽  
M. P. Vu ◽  
T. T. H. Cu
Keyword(s):  
Power Plant ◽  
Power Plants ◽  
Solar Power ◽  
Small Scale ◽  
Solar Power Plant ◽  
Power Station ◽  
Power Stations ◽  
Solar Power Plants ◽  
Solar Power Station ◽  
Rooftop Solar

Vietnam is a country of a great solar potential; solar technology is growing rapidly in Vietnam and investors are very interested in building solar power plants. Construction of the rooftop solar power stations can help owners reduce monthly electricity costs and even get economic benefits by selling excess electricity coming from a solar power plant (PV) to the utility grid. In this study, the design results of a rooftop grid-tied solar power station with the capacity of 26 kWp for a commercial building were introduced to have a basis to assess the operation ability of solar power station under solar radiation conditions in Hanoi city, Vietnam. The simulation results using the PVsyst program have made it possible to calculate the solar energy potential in Hanoi city, the power generation and efficiency of the grid-tied solar power station. Solar power has been applied in Vietnam since the 1990s but is mainly used for areas that were far from national power grid such as mountainous areas, islands. Small scale grid-tied solar power has been developed since 2010 and mainly is used for residential applications or small and medium scale consumers. The total capacity of electricity produced by solar power plants in Vietnam by 2017 was only about 8 MW; this value is very low as compared to the potential of solar power in Vietnam. This is due to the absence of the government support for the policy of developing solar power. In accordance with the current roadmap of raising electricity prices in Vietnam, construction investment of rooftop solar power stations is economically feasible while contributing to environmental protection and counteracting climate change phenomenon by reducing the amount of CO2 emitted into the environment.

scholarly journals Effect of operational condition of rotational subsystem on attitude control for space solar power station

2021 ◽  
Vol 34 (5) ◽  
pp. 289-297
Author(s):  
Xiangfei JI ◽  
Baoyan DUAN ◽  
Yiqun ZHANG ◽  
Guanheng FAN ◽  
Meng LI ◽  
...  
Keyword(s):  
Attitude Control ◽  
Solar Power ◽  
Power Station ◽  
Space Solar Power ◽  
Solar Power Station

scholarly journals Weather data errors analysis in solar power stations generation forecasting

2018 ◽  
Vol 51 ◽  
pp. 02002 ◽  
Author(s):  
Stanislav Eroshenko ◽  
Alexandra Khalyasmaa
Keyword(s):  
Detailed Analysis ◽  
Solar Power ◽  
Weather Data ◽  
Forecasting Model ◽  
Short Term ◽  
Data Errors ◽  
Power Stations ◽  
Software Product ◽  
Short Term Forecasting ◽  
Errors Analysis

The paper presents a short-term forecasting model for solar power stations (SPS) generation developed by the authors. This model is based on weather data and built into the existing software product as a separate short-term forecasting module for the SPS generation. The main problems associated with forecasting the SPS generation on cloudy days were revealed in the framework of authors' research, which is due not to the error of the developed model but to the use of the same learning sample for both solar and cloudy days. This paper contains analysis of the main problems related to the learning sampling, samples pattern, quality and representativeness for forecasting the SPS generation on cloudy days. Besides, the paper includes a calculation example performed for the existing SPS and a detailed analysis of the forecast generation on cloudy days based on the actual weather provider data.

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