Abstract

In the presented paper data on solar power stations power in the world and Ukraine are given. Also data on the installed peak power of solar power stations in Ukraine in 2016 are given. It is shown that the efficiency of such power stations is provided by maximum energy selection from solar panels at each specific moment in time and efficient operation of the storage on some basic interval. The necessity of implementation of two-channel control in distributed generation systems due to Heisenberg uncertainty principle is shown. It should control the basic interval to ensure the necessary level of energy to charge the storage duration and the minimal duration of observation interval to ensure the maximum level of energy, taken from solar panels. The maximum value of the energy generated by solar panels depends on the existence of clouds and their density, because when the cloud passes over solar panels, part of them is shaded and the level of output energy decreases. Knowing the average level of energy that can be obtained from solar power station and energy levels that excess and is less than average, allows implementing the predictive control on the next basic interval. However, such control is inaccurate. One of the approaches to improve the accuracy is a prediction on a certain small interval with subsequent correction and step-by-step displacement until the end of the basic interval. Considering the solar panels output current as a final result of solar radiation passage through the external environment it is advisable to assess the impact of this environment on the magnitude of generated energy. One of the steps of this identification is to determine the clouds density, on the magnitude of which the amount of energy that falls on the solar panels surface depends. The Beer law is presented. It describes the reduction of the total irradiation intensity, calculated per unit of surface area perpendicular to the direction of irradiation propagation. The method for determination of the virtual cloud density, which takes into account both the values of direct and reflected solar radiation, with reverse transformation is given. It enhances the value of the average level of energy, generated by solar power station on some basic interval. It is shown that in order to find the cloud density it is necessary to have a set of projections for all possible positions of the cloud. It is proposed to approximate the form of the cloud projection with a circle of defined radius to simplify the calculations. Three cases of the ratio between the linear velocity of the clouds and the velocity of the sun, which is defined by its angular displacement, are considered: first is when the linear velocity of the clouds is much greater than the velocity of the sun, which is defined by its angular displacement, then at some observation interval the position of the sun is fixed; second is when the velocity of the clouds is much less than the velocity of the sun; and third is when the velocity of clouds and the velocity of the sun are the values of the same order. This case combines the features of the previous two cases. For each case the scheme for virtual cloud density calculation, formulas for calculation of solar irradiation intensity, cloud projections on the solar panels and the linear absorption coefficient, which values are correlated with the density of the cloud are given.Ref. 13, fig. 4.

Highlights

  • One of the approaches to improve the accuracy is a prediction on a certain small interval with subsequent correction and step-by-step displacement until the end of the basic interval

  • Key words — solar power station; virtual cloud density; maximum power point tracking; inverse transformation method; Fourier transform

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Summary

Електронні системи

Визначення віртуальної щільності хмар із застосуванням методу зворотного перетворення. Оскільки сумарна інтенсивність сонячного випромінювання визначається потоком прямого сонячного випромінювання, що проходить через хмару; поглиненим потоком; потоком, відбитим поверхнею Землі; потоком, перевідбитим від поверхні хмари, а також наведеним потоком від інших об’єктів на поверхні [11], то для спрощення розрахунків будемо використовувати деяку еквівалентну віртуальну щільність хмар, яка буде враховувати як величину прямого, так і величину відбитого випромінювання. Для визначення віртуальної щільності існує декілька методів, одним з яких є метод зворотного перетворення, який дозволяє визначити щільність об’єкту за набором його проекцій на деяку площину [12]. Що лінійна швидкість руху хмари значно більша за швидкість Сонця, яка визначається його кутовим переміщенням, схема розрахунку віртуальної щільності хмари за набором її проекцій при застосуванні методу зворотного перетворення полягає у наступному. Запишемо вираз для проекції хмари на сонячну панель наступним чином: xy p(x, y=) ∫ ∫ μ(x − χ, y − γ)dχd γ

Oz визначається оператором pz
Findings
Oξ на вісь
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