## Operative Forecasting of the Random Process of Active Power Consumption in the Electric Power System and Its Main Nodes

D. Nikolov (Bulgaria)

### Keywords

Forecasting, Active electrical load, Random process, Modeling, Trigonometric polynomials With the used deterministic approach, modeling of active power load schedule is made by means of interpolation. It is necessary that the values of the interpolating function P(t) in uniformly arranged points and its derivatives up to a certain order should be known. Usually, this function is an algebraic polynomial. The next step is the formulation of Eremite’s trigonometric polynomials through which

### Abstract

Although the use of active power is set in discrete values, it represents a continuous random process. The analysis of the methods for presenting continuous random processes shows that the most effective one is their decomposition to trigonometric orders or through algebraic orthogonal polynomials. The application of trigonometric polynomials is very successful. Their direct application is not efficient due to their labor-consuming computation, which renders them inconvenient for the purposes of operative management of regimes in EPS [1]. In order to facilitate the computational process, it is necessary to introduce changes in the principle of trigonometric polynomial formation. The optimal management of regimes in the electric power system (EPS) requires considerably accurate forecasting of the active electrical loads of EPS and its main nodes. For the operative forecasting of such loads it is proposed to decompose the random process to orthogonal components. For this purpose trigonometric polynomials are used. Their direct computation is associated with labor-consuming calculations. Changes are introduced in the principle of their formulation, whereby the computing process is simplified. Experiments are also carried out for operative forecasting of active levels of the EPS and some main nodes that demonstrate the considerable accuracy of the mathematical model proposed. 2. Problem Formulation