Abstract
In this paper, point estimation approach is used to calculate the statistical moment of a random quantity that is a function of <i>m</i> input random variables. In this work, loads of the proposed network is considered as a random variable. Two special cases of point estimation approach are considered such as <i>2m</i> and <i>2m+1</i> concentration schemes. In <i>2m</i> concentration scheme, skewness is considered, but in <i>2m+1</i> concentration scheme, both skewness and kurtosis are taken into account for probability density function. The proposed model is investigated using P. M. Anderson 9-bus test system. As a result, by changing the value of a random variable that follows a predefined distribution, expected bus voltage magnitude and expected line loading are identified. For the comparison purpose, <i>2m</i> and <i>2m+1</i> scheme was compared with deterministic load flow analysis.
Highlights
Power flow study in power system is an important tool
Probabilistic power flow model is proposed with point estimation method, two special cases 2m and 2m+1 concentration schemes are used, a total load of the proposed network is considered as a mean value, and an arbitrary value of standard deviation is selected for creating the uncertainty in load
The proposed model based upon the point estimation method, 2m and 2m+1 concentration scheme were used to evaluate the points of an input random variable
Summary
Power flow study in power system is an important tool. It is mostly used to evaluate the voltage magnitude and angle at different buses in power system, active and reactive power flow through the line. Different types of changes are noticed in recently published papers [3], [4] Among of these problems, uncertainty in renewable sources is a major challenge for engineers. To handle the said problem, probabilistic power flow (PPF) analysis is taken into consideration. Probabilistic power flow model is proposed with point estimation method, two special cases 2m and 2m+1 concentration schemes are used, a total load of the proposed network is considered as a mean value, and an arbitrary value of standard deviation is selected for creating the uncertainty in load. By varying the value of skewness and kurtosis different results are observed These results can be used for future planning, corrective action, and operation of electric power distribution system.
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