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Fuzzy vs. Probabilistic Techniques to Address Uncertainty for Radial Distribution Load Flow Simulation

Energy and Power Engineering 2012年第2期4卷 99-105页

作者： roma raina Mini Thomas Faculty Manipal University Dubai UAE Jamia Millia Islamia University New Delhi India

For Power distribution system the most important task for distribution engineer is to efficiently simulate the system and address the uncertainty using a suitable mathematical method. This paper presents a comparison of two methods used in analyzing uncertainties. The first method is Montecarlo simulation (MCS) that considers input parameters as random variables and second one is fuzzy alpha cut method (FAC) in which uncertain parameters are treated as fuzzy numbers with given membership functions. Both techniques are tested on a typical Load flow solution simulation, where connected loads are considered as uncertain. In order to provide a basis for comparison between above two approaches, the shapes of the membership function used in the fuzzy method is taken same as the shape of the probability density function used in the Monte Carlo simulations. For more than one uncertain input variable, simulation result indicates that MCS method provides better output results compared to FAC, however takes more time due to number of runs. FAC provides an alternate method to MCS when addressing single or limited input variables and is fast.

关键词： Fuzzy Set Radial Power Distribution Montecarlo Load Flow

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Probabilistic Fuzzy Approach to Assess RDS Vulnerability and Plan Corrective Action Using Feeder Reconfiguration

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Energy and Power Engineering 2012年第5期4卷 330-338页

作者： Mini S Thomas Rakesh Ranjan roma raina Director IITB Sonepat India Faculty Manipal University Dubai Professor JamiaMilliaIslamiaUniversity New Delhi

Two common problems for a typical Power distribution system are voltage collapse & instability. Challenge is to identify the vulnerable nodes and apply the effective corrective actions. This paper presents a probabilistic fuzzy approach to assess the node status and proposes feeder reconfiguration as a method to address the same. Feeder reconfiguration is altering the topological structures of distribution feeders by changing the open/closed states of the sectionalizing and ties switches. The solution is converge using a probabilistic fuzzy modeled solution, which defines the nodal vulnerability index (VI) as a function of node voltage and node voltage stability index and predicts nodes critical to voltage collapse. The information is further used to plan best combination of feeders from each loop in distribution system to be switched out such that the resulting configuration gives the optimal performance i.e. best voltage profile and minimal kW losses. The proposed method is tested on established radial distribution system and results are presented.

关键词： Branch Voltage Three Phase Load Flow Voltage Stability Index (SI) Radial Distribution System (RDS) Monte Carlo Probability Distributions Fuzzy Set Node Vulnerability Index(VI) Feeder Reconfiguration

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Fuzzy vs. Probabilistic Techniques to Address Uncertainty for Radial Distribution Load Flow Simulation

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Energy and Power Engineering（能源与动力工程） 2012年第2期

作者： roma raina Mini Thomas

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Probabilistic Fuzzy Approach to Assess RDS Vulnerability and Plan Corrective Action Using Feeder Reconfiguration

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Energy and Power Engineering（能源与动力工程） 2012年第5期

作者： Mini S Thomas Rakesh Ranjan roma raina

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