Calculations & programs for power system networks
Calculations & programs for power system networks
On assessing the H value in fuzzy linear regression
Fuzzy Sets and Systems
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Power System Analysis and Design: With Personal Computer Applications
Power System Analysis and Design: With Personal Computer Applications
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This paper presents a new approach to solve the load-flow problem using Tanaka's Fuzzy Linear Regression formulation (FLR). The load-flow model is formulated as a fuzzy linear optimization problem, where the objective is to minimize the sum of the spread of the states, subject to double inequality constraints on each pre-specified active and reactive power to guarantee that the original membership is included in the state membership. Linear programming is employed to obtain the middle and the symmetric spread for every state variable. The estimated middle corresponds to the value of the state. While the symmetric spreads in the membership functions of the state variables represents the uncertainty (vagueness) around the state. The proposed formulation has been applied to various test systems. The outcome is very encouraging and proves that proposed (FLR) is very applicable and shows reliability, accuracy in solving the power-flow problem.