A NEW HYBRID ALGORITHM FOR MULTI-OBJECTIVE DISTRIBUTION FEEDER RECONFIGURATION
Cybernetics and Systems
Nature-Inspired Metaheuristic Algorithms
Nature-Inspired Metaheuristic Algorithms
A new stochastic framework for optimal generation scheduling considering wind power sources
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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This paper proposes a new stochastic framework based on point estimate method to solve the optimal operation management of Distribution Feeder Reconfiguration DFR considering several Wind Turbines WTs in the system. The proposed method can properly solve the complex and discrete DFR optimization problem by the use of an adaptive modification approach based on firefly algorithm FA. In addition, a new stochastic solution based on 2m Point Estimate Method 2m PEM is proposed to handle the uncertainty associated with the problem random variables including the active and reactive loads as well as the wind speed variations effectively. The problem is then formulated in a multi-objective optimization structure including four significant targets: 1 active power losses, 2 bus voltage deviation, 3 total system costs and 4 total pollution produced. As a result of the conflicting behavior of the four objective functions, a fuzzy based clustering technique is employed to reach the set of optimal solutions called Pareto solutions. The feasibility and satisfying performance of the proposed method is examined on the IEEE 32-bus standard test system.