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Techniques to reduce the search space when an optimizer seeks an optimal value are studied in this paper. A new mutation technique called the “Exponential Moving Average” algorithm (EMA) is introduced. The performance of EMA algorithms is compared to two other similar Computational Intelligence (CI) algorithms (an ordinary Evolutionary Algorithm (EA) and a “Mean-Variance Optimization” (MVO)) to solve...
The power systems of the future - smart grid - will see an increase in both renewable energy sources and load demand increasing the need for fast dynamic reconfiguration of system parameters. Advanced simulation capabilities are needed to support future planning and to implement real-time dynamic optimization. To achieve this, intelligent algorithms are needed for prediction and system monitoring...
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