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Shehata, T., M. A. S. moteleb, and E. M. A. El-Zahab, "STATCOM controllers based on fuzzy PI approach", Indonesian Journal of Electrical Engineering and Computer Science, vol. 18, issue 3, pp. 1138-1147, 2020. Abstract

The electricity companies enforced some legislation on the electricity consumption contracts because the electricity network cannot bear the increasing demands of consumers. Therefore, a new controlling system is required to improve the frequent variations of the power system operating point (OP). Consequently, the flexible AC transmission systems (FACTS) controllers should be able to integrate with recent OP. Coordination of FACTS controller is more sophisticated due to various OP and uncertainties parametric in cooperation with the non linearity of power system (PS). Static Synchronous Compensator (STATCOM) plays very important role like the stability support of large and small transient-disturbance in PS. Therefore, the aim of this research is presents fuzzy logic (FL) with the PI controller (a novel controller) its ability to improve the performance of the power system along with the capability of switch irregular and rough actual world data. This new controlling system may be suitable for a wide range of applications especially the models which deal with huge and complicated data analysis. This new controller system carries out the adjustments of the voltage on DC capacitor under transient and steady-state conditions.

Hamdy, M., M. Elshahed, D. Khali, and E. E. - D. A. El-Zahab, "Stochastic Unit Commitment Incorporating Demand Side Management and Optimal Storage Capacity", Iranian Journal of Science and Technology, Transactions of Electrical Engineering, vol. 43, issue 1, pp. S559–S571, 2019. Abstract

High penetration of wind energy imposes several operational challenges due to its uncertainty and intermittent nature. Flexible energy resources represent key solutions to compensate for power mismatch associated with wind power (WP) uncertainty and intermittency. This paper proposes a new stochastic unit commitment (SUC) problem formulation including high penetration of wind energy, energy storage system (ESS), and demand side management. Firstly, the Latin hypercube sampling is combined with Cholesky decomposition method to generate different WP scenarios. The simulated scenarios are then reduced using the fast forward selection algorithm. Finally, a novel SUC formulation implements these reduced scenarios to size the ESS optimally, considering its cost and benefit maximization of wind energy. To validate the proposed approach, a nine-unit test system is used to demonstrate the reduction in the operational cost and the increase in the utilized wind energy under different operational conditions.