Omar, A. I., Z. M. Ali, S. A. H. E. Aleem, E. E. M. Abou-El-Zahab, and A. M. Sharaf,
"A Dynamic Switched Compensation Scheme for Grid-Connected Wind Energy Systems Using Cuckoo Search Algorithm",
International Journal on Energy Conversion (IRECON), vol. 7, issue 2, pp. 64-74, 2019.
AbstractThis paper presents a novel stabilization FACTS-based scheme that acts as a switched compensator for grid-connected wind energy systems. It is a member of a family of devices and switched dynamic voltage stabilization converters that were developed to ensure minimal loss of excitation, voltage stabilization, energy efficient utilization, power quality enhancement and harmonic distortion reduction in AC distribution grid networks. A novel-dual action distributed FACTS based–switched power filter compensator (SPFC) scheme is developed for efficient utilization of wind energy under varying wind conditions and major load excursions. A dynamic multi-level error-driven decoupled time de-scaled multi regulation control strategy is used to guarantee better power quality performance in terms of voltage enhancement and stabilization of the AC buses, improvement of power factor, and harmonic distortion reduction. The proposed SPFC was controlled using an inter-coupled weighted modified proportional-integral-derivative (WM-PID) controller. Cuckoo search (CS) optimization algorithm is employed to get the PID controller gains in terms of variations and excursions in wind speed and dynamic load excursions to reflect the performance of the compensator scheme. The effectiveness of the proposed SPFC with the multi-level control strategy has been assessed by time-domain simulations in Matlab/Simulink environment. The results obtained show the robustness of the proposed topology.
Omar, A. I., S. A. H. E. Aleem, E. E. A. El-Zahab, M. Algablawy, and Z. M. Ali,
"An improved approach for robust control of dynamic voltage restorer and power quality enhancement using grasshopper optimization algorithm",
ISA Transactions, vol. 95, issue Dec. 2019, pp. 110-129, 2019.
AbstractThis paper presents a novel contribution of a low complexity control scheme for voltage control of a dynamic voltage restorer (DVR). The scheme proposed utilizes an error-driven proportional–integral–derivative (PID) controller to guarantee better power quality performance in terms of voltage enhancement and stabilization of the buses, energy efficient utilization, and harmonic distortion reduction in a distribution network. This method maintains the load voltage close to or equal to the nominal value in terms of various voltage disturbances such as balanced and unbalanced sag/swell, voltage imbalance, notching, different fault conditions as well as power system harmonic distortion. A grasshopper optimization algorithm (GOA) is used to tune the gain values of the PID controller. In order to validate the effectiveness of the proposed DVR controller, first, a fractional order PID controller was presented and compared with the proposed one. Further, a comparative performance evaluation of four optimization techniques, namely Cuckoo search (CSA), GOA, Flower pollination (FBA), and Grey wolf optimizer (GWO), is presented to compare between the PID and FOPID performance in terms of fault conditions in order to achieve a global minimum error and fast dynamic response of the proposed controller. Second, a comparative analysis of simulation results obtained using the proposed controller and those obtained using an active disturbance rejection controller (ADRC) is presented, and it was found that the performance of the optimal PID is better than the performance of the conventional ADRC. Finally, the effectiveness of the presented DVR with the controller proposed has been assessed by time-domain simulations in the MATLAB/Simulink platform.
Younis, R. A., D. K. Ibrahim, E. M.Aboul-Zahab, and A. ’fotouh El'Gharably,
"Power Management Regulation Control Integrated with Demand Side Management for Stand-alone Hybrid Microgrid Considering Battery Degradation",
International Journal of Renewable Energy Research, vol. 9, issue 4, pp. 1912-1923, 2019.
AbstractA new Power Management Regulation Control (PMRC) integrated with Demand Side Management (DSM) strategies is proposed to enhance the Energy Management System (EMS) of a stand-alone hybrid microgrid. The microgrid combines Wind and PV systems as Renewable Energy Sources (RES) with a hybrid Energy Storage System (ESS) of Battery and Fuel Cell/Electrolyzer set. Towards achieving Net Zero Energy Supply, such microgrid is adequate in remote and isolated new communities with AC controllable critical and noncritical loads. The proposed PMRC implies two-levels of control based on Multi-Agent System (MAS). The first level keeps the output power of each source in its maximum available output power by applying maximum power point tracking (MPPT) techniques. The second level is based on making proper decisions for achieving the power balancing regulation and coordination between the available and the reserve power of the RES and ESS under different operating modes. Valley Filling, Energy Conservation and Load Shifting are applied as DSM strategies to improve loads sustainability during system contingencies. Considering the battery as the most expensive part in the microgrid, the effectiveness of the proposed strategy is further verified by determining the maximum permissible estimated battery lifetime during the operation in all possible scenarios. Extensive simulation studies for various scenarios of microgrid operation in a year were carried out using Matlab/ Simulink with realistic typical wind speed, solar irradiation data and restricted by the status of available ESS.
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.
AbstractHigh 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.