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This article proposes an enhanced quasi-reflection jellyfish optimization (QRJFO) algorithm for solving the optimal power flow (OPF) problem. The multi-dimension objective functions are the fuel costs, transmission losses and pollutant emissions. Despite the simple structure of the jellyfish optimization algorithm, it requires significant exploitation and exploration control characteristics to support its capability. In the proposed QRJFO, a cluster is chosen randomly for every jellyfish from the population to reflect the social group that shares information in it. It varies from one to the next. The exploration phase is supported by introducing quasi-opposition-based learning. The performance of the proposed QRJFO algorithm is evaluated on the IEEE 57-bus, practical West Delta Region system and large-scale IEEE 118 bus. The simulation results demonstrate the quality of the solution and resilience of QRJFO. It is very significant for operating power systems from economic, technical and environmental perspectives. [ABSTRACT FROM AUTHOR]

A new procedure to optimally identifying the prediction equation of oil breakdown voltage with the barrier parameters’ effect is presented. The specified equation is built based on the results of experimental works to link the response with the barrier parameters as the inputs for hemisphere-hemisphere electrode gap configuration under AC voltage. The AC HV is applied using HV Transformer Type (PGK HB-100 kVAC) to the high voltage electrode in the presence of a barrier immersed in Diala B insulating oil. The problem is formulated as a nonlinear optimization problem to minimize the error between experimental and estimated breakdown voltages (VBD). Comprehensive comparative analyses are addressed using three recent innovative marine predators, grey wolf, and equilibrium optimization algorithms to reduce the error between the experimental and estimated breakdown voltages. In addition, the experimental results are expressed in two different models via grey and real coding. Finally, simulation results are conducted with statistical indices that show the effectiveness of the proposed models for experimental verification. The total percentage errors of the tested samples between the observed and estimated VBD are 1.207, 1.222, and 1.207 for EO, GWO, MPA, respectively. The marine predator algorithm has the best performance compared with the other two competitive algorithms for grey and actual codes. [ABSTRACT FROM AUTHOR]

In this paper, we studied the vibration performance, energy transfer and stability of the offshore wind turbine tower system under mixed excitations. The method of multiple scales is utilized to calculate the approximate solutions of wind turbine system. The proportional-derivative controller was applied for reducing the oscillations of the controlled system. Adding the controller to single degree of freedom system equation is responsible for energy transfers in offshore wind turbine tower system. The steady state solution of stability at worst resonance cases is studied and examined. The offshore wind turbine system behavior was studied numerically at its different parameters values. Furthermore, the response and numerical results were obtained and discussed. The stability is also analyzed using technique of phase plane and equations of frequency response. In addition, the numerical results and comparison between analytical and numerical solutions were obtained with MAPLE and MATLAB algorithms. [ABSTRACT FROM AUTHOR]

This paper investigates the vibration control, stability, and energy transfer of the offshore wind turbine tower system with control force and nonlinearity terms. A nonlinear proportional derivative (NPD) controller was connected to the system to reduce a high oscillation amplitude and to transfer the energy in the wind turbine system. Furthermore, the averaging method and Poincaré maps were used with respect to the controlled system to study the stability and bifurcation analysis in the worst resonance cases. The curves of force response and frequency response were plotted before and after the control unit was added to the wind turbine system. In addition, we discuss the performances of the control parameters on the vibration magnitudes. Numerical simulations were carried out with Maple and Matlab algorithms to confirm the analytical results. The results show the effectiveness of the NPD controller in suppressing the nonlinear oscillations of the wind turbine system. [ABSTRACT FROM AUTHOR]