Optimization technologies have drawn considerable interest in power system research. The success of an optimization process depends on the efficient selection of method and its parameters based on the problem to be solved. Firefly algorithm is a suitable method for power system operation scheduling. This paper presents a modified firefly algorithm to address unit commitment issues. Generally, two steps are involved in solving unit commitment problems. The first step determines the generating units to be operated, and the second step calculates the amount of demand-sharing among the units (obtained from the first step) to minimize the cost that corresponds to the load demand and constraints. In this work, the priority list method was used in the first step and the second step adopted the modified firefly algorithm. Ten generators were selected to test the proposed method, while the values of the cost function were regarded as criteria to gauge and compare the modified firefly algorithm with the classical firefly algorithm and particle swarm optimization algorithms. Results show that the proposed approach is more efficient than the other methods in terms of generator and error selections between load and generation.

<p>The balance of the power supply and demand (frequency control) is one of the most ancient approaches for the power systems, which is considered as a highly complex system.The power systems frequency response is a perfect indicator of the resilience to the multi-disturbances. In this work, the fuzzy logichas been scaledusing PSO segmentation (SePSO) and suggested to get high performance of frequency stability. PSO has participated into multi-segments for calculating the scald-fuzzy membership with basic rules. Two identical interconnectedpower areas wereselected to exam the new scaled fuzzy method. The time response of the results has undertaken the effectiveness of the controller reactionusing the MATLAB Simulink. The work feed back proved that the proposed SePSO optimization for the controlhas significantly faster with low undershot concerningthe classical controllers in differenttime schedules and disturbance values.</p>

<span lang="EN-US">The paper proposes a protection to dual stator generator, reluctance rotor, from asymmetrical fault. Which prevents the dual stator generator, reluctance rotor, from electrical sage through working process in order to avoid any interruption in the generator-grid connection. The procedure consummated with injecting suitable reactive power during the fault period. The proposed method that makes it possible for wind turbine application via dual stator winding generators (DSWRG) synchronous mod to stay connected to the grid during asymmetrical faults. It has been built according to trusted simulating mode considering all tested parameters according to experiment work. The expirment, consider the DC link side stability and care about the behavior and performance of machine side parameter. As well the machineability is evaluated to ride through asymmetrical fault by observing the secondary side current which has a big role in saving grid side converter. The control takes a response within 200 ms after fault trigger recognition. The generator ability of dynamically remaining connected stable and existing in the network, which is sustained a series voltage disturbance by injecting appropriate amount of reactive power. The main interest required in this paper is the capability of a machine to overcome the asymmetrical fault.</span>

<span>A modified firefly algorithm (FA) was presented in this paper for finding a solution to the economic dispatch (ED) problem. ED is considered a difficult topic in the field of power systems due to the complexity of calculating the optimal generation schedule that will satisfy the demand for electric power at the lowest fuel costs while satisfying all the other constraints. Furthermore, the ED problems are associated with objective functions that have both quality and inequality constraints; these include the practical operation constraints of the generators (such as the forbidden working areas, nonlinear limits, and generation limits) that makes the calculation of the global optimal solutions of ED a difficult task. The proposed approach in this study was evaluated in the IEEE 30-Bus test-bed; the evaluation showed that the proposed FA-based approach performed optimally in comparison with the performance of the other existing optimizers, such as the traditional FA and particle swarm optimization. The results show the high performance of the modified firefly algorithm compared to the other methods.</span>

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