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Low-frequency oscillations (LFO) are an inevitable problem of power systems and they have a great effect on the capability of transfer and power system stability. The power system stabilizers (PSSs) as well as flexible AC transmission system (FACTS) devices can help to damp LFO. The target of this study is to tackle the problem of a dual-coordinated design between PSS and unified power flow controller (UPFC) implementing the task of power oscillation damping (POD) controller in a single machine infinite bus (SMIB) system. So, dolphin echolocation optimization (DEO) technique is utilized as an optimization tool to search for optimal parameter tunings based on objective function for enhancing the dynamic stability performance for a SMIB. DEO an algorithm has a few parameters, simple rules, provides the optimum result and is applicable to a wide range of problems like other meta-heuristic algorithms. Use DEO gave the best results in damping LFO compared to particle swarm optimization (PSO) algorithm. From the comparison results between PSO and DEO, it was shown that DEO provides faster settling time, less overshoot, higher damping oscillations and greatly improves system stability. Also, the comparison results prove that the multiple stabilizers show supremacy over independent controllers in mitigationg LFO of a SMIB.

<p>Distribution Network Reconfiguration (DNR) is a significant problem for<br />keeping the network running under normal conditions. In this study, for<br />preventing the premature convergence issue, also to improving the searching<br />ability of the Binary Particle Swarm Optimization (BPSO) algorithm, chaotic<br />strategy is incorporating with BPSO algorithm to create a new hybrid<br />algorithm called Chaotic BPSO (CBPSO). Undeniably, the chaotic strategy<br />enables the hybrid CBPSO algorithm to slip from the local optima and also to<br />reach optimal solution in fewer number of iterations compare to BPSO due to<br />the remarkable behavior and ergodic of the chaos strategy than random<br />search in BPSO algorithm. The CBPSO algorithm is presented as a<br />advantageous optimization tool for solving DNR. In this problem, decreasing<br />of real power loss () is an objective function while node voltage, system<br />radially and line current have been utilized as a constrains of the system. The<br />search space in this problem for the presented technique is a group of lines<br />(switches) that are normally opened or closed. Two types of loads are<br />presented: the constant and variable loads for testing the efficacy of the<br />CBPSO method for tackling DNR problem when the load is changes. The<br />proposed technique is implemented on IEEE Node system by utilizing<br />R2013b software for verifying the efficacy of CBPSO technique. The<br />simulation results confirm that technique has high ability in reducing and<br />raising the voltage profile of the grid compared to and other procedures in<br />the literature.</p>

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Distributed generation (DG) units have an important number of economic, environmental and technical features, which can contribute to the improvement of the reliability and security of the electric grid. However, all benefits that mentioned before cannot be maximised and enhanced unless the best sizing and position of distributed generation units are accurately determined. The arbitrary placement of DG units can lead to negative influences on the electrical networks. A noteworthy number of methods have been suggested to compute the optimal sizing and position of Distributed generation (DG) units in distribution networks. However, some of them focused on an analytical approach to estimate the optimum allocation of DG units in the radial distribution networks. Indeed, although this method was considered both constant and variable loads, as well as this method, overcome the problem of convergence, but the optimal sizing of DG units was not considered. The main intention of this study is to improve a technique that based on an intelligent algorithm for optimal planning and operation of DG technologies to minimise the real power losses, boost the voltage profile and enhance the overall reliability. IEEE Node-15 system has been taken to perform this study based on a MATLAB environment.in a single paragraph.