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Nowadays, penetration of DG resources into the power systems due to their advantages is rapidly increasing. Islanding performance is one of the most disadvantages of using DGs, which should be considered, because this option may lead to negative effects on the protection, performance, and operation management of distributed systems implementation. An island must be detected in less than 2 sec based on IEEE STD 1547-2003 standard, and DG resources must be disconnected from distribution network immediately. In this paper, a novel hybrid algorithm to identify the islanding has been proposed based on the passive parameters (ROCOV and ROCORP) and capacitor bank connection strategy. In the incompatibility conditions of the large-scale power, by combining two parameters i.e. ROCOV and ROCORP and investigating their changes, the islanding is carefully and quickly identified. This strategy is completely verified in the mismatch conditions of small-scale power by applying the capacitor bank connection strategy. The presented approach is tested on two case studies and the detailed results were completely reported. As it was shown, the proposed approach is able to distinguish between islanding and the other events. [ABSTRACT FROM PUBLISHER]

The application of the turbo-expander in the auxiliary service system of Neka power plant in Iran causes considerable voltage sag, which is very dangerous to the auxiliary service system. To reduce the voltage sag, the dynamic voltage restorer (DVR) is proposed. The auxiliary service system and main substation of the power plant with compensators are simulated by Power System Computer Aided Design (PSCAD/EMTDC) software. The application of the static synchronous compensator in different scenarios is discussed, and the results are compared with the results of the application of the DVR, which has a new topology and minimum injection power control strategy. It is shown that the results of the DVR application are better in all tested scenarios. Also, the economic assessment shows that the payback period is reduced to half in case of using DVR instead of static synchronous compensator. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper presents an interactive fuzzy satisfying method based on Improved θ-Particle Swarm Optimization (Iθ-PSO) to solve the Multi-objective Optimal Operation Management (MOOM) problem which can be affected by Fuel cell power plants (FCPPs). The objective functions should be minimized are total electrical energy losses, total electrical energy cost, total pollutant emission produced by sources and deviation of bus voltages. A new interactive fuzzy satisfying method is presented to solve the multi-objective problem by assuming that the decision-maker (DM) has fuzzy goals for each of the objective functions. Through the interaction with the DM, the fuzzy goals of the DM are quantified by eliciting the corresponding membership functions. Then by considering the current solution, the DM acts on this solution by updating the reference membership values until the satisfying solution for the DM can be obtained. The MOOM problem is modeled as a mixed integer nonlinear programming problem. Therefore, in order to solve this problem, evolutionary methods because of independence on the type of objective function and constraints can be used. θ-PSO is based on the phase angle vector and can generate a high-quality solution within shorter calculation time in comparing with original PSO and other stochastic methods. θ-PSO the same as PSO is easy to fall into stagnation when no particle discovers a position that is better than its previous best position for several generations. In order to avoid this shortcoming, we have proposed an Improved θ-PSO algorithm to solve MOOM problems. Numerical results for a 69-bus distribution test system have been presented to illustrate the performance and applicability of the proposed method. [ABSTRACT FROM AUTHOR]

The solution of the unit commitment problem (UCP) is a complex optimization problem. The exact solution of the UCP can he obtained by a complete enumeration of all feasible combinations of generating units, which could be a huge number. The objective is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal generating unit commitment in the power system for the next hours. This paper presents a Modified Shuffled Frog Leaping Algorithm (MSFLA) to solve optimal Unit Commitment Problem (UCP). The MSFLA is applied to the widely used ten-unit test system and its multiples (10-100). Comparing our results with those of many UC solving methods demonstrate that not only the MSFLA procedure consider is the constraints very well, but also has some advantages, such as good convergence, fast calculating speed and high precision. [ABSTRACT FROM AUTHOR]

In this paper, an exhaustive search algorithm optimization technique is applied to multilevel inverter to determine the optimum switching angles for cascaded multilevel inverters for eliminating some higher order harmonics while maintaining the required fundamental voltage. This technique can be applied to the multilevel inverters with any number of levels; for example, the 7-level, 9-level and 11-level inverters, and the optimum switching angles are calculated offline to eliminate the 5th and the 7th harmonics. Then, these angles are used in an experimental setup to validate the results. [ABSTRACT FROM AUTHOR]