Power system security analysis plays key role in enhancing the system security and to avoid the system collapse condition. In this paper, a novel severity function is formulated using transmission line loadings and bus voltage magnitude deviations. The proposed severity function and generation fuel cost objectives are analyzed under transmission line(s) and/or generator(s) contingency conditions. The system security under contingency conditions is analyzed using optimal power flow problem. An improved teaching learning based optimization (ITLBO) algorithm has been presented. To enhance the system security under contingency conditions in the presence of unified power flow controller (UPFC), it is necessary to identify an optimal location to install this device. Voltage source based power injection model of UPFC, incorporation procedure and optimal location identification strategy based on line overload sensitivity indexes are proposed. The entire proposed methodology is tested on standard IEEE-30 bus test system with supporting numerical and graphical results. Ó 2015 Faculty of Engineering, Ain Shams University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Abstract:The power system becomes more severe under contingency conditions. In general, the contingencies may be outage of transmission lines or generators. To identify the effect of outages on system security, the contingency analysis is one of the analytical tools. The congestion on a system must be manages using generation rescheduling and with the proper control of the compensation equipments. The transmission line outage sometime increases the total power system losses, cascading outage of transmission lines, etc. Finally, the system leads to collapse condition. To avoid this type of uncontrolled condition, the power system security needs to be analyzed under transmission line outage condition. In this paper, the most critical transmission lines are identified using line collapse proximity index values and the system severity is analyzed in terms of transmission line loadings, bus voltage magnitude variations are tested on standard IEEE-14 bus test system and the analytical results are presented in numerically and as well as graphically.

A new optimization technique is proposed for solving optimization problems having single and multiple objectives, with objective functions such as generation cost, loss, and severity value. This algorithm was developed to satisfy the constraints, such as OPF constraints, and practical constraints, such as ram rate limits. Single and multi-objective optimization problems were implemented with the proposed hybrid fruit fly-based artificial bee colony (HFABC) algorithm and the non-dominated sorting hybrid fruit fly-based artificial bee colony (NSHFABC) algorithm. HFABC is a hybrid model of the fruit fly and ABC algorithms. Selecting the user choice-based solution from the Pareto set by the proposed NSHFABC algorithm is performed by a fuzzy decision-based mechanism. The proposed HFABC method for single-objective optimization was analyzed using the Himmelblau test function, Booth’s test function, and IEEE 30 and IEEE 118 bus standard test systems. The proposed NSHFABC method for multi-objective optimization was analyzed using Schaffer1, Schaffer2, and Kursawe test functions, and the IEEE 30 bus test system. The obtained results of the proposed methods were compared with the existing literature.

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This paper proposes a Fast Load Voltage Stability Index (FLVSI) constrained Binary Integer Programming (BIP) method for Phasor Measurement Unit placement at optimal locations in network to obtain complete observability. Every load bus of network is considered to sort out weak load bus from proposed FLVSI approach. PMUs are constrained to place at weak load buses using BIP approach for observability of network. Zero Injection (ZI) modeling is suggested to reduce PMU placement locations in network. Single line outage or PMU loss constraints are formulated for placement of PMUs. Bus Redundancy Index (BRI) is formulated and considered for every bus of network. With and without ZI modeling under normal and line outage cases is compared to present effectiveness of approach. IEEE –14- 30-and 57- bus networks are tested with MATLAB Programming and compared with other methods to show its effectiveness.