Introduction Transmission system security management under (N−1) line contingency is one of the typical and essential tasks in power system operation and control. This paper examines the impact of the optimal unified power flow controller (OUPFC) and renewable energy sources (RES) on the severity of (n−1) line contingency on transmission system security. Materials and methods To test the performance of OUPFC device under single line contingency conditions, an optimal power flow (OPF) based multi-objective function is formulated using real power loss and line collapse proximity indicator (LCPI). Primarily, the optimal location of the OUPFC is determined using LCPI index and then (n−1) contingency analysis is performed by considering OUPFC device at different RES generation levels. Here, the control variables of OUPFC, tapchangers, VAr injections, output power of conventional energy sources (CES), bus voltages and bus angles are optimized with two different variants of the cuckoo search algorithm (CSA) namely (1) dynamically increasing switching parameter in power of three (CSA1) and (2) exponentially increasing switching parameter (CSA2). Conclusion The simulation results of various case studies on a standard IEEE-30 bus test system have shown the superiority of CSA2 in solving the multi-objective, non-linear complex optimization problem over CSA1 and time-varying acceleration coefficient-particle swarm optimization (TVAC-PSO). Also, the ability of OUPFC for managing the impact of (n−1) line contingency and variable RES generation is shown in terms of decreased real power loss, improved voltage profile and enhanced security margin.

Currently, most of the power systems are being integrated with flexible AC transmission system devices and renewable energy sources for operating with enhanced security margins and balancing the increasing demand cost-effectively. On the other side, the trend of increasing global warming and extremely changing weather conditions is continuing across the world. Under this scenario, it is essential to realize their effect on various power system components and its economic operation. In this paper, the parameters namely resistance of the transmission line/transformer, load and solar photovoltaic generation are modeled considering ambient temperature effect. Later, economic schedule under changing weather conditions is proposed for attaining multi-objectives simultaneously like total operating cost of conventional energy, real power loss, average voltage collapse point indicator index and average voltage deviation index. Also, the dispatchable problems in the transmission system and various practical operating constraints are handled via optimally setting the parameters of optimal unified power flow controller. The optimization problem is solved using adaptive cuckoo search algorithm (ACSA), in which a dynamically increasing switching parameter in a power of three is adopted for adjusting the random walk between local optima and global optima. The superiority of the proposed ACSA in solving the multiobjective, nonlinear complex optimization problem over basic CSA and particle swarm optimization, chicken swarm optimization and flower pollination algorithm is presented by illustrating various case studies on standard IEEE 14, 30 and 118–bus test systems.

In this paper, a novel flexible AC transmission system (FACTS) device named generalized optimal unified power flow controller (GOUPFC) is introduced to control the power flows in multi transmission lines and to regulate the voltages and angles at the load buses. The detailed power injection modeling of GOUPFC is presented in this paper. The optimal location of GOUPFC is determined based on line collapse proximity indicator (LCPI). A multi-objective function is framed in terms of average voltage deviation (AVDI), real power loss (Ploss) and average line collapse proximity indicator (LCPIavg) to test the effectiveness of the proposed device. The simulation studies are performed on standard IEEE 57-bus test system under single line contingency and considering various renewable energy source (RES) penetrations. The control parameters of GOUPFC are optimized by using whale optimization (WO-BAT) algorithm, by hybridizing WOA and BAT algorithms, and the superiority of WO-BAT is observed in minimizing the proposed objective function and enhancing the voltage profile.

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