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The electric power system is a complex system, whose operating condition may not remain at a constant value. This necessitates the power system operator be alert to keep the system performance under normal condition. The various contingencies like, large load variations, outage of components (transmission lines, transformers, generators, etc.) are more common. Any of these conditions causes overloads and system parameters to exceed the limits thus resulting in an insecure system. Hence the operator has to maintain the security level by proper analysis and reschedule the system accordingly. The most practiced techniques for overload alleviation is generator rescheduling and/or load shedding. The conventional method is to solve an optimal power flow problem to find out the rescheduling for overload alleviation. But this will not give the desired speed of solution. This paper considers the application of fuzzy logic to dispatch the generator to relieve the overload in power system. A fuzzy rule based controller is developed which reschedules the real power generation. The system parameters such as overload factor (OF), generation shift sensitivity factor (GSSF) and sensitivity of vulnerability index of generation system (SVIGS) are given to a fuzzy inference system (FIS) as inputs. The output from the FIS gives the quantity of generation to be rescheduled. The proposed approach is illustrated with 39 bus New England system. The validity of the proposed method is done using MATPOWER.Index Terms-fuzzy logic control, generator rescheduling, overload alleviation, sensitivity factors and vulnerability index.

This paper presents an effective method of network overload management in power systems. The three competing objectives 1) generation cost 2) transmission line overload and 3) real power loss are optimized to provide pareto-optimal solutions. A fuzzy ranking based non-dominated sorting genetic algorithm-II (NSGA-II) is used to solve this complex nonlinear optimization problem. The minimization of competing objectives is done by generation rescheduling. Fuzzy ranking method is employed to extract the best compromise solution out of the available non-dominated solutions depending upon its highest rank. N-1 contingency analysis is carried out to identify the most severe lines and those lines are selected for outage. The effectiveness of the proposed approach is demonstrated for different contingency cases in IEEE 30 and IEEE 118 bus systems with smooth cost functions and their results are compared with other single objective evolutionary algorithms like Particle swarm optimization (PSO) and Differential evolution (DE). Simulation results show the effectiveness of the proposed approach to generate well distributed pareto-optimal non-dominated solutions of multi-objective problem.

Purpose – The electric power system is a complex system, whose operating condition may not remain at a constant value. The various contingencies like outage of lines, transformers, generators and sudden increase of load demand or failure of equipments are more common. This causes overloads and system parameters to exceed the limits thus resulting in an insecure system. The purpose of this paper is to enhance the power system security by alleviating overloads on the transmission lines. Design/methodology/approach – Fuzzy logic system (FLS) with particle swarm optimization based optimal power flow approach is used for overload alleviation on the transmission lines. FLS is modeled to find the changes in inertia weight by which new weights are determined and their values are applied to particle swarm optimization (PSO) algorithm for velocity and position updation. Findings – The proposed method is tested and examined on the standard IEEE-30 bus system under base case and increased load conditions at different contingency. This method gives better results in terms of optimum fuel cost and fast convergence under base case and could alleviate the line overloads at different contingency with optimum generation cost, when compared to adaptive particle swarm optimization (APSO) and PSO. Originality/value – FLS is modeled in MATLAB environment. The effectiveness of the proposed method is tested and examined on the standard IEEE-30 bus system and their results are compared with APSO and PSO under MATPOWER environment. The results show that the proposed algorithm is capable of improving the transmission security with optimum generation cost.

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