Journal of Electrical and Control Engineering JECE JECE Vol. 4 No. 1, 2013 PP. 16-25 www.joece.org/ © American V-King Scientific Publishing 16 Optimal Power Flows with security constraints using Cubic Lattice structured multi agent based PSO algorithm by optimal placement of Multiple TCSCs K. Ravi Kumar 1 , Dr. M. Sydulu 2 1 Associate Professor, EEE Department Vasavi College of Engineering, Hyderabad 2 Professor ,EE Department National Institute of Technology, Warangal 1 ravikadali12345@rediffmail.com; 2 sydulumaheswarapu@yahoo.co.in Abstract- This paper puts forward the implementation of Cubic lattice structured multiagent based PSO algorithm (CLSMAPSO) to obtain the optimal power flows by optimally placing TCSC devices. The Thyristor Controlled Series Capacitor (TCSC) is modeled using susceptance model with modifications in the Y bus of the Newton Raphson Algorithm. The constraints related to violation limits, minimization of line overload factor, and line loss are dealt using penalty factor approach. The new multi agent based cubic lattice structured PSO algorithm was considered for optimizing power flows while satisfying all the constraints mentioned above. This algorithm was tested on IEEE14, IEEE 30 and IEEE 57 bus systems to identify the suitable location, its reactance value and firing angle. The above results have been validated using Linear programming method in powerworld simulator. The results obtained were quite encouraging and will be useful in electrical restructuring. General Terms- Multi agent systems, Particle swarm optimization, Optimal power flows, security constraints, Thyristor controlled Series Capacitor (TCSC), FACTS (Flexible AC transmission systems) Keywords- Multi agent systems; Optimization techniques; Particle swarm optimization; Optimal power flows; security constraints I. INTRODUCTION Now a days, utilities are facing rapid increase in electricity demand with slow reinforcement projects due to financial and political issues. Proper operation and planning requires consideration of various factors such as reduction of generation cost, losses, security of power system, and FACTS application etc. In this aspect, the optimal power flows has become the leading research field with potential applications for both planning and operation of power system. An operational point of a power system not only is a stable equilibrium of differential and algebraic equations (DAE), but also must satisfy all of the static constraints of the equilibrium such as upper and lower bounds of generations, voltages of all buses and line flow units of all the transmission lines. This operation point in the power system is solved by OPF. In other words, OPF is to minimize the operating costs of the power system, transmission losses or other appropriate objective functions at the specified time instance subject to equality and inequality constraints, by determining an equilibrium operating state variables corresponding to power output of generators, transformer tap positions, phase shifter angle positions, shunt capacitors / reactors values, voltage values etc. Conventionally, OPF is used to solve security and economic operation of the power system. A wide variety of optimization techniques have been applied in solving the OPF problem such as non-linear programming, Quadratic Programming, Linear Programming, Newton based methods, Sequential unconstrained minimization technique, interior point methods, Genetic Algorithm, Evolutionary Programming. Heuristic algorithms such as Genetic Algorithms (GA) and Evolutionary programming which have been reported as show promising results for further research in this direction. Recently, a new evolutionary computation technique, called Multi agent based Particle Swarm Optimization (MAPSO) 2 , has been proposed. Particle Swarm Optimization (PSO) is one of the evolutionary computation techniques. In PSO, search for an optimal solution is conducted using a population of particles, each of which represents a candidate solution to the optimization problem. It was developed through the simulation of flock of birds to search for food in an optimal manner through their velocity and position up gradation. The PSO technique has been widely used for the optimization of various power system problems. However, the major drawback with PSO is that, it may need several iterations and may get trapped in local optima. Therefore, several strategies have been developed to overcome the limitations of PSO, such as modified PSO, and attractive and Repulsive PSO. These all were proved to be effective and boosted the development of MAPSO. Agent based computation has been introduced recently by Wooldridge 11 and applied for various optimization problems. In this paper, Multi agent based lattice structure and PSO have been integrated to obtain optimal Power Flows. In CLSMAPSO, each agent in cubic lattice structure represents a particle to PSO and a candidate solution to the optimization problem. All agents live in a cubic lattice structured environments, with each agent located on a lattice point. TO obtain optimal solution quickly, competition and cooperation operators have been used with their neighbors, and they can also use their own knowledge. With the search mechanism of PSO and agent-agent interactions, CLSMAPSO can obtain global solution with faster convergence characteristics. Today technologies developed as a part of flexible AC Transmission system (FACTS) can be handy to corrective methods, so that the system operates smoothly and consistently without violating thermal and operational limits.