Coordinated control of SVC and TCSC for voltage profile improvement employing particle swarm optimization

Flexible AC transmission system (FACTS) devices are widely used in power system. They have characteristics to perform faster and can solve many problems in power system study. With regards to this, a particle swarm optimization (PSO) algorithm is applied so that to design the coordinated parameters of static VAR compensator (SVC) and Thyristor Controlled Series Capacitor (TCSC) is presented here. With behavioral nonlinearities of the power system, linear methods cannot be used to design coordinated parameters of controllers. Simulations has been done on IEEE (WSCC) 9 bus power system in MATLAB and its toolboxes. The results are compared and found that coordination of FACTS devices with each other confirm the efficiency of the proposed method for improving the voltage profile. When function of TCSC is impelled by some curb, adjustable SVC can supply additional support to upgrade the gross performance.


I. INTRODUCTION
Flexible ac transmission system controllers have ability to extend the power transfer capability and also to enhance the stability within given limits, along with improvements in power system operation [3]. Voltage stability has been seen as a steady state problem involving static power flow studies for analysis. The voltage at various buses, the flow of active and reactive power, etc. keep on changing. It is understood that the FACTS controller will normally be equipped with higher order controllers such as power swing damping controller, Sub Synchronous Resonance (SSR) damping controller etc. Still to develop an insight, the FACTS controller is assumed to be equipped with simple PI controller only [1]. For improvement in operation of power system kind of interaction can occur amongst different types of FACTS controllers, which may include the interaction of stabilizers and High voltage DC (HVDC) controllers, too. It is categorized on the base of different frequency ranges. The term coordination haven't a meaning for centered control; instead, it understood that the tuning of the FACTS controllers will be done together for ensuring the promising, positive improvement of the overall control scheme. It is implied that the each controller depends chiefly on measure of topically useable quantity. It will act separately on connected FACTS devices.
The TCSC is a prime element of FACTS (Flexible AC Transmission Systems). With the firing control of the thyristors, it can change its apparent reactance smoothly and rapidly [2]. The TCSC is able to directly schedule power flow along required trails and allow the network to run near to the line limits [9]. The SVC is a shunt compensation component. It is actually drafted for voltage maintenance in power structures. Ample as the TCSC, the SVC is also capable of flexible adjustment. In conventional methods, when performance of power system is normally linear, it is designed and engaged cautiously. In the occurrence of large perturbation, power system operating point changes considerably. However, in these conditions, nonlinearities of power system have substantial effects and linear methods cannot be capable of endure its stability [10]. Therefore, it is essential to consider the effect of nonlinearities of power system [9]. Recent years, intelligent optimization algorithms has been broadly used to design power system stabilizers. In this context, tabu search algorithm [6], genetic algorithm [7], simulated annealing, bacterial foraging algorithm (BFA) and small population-based PSO are applied as intelligent algorithms for one to one coordination of stabilizer in power system. In various literature many researchers proposed the coordination betwixt Power system stabilizer and FACTS controller for encompassing the vigorous performance of the power network. In [8], global tuning method for PSS and FACTS devices using a parameter forced no dimensional optimization algorithm is shown. The integral of squared error process is utilised for global attuning in the stabilizers by considering the multimachine power area containing SVC and TCSC besides PSS to manifest the efficient and hardiness of the proposed tuning procedure is discussed in [10].

SVC & TCSC
According to IEEE definition, SVC, known as a shunt connected static var generator; capable of stepless adjustment of reactive power over an unlimited range i.e. lagging or leading without any time delay. In its basic form it comprises of fixed capacitor bank and switched reactor bank in parallel. A duet of reverse poled thyristors is attached in sequence with a confirmed inductor to frame a Thyristor Controlled Reactor (TCR) module. When the thyristors, connected in succession with a capacitor they will pattern Thyristor Switched Capacitor module. These will draw reactive power from the line and thereby regulating voltage, improve both steady-state and dynamic stability and reduce voltage flicker. Hence it will drastically improve the voltage profile. The main chore of SVC is to endure the voltage of a specific bus with reactive power compensation which is normally done by adjusting the firing angle of the thyristors. Moreover to this, Static VAR Compensator (SVC) is normally fixed in parallel with line and main function is to modulate the voltage at sated bus by supervising its identical reactance. Generally there are two layout of the SVC i.e. as per Fig. 1. The SVC can be modelled as a first order linear differential equation model. Basically, it is at the middle of a transmission line or sometimes at a load bus, too.
The fundamental arrangement of the TCSC is as per Fig.2. The structure comprises of a Thyristor controlled reactor (TCR), a parallel capacitor and a Metal Oxide Varistor (MOV). In the same, one may found restriction in limit of firing angles, safety measure of voltage in MOV as well as the harmonic current(I), resting on line current. Consequently, the span of Reactance is further little. Potential of TCSC may be elucidated with regard to their reactance against the line current.
TCSC will react as an inductive or capacitive compensator by reshaping its equivalent reactance XTCSC of transmission line [13]. Its value is maintained within definite capacitive reactance span, while supplying damping to power structure. In the transient process, this controls line power flow by rapidly changing equivalent reactance. The TCSC furnishes muscular meaning of commanding and enlarging power transferal level of the system by differing the noticeable impedance of a determined transmission line. A TCSC is exploited in a drafted way for contingency to escalate power system stability [5].

A. Basics of PSO
Particle swarm optimization is a robust stochastic optimization technique based on the movement and intelligence of swarms. PSO applies the concept of social interaction to problem solving. It was developed in 1995 by James Kennedy (socialpsychologist) and Russell Eberhart (electrical engineer) [4]. PSO has a pliant and finely adjusted mechanics to raise the global and local expedition abilities. It is applying a various agents (particles) which represents a swarm travelling in the search margin, focusing for the best solution. Each particle is viewed as a spot in an N-dimensional space, which calibrates its "flying" in fulfilment of its own flying occurrence besides the "flying" occurrence of additional agents. The agents in the optimization formulation contribute its data with one and all & run so as to approach the foremost flight for detecting optimal result by number of iterations. In apiece iteration, agents will have to revise their velocities and positions by operating the following equations: Vi k+1 = W* Vi k +C1 rand1(…) * (Pbest-si k ) + C2 rand2(…) * (gbest-Si k ) … (1) where, Vi k = Velocity of agent I at iteration k, W = Weighting function, Ci = weighting factor, rand = uniformly distributed number b/w 0 and 1, The PSO iteration is carried out to obtain the smooth voltage profile according to the algorithm of it, as shown in fig. (3). The optimization issue considered in this occasion is to curtail the cost. Target in this optimization issue is to operate as a fitness function in the problem.

No. of Particles 10
Max. Inertia weight 0.9 Min. Inertia weight 0.4 C1, C2 0.5, 3.5 No. of Iterations 10 With the perspective of an advancement, functioning of the PSO is wagerer with respect to GA [12] and then it is proved that PSO appears with its terminal parameter data in very lesser number of generations than the GA. Apart from that it was found that several stabilizers like PSS, SVC, TCSC etc. are individually can improve the system stability. With balancing to GA, PSO was gentle to enact and it comprises of very less variables to adapt [11]. All agents in process are kept as a fellow of society through the course of procedure. PSO is the sole algorism that will not execute the existence of the fittest. In Evolutionary Programming (EP), poise between the global and local search should be managed through the strategy variable, while in PSO the poise will accomplish by the inertial weight factor (w). Apart from all, PSO has many variants like discrete PSO, MINLP PSO, Hybrid PSO etc. Ordinary PSO have demerit of the short of convergense directed to global optima.

A. Representation of Power System
To examine the network, the Western System Coordinated Council (WSCC) 3-machine, 9-bus system shown in Fig. 4 is depicted. Base MVA is considered as 100 MVA, and system frequency is taken as 60 Hz. The system parameters is also given in Appendix. In Fig. 4 Bus numbers are shown as 1,2,3,…,9. V.

RESULT AND DISCUSSION
In this study, PSO algorism is put upon to navigate the datas of SVC and TCSC controller coordinately by solving equation (1). In order to formalize the said method, the simulations are put through the multi machine system in MATLAB using i t s toolboxes. PSO [4] used here is based on finding the value of L & C of SVC from which we get good and fine co-ordination.
Here, PSO is used with some modification like change in PSO range & number, change in selection criteria technique, control technique compare to Generalize PSO. Now the execution of the projected coordinated act is studied for a multi machine system as per Figure 4 with a SVC of 300 MVA installed at bus 6. Also, between transmission line 8-9, TCSC is connected. SVC initiation in the transmission line for bettering the voltage profile in the system is being carried. Parameters of PSO algorithm is as per Table 1. Results for voltage profile improvement at buses 1, 2 and 3 are tabulated in Table 2. Figure 5(

VI. CONCLUSION
This paper gives a concise idea on effect of Coordination. Their individual contribution towards the improvement of voltage profile which have experimented on a 9-bus system. The combination comprised, SVC and TCSC has been considered, as a multi type FACTS devices effect on the maintenance of the voltage profile. The proper tuning optimizes the parameters of the controllers. Also, results of simulation clearly validating that Voltage Profile is effectively improved with coordinated control technique.