Improving Frequency Stability of the Nigerian 330kv Transmission Network Using Fuzzy Controller

: The frequency instability observed in the power transmission network was mainly as a result of the per unit volts not falling within 0.95 through 1.05 P.U, volts. This has caused constant power failure in our transmission net work. This sad situation of power failure noticed in the power transmission network is contained by introducing an improvement in frequency stability of the Nigerian 330kV transmission network using fuzzy controller. It was achieved by first characterizing the 330kv transmission network by running load flow on the network, designing conventional SIMULINK model for improving frequency stability of the Nigerian 330kv transmission network, designing a rule base that makes these faulty buses to attain stability, integrating the designed rule to the conventional SIMULINK model for improving frequency stability of the Nigerian 330kv transmission network. The results obtained are conventional bus 1 per unit volts at 4s through 10s is 0.94. On the other hand, when fuzzy controller is incorporated in the system it is 1.043P.U volts. This shows that there is frequency stability when fuzzy controller is incorporated in the system since the per unit volts fall within the range of 0.95 through 1.05 P.U. volt and conventional per unit volts is 0.944 which makes the frequency unstable since the volts does not attain stability. Meanwhile, when fuzzy controller is incorporated in the system the per unit volts is 1.047. With these results, it shows that there is frequency stability when fuzzy controller is imbibed in the system. Since the per unit volt fall within the stability range of 0.95 through 1.05P.U. Volts.


Introduction
Nigerian national grid had experienced epileptic power supply for over a decade. The federal Government decided to privatize the generating and distribution sectors to improve performance and satisfy the consumers of electricity. This measure has not yielded considerable improvement due to technical reasons. The frequency instability observed in the power transmission network was mainly as a result of the per unit volts not falling within 0.95 through 1.05 P.U, volts. The research will seek to address the cause of instability and try to proffer solutions to the endemic complexity that has made industrialists to provide their individual generating plants. We have recorded incessant power failures for the last five years without any technical solution. The instability of system frequency and poor voltage profile had become an endemic complexity in our national grid. Power system stability is an important part of carrying out an assessment in transmission system security with a view to ensuring systems ability to withstand sudden disturbances under load application, switching operations, three phase short-circuit (symmetrical) faults, rotor angle swing/power frequency oscillations and loss of system elements when relay switch off affects some part of the network. In the electrical grid of today, there are many challenges ranging from changing generation landscape to increasing renewable energy inputs as well as remote power generations and aging AC transmission infrastructure with respect to ever increasing need for global demand for electricity. It is in the light of the foregoing that the need to enhance frequency stability of the Nigeria 330kv transmission network using ultra-capacitor has become expedient in this research.

Extent of Past Work
For over a decade, transmission networks had been overloaded and are subjected closer to their stability limits. This is not unconnected with the increasing demand for electricity as a result of the growing population accompanied by industrialization. This could harm the power system security. Power system security in the real sense is the ability of the network to withstand disturbances without breaking down [1]. The key performance indices needed to assess the state of security of a power system is the transient stability [2] and it requires the ability of the power system to remain unaltered or in equilibrium and should return to an acceptable stability margin when there is a system surge or disturbance [3]. There are many methods of determining the transient instability in the power system which are numerical integration, direct method, a probabilistic method [4], and artificial intelligence methods such as artificial neural networks [5]. Recall that, transient stability is assessed by the system Critical Clearing Time (CCT) in response to system surge due to large disturbance such as faults, loss of large load, loss of generation, and major lines loss [6]. CCT gives the maximum duration of time a power system can remain stable under a given large disturbance condition [7]. The robustness of a power system is generally dependent on its response to disturbances. A higher value of CCT denotes a robust and better-secured system [8]. The level of network security is a factor that determines the level of integrity of a power system (i.e. transmission capability limit and flexibility of power system) [9]. Therefore, power system grid integrity can be enhanced by devising a means of improving Frequency stability [10]. Transmission Systems (FACTS) devices have been identified as cost-effective means of improving transient stability without the need for constructing new transmission lines [11]. Several devices have been proposed for improving the power system operation and they are [12]: the Static Var Compensator (SVC), Controllable Series Compensator (CSC), Phase Shifter (PS), Series Capacitors (SC), Thyristor Controlled Series Capacitors (TCSC), Unified Power Flow Controller (UPFC), Convertible Series Compensator (CSC), Inter-phase Power Flow Controller (IPFC), Static Synchronous Series Controller (SSSC), STATCOM, etc. Of these various FACTS devices, a suitable controller is desired when appropriately sized [13]. A fuzzy controller is an effective means of regulating system frequency [14]. SVC serving alongside the Fuzzy controller would yield good results since they are shunt-connected and are usually installed at the midpoint of the transmission line or the line ends through a coupling transformer. It can improve transient stability by effectively controlling its reactive power output [15]. Nigeria power system is faced with series of technical challenges due to long, radial, weak, and aging transmission network This present paper aims at investigating the improvement of the transient stability of the Nigerian 330kV transmission network by improving the frequency stability of the Nigerian 330kV Transmission Network using a Fuzzy controller. Appropriately sizing and locating SVC within the network can assist to get the expected improvement in the network. In this way, the security of the system is improved thereby challenging the need for immediate construction of new transmission lines. This would allow time for proper planning for a later upgrade

Characterization of 330kv Transmission Network by Running Load Flow on the Network.
Methodology used to improve frequency stability of Nigeria 330Kk Transmission network using Fuzzy Controller followed the sequence of stated objectives from step 1 to step 5; the collection and tabulation of data as shown in Table 1 is the important step used to initiate the concept. The collection of data from the substation controlling the 330kV transmission line was by personal interview. The control room Operation engineers were interviewed and the reason for the work was explained in order to get access to classified data. The second step was the characterization of the network and performing load flow analysis on the network find the faulty buses whose per unit Volts did not fall within the range of 0.95 through 1.05. The third step was the designing of a conventional SIMULINK model for improving frequency stability of the system or network. The fourth Step is the designing of a 'Rule base that makes these faulty buses to attain stability. The fifth and last stage is to integrate the designed rule to the conventional Simulink model for improving frequency stability of the national grid.          Figure 4. Designed rule base that makes these faulty buses to attain stability.

Results and Discussion
In Figure 1, the load flow program that detects the fault buses did not fall within the stability range of 0.95 through 1.05P.U. Volts. Figure 2 shows the load flow program results that detects the faulty buses that cause frequency instability. These faulty buses are 1, 2, 3, 6 and 9 that the per unit volt does not fall within 0.95 through 1.05 P.U volts. Their per unit volts are 0.940, 0.9441, 0.933, 0.934 and 0.944 P.U volts. Figure 3 shows designed conventional SIMULINK model for improving frequency stability of the Nigerian 330kv transmission network. The result obtained are as shown in figures 6 and 7. Figure 4 shows designed rule base that makes these faulty buses to attain stability. Figure 5 shows integrated designed rule to the conventional SIMULINK model for improving frequency stability of the Nigerian 330kv transmission network. The result obtained are shown in figures 6 and 7. Figure 6 shows Comparison between conventional and fuzzy controller volts in improving frequency stability of the Nigerian 330kv transmission network in bus 1. The conventional bus 1 per unit volts at 4s through 10s is 0.94. On the other hand, when fuzzy controller is incorporated in the system it is 1.043P.U volts. This shows that there is frequency stability when fuzzy controller is incorporated in the system since the per unit volts fall within the range of 0.95 through 1.05 P.U. volt. Figure 7 shows the Comparison between the conventional and fuzzy controller volts in improving frequency stability of the Nigerian 330kv transmission network in bus 9. In figure 7 the conventional per unit volts is 0.944 which makes the frequency unstable since the volts does not attain stability. Meanwhile, when fuzzy controller is incorporated in the system the per unit volts is 1.047. With these results, it shows that there is frequency stability when fuzzy controller is imbibed in the system. Since the per unit volt fall within the stability range of 0.95 through 1.05P.U. Volts.

Conclusion
The frequency in stability in the transmission network has arisen as a result of per unit volts not falling within the range of 0.95 through 1.05P.U. volts. This frequency instability cause, intermittent power supply. This is overcome by improving frequency stability of the Nigerian 330kv transmission network using fuzzy controller, It is done in this manner, characterizing 330kv transmission network by running load flow on the network, designing conventional SIMULINK model for improving frequency stability of the Nigerian 330kv transmission network, designing a rule base that makes these faulty buses to attain stability, integrating the designed rule to the conventional SIMULINK model for improving frequency stability of the Nigerian 330kv transmission network. The results obtained are conventional bus 1 per unit volts at 4s through 10s is 0.94. On the other hand, when fuzzy controller is incorporated in the system it is 1.043P.U volts. This shows that there is frequency stability when fuzzy controller is incorporated in the system since the per unit volts fall within the range of 0.95 through 1.05 P.U. volt and conventional per unit volts is 0.944 which makes the frequency unstable since the volts does not attain stability. Meanwhile, when fuzzy controller is incorporated in the system the per unit volts is 1.047. With these results, it shows that there is frequency stability when fuzzy controller is imbibed in the system. Since the per unit volt fall within the stability range of 0.95 through 1.05P.U. Volts. resource materials necessary for the completion of this