BACKGROUND OF THE STUDY
Electricity is a component that cannot be overlooked in any contemporary economy. It is essential for the expansion of a nation's economy and its overall development that the nation have access to an affordable and dependable source of electricity (Chidanandappa et al., 2015). Therefore, electric power utilities all over the world work hard to satisfy consumer expectations in the most cost-effective manner while still providing a satisfactory level of service (Okorie et al., 2015). In order for the power utility to be able to fulfill the requirements of its customers, it is necessary for the system infrastructure to be upgraded and effectively maintained (Jokojeje et al., 2015). Analysis conducted around the globe reveals that about 90 percent of all issues pertaining to customer dependability are the result of issues in the distribution system; hence, increasing the reliability of the distribution system is essential to increasing consumer reliability (Brown, 1998). The purpose of the Power Holding Company of Nigeria (PHCN) is to transmit, distribute, and deliver appropriate energy in a way that is safe, dependable, and efficient, and this mission must be achieved (Okorie et al., 2015). On the other hand, the utility business is becoming increasingly concerned about the unreliable supply of electricity that is provided to clients via the power system network in Nigeria. The system network has been the focus of the efforts of a great number of power systems engineers, who have conducted a variety of optimization studies, including those based on heuristics, network layout, integration of renewable energy resources, and coordination of dispersed generation (Eseosa & Roland, 2014).
These studies (Eseosa & Roland, 2014) used genetic algorithm (GA) based optimization to optimally locate FACTS devices - Unified Power Flow Controllers (UPFC) and the Thyristor Controlled Series Controllers (TCSC) devices in the Nigeria 330kV integrated power network for power transfer increase and loss minimization at different active and reactive power loadings. This was done in order to maximize power transfer and minimize loss (Chidanandappa et al., 2015). After optimally incorporating TCSC and UPFC devices into the network, the results revealed that there was a reduction in transmission line losses of both active and reactive power. This reduction occurred after the network was optimized to incorporate TCSC and UPFC devices. When a high-quality solution is required, this optimization strategy approach, which begins with the random creation of the population, will always lack the precision necessary to meet the requirements. The authors (Satish et al., 2013) used a technique called particle swarm optimization (PSO) to find the best placement of DG in the distribution network of 33 and 69-bus systems. In the study, many kinds of DGs were presented, each of which utilized the PSO approach for active and reactive power compensation. The goal of the study was to reduce the amount of actual power that was lost in main distribution networks. It has been hypothesized that the ideal size and location of DG in the distribution network may be determined using a genetic algorithm (Deependra et al., 2007, Mithulananthan et al., 2004, Soma et al., 2011, Rashmi et al., 2014, Shukla et al., 2008, Zahra et al., 2013). The GA techniques are used to discover the ideal size and bus placement for installing DG in a network system based on bus admittance, generating information, and load distribution of the system. This helps to minimize power loss and energy loss in the network (Ayodele et al., 2016). The topic of network reconfiguration was solved by the authors (Rajaram et al., 2015, Chidanandappa et al., 2015) in order to limit the amount of actual power that was lost in the system. They were successful in accomplishing the goal by utilizing a meta-heuristic optimization strategy. The created method makes a prediction about the switching pattern for reconfiguration, and this pattern delivers the least amount of voltage variation and loss possible. Additionally, it cuts down on the total number of switching operations while also meeting the limitations (Ankur et al., 2015). For the purpose of radial distribution network reconfiguration, Rama Rao et al (2010) introduced a technique that makes use of a plant growth simulation algorithm (PGSA). On a radial distribution system with 69 nodes, this concept was evaluated to see how successful it is. The outcome, when compared with the optimization approach based on the genetic algorithm, demonstrated that PGSA was successful in locating a global solution with a high likelihood of approximating the answer (Jibril et al., 2013). Ankur et al. (2015) came up with the idea for a network reconfiguration that is based on a genetic algorithm and makes use of the graphical user interface (GUI) that is included with the MATLAB program. Although the study is based mainly on theoretical assumptions, the tests that were carried out on 6-bus, IEEE 14-bus, IEEE 30-bus, and IEEE 57-bus test systems were successful.
1.2 STATEMENT OF THE PROBLEM
The principal function that reliability indices are intended to fulfill is that of providing a foundation for power system planning (Jibril et al., 2013). It is reasonable to anticipate that system planners will make use of indices if it can be demonstrated that they would facilitate the planning of the decision-making process, and provided the computation of the index is economically feasible (Rajaram et al., 2015). During these unforeseen circumstances, a dependable power system can keep the lights on by utilizing power plants that have the ability to quickly adjust their output or by encouraging end users to minimize the amount of electricity they use (Jokojeje et al., 2015).
A static var compensation, or SVC, was carried out on the Nigerian 330kV transmission network in the research carried out by Ayodele et al., (2016). The purpose of this research was to develop indices for enhancing the transient stability of the network by making use of an appropriate size to locate SVC nodes within the network. The findings demonstrated an increased stability of the network as well as a better voltage profile; nevertheless, the authors only considered the ideal size of the DG. Kotamarty et al. (2008) made the suggestion that a contingency analysis should be done in the system because of the location and size of the DG. The approach did not fulfill the criteria of robustness, which was the objective function of the method. The objective function was to locate the ideal position and size of DG to minimize voltage departure from a specified profile. Jokojeje et al. (2015) conducted research with the goal of enhancing the 330kV Nigeria grid network with static synchronous compensator (STATCOM). In the research that they conducted, the authors investigated how applying a static synchronous compensator and a FACTS controller impacted the functionality of a power system in Nigeria that had 330kV and 28 buses. Conventional and modified Newton-Raphson based power flow equations were used to describe the steady-state condition through the system before and after compensation was applied. The findings of the study revealed that five out of the sample system's twenty-eight buses had voltage magnitudes that fell outside the regulatory limits of 0.95 vi 1.05, which were improved, and the overall system power losses were decreased by 5.88%.
The capability of providing uninterrupted service to customers is what's meant when we talk about the reliability of a power distribution system. The dependability of individual customers, feeders, and system-oriented indices connected to substations can be reflected through the presentation of distribution system reliability indices in any one of a number of different ways (Ankur et al., 2015). Hence, this study seeks to carry out an investigation on reliability and protection in distribution power system considering customer based indices.
1.3 OBJECTIVES OF THE STUDY
The primary objective of this study is to study reliability and protection in distribution power system considering customer based indices. This study proposes the use of mitigation strategies through the development of an algorithm for improving the reliability and protection of the system network. A 33kV feeder network supplying electricity from Gusua to Kaura-Namoda Zamfara state, Nigeria is used as a case study.
1.4 SCOPE OF THE STUDY
In order to achieve the focus of this study, this study will make use of a 33kV feeder network supplying electricity from Gusua to Kaura-Namoda Zamfara state, Nigeria as a case study. Hence, this study is delimited to Zamfara State.
1.5 SIGNIFICANCE OF THE STUDY
This will be of benefit to the Power Holding Company of Nigeria because it will expose them the various ways of maintaining reliable and protected distribution of power system in order to serve the customer based indices better. This study developed a system planning approach which will serve as part of the key mitigation strategies for improved reliability and protection of the distribution network. This study will also add to existing literature on this study area and shall serve as reference material to students, researchers and scholars who may wish to carry out further studies on this topic or related domain in the future.
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STATEMENT OF THE PROBLEM
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BACKGROUND OF STUDY
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