Isaiah G. Adebayo

Optimal location identification of FACTS devices through genetic algorithm and the network structural characteristics techniques

In this paper, the use of techniques based on the Artificial Intelligent (AI) and the network topological structure of the power system network, for optimal location of the reactive power compensator is investigated. To determine the suitable location for the power electronics based UPFC and TCSC FACTS devices, with the proposed Network Structural Characteristics Participation factor (NSCPF), the critical mode and the associated eigenvectors of the system are found. Comparative analysis with an optimization technique of genetic algorithm (GA) to determine the optimal location, size and rating of each UPFC and TCSC FACTS devices is also carried out. All the techniques presented are tested on the IEEE 14 bus power system. The results of simulation obtained show that, the proposed NSCPF is more superior in the identification of suitable nodes for the placement of FACTS devices compared to the traditional approach of GA, as it saves time and require no iteration processes before the best location is identified.

Identification of suitable nodes for the placement of reactive power compensators

The occurrence of Voltage collapse has been considered a frequent phenomenon in the recent time and has been a growing concern to the power system utility. Thus, the importance of identifying nodes where reactive power compensator can be placed for voltage stability enhancement. This paper proposed a technique based on the network topological structure of the power system. The suggested technique is found by computing the critical mode and the associated eigenvectors of the system. The node, which has the highest contributions to the critical mode identified is computed and considered as the weakest node. Comparative analysis of the suggested approach with the power flow based technique of modal analysis is also done. The results obtained show that suitable node for the placement of reactive power compensators is better identified using the suggested approach as it saves time and does not depend on performing a time consuming power flow solution before the weakest node is identified.

Static voltage stability enhancement using FACTS controller

The modern day power system is faced with challenges of voltage instability and has become a great concern to the power system industries. In this work, we proposed a technique of the Network structural Characteristics Participation Factor (NSCPF) to identify the most critical node where reactive power compensator can be placed for voltage stability enhancement. The approach is based on the use of eigenvalue decomposition technique on the submatrix of the partitioned bus admittance matrix. Conventional power flow based approach of voltage stability index (L-Index) and the modal analysis methods are used as benchmarks to the proposed approach to determine its effectiveness. The STATCOM FACTS controller is in turn installed at the critical bus as identified by both techniques. Simulation results obtained show that, the suggested approach saves time and is more advantageous in identifying the suitable bus for the placement of STATCOM.

Detection of weak bus through Fast Voltage Stability index and inherent structural characteristics of power system

Modern power system is large, complex and characterized by continuous increase in electrical load demand. As a result, the system is stressed to operate closer to stability limit and this may result in voltage collapse. Therefore, it becomes imperative to implement techniques for detecting collapse in bus bar or lines before its occurrence in the power system. This paper presents the concept of inherent structural characteristics of power networks and the power flow based technique of the Fast Voltage Stability index (FVSI). To detect the weakest line with respect to a bus using the conventional based approach of the Fast Voltage Stability Index (FVSI), a repetitive power flow solution is performed while varying the reactive power load at a particular load bus. The line or bus that has its FVSI closest or equal to 1 is identified as the weakest line or bus. The concept of inherent structural characteristics of the power network is formulated based on the fundamental circuit theory laws which employs the use of eigenvalue decomposition method in predicting the bus liable to instability. The two approaches are then compared. The result obtained shows that, weak bus is better detected through the concept of inherent structural characteristics of power network as it saves time and does not involve performing the time consuming traditional load flow before the weak bus is known.

Prediction of voltage collapse through voltage collapse proximity index and inherent structural characteristics of power system

The frequent incident of voltage collapse in the modern power system due to incessant increase in load demand has posed a great challenge to power system utilities. This paper demonstrates the concept of inherent structural characteristics and the traditional approach of voltage collapse proximity index (VCPI) in predicting the collapse point in the power system network. The conventional technique for collapse point detection through the use of the voltage collapse proximity index is achieved by running a repetitive load flow solution while increasing the reactive power load of a particular load bus. On the other hand, the approach due to inherent structural characteristics of power system is formulated based on the fundamental circuit theory laws and it employs the use of eigenvalue decomposition method in predicting the bus liable to instability. The results of the simulations show that voltage collapse point is easier and quicker to predict with the technique based on the inherent structural characteristics without necessarily going through the rigor of a time consuming and repetitive load flow based voltage collapse point proximity index (VCPI).

Techniques for the Identification of Critical Nodes Leading to Voltage Collapse in a Power System

Abstract This paper proposes two techniques for the identification of critical buses in a power system. The technique of Network Structural Theory Participation Factor (NSTPF) depends on the network structural interconnection of buses as captured by the admittance matrix of the system and is formulated based on the fundamental circuit theory law using eigenvalue decomposition method. Another power flow based technique which depends on the system maximum loadability, the system step size among other factors is also proposed. Traditional power flow based techniques are used as benchmarks to determine the significance of the proposed methods. To ensure voltage stability enhancement, STATCOM FACTS device is installed at the selected weak load buses of the practical Nigerian 24 bus and IEEE 30 bus test systems. The results of the simulation obtained show that, the suggested approach of NSTPF is more suitable in the identification of weak buses that are liable to voltage instability in power systems as it requires less computational burden and also saves time compared to techniques based on power flow solutions.

An alternative method for voltage stability assessment in power system

Voltage stability assessment in power system has recently been a growing concern to power system utilities due to blackout experienced in a couple of years in some developed and underdeveloped nations. This paper presents an alternative method which is based on the topology of the power network to identify weak load buses that are susceptible to voltage instability. The method makes use of the critical mode and the eigenvectors to determine the weak bus of the system. To determine the critical mode of the system, eigenvalue decomposition technique is used. Comparison analysis with the power flow based voltage collapse proximity index (VCPI) is performed to show the significance of the suggested approach. Results obtained show that voltage stability assessment in power system could as well be done using the structurally based approach as it saves time and reduces the computational burden compared with the traditional power flow based approach of VCPI.

A comparison of voltage collapse point prediction capabilities of voltage stability index and inherent structural characteristics

Modern power systems are highly interconnected and heavily loaded. The continuous load increase may drag the whole systems to a condition of voltage instability and this may result in voltage collapse. Prediction of the proximity of the system to voltage collapse is therefore an important task in power system operation and planning. Presented in this paper is the application of two techniques that can be used to determine the voltage collapse point in a power system network. At first, the conventional approach of voltage stability index, which is solely based on running repetitive load flow solutions while finding the point susceptible to system voltage collapse, is considered. The inherent structural characteristic of the power system network, which is the structural interconnections between the nodes governed by the impedances or admittances between them, is also presented. The formulation of which is done based on the basic circuit theory laws. Simulations are done using MATLAB software package. Results obtained show that voltage collapse point is easily and quickly detected and predicted with the approach of inherent structural characteristic without necessarily going through the rigor of a time consuming and repetitive load flow based voltage stability index (L-index).