Hussain Shareef

A Comparison of Electric Power Tracing Methods Used in Deregulated Power Systems

Tracing the flow of electricity becomes an important issue under transmission open access. In practice, power flow follows the physical laws of electricity and therefore it is not straightforward to map out how the participants make use of the system. This paper focuses on presenting an analysis of the performance of major power tracing methods based on proportional sharing principle namely the graph, node and commons method. A number of simulations are performed based on their assumptions to critically compare their performance and validate the exactness of each method. Finally, conclusions and recommendations are stated.

Real and reactive power transfer allocation utilizing modified Nodal equations

This paper proposes a new method to identify the real and reactive power transfer between generators and load using modified nodal equations. Based on available load flow results, the method partitions the Y-bus matrix to decompose the current of the load buses as a function of the generators current and load voltages. Then, it uses the modified admittance matrix to decompose the load voltage-dependent term into components of generator dependent terms. By using these two decompositions of current and voltage terms, the real and reactive power transfer between loads and generators are obtained. The effectiveness of the proposed method is demonstrated by using a simple 5-bus system and the modified IEEE 30-bus system. The proposed methodology provides reasonable and acceptable results to real and reactive power transfer allocation.

Real power loss allocation using modified nodal equations

This paper introduces a new method to allocate real power loss caused by generators and loads using modified nodal equations. Based on solved load flow results, the method partitions the Y-bus matrix to decompose the current of the load buses as a function of the generators current and load voltages. Then it uses the modified admittance matrix to decompose the load voltage dependent term into components of generator dependent terms. By using these two decompositions of current and voltage terms, the real power loss allocations caused by the generators are obtained. Similarly, in case of real power loss allocations caused by the loads, the generator voltage dependent term can be decomposed into components of load dependent terms. Likewise, by using these two decompositions, the real power loss allocations caused by the loads are determined. The proposed method is illustrated on a simple 5-bus system and tested on the modified IEEE 30-bus system. The proposed methodology provides reasonable and accurate results to real power loss allocation.

A new method for real power transfer allocation using modified nodal equations

This paper proposes a new method to identify the real power transfer between generators and load using modified nodal equations. Based on solved load flow results, the method partitions the Y-bus matrix to decompose the current of the load buses as a function of the generatorspsila current and load voltages. Then it uses the modified admittance matrix to decompose the load voltage dependent term into components of generator dependent terms. Finally using these two decompositions of current and voltage terms, the real power transfer between loads and generators are obtained. The effectiveness of the proposed method is demonstrated by using a simple 5-bus system and the practical 25-bus equivalent power system of south Malaysia. The proposed methodology provides reasonable and acceptable results to real power transfer allocation.

A Hybrid Power Transfer Allocation Approach for Deregulated Power Systems

Power transfer allocation is one of the major issues in deregulated power industry. This paper presents a hybrid technique for power transfer allocation. It is based on combining the existing power flow tracing methods that determines the power share from generators to line flows and loads. The advantages of the proposed method are demonstrated by the tests conducted on the IEEE 30-bus system and also on a practical bus equivalent power system of south Malaysia. The proposed method provides better reliability and minimizes the limitations of conventional power flow tracing methods.

SVC damping controller design based on firefly optimization algorithm in multi machine power system

Power system stability is a great concern in todays interconnected power system especially when the system is subjected to a fault. These faults occasionally lead to Low Frequency Oscillation (LFO). Therefore, Shunt Flexible AC Transmission System (FACTS) devices for example, SVC are employed to provide damping to attain system stability. The performance of SVC is totally dependent on proper tuning of its controller and usually heuristic optimization techniques are used to search the best controller parameters. In this paper, a popular metaheuristic optimization technique known as Firefly Algorithm (FA) is presented for optimal design of SVC controller in multi machine power system. In the simulation, the linearized model of power system and conventional lead-lag controller as SVC damping controller are used. The performance of obtained results using Firefly Algorithm (FA) is compared with the results obtained from Particle Swarm Optimization (PSO) Algorithm. The comparison of attained results show that FA can find more optimal parameter values of SVC damping controller and subsequently enhance power system stability.

An ANFIS Approach for Real Power Transfer Allocation

This paper proposes an adaptive neurofuzzy interface system (ANFIS) approach to identify the real power transfer between generators. Based on solved load flow results, it first uses modified nodal equation method (MNE) to determine real power contribution from each generator to loads. Then the results of MNE method and load flow information are utilized to train the designed ANFIS. It also incorporated an enhanced feature extraction method called principle component analysis (PCA) to reduce the input features to the ANFIS. The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of the ANFIS output compared to that of the MNE method. The ANFIS output provides promising results in terms of accuracy and computation time. Furthermore, it can be concluded that the ANFIS with enhanced feature extraction method reduces the time taken to train the ANFIS without affecting the accuracy of the results.

Modeling and simulation of overvoltage surges in low voltage systems

Power system disturbances have been present since the inception of the electric utility industry. However, yesterdaypsilas loads are more forgiving of disturbances than todaypsilas modern equipment. The proliferation of sensitive electronic equipments such as PCs, variable speed drives and industrial programmable controllers has made us more aware of power system disturbances, which went unnoticed in the past. In the normal operation of power systems, unavoidable disturbances may happen due to sag, swell, noise, and overvoltage surges. Overvoltage surges, however, are damaging in nature and result in more frustrations and even fire in rare cases. This research aims to investigate overvoltage surges due to possible causes such as lightning and switching operations in a low voltage system. Then it compares simulated overvoltage surges with the design goals of the Information Technology Industry Council (ITI) power acceptability curve. Finally a study was undertaken to see how surge arresters could be used to protect a given system against unacceptable overvoltage levels.

Optimum APC Placement and Sizing in Radial Distribution Systems Using Discrete Firefly Algorithm for Power Quality Improvement

This paper presents an improved solution to determine simultaneously the optimal location and size of active power conditioners (APCs) in distribution systems using the discrete firefly algorithm (DFA) for power quality enhancement. A multi-criterion objective function is defined to enhance voltage profile of the system, to minimize voltage total harmonic distortion and total investment cost. The performance analysis of the proposed DFA is performed in the Matlab software on the radial IEEE 34-bus test system to demonstrate its effectiveness. The DFA results are then compared with the standard firefly algorithm, standard particle swarm optimization (PSO), genetic algorithm, and discrete PSO. The simulation and comparison of results prove that the DFA can accurately determine the optimal location and size of the APCs in radial distribution systems.

Application of ANN to Real and Reactive Power Allocation Scheme

This chapter describes the implementation of ANN for real and reactive power transfer allocation. The 25 bus equivalent power system of south Malaysia region and IEEE 118 bus system are used to demonstrate the applicability of the ANN output compared to that of the Modified Nodal Equations (MNE) which is used as trainers for real and reactive power allocation. The basic idea is to use supervised learning paradigm to train the ANN. Then the descriptions of inputs and outputs of the training data for the ANN are easily obtained from the load flow results and each method used as teachers respectively. The proposed ANN based method provides promising results in terms of accuracy and computation time. Artificial intelligence has been proven to be able to solve complex processes in deregulated power system such as loss allocation. So, it can be expected that the developed methodology will further contribute in improving the computation time of transmission usage allocation for deregulated system.