Applied Mechanics and Materials Vol. 785

Abstract: Directional Overcurrent relays (DOCR) applications in meshed distribution networks (MDN), eliminate short circuit fault current due to the topographical nature of the system. Effective and reliable coordination’s between primary and secondary relay pairs ensures effective coordination achievement. Otherwise, the risk of safety of lives and installations may be compromised alongside with system instability. This paper proposes an Artificial Neural Network (ANN) approach of optimizing the system operation response time of all DOCR within the network to address miscoordination problem due to wrong response time among adjacent DOCRs to the same fault. A modelled series of DOCRs in a simulated IEEE 8-bus test system in DigSilent Power Factory with extracted data from three phase short circuit fault analysis adapted in training a custom ANN. Hence, an improved optimized time is produced from the network output to eliminate miscoordination among the DOCRs.

Abstract: This paper presents the improvement on accuracy and reliability of the load forecast model. It is well-known that characteristics of a load series is a non-stationary data, which is a constraint for the load forecast methods to achieve accurate and robustness responses. To overcome this limitation, a synergized method between wavelet transform and artificial neural network is proposed for short-term load forecasting. The modeling processes such as minimizing distorted data due to convolution operator of the wavelet transforms, model inputs and neural network design are presented. The proposed method is tested using historical load data of independent system operation New England. The results of the proposed model significantly outperform either accuracy or robustness results over neural network model.

Abstract: Installing capacitors in a large unbalanced electrical distribution system will indeed improves the performance of the system in terms of its voltage profile and real power loss stability. However, determining the suitable locations for capacitors installation with an appropriate sizing in an unbalanced electrical distribution system involves an intricate process. This impediment can be resolved by implementing an optimal capacitors placement and sizing. The proposed technique is a highly nonlinear optimization problem which requires discrete and multi-dimensional control variables of capacitor locations and sizes. This paper proposed a new artificial intelligence approach used to reduce the total line real power loss and total real power consumption while maintaining the voltage profile along the feeders. It was done by integrating the circuitry schematic diagram of an unbalanced electrical distribution system modeled in SIMULINK^® software with the computational programming based differential evolution particle swarm optimization (DEPSO) for optimal capacitors placement and sizing developed under the MATLAB^® software. In this study, pre-selection of the capacitor locations can be considered as the first stage of the proposed concept and it is commenced prior to the optimization process performed by the DEPSO algorithm considered as the second stage of the proposed concept. A modified IEEE 13-bus unbalanced radial distribution system is used verify effectiveness of the proposed technique in solving the problem. The results will be discussed notably through comparative studies on the objective function of total cost and performance of the DEPSO technique.

Abstract: This study proposed a way to solve problem efficiently which is through structural learning of Boltzmann machine. This method used mixed integer quadratic programming to solve the problem. An analysis is conducted by using the ideas of the reliability and risks of units assessed using a variance-covariance matrix and the effect and expanses of replacement are determined. In this study, the mean-variance analysis is formulated as a mathematical program with two objectives: (1) minimization of risk and (2) maximization of expected return. Lastly, the effectiveness of proposed method is illustrated by way of a life cycle management example. The result of this suggested method was demonstrated at the end. By using this method, more effective selection of results is gathered. Thus, this prove that the effectiveness of the decision making process can be reinforced.

Abstract: Today, load characteristic analysis plays a vital role in network planning, operation and control. In particular, with massive demand side participation activities on the network, the characteristics of individual load determines the way of the active load management as well as the network pricing strategies. In this paper, the load characteristics are analyzed utilizing clustering techniques for a tropical isle with massive temperature sensitive loads. Through deeply mining of real data, the features of individual loads were observed to define the way of load participation.

Abstract: The load flow or power flow computer program is the basic tool for investigating the steady-state conditions of power system. This paper introduces improved algorithms based on the basic Second-order Load Flow method for a wide range of electrical bus system sizes. It is attractive for accurate or approximate off- and on-line calculations for routine and contingency purposes. Tests of 4 different variations based on the basic Second-order Load Flow method are run on 6 different standard bus systems and the results are discussed in this paper.

Abstract: The optimal capacitor placement problem involves determination on the type, number, location and size of capacitors to be placed in a distribution system for the attainment of energy efficiency. The main objectives of the capacitors placement and sizing are to reduce total line loss and energy consumption while satisfying the operational constraints. This paper presents the optimal capacitor placement and sizing problems solved by using the Ant Colony Optimization (ACO) technique with the integrated of circuitry unbalanced electrical distribution modeled in SIMULINK^® MATLAB^® software. The proposed technique was tested on a modified IEEE 13-bus unbalanced radial distribution system and the results revealed that the proposed technique has the merit in achieving optimal solution for addressing the problems.

Abstract: This paper introduced a new heuristic method the Improved to Bacterial Foraging Optimization Algorithm or IBFO to provide minimize objective functions in Secured Environmental Economic Dispatch (SEED) problems. An optimization problem may involve the highly non linear, non convex and non differentiable tends the solutions observed from a multiple local minima. The limitation faced by conventional methods are being trapped at any this local minima and prevent to reach the global minima. For that reason, this approach IBFO is tested under IEEE 118 bus system to obtain the minimum total cost function with less emission involved. Additionally, the proposed optimization approach is compared to original Bacterial Foraging Optimization Algorithm (BFO). As a result, all findings supported the novel IBFO as the competent and reliable technique.

Abstract: In this paper, a design circuit of neutral point type buck boost has been utilized for wireless transfer energy application. Resonance magnetic field was used as the preferred wireless energy transfer approach due to its ability to generate high efficiency and an increased in distance between the transmitting and receiving coil. The constructed circuit has been found to be able to transmit a DC voltage output to the receiver coil with relatively small ripple voltage output at a limited range of around 15 centimetres.

Abstract: Cascaded H-Bridge (CHB) multilevel inverter (MLI) is among the most preferred topology in solar PV systems. While traditional asymmetric CHB MLI is easy to achieve higher number of output voltage levels compared to traditional symmetric CHB MLI, charge balancing between the voltage sources remains a challenge for asymmetric CHB MLI. This drawback results in unsteady DC voltage levels due to unbalanced power drawn from each voltage sources. Besides that, in battery powered applications, unbalanced power drawn results in unequal discharged in the batteries. In this paper, an asymmetric CHB MLI topology is proposed which is easier to modularize as for symmetric CHB MLI while maintaining the ease in charge balancing control. The performance of this proposed asymmetric CHB MLI with charge balance control has been evaluated using PSIM software.