No abstract

As the world is progressing forward, the load demand in the power system has been continuously increasing day by day. This situation has forced the power system to operate under stress condition due to its limitation. Therefore, due to the stressed condition, the transmission losses faced higher increment with a lower minimum voltage. Theoretically, the installation of the Flexible AC Transmission System (FACTS) device can solve the problem experienced by the power system. This paper presents the Whale Optimization Algorithm for loss minimization using FACTS devices in the transmission system. Thyristor controlled series compensator (TCSC) is chosen for this study. In this study, WOA is developed to identify the optimal sizing of FACTS device for loss minimization in the power system. IEEE 30-bus RTS was used as the test system to validate the effectiveness of the proposed algorithm.

<p>Nowadays, the location and sizing of distributed generation (DG) units in power system network are crucial to be at optimal as it will affect the power system operation in terms of stability and security. In this paper, a new technique termed as Immune Log-Normal Evolutionary Programming (ILNEP) is applied to find the optimal location and size of distributed generation units in power system network. Voltage stability is considered in solving this problem. The proposed technique has been tested on the IEEE 26 bus Reliability Test System to find the optimal location and size of distributed generation in transmission network. In order to study the performance of ILNEP technique in solving DG Installation problem, the results produced by ILNEP were compared with other meta-heuristic techniques like evolutionary programming (EP) and artificial immune system (AIS). It is found that the proposed technique gives better solution in term of lower total system loss compared to the other two techniques.<em></em></p>

In the era of millennium, the electric vehicle (EV) has a high demand from many sector which is to replace the existing internal combustion vehicle since it has given a negative side impacts towards the environment and also due to the increasing of the price of the fossil fuels that decreasing day by day. The electric vehicle is one of the alternative way to reduce pollution by moving the electric vehicle by using the energy that stored in the battery's car and after the battery has reach its limit, only then the petroleum will continue the role of the energy to move the electric vehicle. The energy that required by the battery's car are generated from the charging station which it connected to the distribution network. The charging or discharging of the electric vehicle could cause some power quality issues in a few terms such as voltage profile, power losses etc. This paper presents the Evolutionary Programming Based Technique for Plug-In-Hybrid Electric Vehicle Charging System. The proposal technique has been tested on the IEEE 33-bus distribution system. The results shown that the proposed technique managed to maximize the voltage level in the system in the plug-in-hybrid electric vehicle charging system environment.

The advancement of Distributed Generation (DG) technologies have caused great impact to power system operation. Inappropriate installation of DGs may lead to over-compensation or under-compensation situation. Thus, a reliable optimization is urgent to avoid any unwanted effect. This paper analyses the installation impact of different types-multi-DGs determined using a pre-developed hybrid optimization technique termed as Immunized-Brainstorm-Evolutionary Programming (IBSEP). It is imperative to study the effect of multi-DGs installation such that a relevant utility can make a correct decision, whether its installation is worth or vice versa. Rigorous study has been conducted in terms of identifying the optimal location and sizing, installed on transmission system for voltage control involving different DG types. Comprehensive results are embedded in this paper to demonstrate the effect of multi-DGs installation in transmission system which in turns beneficial to the utility.  Effect of optimal multi-DG siting and sizing in transmission system… (Sharifah A. Shaaya) 647 ability to deliver or absorb reactive power [13,14]. These studies found that different type of DG will affect power network performance differently.Inventing robust and reliable optimization technique to determine optimal DG location and size is currently trending in the researchers community, aiming at alleviating setbacks in the existing optimization techniques [15][16][17][18][19][20]. Apart from finding higher probability of optimum solution towards meeting the objective functions, new optimization algorithms are developed to reduce computational burden in the classical optimization techniques [21,22] Brainstorm Optimization (BSO) is a newly developed algorithm that made its appearance in 2011. An algorithm that mimics the collective behavior of human has caught attention of many researcherst. Though it is proven reliable in solving science and engineering problems, it does has high computational burden due to its K-means clustering technique as well as easily trapped in the local maxima [23][24][25][26]. In this paper, an optimization technique that embed Artificial Immune System (AIS) optimization technique and BSO into the frame of Evolutionary Programming (EP) algorithm is used to determine optimal locations and sizes of multiple DGs, of different power delivering capabilities, in power transmission system for voltage control. The hybrid technique is termed as Immunized-Brainstorm-Evolutionary Programming (IBSEP).