<span>Distributed generation (DG) plays an important role in improving power quality as well as system realibility. As the incorporation of DG in the power distribution network creates several problems to the network operators, locating a suitable capacity and placement for DG will essentially help to improve the quality of power delivery to the end users. This paper presents the simulation of an application of firefly algorithm (FA) for optimally locating the most suitable placement and capacity of distributed generation (DG) in IEEE 33-bus radial distribution network. This strategy aims at minimizing losses together with improving the voltage profile in distribution network. The losses in real power and voltages at each bus are obtained using load flow analysis which was performed on an IEEE 33-bus radial distribution network using forward sweep method.  The proposed method comprises of simulation of the test system with DG as well as in the absence of DG in the system. </span><span>A comparison between the Firefly Algorithm (FA) with Genetic Algorithm (GA) is also demonstrated in this paper. The results obtained have proven that the Firefly Algorithm has a better capability at improving both the voltage profile and the power losses in the system.</span>

This paper presents a Genetic Algorithm (GA) for optimal location and sizing of multiple distributed generation (DG) for loss minimization. The study is implemented on a 33-bus radial distribution system to optimally allocate different numbers of DGs through the minimization of total active power losses and voltage deviation at power constraints of 0 – 2 MW and 0 – 3 MW respectively. The study proposed a PQ model of DG and Direct Load Flow (DLF) technique that uses Bus Incidence to Branch current (BIBC) and Branch Current to Bus Voltage (BCBV) matrices. The result obtained a minimum base case voltage level of 0.9898 p.u at bus 18 with variations of voltage improvements at other buses after single and multiple DG allocations in the system. Besides, the total power loss before DG allocation is observed as 0.2243 MW, and total power loss after DG allocation was determined based on the power constraints. Various optimal locations were seen depending on the power limits of different DG sizes. The results have shown that the impact of optimal allocation and sizing of three DG is more advantageous concerning voltage improvement, reduction of the voltage deviation and also total power loss in the distribution system. The results obtained in the 0 – 2 MW power limit is consistent to the 0 – 3 MW power limits regarding the influence of allocating DG to the network and minimization of total power losses.

This study is about implementing a power line vandalism monitoring system over the Internet of Things. The device is a tamper-resistant electronic security device for high-voltage transmission lines, specifically designed for remote monitoring and protection of the lines against vandals. This system detects when the transmission line is vandalized and when the vandals invade the environment where the transmission line tower, transformer, or any infrastructure is installed. The development involves different sections ranging from the power supply to the alarm unit. The power supply was designed by selecting the components based on the required specification for the transformer, diodes, capacitor, and voltage regulator. Based on its unique characteristics, the microcontroller unit was developed using the ATMEGA 328P IC. The communication and the sensor unit were designed considering their different specifications. An ultrasonic sensor and SIM900 for the Global System For Mobile Communications module were chosen. The study was implemented so that the motion sensor detects when vandals litter the restricted area of the power line or substation and communicates with the microcontroller, which triggers the alarm and the Global System for Mobile Communications module to send Short Message/Messaging Service.