Faktor- Faktor yang Mempengaruhi Dividend Payout Ratio pada Sektor Perbankan yang Terdaftar di Bursa Efek Indonesia Periode 2012-2016

Dividend Payout Ratio (DPR) adalah rasio yang menunjukan persentase dividen yang dibagikan kepadapemegang saham dari laba yang diperoleh. Penelitian ini bertujuan untuk menguji dan menganalisispengaruh dari Debt to Equity Ratio (DER), Biaya Operasional terhadap Pendapatan Operasional (BOPO),Capital Adequacy Ratio (CAR), Investment Opportunity Set (IOS) dan Firm Size (KBUKU) terhadapDividend Payout Ratio pada Perusahaan sektor perbankan di Bursa Efek Indonesia periode tahun 2012-2016. Teknik sampel yang digunakan dalam penelitian ini adalah purposive sampling. Ada 14perusahaan sampel yang digunakan dan analisis yang digunakan dalam penelitian ini adalah analisisregresi data panel dengan EViews 9. Sampel data diuji dengan uji hipotesis yang dilakukan denganmenggunakan R-square dan uji T. Hasil penelitian menunjukan bahwa secara parsial BOPO, CAR dan FSberpengaruh signifikan dan positif terhadap DPR. DER dan IOS tidak berpengaruh signifikan terhadapDPR

Investigating the impact of distributed generators power factor to simultaneous optimization analysis

In this paper, the Particle Swarm Optimization (PSO) technique is used to determine the optimal coordination for Distributed Generator (DG). The DG output and location is determined simultaneously. Furthermore, this study covers both single and multiple DGs analyses. Five different Power Factor (PF) values are also assigned to the DG units, which are 0.8, 0.85, 0.9, 0.95 and 1.0. Thus, the impacts of DG power factor to the optimal placement and output are investigated. From the result, the optimal DG placement is similar, regardless of the PF condition. For the single DG unit, the optimal location is bus 6 and for three DGs analysis, the optimal locations are at buses 14, 24, 30. However, the PF significantly influences the optimal DG output, power loss reduction and voltage profile improvement. Three DGs with PF 0.8 is the best option to reduce the power loss in the distribution network to the lowest valu

Minimizing harmonic distortion impact cause by CS using meta heuristic technique

Non-linear load in the distribution system has caused negative impact to its power quality especially on harmonic distortion. Charging Station (CS) is a non-linear load that widely promoted with the aim to support the continuous usage of Electric Vehicle (EV). This research is focusing on optimal placement and sizing of multiple passive filter to mitigate harmonic distortion due to CS usage at distribution system. There are 6 units of CS which being placed in low voltage buses which indirectly will inject harmonic to the system during charging. Power system harmonic flow, passive filter, CS, battery and the analysis will be model in MATLAB. Multi-objective function which are weight summation approach (WSA) and Pareto Front are used to assist meta heuristic technique which is Modified Lightning Search Algorithm (MLSA) to identify optimum location and sizing of passive filter based on improvement on propose five parameters. From the result, the optimal placements and sizing of passive filter able to reduce the maximum Total Harmonic Distortion (THD) for voltage, current and apparent losses respectively. Therefore, the propose method is suitable to reduce harmonic distortion as well as apparent losses at distribution system with present of CS

DAMPING LOW FREQUENCY OSCILLATIONS IN POWER SYSTEMS USING ITERATION PARTICLE SWARM OPTIMIZATIONS

ABSTRACT The major concern in power systems has been the problem of low frequency oscillations (LFO) that results in the reduction of the power transfer capabilities. The applications of power system stabilizers (PSS) are commonly employed to dampen these low frequency oscillations. The parameters of the PSS are tuned by considering the Heffron-Phillips model of a single machine infinite bus system (SMIB). Tuning of these parameters for the system considered can be done using iteration particle swarm optimization (IPSO) technique in this paper; mainly the lead lag type of PSS was used to damp these low frequency oscillations. The proposed technique (IPSO)'s capabilities are compared with the traditional PSO and genetic algorithm (GA) technique in terms of parameter accuracy and computational time. Also the results of nonlinear simulations and eigenvalue analysis reveals that, the IPSO is much better optimization technique as compared to traditional PSO and GA

Comparative study on distributed generator sizing using three types of particle swarm optimization

Total power losses in a distribution network can be minimized by installing Distributed Generator (DG) with correct size. In line with this objective, most of the researchers have used multiple types of optimization technique to regulate the DG’s output to compute its optimal size. In this paper, a comparative studies of a new proposed Rank Evolutionary Particle Swarm Optimization (REPSO) method with Evolutionary Particle Swarm Optimization (EPSO) and Traditional Particle Swarm Optimization (PSO) is conducted. Both REPSO and EPSO are using the concept of Evolutionary Programming (EP) in Particle Swarm Optimization (PSO) process. The implementation of EP in PSO allows the entire particles to move toward the optimal value faster. A test on determining optimum size of DGs in 69 bus radial distribution system reveals the superiority of REPSO over PSO and EPSO

Enhancing power loss by optimal coordinated extensive CS operation during off-peak load at the distribution system

Minimise dependency of energy from depleted non-renewable had pushed the usage of electric vehicle (EV). However, the presence of charging station (CS) may cause another impact such as higher power loss, especially involving uncoordinated CS. The impact becomes vital when the numbers of CS to charge the EV increased dramatically. From research, CS at residential usually operated during off-peak load. Furthermore, the variation of the charging pattern that difficult to perceive had added severe condition. Thus, the exploration of the mitigation method is necessary to avoid the stress at the existing distribution network. This paper suggests a coordinated method based on the power loss forecast throughout the charging time. The method will prioritise the buses based on power loss impact on the network, which later to determine the suitable numbers of CS operation. The approach considers customer satisfaction to charge the EV at a specific duration fully. Thus, to present the effectiveness of the approach, the analysis conducted using a suitable distribution system with residential block. The results show a positive outcome in enhancing distribution power loss without interrupt customer satisfaction. The method is suitable to deal with many CS that operates simultaneously during off-peak load

Power loss mitigation and voltage profile improvement by optimizing distributed generation

In a developing country, electricity has become the necessity of the growth industries; thus, the distribution system power quality and reliability are crucial. With low carbon initiatives, renewable energy or distributed generation (DG) is a promising source of electricity and leads the complex distribution system. Vital rises in DGs in power grids will significantly impact the system reliability and security, especially in power losses and voltage profiles parameters. This research focuses on an optimization placement and size of DGs in distribution systems to minimize power loss and improve voltage profile using the Modified Lightning Search Algorithm (MLSA). This research has modelled the practical 69-bus radial distribution system. Then MLSA with a weight summation approach is used to identify the suitable location and size for the DGs in the design proposal stage. The optimization objectives are to reduce power losses and improve the voltage profile, especially at the connection point of DGs. Besides that, load profile, DGs constant load and the solar load in distribution system modelled using MATLAB software. The results of the simulation using MLSA indicated that the optimization allocation and sizes of solar DGs applied with current load and load changes can minimize the power losses and improve voltage profile. These results verify the proposed approach's effectiveness and success in determining the optimal location and sizing of solar DGs to reduce power losses as well as improve voltage profiles

Progress on protection strategies to mitigate the impact of renewable distributed generation on distribution systems

The benefits of distributed generation (DG) based on renewable energy sources leads to its high integration in the distribution network (DN). Despite its well-known benefits, mainly in improving the distribution system reliability and security, there are challenges encountered from a protection system perspective. Traditionally, the design and operation of the protection system are based on a unidirectional power flow in the distribution network. However, the integration of distributed generation causes multidirectional power flows in the system. Therefore, the existing protection systems require some improvement or modification to address this new feature. Various protection strategies for distribution system have been proposed so that the benefits of distributed generation can be fully utilized. This paper reviews the current progress in protection strategies to mitigate the impact of distributed generation in the distribution network. In general, the reviewed strategies in this paper are divided into: (1) conventional protection systems and (2) modifications of the protection systems. A comparative study is presented in terms of the respective benefits, shortcomings and implementation cost. Future directions for research in this area are also presented

Distribution power loss minimization via distributed generation, capacitor and network reconfiguration

This paper presents a solution to solve the network reconfiguration, DG coordination (location and size) and capacitor coordination (location and size), simultaneously. The proposed solution will be determined by using Artificial Bee Colony (ABC). Various case studies are presented to see the impact on the test system, in term of power loss reduction and also voltage profiles. The proposed approach is applied to a 33-bus test system and simulate by using MATLAB programming. The simulation results show that combination of DG, capacitor and network reconfiguration gives a positive impact on total power losses minimization as well as voltage profile improvement compared to other case studies