Adaptive Embedded Clonal Evolutionary Programming (AECEP) for optimal Distributed Generation (DG) location and sizing in a distribution system

Distributed Generation (DG) has gained increasing popularity as a viable element of electric power systems. DG as a small scale generation sources located at or near load center is usually deployed within the distribution system. Installation of DG has many positive impacts such as reducing transmission and distribution network congestion, differing costly for upgrading process, and improving the overall system performance by reducing power losses and enhancing voltage profiles. To achieve these positive impacts from DG installation, the DG has to be optimally placed and sized. Since last decade, Artificial Intelligence (AI) methods have been used to solve complex DG problems because in most cases they can provide global or near global solution. The major advantage of the AI methods is that they are relatively versatile for handling various qualitative constraints. AI methods mainly include Artificial Neural Network (ANN), Expert System (ES), Genetic Algorithm (GA), Evolutionary Programming (EP), Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). The purpose of this thesis is to presents a new technique namely Adaptive Embedded Clonal Evolutionary Programming (AECEP). The objective of the study is to employ AECEP optimization technique for loss minimization and voltage profile monitoring. First step study started by using a conventional technique as a pre-study of DG location and sizing. The Heuristic Search Technique (HST) was developed to empirically determine the location and sizing of DG for the same purpose. This technique was performed on the IEEE 41-Bus and 69-Bus RDS for several cases in terms of loading conditions. The proposed AECEP was implemented for single DG, two DGs and three DGs installation. The result of the proposed AECEP technique was found in a good agreement with those obtained from the EP and AIS in terms of loss minimization and voltage profile improvement

The Influence of Corporate Governance to the Firm Performance in Logistics Industry

The aim of this study is to break down the execution of logistics industries in United Kingdom (UK) throughout five years. The analysis is employ on the sample of six organization in UK over the period in the vicinity of 2013 and 2017. The information is derived from annual report of Kerry Logistic, Wincanton, DFDS Seaways, Easy Jet and Stobart Group. This study utilizing a clear descriptive analysis, for example profitability, liquidity risk, credit risk, operational risk and also economic environment as to look at the performance of the organization include in logistics industries. The information ascertained is on average. The result show that the company performance can be influenced by the risk and economic environment. The study found the profitability ratio in term of current, quick ratio and debt to income are significant to independent variable which are to the return on asset. While, return on asset are significant to average collection period, liquidity ratio, unemployment rate, interest rate and operational ratio

The Influence of Corporate Governance to the Firm Performance in Logistics Industry

The aim of this study is to break down the execution of logistics industries in United Kingdom (UK) throughout five years. The analysis is employ on the sample of six organization in UK over the period in the vicinity of 2013 and 2017. The information is derived from annual report of Kerry Logistic, Wincanton, DFDS Seaways, Easy Jet and Stobart Group. This study utilizing a clear descriptive analysis, for example profitability, liquidity risk, credit risk, operational risk and also economic environment as to look at the performance of the organization include in logistics industries. The information ascertained is on average. The result show that the company performance can be influenced by the risk and economic environment. The study found the profitability ratio in term of current, quick ratio and debt to income are significant to independent variable which are to the return on asset. While, return on asset are significant to average collection period, liquidity ratio, unemployment rate, interest rate and operational ratio

Sintesis, aktiviti antiplasmodium dan kesitotoksikan secara in vitro sebatian porfirin logam ke atas strain Plasmodium falciparum K1

Jangkitan malaria adalah penyakit berjangkit serius yang disebabkan oleh parasit plasmodium dan harus dirawat sebagai perubatan kecemasan. Sehingga kini, tiada vaksin yang sudah dikomersialkan untuk mencegah malaria. Enam sebatian porfirin logam nikel(II) dan zink(II) berasaskan porfirinmeso bebas bes 5,15-difenilporfirin (2), 5,15-diheksilporfirin (3) dan 5,10,15,20-tetrafenilporfirin (4) iaitu NiDDHP, NiDPP, NiTPP, ZnDHP, ZnDPP dan ZnTPP dihasilkan melalui penyejatan Lindsey sebelum dicirikan secara spektroskopi (resonans magnet nukleus, ultra lembayung boleh nampak, spektrometri jisim) dan fizikal (takat lebur). Aktiviti antiplasmodium dan kesitotoksikan secarain vitro terhadap strain rintang-klorokuina, P. falciparum K1 dinilai dan dibandingkan dengan aktiviti antiplasmodium dadah rujukan seperti klorokuina dan artemisinin. ZnDHP, ZnTPP dan NiDPP merencat pertumbuhan parasit dengan 50% kepekatan perencatan berkesan (EC50) dalam julat aktiviti antiplasmodium sederhana iaitu 21.4 sehingga 36.0 µM. Aktiviti kesitotoksikan terhadap sel mamalia Vero yang ditunjukkan oleh NiDPP, ZnDHP dan ZnTPP berada dalam julat tidak toksik iaitu 97 sehingga 587 µM. ZnDHP mempunyai nilai indeks pemilihan yang paling tinggi iaitu 27.2 µM, menunjukkan aktiviti antiplasmodium yang selektif terhadap perencatan plasmodium dan tidak toksik terhadap sel mamalia

Effect of Multi-DG Installation to Loss Reduction in Distribution System

Since last decade, Artificial Intelligence (AI) methods have been used to solve complex DG problems because in most cases, they can provide global or near global solution. The major advantage of the AI methods is that they are relatively versatile for handling various qualitative constraints. AI methods mainly include Artificial Neural Network (ANN), Expert System (ES), Genetic Algorithm (GA), Evolutionary Programming (EP), Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). The purpose of this paper is to present a new technique, namely Adaptive Embedded Clonal Evolutionary Programming (AECEP). The objective of the study is to employ AECEP optimization techniques for loss minimization. This technique was developed to optimally determine the location and sizing of DG. The IEEE 41- Bus RTS was implemented for testing several cases in terms of loading conditions

Aktiviti antimalaria secara in vitro kompleks logam ligan makrosiklik tetraaza terhadap strain Plasmodium falciparum K1

Malaria masih lagi kekal menjadi salah satu penyakit endemik yang boleh membawa maut dan rawatan yang digunakan kini untuk merawat malaria adalah terapi gabungan artemisinin. Namun begitu, akses kepada rawatan ini adalah sangat terhad dan memberi kesan besar kepada negara miskin disebabkan kos terapi yang tinggi. Penilaian aktiviti antimalaria bagi kompleks organologam berasaskan ligan makroksiklik tetraaza masih kurang meluas dijalankan. Ligan makrosiklik tetraaza 5,5,7,12,12,14- heksametil-1,4,8,11- tetraazasiklotetradeka-7,14-dienium bromida, dikomplekskan dengan empat logam peralihan iaitu Cu(II), Pb(II) dan Ni(II) dan Cd(II). Aktiviti antimalarial secara in vitro ke atas strain parasit Plasmodium falciparum yang rintang terhadap klorokuina, K1 ditentukan dan dibandingkan dengan aktiviti antiplasmodial sebatian klorokuina dan artemisinin. Kompleks [Cd(L)(OAc)]Br- merencat pertumbuhan parasit dengan 50% kepekatan perencatan berkesan (EC50) dalam julat aktiviti antiplasmodium yang poten (EC50100 μM). Nilai indeks pemilihan yang tinggi turut ditunjukkan oleh kompleks Cd(II) iaitu 60.5 seterusnya menjadikan kompleks ini berpotensi untuk dibangunkan sebagai agen antimalaria

Optimal TCSC Allocation via Chaotic Immune Symbiotic Organisms Search for Voltage Profile Improvement

As the load demand in a power system increases, power system operators struggle to maintain the power system to be operated within its acceptable limits. If no mitigation actions are taken, a power system may suffer from voltage collapse, which in turn leads to blackout. Flexible AC Transmission System (FACTS) devices can be employed to help improve the voltage profile of the power system. This paper presents the implementation of Chaotic Immune Symbiotic Organism Search (CISOS) optimization technique to solve optimal Thyristor Controlled Series Compensator (TCSC) in a power system for voltage profile improvement. Validation process are conducted on IEEE 26-bus RTS resulting in the capability of CISOS in solving the allocation problem with a better voltage profile. Comparative studies conducted with respect to Particle Swarm Optimization (PSO) and Evolutionary Programming (EP) has revealed the superiority of CISOS over PSO and EP in solving the optimal allocation problem by producing optimal solution with a better voltage profile. The results and information obtained from this study can help power system operator in terms of optimal compensation in power system as well as improving the operation of a power system