Prof. Nicodemus Abungu Odero

When an insulator is placed in an electrode gap, its surface charge field distorts the geometric field, leading to a flashover at a voltage value dependent on the degree of the gap field distortion. This paper reports on studies conducted to determine the relationship between flashover voltages and electric filed distribution along solid insulator surfaces. The surface electric field distribution along different insulator profiles was determined using the Finite-Difference method, and the flashover of the actual profile model measured. The obtained results show that each profile had a peak surface electric field and the higher the peak value, the lower the flashover voltage. The correlation curve for peak electric field and flashover voltage was developed using a curve fitting technique based on the Nelder-Mead simplex algorithm.

When an insulator is placed in an electrode gap, its surface charge field distorts the geometric field, leading to a flashover at a voltage value dependent on the degree of the gap field distortion. This paper reports on studies conducted to determine the relationship between flashover voltages and electric filed distribution along solid insulator surfaces. The surface electric field distribution along different insulator profiles was determined using the Finite-Difference method, and the flashover of the actual profile model measured. The obtained results show that each profile had a peak surface electric field and the higher the peak value, the lower the flashover voltage. The correlation curve for peak electric field and flashover voltage was developed using a curve fitting technique based on the Nelder-Mead simplex algorithm.

In this paper a hybrid numerical technique is presented, suitable for analyzing transmission properties of an arbitrarily shaped slot in a thick conducting plane. The slot is  excited by an electromagnetic source of arbitrary orientation. The analysis of the problem is based on the "generalized network formulation" for aperture problems. The problem is solved using the method of moments(MOM) and the finite element method(FEM) in a hybrid format. The finite element method is applicable to inhomogeneously filled slots of arbitrary shape while the method of moments is used for solving the electromagnetic fields in unbounded regions of the slot. The cavity region has been subdivided into tetrahedral elements resulting in triangular elements on the surfaces of the apertures.  Validation results for rectangular slots are presented. Close agreement between our data and published results is observed.  Thereafter, new data has been generated for cross-shaped, H-shaped and circular apertures.

In this paper a hybrid numerical technique is presented, suitable for analyzing transmission properties of an arbitrarily shaped slot in a thick conducting plane. The slot is  excited by an electromagnetic source of arbitrary orientation. The analysis of the problem is based on the "generalized network formulation" for aperture problems. The problem is solved using the method of moments(MOM) and the finite element method(FEM) in a hybrid format. The finite element method is applicable to inhomogeneously filled slots of arbitrary shape while the method of moments is used for solving the electromagnetic fields in unbounded regions of the slot. The cavity region has been subdivided into tetrahedral elements resulting in triangular elements on the surfaces of the apertures.  Validation results for rectangular slots are presented. Close agreement between our data and published results is observed.  Thereafter, new data has been generated for cross-shaped, H-shaped and circular apertures.

In this paper a hybrid numerical technique is presented, suitable for analyzing transmission properties of an arbitrarily shaped slot in a thick conducting plane. The slot is  excited by an electromagnetic source of arbitrary orientation. The analysis of the problem is based on the "generalized network formulation" for aperture problems. The problem is solved using the method of moments(MOM) and the finite element method(FEM) in a hybrid format. The finite element method is applicable to inhomogeneously filled slots of arbitrary shape while the method of moments is used for solving the electromagnetic fields in unbounded regions of the slot. The cavity region has been subdivided into tetrahedral elements resulting in triangular elements on the surfaces of the apertures.  Validation results for rectangular slots are presented. Close agreement between our data and published results is observed.  Thereafter, new data has been generated for cross-shaped, H-shaped and circular apertures.

The paper deals with an extension of the previous work appearing in a past issue of this transaction by the authors on hybrid FEM/MOM technique for analyzing transmission properties of arbitrarily shaped apertures on a thick conducting screen. In the present work, the effect of placing different dielectric material slabs in the conducting screen cavity on the electromagnetic transmission parameters is first analyzed and, then, the effect of interchanging the positions of these dielectric slabs relative to the incident field. Validation results for rectangular and cross-shaped slots are presented. Close agreement between our data and published data is observed.  Further data has been generated for rectangular, circular, diamond-shaped and cross-shaped apertures.

This paper presents a summary of the current status of Electrical Power Engineering Education at Kenyan universities, followed by a summary of the situation on the same at universities world-wide. Against a backdrop of expected changes in the Kenyan power industry, the paper discusses the industry expectations of a power systems graduate currently and in the future, making a case for the revision of the current power engineering syllabi, concluding with recommendations and strategies for making the required changes.

Power utility companies are required to supply customers with power within specified voltage limits. Voltage rise in networks with distributed generators therefore poses a challenge. This paper presents a coordinated network controller whose objective is to maintain an optimal voltage profile across the power network. The operations of distributed generators, on-load tap-changing transformers and reactive power sources are controlled. The controller is modelled as an optimisation problem which is solved using Particle Swarm Optimisation. The IEEE 30-bus test network is then used to verify the effectiveness of the controller. The results obtained show that this controller can greatly improve the voltage profile of a power network by varying the parameters of existing generation and voltage control equipment.

Power utility companies are required to supply customers with power within specified voltage limits. Voltage rise in networks with distributed generators therefore poses a challenge. This paper presents a coordinated network controller whose objective is to maintain an optimal voltage profile across the power network. The operations of distributed generators, on-load tap-changing transformers and reactive power sources are controlled. The controller is modelled as an optimisation problem which is solved using Particle Swarm Optimisation. The IEEE 30-bus test network is then used to verify the effectiveness of the controller. The results obtained show that this controller can greatly improve the voltage profile of a power network by varying the parameters of existing generation and voltage control equipment.

Power utility companies are required to supply customers with power within specified voltage limits. Voltage rise in networks with distributed generators therefore poses a challenge. This paper presents a coordinated network controller whose objective is to maintain an optimal voltage profile across the power network. The operations of distributed generators, on-load tap-changing transformers and reactive power sources are controlled. The controller is modelled as an optimisation problem which is solved using Particle Swarm Optimisation. The IEEE 30-bus test network is then used to verify the effectiveness of the controller. The results obtained show that this controller can greatly improve the voltage profile of a power network by varying the parameters of existing generation and voltage control equipment.

The problem of power system optimization has become a deciding factor in current power system engineering practice with emphasis on cost and emission reduction. The economic and emission dispatch problem has been addressed in this paper using two efficient optimization methods, Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO). A hybrid produced from these two algorithms is tested on a 10 generator test system with valve point effects. The results are compared with differential evolution (DE), Strength Pareto Evolutionary Algorithm (SPEA) and Non Sorting Genetic Algorithm (NSGA) and found to be effective on the combined economic and emission dispatch problem.

With the increased penetration of distributed generation into the power distribution system, the traditional
load flow analysis that assumes a single slack bus has become impractical. The existing literature focuses on slack bus placement taking only real power losses into place. However with increasing need of reactive power in maintaining voltage stability at the consumer end; reactive power generation management cannot
be ignored any further. Thus a distributed slack bus model taking into consideration both real and reactive power losses is of paramount importance. The wind based doubly fed induction generator is an attractive option for both real and reactive power loss compensation since it is economically attractive, can be grid
connected and it has the capability to generate and absorb reactive power. A distributed slack bus model
using combined participation factors is developed in this paper to distribute the slack(real and reactive power losses). The combined participation factors are formulated using the method of Lagrange
multipliers and the distributed slack bus model employs a Genetic Algorithm of a Newton Raphson Solver.

Power utility companies are required to supply customers with power within specified voltage limits. Voltage rise in networks with distributed generators therefore poses a challenge. This paper presents a coordinated network controller whose objective is to maintain an optimal voltage profile across the power network. The operations of distributed generators, on-load tap-changing transformers and reactive power sources are controlled. The controller is modelled as an optimisation problem which is solved using Particle Swarm Optimisation. The IEEE 30-bus test network is then used to verify the effectiveness of the controller. The results obtained show that this controller can greatly improve the voltage profile of a power network by varying the parameters of existing generation and voltage control equipment.

The global rise in energy demand has resulted to the over exploitation of both renewable and non renewable energy sources. Most feasible hydroelectric power (HEP) plants sites have been exploited and the current focus is on harnessing energy from small HEP plants which have low head and flow velocity rendering them unsuitable for HEP generation. Previous research work focused on improving the turbine shape and efficiency; designing better water intake, improving the generator and development of turbines suitable for low heads. The main aim of this research was to optimize the power generated by low head small hydro plants through the use of hydraulic ram pump (hydram) to boost the water pressure before it impinges on the turbine. In the current work, a smallHEP prototype system was designed fabricated and test runs conducted. The prototype comprised of; a low head water reservoir, a hydraulic ram pump which was used to increase the head of the water emanating from a low head source, a high head reservoir mounted at a the most optimal height based on the hydram flow rate and pressure considerations and a double cup pelton wheel turbine suitably designed to extract power from the water jet. A drive pipe was used to connect thehydram pump to the low head reservoir while the delivery pipe connected the pump to the high head reservoir. Water from the high head reservoir was used to turn the pelton turbine which was coupled to a generator. The flow rate in the drive pipe and the delivery pipe as well as the pressurein the hydram were optimized by adjusting the waste valve stroke length. It was observed that the hydram was able to pump water to a higher head which then increased the power produced by the turbine.

The problem of power system optimization has become a deciding factor in current power system engineering practice with emphasis on cost and emission reduction. The economic and emission dispatch problem has been addressed in this paper using two efficient optimization methods, Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO). A hybrid produced from these two algorithms is used on the 30-bus 6 generator IEEE test system. The results are compared with ABC, Fuzzy Controlled Genetic Algorithm (FCGA) and Non Sorting Genetic Algorithm (NSGA-II) and found to be effective on the combined
economic and emission dispatch problem.

Power utility companies are required to supply customers with power within specified voltage limits. Voltage rise in networks with distributed generators therefore poses a challenge. This paper presents a coordinated network controller whose objective is to maintain an optimal voltage profile across the power network. The operations of distributed generators, on-load tap-changing transformers and reactive power sources are controlled. The controller is modelled as an optimisation problem which is solved using Particle Swarm Optimisation. The IEEE 30-bus test network is then used to verify the effectiveness of the controller. The results obtained show that this controller can greatly improve the voltage profile of a power network by varying the parameters of existing generation and voltage control equipment.

The 21st Century Power Transformer is produced by combining modern high voltage cross-linked polyethylene (XLPE) cable technology with conventional transformer. The technique of solid insulation is adopted in the new dry transformer so that the pollution from leakage of insulating oil can be avoided, and so XLPE cable-winding transformer is very suitable in environment sensitive places such as populous cities, hydropower stations, and underground caver and so on. This paper is meant to show that the marriage of the well-proven high voltage power cable technology with transformer technology sets a new standard in improving power system voltage stability.

Reduction of system losses and improvement of voltage profile is one of the key aspects in power system operation. Though many methods are used to achieve this aspect, Distributed Generation (DG) has found increased usage nowadays due to its many advantages. Majority of algorithms proposed in this area have emphasized on real power losses only in their formulations. In modern practical power systems reactive power injection plays a critical role in voltage stability control, thus the reactive power losses need to be incorporated in optimizing DG allocation for voltage profile improvement. This paper aims at solving this problem by proposing a hybrid of GA and IPSO to optimize DG location and size while considering both real and reactive power losses. The hybrid technique aims at inheriting the good traits from the two techniques while avoiding the undesirable ones. Arithmetic crossover and mutation has being employed in the proposed algorithm.

Due to the increased importance of DFIGs in optimization of real and reactive power losses and the maintenance of voltage profile, the general methods of DG placement and sizing in the existing literature cannot be of practical importance in DFIG .In this paper a pure PSO method used in general DG is compared with a HGAPSO in the siting and sizing of DFIG with the objective of minimizing power losses .The corresponding Combined participation factors are assigned using the DFIG Domain Distributed Slack Bus Model and a comparison made on the two schemes of loss minimization. The obtained results for the real and reactive power losses and voltage voltage profile illustrate the DFIG need in the modern power system.

Past literature has attempted to solve the problem of network reconfiguration with Distributed Generators(DGs) without taking into consideration the intermittent renewable at a close proximity. Distribution Network Reconfiguration (ADNR) must account for uncertain behavior of loads and wind when the commercial wind based DG, Doubly Fed Induction Generators (DFIG) supports a significant part of network. In this paper, a new Hybrid Bacterial Foraging and Differential Evolution (HBFDE) algorithm is considered for the ADNR problem with minimum loss and an improved voltage profile. In the HBFDE algorithm the Differential Evolution (DE) algorithm is combined with the Bacterial Foraging (BF) algorithm to overcome slow and premature convergence of BF. Indeed, the proposed algorithm is based on the evolutionary natures of BF and DE, to take their advantage of the compensatory property, and avoid their corresponding drawbacks. In addition, to cope with the uncertainty behavior of loads and wind, a stochastic model is presented to solve the ADNR problem when the uncertainty related to wind and load forecast is modeled in a stochastic framework on scenario approach basis. The proposed algorithm is tested on the IEEE 33 - Bus Radial Distribution Test Systems. The results of the simulation show the effectiveness of proposed algorithm real time and real world optimization problems facing the smart grid.

Load forecasting refers to the prediction of future load conditions based on present or historical data. This is important especially for transmission planning and economic dispatch. In this paper, an Artificial Neural Network (ANN) is trained using historical data for a sub-station at Ruiru, Kenya and the corresponding loading conditions for the sub-station are used to test its accuracy in forecasting the electrical load when given other parameters.

Due to the increased importance of DFIGs in optimization of real and reactive power losses and the maintenance of voltage profile, the general methods of DG placement and sizing in the existing literature cannot be of practical importance in DFIG .In this paper a pure PSO method used in general DG is compared with a HGAPSO in the siting and sizing of DFIG with the objective of minimizing power losses. The corresponding Combined participation factors are assigned using the DFIG Domain Distributed Slack Bus Model and a comparison made on the two schemes of loss minimization.