Lungile Nyanga

A decision support tool for rural electrification grid design

This paper investigates the optimization of the electricity grid network in rural community of Chegutu district, in Zimbabwe. The Kruskals algorithm is used to minimize the total distance of the network connections, thus optimise resources for carrying out projects. Rural Electrification Agency has been failing to meet their targets for extension of the electricity grid network because of shortage of resources and input capital, thus this research adopts the idea of network optimization as a way of saving resources so that they can be used for other projects. The optimisation process shows that a total of 74km of 11kV power line could be saved from the network.

Implementation of an Energy Usage Optimization System on a Pharmaceutical Company

Companies in this era are under severe competition due to globalization and in order to sustain a competitive edge they need to adopt appropriate manufacturing systems that address optimum utilisation of machinery and energy. This will result in reduction of production costs and make the companies competitive. The paper shows attempts to improve Energy Usage at a Pharmaceutical industry using monitoring and targeting techniques. An audit in a company was done so as to get the energy consumption trends and to find opportunities for energy savings. An ABC analysis of energy cost savings for machinery in the plant was made. A monitoring and targeting system was then developed to increase awareness of energy consumed.

A fuzzy controller based demand - side management system design for optimization of induction furnaces.

From Conference Proceeding (714) Power and Energy Systems - 2011,The paper is a design of an automated Demand-side management system that will optimize electricity usage in a manufacturing plant using induction furnaces, through a multi-furnace controller. The multi-furnace controller controls two furnaces which alternate in between being a melting and a holding furnace. The control system selectively delivers preselected percentages of available power to furnaces. The power supply delivers power to both furnaces. A capacitor station in parallel connection to the power supply and the furnaces is tuned to form a tank circuit therewith and acts as the power factor correction device. Switches control the selected power delivered to the furnaces respectively and control the delivery of a first portion of the power for holding molten product in the hold furnace as the master control. Simulation model was design using fuzzy logic controller.The results show that using the multi-furnace controller results in a 30% decrease in the operating costs of the furnaces as demonstrated by the model plots.