ENERGY MANAGEMENT PLAN OF AN OPTIMIZED WOOD-FIRED BOILER IN A TEA PROCESSING FACTORY IN KERICHO, KENYA

Abstract

Energy resources are generally constrained and costly, resulting in a gap between the rising demand for energy and the available supply. Tea factories are no exception, as many rely on boiler as a source of energy for their operations. The high cost of fuel has led these factories to adopt challenging solutions, such as using wood as a combustion source for boilers. Given that wood is an expensive source of fuel, implementing effective energy management strategies is crucial to ensuring sustainable productivity. This research aimed to optimize boiler energy usage and develop an energy management plan (EMP) to enhance boiler efficiency and minimize gas emissions. The study was grounded in three theories: the Theory of Moisture Sorption, the Phlogiston Theory, and the Lavoisier Theory. The researcher applied the research onion framework, focusing on factors such as air- fuel ratio, the boiler’s surface heat loss, the fuel's moisture content, and boiler flue gas losses. A fuzzy logic controller was designed to optimize the combustion process of the boiler. Simulations revealed that the fuzzy logic controller significantly improved the AF ratio, boosting efficiency from 78% to 81% during combustion. The optimized parameters enabled the creation of an energy management plan (EMP), which was validated using a continuous-time dynamic model. Validation results indicated an initial linear temperature increase, suggesting enhanced heat transfer and accelerated heat absorption by water. Near the boiling point of water (373.15 K or 100°C under standard atmospheric pressure), the graph plateaued, as additional heat contributed primarily to the phase change from water to steam. Applying the developed EMP in industrial settings would improve boiler combustion efficiency, enhance productivity, and reduce emissions, thereby mitigating environmental pollution.