The Optimization Of Generating Plants In A Microgrid: The Covenant University Electric Power Network Experience

ABSTRACT

The use of fossil fuel in electricity generation has created three significant issues for the world to deal with. The issues are security (availability and reliability) of supply, climate change and the cost of fuel required for electricity generation. Covenant University, currently running a cluster of stand-alone diesel powered generating plants situated at different locations within the campus has a lot of unused available capacity within the system which invariably increases the operating (fuel) cost of power generation and also contributes to the environmental pollution through the emission of greenhouse gases within the campus. This research work, using a bottom- up approach, developed a new Electric Power network arrangement by integrating the power generators into a microgrid where there would be a common pool of energy sources for all the loads attached to the power network. The network operational functionality and a developed optimized dispatch algorithm were simulated in Matlab to select generators based on their operating parameters to serve the required loads. Hybrid System Optimization Model for Electric Renewables (HOMER 2.81) software was used as the simulation, sizing and optimization tool to evaluate the performance of the developed network. This method minimized the unused capacity being wasted by reducing power plant engagement and consequently reducing the cost of fuel and carbon-based environmental pollution from the power generators that are operated in the campus. This, in turn, should encourage greenness, curbed pollution, and enhances system security and reliability. The fuel cost and emission were reduced by as much as 44.3% and 51.8% respectively. Consequently, for the specific problem identified in the operation of the Covenant University Electric Power Network, a model was developed to solve it. The developed model, in all its intent and purposes, can be generalized; that is, it can be applied to any cluster of independent dissimilar power generating plants.