Minimization of Environmental Impact of Energy by Optimization Energy Mix Technique

ABSTRACT

The development and utilization of energy has led to environmental degradation with associated health hazard. Hence the trust of this project is to optimize energy mix in a reliable, affordable, available, safe, efficient, effective and sustainable way at control cost subject to environmental constraints. In other to achieve the desired goal, the optimization model is derived with unit cost of each of the various energy sources as the objective function and environmental impact as constraints with energy sources as decision variable. The solution was obtained using Frontline Solver optimization linear programming software model and the solution verified and compared with existing energy in use. Result shows that the implementation of this optimization utilization strategy yields 8.06% reduction in cost with 15% reduction in environmental impact over the existing practice compliance with United Nations Framework on Climate Change target. The sensitivity analysis first examined the impact of the variation of unit cost (objective function) on optimization cost by varying the unit cost of each of the energy sources by -5%, -2.5%, +2.5%, +5% each at a time while every other things remain constant and noted that uniformly as the unit cost of each of the energy sources increases, the optimization cost also increases linearly accordingly in proportionate. The sensitivity analysis in another condition examined the impact of the variation of the value of the pollutants (constraints) on optimization cost by varying the value of each of the pollutants by -5%, -2.5%, +2.5%, +5% each at a time while every other things remain constant and observed that varying the value of each of the pollutants at the same percentage does not produce similar, uniform and the same linear graph like the previous case. A further sensitivity analysis examined the impact of the variation of the value of the energy sources (decision variables) on optimization cost by varying the value of each of the energy sources by -5%, -2.5%, +2.5%, +5% each at a time while every other things remain constant and revealed that the corresponding response are not similar to each other because some of them are having a uniform linear graph while the others do not have uniform linear graph. The application of this work is in government policy on energy production that favours more environmental friendly optimized energy mix rather than depending on one exhaustible nonenvironmental polluting fossil fuels source of energy.