The estimation and projection of the electric power generation from corn residues in Nigeria based on liner regression analysis

A global desire for sustainable energy development to combat greenhouse gases (GHGs) emissions from energy sector has incited research endeavours on the exploitation of various kinds of renewable energy. However, presence of biomass resources in nearly every part of the world coupled with their ability to decarbonise electric power sector when used for electricity generation has attracted a very important attention for their exploitation. Thus, estimation and projection of the potential capability of different kinds of biomass resources for power generation is imperative. In the estimation and projection of electric power potential of a bioresidue, a standard formulation involving only two parameters is commonly employed by researchers. The parameters are the calorific value of residue and residue conversion factor. The estimations were made in country case study without taking into account another factor where some quantity of residues is diverted for contending applications. Therefore, this research presents a new mathematical technique called a Modified Nominal Bio-Power Capacity (MNBPC) by introducing the concept of residue availability factor. The new formulation is used for estimating the nominal power capacity of three corn residues (cob, straw and stalk) in Nigeria as a case study. A period of 15 years (1996-2010) is chosen for the estimation using corn production quantity obtained from United Nations Food and Agriculture Organisation while the calorific values of the sample residues are obtained experimentally. The computation is also based on the average of different gasification efficiency of 31% adopted from literature. A projection of 10 years (2011-2020) based on the new formulation was performed using linear regression which is in line with the plan of action to integrate bioelectricity into the nation?s power sector by the year 2020. The least squares technique is considered to be superior for the projection because of its ability to correlate production quantity with time in a long forecasting scenario compared to other techniques. Based on the 70% collection rate (availability factor) of the residue surveyed in the country case study, computational findings estimated 2,570 MW (2.57 GW) nominal power capacity in the year 2010. This potential is approximately 33% of the total current installed capacity of 7,876 MW and 25.7% of the national electric power demand of 10,000 MW. The projection result shows that by the year 2020, a total capacity of 3,200 MW (3.2 GW) could be achieved with corn stalk residue exhibiting the highest potential of 73.1% of the total. This is based on 61% coefficients of determination between the residues? production trend with respect to time variation as evaluated using Pearson?s Product Moment Correlation Coefficient. Finally, the estimated and projected potential in this study has shown a significant contribution from the corn residues to the proposed biomass power generation in the country.