TITLE:
Analysis of Nigerian Electricity Generation Multi Year Tariff Order Pricing Model
AUTHORS:
Nnamdi B. Anosike, Jude E. Dara, Ugochukwu C. Ngwaka, Frances O. Enemuoh
KEYWORDS:
Nigerian electricity Market, Generation Multi Year Tariff Order (MYTO), Combustion Turbine, Electricity Price Uncertainty, Government Interventions
JOURNAL NAME:
Energy and Power Engineering,
Vol.9 No.10,
September
11,
2017
ABSTRACT: The Multi Year Tariff Order (MYTO) is the Nigerian Electricity Regulatory Commission (NERC) pricing framework for determining the Nigerian Electricity Supply Industry (NESI) pricing model. One of the objectives of the NERC’s MYTO pricing model is to ensure regulated electricity end user tariff without compromising return on investment. Achieving this objective is imperative to attract investors in the growing Nigerian electricity market. However, NESI has hitherto been faced with challenges ranging from its inability to provide sufficient power to its customers to not being viable enough to provide return on capital invested. In this paper, sensitivity analysis of power plant operation and performance parameters on the cost of electricity (CoE) generation using MYTO (power generation) pricing model were evaluated. Thermodynamic modeling and simulation of an open cycle gas turbine (OCGT) was carried out to augment scarce data on power plant performance and operation in Nigeria. Sensitivity analysis was carried out using probabilistic method based on Monte Carlo simulation (MCS) implemented in commercial software (@ Risk®). The result highlighted sensitivity of the model input parameters to cost of electricity generation based on technical and financial assumptions of MYTO model. Seven most influential parameters affecting generation cost were identified. These parameters and their correlation coefficients are given as: 1) foreign exchange rate, 0.76; 2) cost of fuel, 0.51; 3) thermal efficiency, -0.23; 4) variable operation and maintenance cost, 0.22; 5) fixed operating and maintenance cost, -0.03; 6) capacity factor, -0.02; and 7) average capacity degradation, 0.01. Based on the gas turbine engine and input parameter distributions statistics for this study, the generation cost lies between 9.84 to 15.45 N/kWh and the probabilities of CoE within these values were established.