Market Clearing Price (MCP) of an energy market is an operating equilibrium attained, when consumer demand and supply bid curves intersect with each other. Early anticipation of MCP provides an upper hand to any generating company to exercise the market power in its own favour. MCP prediction technologies are evolved in recent years and emphasis is given on developing a robust mechanism for anticipating dynamic conditions. This work presents an application of a nonlinear whitening term enabled grey model for prediction of the MCP. Detailed mathematical analysis and development of the model is presented. The proposed model is named as Nonlinear Hyperbolic Optimized Grey Model (NHOGM). For optimizing the whitening equation parameters, Linear Population Size Reduction (LPSR) Success History Based Parameter Adaption Differential Evolution (L-SHADE) algorithm has been applied. Results reveal that proposed nonlinear hyperbolic grey model yields satisfactory results as compared with the state of art grey methods and other well-known optimization based methods.