Optimized Fractional Overhead Power Term Polynomial Grey Model (OFOPGM) for market clearing price prediction

Abstract

Market Clearing Price (MCP) prediction methods are beneficial for framing the profit making strategies for a generating company. Early anticipation of this information can be helpful to judge the behaviour of rivals in the energy market. Companies are always striving to develop methodologies, by which early anticipation of the market clearing conditions can be emulated. The work presented in this paper is the development of an Optimized Fractional Overhead Power Term Polynomial Grey Model (OFOPGM). Mathematical aspects of this model are explained. The coefficients of polynomial grey action quantity are obtained with an aim to minimize the prediction error. An optimization routine based on L-SHADE algorithm is developed. First the application of L-SHADE and other contemporary optimizers are reported to optimize whitening equation. Then, the decisive evaluation has been made on the basis of convergence property analysis of L-SHADE and statistical attribute analysis of optimization runs. Further, OFOPGM with L-SHADE is considered for prediction of MCPs. A comparative analysis of contemporary grey models is presented on the basis of prediction error analysis on the MCP data of Indian Energy Exchange. The results reveal that proposed model yields better fitting as compared to other models. Further the evaluation of forecasting method is conducted through several analyses. • A grey model based on Optimized Whitening Equation is proposed. • Powerful optimization Algorithm L-SHADE is applied to handle the optimization routine. • The comparative analysis of some conventional and contemporary grey models are conducted with the proposed. • Error indices of forecast are reported in the work.