  Day Ahead Electricity Markets (DAMs) in India are thin but growing.
Consistent price forecasts are important for their utilization in portfolio
optimization models. Univariate or multivariate models with standard exogenous
variables such as special day effects etc. are not always useful. Drivers of
demand and supply include weather variations over large geographic areas,
outages of power system elements and sudden changes in contracts which lead the
players to access power exchanges. These needs to be considered in forecasting
models. Such models are observed to considerably reduce forecasting errors by
outperforming other models under conditions, which are neither infrequent nor
recur at defined intervals. This paper develops models for India and tests the
utility of these models using Model Confidence Set (MCS) approach which picks
up the best models. The approach has been developed for a power utility in
India over a period of two years in live business environment.
