  This paper evaluates the impact of the power extent on price in the
electricity market. The competitiveness extent of the electricity market during
specific times in a day is considered to achieve this. Then, the effect of
competitiveness extent on the forecasting precision of the daily power price is
assessed. A price forecasting model based on multi-layer perception via back
propagation with the Levenberg-Marquardt mechanism is used. The Residual Supply
Index (RSI) and other variables that affect prices are used as inputs to the
model to evaluate the market competitiveness. The results show that using
market power indices as inputs helps to increase forecasting accuracy. Thus,
the competitiveness extent of the market power in different daily time periods
is a notable variable in price formation. Moreover, market players cannot
ignore the explanatory power of market power in price forecasting. In this
research, the real data of the electricity market from 2013 is used and the
main source of data is the Grid Management Company in Iran.
