Paper Title
Price Forecasting for Day Ahead Electricity Market using Recursive Neural Network

Abstract
Price forecasting has becomes a very valuable tool in the current upheaval of electricity market deregulation. It plays an important role in power system planning and operation, risk assessment and other decision making. This paper provides a method for predicting hourly prices in the day-ahead electricity marketusing Recursive Neural Network (RNN) technique, which is based on one output node, which uses the previous prediction as input for the subsequent forecasts. In this way, it is carried out recursively for twenty four steps to preict next 24 hour prices. Comparison of forecasting performance of the proposed RNN model with similar days along with other literature is presented. The proposed method is examined on the PJM electricity market. The result obtained through the simulation show that the proposed RNN model can provide efficient, accurate and better results. Index Terms- Electricity market, price forecasting, recursive neural networks, similar days.