An integrated access to electricity price forecasting using K means based ANN

Abstract

Mid-time period strength market Clearing charge (MCP) looking forward to is some days beforehand forecasts for each day facts. It has ended up being vital for better implementation of asset appropriation, making plans, respective contracting and arranging reasons for a strength exhibit. in this paper, an integrated midterm strength MCP estimating version is proposed to foresee the hourly MCPs for an entire month. The proposed model incorporates a k manner bunching module and artificial Neural network (ANN) guaging module. The ok way bunching module is applied to signify the 24 hours of multi day into some gatherings dependent on the closeness in cost. After the association, a Multi Layered Perceptron (MLP) is used to gauge the fee esteems in every one of the gatherings. to check the exactness of the proposed version the imply Absolute percent error (MAPE) and relapse coefficients are resolved for each one of the gatherings. Trial outcomes making use of recorded records from the Indian power Markets showed that the proposed included anticipating version can enhance the expectation exactness of price esteems and ultimately enhance the overall framework exhibitions.