Abstract
Indian electricity industry is under transition from vertical to restructured structure. In a 24 h electricity market, the operator performs auction for each hour in a day. Each time slot corresponds to different market clearing price. Energy consumption cost of intensive users can be reduced through demand response programs that involve planning of various processes stages in industries. This requires prediction of market price. This research work presents demand management planning model based on predicted price for a 24 h day ahead Indian electricity market. The proposed system is employed on the cooling production and distribution segment in a meat industry to control the chillers and dryers. The system employs autoregressive integrated moving average model to predict the Indian market price using real-time data. The ARIMA (2, 1, 5) appears to be an adequate model. The proposed model provides an evidence of significant saving in consumption cost in a day.
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Lekshmi, R.R., Bansi, C. (2023). A Demand Management Planning System for a Meat Factory Based on the Predicted Market Price Under Indian Market Scenario. In: Bindhu, V., Tavares, J.M.R.S., Vuppalapati, C. (eds) Proceedings of Fourth International Conference on Communication, Computing and Electronics Systems . Lecture Notes in Electrical Engineering, vol 977. Springer, Singapore. https://doi.org/10.1007/978-981-19-7753-4_34
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