@inproceedings{9eb898da02cd489481a642149a0b675d,
title = "Revenue Maximization of Utility based on Price Forecasting and Energy Scheduling in LMP Market",
abstract = "The Locational Marginal Pricing (LMP) approach to electricity pricing generally supports the efficient operation of existing resources. Forecasting of the load and the price of electricity can be achieved vibrantly apace with the help of LMP. Load and price forecasting of the system is much indispensable to have a smooth running of the system operation in the aspect of utility and consumer. Price forecast may result in significantly different economic impacts on the utility. The inaccuracy in the forecast can be quantified by implementing the penalizing concept for the error raised in the forecasting of the load. By means of indulging the approach of penalizing the usage of load beyond the forecast, the revenue of the utility can be increased alongside boosting the customer to stick with the concept to conserve and manage the consumption of energy utilized.",
keywords = "Load Forecasting, Locational Marginal Pricing, Penalty, Profit Maximization",
author = "Sivasankari, {G. S.} and S. Prasanthini and N. Vijithra and K. Narayanan and Gulshan Sharma and Tomonobu Senjyu",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2nd International Conference on Power Electronics and IoT Applications in Renewable Energy and its Control, PARC 2022 ; Conference date: 21-01-2022 Through 22-01-2022",
year = "2022",
doi = "10.1109/PARC52418.2022.9726664",
language = "English",
series = "2022 2nd International Conference on Power Electronics and IoT Applications in Renewable Energy and its Control, PARC 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2022 2nd International Conference on Power Electronics and IoT Applications in Renewable Energy and its Control, PARC 2022",
address = "United States",
}