Autors: Baeva, S. K., Hinova, I. S.
Title: Comparative Post-Optimal Analysis to Effectively Forecasting the Subscriber's Daily Natural Gas Consumption
Keywords: Input datas, Natural gas consumption, Operational efficiencies, Optimal analysis, Statistical processing, Stochastic optimizations, Utility companies

Abstract: Although there are developments to predict energy consumption, the topic has not been exhausted and remains relevant. It should also be noted that each author uses the power of models differently to interpret inputs and outputs and their effects on the consumption process. Cutting costs and improving operational efficiency is something that energy and utility companies are continually working towards. It's a constant battle, and the work is never complete. This study offers a comparative post-optimal analysis to effectively predict daily consumption through statistical processing of input data and methods of stochastic optimization are applied. Input data are defined indicators of factors affecting the consumption process. These indicators are sampled in the stochastic process

References

    Issue

    International Conference on High Technology for Sustainable Development, HiTech 2019, Sofia; Bulgaria; 10 October 2019 through 11 October 2019, vol. HiTech 2019, pp. Article number 9128253, 2019, Bulgaria, IEEE, https://doi.org/10.1109/HiTech48507.2019.9128253

    Copyright IEEE

    Цитирания (Citation/s):
    1. Georgi Chankov, “Implications for the EU of the Suspension of Oil and Gas Supplies from Russia - Alternatives in the Extended Black Sea Region”, 2022 10th International Scientific Conference on Computer Science (COMSCI), https://doi.org/10.1109/COMSCI55378.2022.9912581, Electronic ISBN:978-1-6654-9777-0, CD:978-1-6654-9776-3, Print on Demand (PoD) ISBN:978-1-6654-9778-7, IEEE, 2022 - 2022 - в издания, индексирани в Scopus или Web of Science

    Вид: пленарен доклад в международен форум, публикация в реферирано издание, индексирана в Scopus