Runoff Passing Simulation Model for Assessing the Efficiency of the Water-Power Conditions of an HPP Cascade

Rusina, Anastasia G.; Beloglazov, A. V.; Sovban, C. A.; Kornilovich, D. V.

doi:10.1007/s10749-023-01477-0

Cited by 2 publications

(1 citation statement)

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“…Известно, что существует большое число переменных, влияющих на режим электропотребления и соответственно на качество его прогноза. Эти переменные имеют разный характер, например, явные и неявные (латентные), экзогенные (внесистемные) и эндогенные (внутрисистемные) [2]. Электропотребление, частота, потери мощности и перетоки относятся к явным эндогенным переменным.…”

Section: Introductionunclassified

Forecasting the daily energy load schedule of working days using meteofactors for the central power system of Mongolia

Rusina

Tuvshin

Matrenin

2022

«Izvestiya vysshikh uchebnykh zavedenii. PROBLEMY ENERGETIKI»

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A feature of the power system is that all the processes of production, transmission and distribution occur simultaneously. This difficult and continuous process requires the management by the regime of the power system. For precise regime managements, it is necessary to study the characteristic of electricity consumption. Forecasting demand allows to optimize the distribution of generation and ensure the safety of the power system. Therefore, forecasting is given a lot of attention in the energy section. Although there are many forecasting methodologies, but there is no exact methodology that is suitable for all power systems.PURPOSE. To forecast the daily load schedule for working days, considering the influence of meteorological factors on the central energy system of Mongolia.METHODS. This study is carried out by the method of statistical analysis on MS Excel. As initial inputs historical data on load, temperature and outdoor air humidity of the central energy system were used, which has the most of the energy demand and sources of Mongolia by 2021.RESULTS. According to the method of statistical analysis, daily load curves were constructed with an absolute percentage error of 2.68%. After adding into account of meteorological factors, the absolute percentage error decreased to 2.26%.CONCLUSIONS. This method corresponds to forecasting daily schedules for working days. By restricting the electricity consumption during long continues non-work days, days with a major accident and planned maintenance will affect negatively to the planned tendency.

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Section: Introductionunclassified