Забезпечення спостережності розподільних електричних мереж з відновлюваними джерелами енергії
Author
Кулик, В. В.
Бурикін, О. Б.
Малогулко, Ю. В.
Тептя, В. В.
Лесько, В. О.
Date
2021Metadata
Show full item recordCollections
- Наукові роботи каф. ЕСС [342]
Abstract
У статті запропоновано метод ідентифікації режимних параметрів розподільних електричних мереж (ЕМ) з відновлюваними джерелами енергії (ВДЕ) на основі псевдовимірювань графіків їх генерування, отриманих за агрегованою інформацією автоматизованих систем комерційного обліку електроенергії (АСКОЕ) та типовими графіками. The paper proposes a method of increasing the observation
of distribution power networks (DPN) with renewable energy
sources (RES) by using aggregated information of automated
systems of commercial electricity metering and pseudo-measurements in the form of typical generation schedules. To solve
this problem, it is proposed to use the typical meteorological
year data set.
Based on typical data sets for the meteorological year, typical renewable energy generation schedules are used to calculate and analyze electricity losses in distributed power networks
using state estimation methods to time synchronize information
and recover time-aggregated electricity generation information.
The advantage of this approach is the ability to analyze the
energy efficiency of distribution power networks with a significant share of renewable energy sources (such as photovoltaic
power plants, wind farms, etc.). Particular attention is paid to
photovoltaic power plants, as they have a fairly predictable generation schedule according to a typical meteorological year.
This allows it to be used in a mathematical model as a typical
one, along with power consumption graphs. It also becomes possible to recover lost information for each specific mode of the
distributed power network, provided it is observed for a certain
period of time. The use of this approach involves the use of functional dependencies of the mode parameters in combination
with other methods of recovering lost data.
Thus, the insufficiency of the observation vector in the target
state estimation function can be compensated by information
from a typical data set, namely the mathematical expectation of
electricity generation of the renewable energy source, its standard deviation and information about the generated power in the
unobserved node from the billing system.
URI:
http://ir.lib.vntu.edu.ua//handle/123456789/38032