Authors :
Christian Ndayishimiye , Lu Ling , Li Chunyu; Wadslin Frenelus
Volume/Issue :
Volume 8 - 2023, Issue 1 - January
Google Scholar :
https://bit.ly/3IIfn9N
Scribd :
https://bit.ly/3YeoEP3
DOI :
https://doi.org/10.5281/zenodo.7588032
Abstract :
The work presented here collects and
synthesises technical requirements, implementation and
optimisation methods for modelling grid-level matrix
models, with particular reference to renewable energy
access and controllable loads. The work presents the
controlled connected load modelling approach and
places it in the same economic modelling and control
framework as the interconnection planning
measurement generation facility. The paper uses system
parameters to test model performance. The test results
are used to illustrate and validate the described
approach. This work will improve energy efficiency and
minimise energy pollution to the environment, which
has become an important issue in the energy sector as
energy and environmental issues become more acute. In
IDR, energy consumers can respond not only by
reducing energy consumption or by choosing off-peak
energy consumption, but also by changing the type of
energy consumption. Increasing the level of integrated
energy use has been a central objective in the optimal
design of integrated energy systems (DIES), which
requires an accurate assessment of energy efficiency.
We introduce a new optimisation model which is
compounded in deep learning techniques.
Keywords :
matrix; IDR; electricity market; model performance; optimization methods.
The work presented here collects and
synthesises technical requirements, implementation and
optimisation methods for modelling grid-level matrix
models, with particular reference to renewable energy
access and controllable loads. The work presents the
controlled connected load modelling approach and
places it in the same economic modelling and control
framework as the interconnection planning
measurement generation facility. The paper uses system
parameters to test model performance. The test results
are used to illustrate and validate the described
approach. This work will improve energy efficiency and
minimise energy pollution to the environment, which
has become an important issue in the energy sector as
energy and environmental issues become more acute. In
IDR, energy consumers can respond not only by
reducing energy consumption or by choosing off-peak
energy consumption, but also by changing the type of
energy consumption. Increasing the level of integrated
energy use has been a central objective in the optimal
design of integrated energy systems (DIES), which
requires an accurate assessment of energy efficiency.
We introduce a new optimisation model which is
compounded in deep learning techniques.
Keywords :
matrix; IDR; electricity market; model performance; optimization methods.
