A REVIEW OF LOAD ESTIMATION AND DISTRIBUTION STRATEGY FOR RENEWABLE ENERGY SOURCES

Abstract

The remarkable increase in per capita power
consumption worldwide has drawn attention towards the
needed growth in renewable energy sector in order to
bridge the gap between overall demand and supply. In this
project various renewable energy sources like solar, wind
and hydro energy are taken into consideration for the load
estimation. Several factors are considered for the making
of dataset related to each energy source which include
environmental factors as well as other supporting factors.
With the collected data, prediction of energy generation is
performed using the machine learning algorithm, Random
Forest. The generation, transmission and distribution of
the energy is achieved through a power grid system which
enables efficient and reliable supply of electrical power
from power plants to various consumers.
Bidding mechanisms are commonly used in renewable
energy markets to allocate and trade energy generated
from renewable sources. Producers, such as solar farms or
wind power facilities, participate in bidding processes to
sell their energy to different distribution centres through
grid. Bids may include details like the quantity of energy,
pricing, and timing of delivery