Abstract
During the last few decades, Pakistan
experienced an energy shortage as well as a surplus. Pakistan
had previously undergone shortages of up to 7,000 MW but
today has a surplus of 12,000 MW, after meeting peak demand.
One of the key causes of the industrial sector's slump is a supply
shortfall that slowed GDP growth. On the other hand, the
current oversupply is producing a steady rise in electricity costs
as well as circular debt. Intelligent demand management has the
potential to decrease circular debt buildup while simultaneously
reducing electricity prices. Demand Side Management (DSM)
technologies provide intelligent load management by providing
energy distribution companies with distinct incentives to lift the
load from peak hour to off-peak hour by reducing the weighted
average cost of generation (WACG). This research develops a
DSM-based tool that allows for data analytics to evaluate the
impact of demand variations on an hourly basis. While
calculating its findings, the tool considers the rates of all
Pakistani generation units, as well as other financial variables
like required capacity and energy payments from IPP
agreements. With only a 5% shift in demand from peak hour to
off-peak hour, the utility will save significantly. Furthermore,
the developed tool assesses the environmental impact of
different operational sets of generating units.