Electricity is unique in that its storage is prohibitively costly; this makes it essential for supply to, at least, meet demand at every second of every day. In times of crisis where demand exceeds its projected amount, system operators need to fall back on different methods to lower demand. One such method is Dynamic Pricing which incentivizes customers to lower their consumption by increasing electricity prices during those times. There are trials that test out this pricing model against a flat rate pricing model. This talk uses mathematics and statistical techniques applied in python to see the impact of dynamic pricing on consumption.