Demand Response Algorithm Incorporating Electricity Market Prices for Residential Energy Management

Demand Side Energy Management has now been established in the smart grid framework in order to meet the fluctuating demand supply gap that exists mainly during peak load periods. Along with the potential of energy efficiency and conservation measures, due to the increasing use of modern domestic appliances

in a developing country like India, Demand Response (DR) has gained a lot of importance in the residential sector. Most of the DR algorithms that have been developed mostly focus on energy consumption scheduling without considering electricity market prices. In this thesis we have proposed a DR algorithm for residential customers, which can be used to optimally schedule appliances, making use of actual day-ahead electricity market price data and also considering user preferences in the operation of appliances. The algorithm has been simulated for five different customers using a flat pricing scheme and two time-differentiated pricing schemes. For each customer, an estimated saving of around 6% is obtained by using hourly pricing. Analysis of the results underlines the importance of formulating effective dynamic pricing policies for successful implementation of DR algorithms for the residential users thereby tapping into the vast DR potential that exists in India.