Abstract
Demand response (DR) modifies the pattern from a straightforward to an interactive one, allowing for the investigation of consumer participation in the power market and progress. The most important technique for evaluating the status of DR program implementation among those discussed in the earlier literature is consumer baseline load (CBL). Without using the DR program, CBL depicts the consumer consumption pattern that might emerge. There hasn’t been much study done on CBL computation for residential consumers, and most of it ignores the influence of weather on these estimates. This study describes a novel method for computing CBL for residential consumers in the context of a smart grid. The findings show how weather affects CBL estimations and consumer desire to upgrade home insulation. The proposed method is examined in four test cases. The day-wise load data for the first test case has been collected from the NO1 region of Nord Pool and the remaining three test case data have been collected from the Connecticut and New Hampshire region of New England ISO.
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