Impact of Consumer Profiles on a Consumer Convenience Prioritised Demand Response

Abstract

Distribution network (DN) load flexibility has simultaneously created challenges and opportunities. The major challenge is to meet the demand-supply balance while maintaining a positive profit-loss ratio. Further, Government enforced climate change policies attract low carbon technology (LCT) distributed energy resources (DER), which further complicate matters. Along with DN, the domestic appliance industry has undergone drastic modernization leading to appliances with advanced control and power efficient technologies as well as automation capabilities. This paper proposes a demand response (DR) program that facilitates these advancements while micromanaging the domestic load consumption pattern so as to manage peak demand in the network. This work identifies consumer conviction towards the DR programs as the major bottle neck for the success of such load management programs. The mixed integer linear programming based DR (MILP – DR) algorithm proposed here, minimizes the consumer inconvenience while facilitating load reduction. Further, attractive consumer engagement plans promoting different levels of engagement (load reduction) are also proposed, which further enhance the choice offering for consumers. The algorithm is tested on a 74 load (domestic) urban distribution network having 8 different consumer profiles. The algorithm is capable of inducing impartiality between consumers by updating a tolerance factor correlating inconvenience of consumers with load deprivation. The results show the capability of the algorithm to distribute load reduction based on the engagement plan, while also minimizing the consumer inconvenience. The results also suggest correlations between social parameters and achievable DR.