Abstract: In this paper, we propose a realistic multiple dynamic pricing approach to
demand response in the retail market. First, an adaptive clustering-based
customer segmentation framework is proposed to categorize customers into
different groups to enable the effective identification of usage patterns.
Second, customized demand models with important market constraints which
capture the price-demand relationship explicitly, are developed for each group
of customers to improve the model accuracy and enable meaningful pricing.
Third, the multiple pricing based demand response is formulated as a profit
maximization problem subject to realistic market constraints. The overall aim
of the proposed scalable and practical method aims to achieve 'right' prices
for 'right' customers so as to benefit various stakeholders in the system such
as grid operators, customers and retailers. The proposed multiple pricing
framework is evaluated via simulations based on real-world datasets.