Abstract:
This article proposes an adaptable incentive framework for an incentive-based demand response (IBDR) program. The framework is based on changes in demand from end-consumers using the bilevel approach to optimize the scheduling of flexible loads. The distribution system operator (DSO) acts as a leader with a multi-objective optimization problem. The objective is to maximize profit while minimizing network energy loss and peak load at the point of common coupling. The DSO’s strategy involves changing demand-based adaptive incentive offers to enhance end-consumers participation in the DR program. Furthermore, the DSO aimed to mitigate phase unbalancing as an objective to address power quality issues caused by imbalances in phase voltage and power. Aggregators are regarded as followers in the bilevel approach, aiming to maximize incentives for mitigating the discomfort caused by scheduling flexible energy resources in the IBDR program. By utilizing Karush-Kuhn–Tucker conditions, the previously mentioned bilevel problem transformed into a single-level optimization problem. This work examined two case studies to determine the effectiveness of the proposed adaptable IBDR model. The efficacy of the proposed framework was assessed on a modified IEEE 25 bus unbalanced distribution system. The evaluation reveals that adaptive IBDR confers advantages to all participants, including DSO and end-consumers.