Enhancing Peak Shaving through Nonlinear Incentive-Based Demand Response: A Consumer-Centric Utility Optimization Approach

This paper presents a comparative study on the implementation of incentive-based demand response programs in power grid management, comparing results obtained from linear and nonlinear models. The challenges faced by grids balancing supply managing price spikes during peak periods are addressed, proposed as an effective strategy. focus is implementing where load serving entities determine optimal incentive reduction. A novel approach presented for simulating consumer behavior based elasticity consumers’ utility function, incorporating both economic calculation reduction aims to maximize welfare, while determination maximizes profit entities. Real data utilized, models implemented using mixed-integer programming (MINLP) method. demonstrate effectiveness providing incentives consumers hours compared other approaches, with comparison between