Optimal Scheduling of Multi-carrier Energy System Considering Nudge-based Behavioral Integrated Demand Response

Nozarian, Mahdi; Monajatipour, Sina; Namazizadeh, Mohamad

doi:10.48308/ijrtei.2025.240665.1094

Optimal Scheduling of Multi-carrier Energy System Considering Nudge-based Behavioral Integrated Demand Response

Document Type : Research Article

Authors

Mahdi Nozarian ¹

Sina Monajatipour ²

Mohamad Namazizadeh ³

¹ Smart Grid Research Group, Faculty of Electrical Engineering, KN Toosi University of Technology, Tehran, Iran

² R&D Department, Monenco Iran Consulting Engineers, Tehran, Iran

³ R&D Department, Monenco Iran Consulting Engineers, Tehran, Iran

10.48308/ijrtei.2025.240665.1094

Abstract

Nudge theory, a concept in behavioral science, advocates for the use of reinforcement, encouragement, and subtle recommendations to encourage voluntary adherence and shape the motivations and decisions of individuals or groups. This approach has emerged as an influential method for steering consumer behavior in energy consumption, thereby optimizing energy system operations. In this regard, demand response (DR) policies in energy systems have significant potential to align with behavioral and nudge theory concepts. This paper incorporates positive real-world incentives into DR modeling for both electricity and heating systems, aiming to influence household and customer decision-making in energy consumption through behavioral concepts. Therefore, this study introduces an optimal scheduling framework for multi-carrier energy systems that incorporates nudge-based behavioral integrated demand response (NBIDR), which combines behavioral principles into a DR program (DRP) for both electricity and heating systems. The suggested mixed integer linear programming (MILP) framework was applied to the IEEE 33-bus test system. Simulation results demonstrate the effectiveness of the proposed framework by smoothing load profiles as well as decreasing operation costs and expected energy not supplied (EENS) for both electricity and heating infrastructures.

Keywords

Mixed integer linear programming

Subtle suggestions

Voluntary compliance

Electricity infrastructure

Heating infrastructure

Subjects