Developing a coordinated energy management system for various hubs with a demand response approach

The integration of heterogeneous energy hubs with renewable generation, demand response, and local energy trading has emerged as a promising strategy for improving the sustainability and operational efficiency of future distribution systems. However, coordinating residential, commercial, and industrial energy hubs under renewable uncertainty while maintaining network feasibility remains a challenging task. This study proposes a coordinated energy management framework that integrates demand response programs (DRP), peer-to-peer energy trading, renewable energy resources, electric vehicles, and energy storage systems within an AC optimal power flow (ACOPF)-based environment. A mixed-integer linear programming (MILP) model was developed in GAMS and solved using CPLEX, while MATLAB/MATPOWER was employed to validate network feasibility. Uncertainties associated with renewable generation and electricity market prices were modeled using Monte Carlo simulation with 1000 scenarios. The proposed framework was validated on a modified IEEE 33-bus distribution network under four operating conditions: Base, Trading, PV, and Trading+PV. The results demonstrate that the coordinated Trading+PV strategy provides the best overall performance. Average network losses decreased from 209.73 kW to 198.45 kW, corresponding to a 5.38% reduction, while the minimum voltage level improved. Reliability assessment showed reductions of 5.43% in Expected Energy Not Supplied (EENS) and 10% in the System Average Interruption Duration Index (SAIDI). Furthermore, the local energy trading mechanism generated an average prosumer profit of $81.01/day and consumer savings of $34.35/day, resulting in a total social welfare improvement of $115.36/day. Monte Carlo analysis further confirmed the robustness of the proposed framework under uncertain operating conditions. The findings demonstrate that coordinated peer-to-peer energy trading combined with distributed renewable generation can simultaneously improve technical performance, reliability, and economic efficiency in multi-energy hub systems. The proposed framework provides a scalable decision-support framework for future sustainable distribution networks and smart energy communities.