Market scheduling of emission-aware smart prosumers in smart grids: A multi-objective bi-level approach

Decentralized coordination between smart grids and smart prosumers in local energy markets is crucial for operators, as it enables optimal utilization of prosumer capacities to enhance economic and environmental performance. This paper introduces an advanced bi-level optimization model for managing local energy markets within smart grids, taking into account the dynamic interactions of smart prosumers, including energy hubs and Electric Vehicle Parking Facilities (EVPFs). The upper level of the model represents individual prosumers, focusing on minimizing daily operational costs through decentralized decision-making. The lower level involves the smart grid operator, who conducts a bi-objective optimization of the local energy market using the epsilon-constraint method, incorporating prosumer preferences and carbon emissions. Additionally, the operator employs a risk-averse approach to address operational uncertainty risks. The proposed model is implemented in the General Algebraic Modeling System (GAMS) environment on a 69-bus renewable distribution network integrated with 25 smart prosumers. Simulation results demonstrate the model's effectiveness in maximizing smart prosumer capacities, thereby improving the technical and environmental performance of smart grids. The findings indicate that by leveraging Integrated Demand Response Programs (IDRPs) in energy hubs, along with smart charging and Vehicle-to-Grid (V2G) services in EVPFs, the model not only enhances the voltage profile of the smart grid but also achieves a 31.23 % reduction in carbon emissions and a 14.28 % reduction in daily costs.