A robust optimization approach for enabling flexibility, self-sufficiency, and environmental sustainability in a local multi-carrier energy community

Abstract

Managing Local Multi-Carrier Energy Communities (LMCECs) has become increasingly complex due to the need to balance sustainability, flexibility, and economic performance in modern energy systems. This challenge is further compounded by uncertainties in energy supply and demand, necessitating advanced optimization approaches. To address this, a robust optimization model has been developed to enable LMCECs to effectively participate in programs emphasizing flexibility, self-sufficiency, and environmental sustainability. The model incorporates electrical flexibility constraints to enhance practical applicability and allows the LMCEC manager to adopt emissions limits recommended by upstream energy networks, promoting environmentally conscious operations. By prioritizing self-sufficiency, the model not only strengthens the resilience of LMCECs but also improves their operational efficiency. Results demonstrate the model's effectiveness in handling uncertainties while minimizing operational costs, achieving an average optimal self-sufficiency rate of 76.36 %. This represents a significant step forward in advancing sustainable and resilient energy management practices. Moreover, a comparison between the robust optimization approach and both the deterministic and Distributionally Robust Chance-Constrained (DRCC) methods highlights the superior performance of the proposed robust optimization under worst-case scenarios.