Optimal Multiobjective Operation of Multicarrier Energy Hub Taking Energy Buffering Into Account

Abstract

This paper introduces a pioneering model for short-term planning of an energy hub (EH) that goes beyond traditional approaches by considering a comprehensive multicarrier energy system. The proposed model focuses on minimizing energy buffering costs while ensuring system operation and optimizing economic performance. The novelty of this study lies in its integrated approach, which simultaneously addresses operational efficiency, energy storage requirements, and overall system performance. The EH in this study is modeled as a prosumer within a day-ahead energy market, where both inflows and outflows of energy are optimized. The system’s capability to interact with upstream energy networks, including gas, heat, and electricity, is a critical aspect of the model. This interaction is managed through various technologies that enhance the hub’s ability to meet local demands efficiently. By employing an advanced improved particle swarm optimization (IPSO) algorithm, this model solves the complex multiobjective optimization problem inherent in EH management. The proposed model’s effectiveness is validated through extensive simulation on a test system, where its performance is compared with conventional heuristic optimization algorithms. The results demonstrate the superior efficiency and applicability of the IPSO algorithm, confirming that the proposed model offers a significant advancement in the field of sustainable energy management.