A distributed multi-objective optimization method for scheduling of integrated electricity and hydrogen systems

Abstract

The growing diversity in energy demand has led to an increasingly intertwined relationship between the electric power system (EPS) and hydrogen energy system (HES). However, these systems are presently managed by entities with distinct interests, resulting in competition and privacy concerns during the scheduling of integrated electricity and hydrogen systems (IEHSs). To address this issue, this paper proposes a multi-objective IEHS scheduling model with the aim of minimizing costs for electricity and hydrogen suppliers, taking into account bi-directional energy transactions between EPS and HES. Furthermore, we present an innovative approach based on alternating direction multiplier method (ADMM) for distributed ξ-constraint optimization. This approach efficiently captures the optimal Pareto frontier while maintaining the privacy of EPS and HES. The proposed methodology is validated on an IEHS composed of an IEEE 33-bus EPS and a 20-node HES. The results demonstrate that no matter how many solution sets, a more uniform pareto front can be obtained than the traditional method. Furthermore, it simplifies the multi-objective optimization problem and effectively protects the privacy of participants at the expense of acceptable solution time.