Abstract
Adopting multi-carrier energy systems (MES) is vital for a sustainable and eco-friendly energy future. MES integration connects diverse energy networks, prompting the deployment of large-scale multi-energy storage systems (MESS) to support interconnected multi-energy distribution systems. This paper proposes a bi-level mixed-integer linear programming (MILP) model to optimise MESS sizing and location in a peer-to-peer (P2P) supported integrated energy distribution network with energy hubs. The MESS, operated by an energy storage system operator (ESSO), stores various energy carriers and exchanges energy with electricity, gas, and heating networks, enabling cross-product arbitrage in P2P and day-ahead markets. The bi-level methodology aims to minimise costs (maximise profit) for ESSO and energy hubs at the upper-level while reducing network power losses at the lower level. By applying Karush-Kuhn-Tucker (KKT) optimality conditions and the big-M approach, the bi-level problem transforms into a single-level MILP. Case studies on an integrated energy network based on the 16-bus 33 kV UK generic distribution system validate the proposed model and methodology, demonstrating its effectiveness in integrated energy networks.
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