Active distribution network operation optimization problem for hybrid energy storage systems containing abandoned mine pumped storage-battery storage: an improved artificial protozoa optimization algorithm

The high penetration of Distributed Renewable Energy sources (DRES) poses significant challenges to the economic and secure operation of Active Distribution Networks (ADNs). To address this challenge, this paper proposes a two-stage optimization framework based on the decoupling of economy and security. This framework, for the first time, features a day-ahead dispatch model that co-optimizes an AMPS-BESS hybrid energy storage system with various grid regulation devices. To efficiently solve the resulting complex Mixed-Integer Non-Linear Programming (MINLP) problem, an improved Artificial Protozoa Optimizer (MFDB-APO) is proposed, whose superior general-purpose optimization capability has been validated on the CEC2017 and CEC2020 benchmark suites. A case study on a modified IEEE 33-bus system demonstrates that the proposed methodology, compared to the baseline case, reduces the system operating cost, equivalent load fluctuation, node voltage deviation, and network loss by 8.43 %, 85.78 %, 35.76 %, and 63.03 %, respectively. The findings confirm that the synergistic application of the two-stage framework and the MFDB-APO algorithm provides an efficient solution for the intelligent operation of ADNs with high renewable penetration that is economical, secure, and practical.