@Article{ee.2026.081800,
AUTHOR = {Jie Ma, Xichao Du, Chunxin Ma, Yinzhen Wang, Yalei Bai, Youwen Zhang, Xingxu Zhu},
TITLE = {Distributed Coordination Control of PV and Energy Storage in Different Low-Voltage Distribution Networks Considering Multi-Objective},
JOURNAL = {Energy Engineering},
VOLUME = {},
YEAR = {},
NUMBER = {},
PAGES = {{pages}},
URL = {http://www.techscience.com/energy/online/detail/27308},
ISSN = {1546-0118},
ABSTRACT = {A large volume of distributed PV and energy storage resources can be integrated into different low-voltage distribution systems which enhances the local absorption of renewable generation. However, low-voltage segments and medium-voltage distribution infrastructure correspond to different stakeholders, whose operational optimization objectives are often mutually conflicting. This paper introduces a collaborative, distributed framework designed to optimize the operation of integrated medium- and low-voltage networks with significant penetrations of behind-the-meter photovoltaic generation and storage. The formulated problem incorporates standard power flow constraints. A unified multi-objective optimization model is formulated with four objectives: (i) minimizing the overall operational cost of the distribution network, (ii) minimizing load rate disparities among transformer zones, (iii) minimizing the operational cost of energy storage systems, and (iv) maximizing photovoltaic (PV) utilization. The multiple objectives are aggregated using an entropy-based weighting method to obtain a scalar optimization problem. The resulting problem is then solved using the Alternating Direction Method of Multipliers (ADMM), enabling each network layer to solve its subproblem independently. The coordination mechanism involves the medium-voltage network broadcasting iterative price signals to guide adjustments in distributed energy resource outputs at the low-voltage level. This approach achieves system-wide multi-objective optimization with minimal exchange of operational data at the network boundary. Case studies using a modified IEEE 33-7 bus test system validate the practical efficacy and computational feasibility of the proposed distributed strategy.},
DOI = {10.32604/ee.2026.081800}
}