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Title: Optimal placement and sizing of energy storage systems in distribution networks: a stochastic optimisation framework

Authors: Peng Wang; ASileng; Jiadong Zhao; Zhu Miao; Jinxiu Hou; Xiaomeng Yan; Jun Guo

Addresses: Inner Mongolia Electric Power Economics and Technology Research Institute, Hohhot, Inner Mongolia, 010000, China ' Inner Mongolia Power (Group) Co., Ltd., Hohhot, Inner Mongolia, 100020, China ' Inner Mongolia Electric Power Economics and Technology Research Institute, Hohhot, Inner Mongolia, 010010, China ' China Electric Power Planning and Engineering Institute, Beijing, 100120, China ' China Electric Power Planning and Engineering Institute, Beijing, 100120, China ' Inner Mongolia Electric Power Economics and Technology Research Institute, Hohhot, Inner Mongolia, 010000, China ' Inner Mongolia Electric Power Economics and Technology Research Institute, Hohhot, Inner Mongolia, 010000, China

Abstract: This study proposes a scenariobased stochastic optimisation framework for the optimal placement and sizing of energy storage systems (ESS) in distribution networks. The model integrates ICTenabled data acquisition and communication infrastructures to process realtime load and renewable energy data. A complete mixedinteger linear programming (MILP) formulation is developed, incorporating power balance, ESS dynamics, and network operational constraints across multiple uncertainty scenarios. The proposed method is validated on a real distribution network case study, demonstrating operational cost reductions, improved grid stability, and enhanced renewable energy utilisation compared with deterministic approaches.

Keywords: energy storage systems; ESS; distribution networks; stochastic optimisation; mixed-integer linear programming; MILP.

DOI: 10.1504/IJICT.2026.153628

International Journal of Information and Communication Technology, 2026 Vol.27 No.50, pp.40 - 69

Received: 19 Sep 2025
Accepted: 11 Feb 2026
Published online: 18 May 2026 *