MILP-Based Multistage Co-Planning of Generation–Network–Storage in Rural Distribution Systems

A multistage coordinated expansion-planning framework for distribution systems is developed to jointly optimize investments in the network, distributed generation (DG), and energy storage systems (ESS). Network reinforcements select from multiple feeder and transformer candidates, while DG installations consider conventional and photovoltaic (PV) options. In this study, a set of candidate buses are considered for the installation of PVs and energy storage systems. Therefore, the expansion plan can determine the optimal installation locations and timing of these candidate assets. The objective minimizes total cost in net-present-value terms, covering investment, maintenance, generation, and operating components. Representative hourly load profiles are incorporated to capture ESS dispatch behavior and PV output variability; operating costs are modeled via piecewise linearization. To preserve connectivity and preclude islanding in the presence of DG and ESS, modified radiality constraints are imposed. The formulation is a mixed-integer linear program solvable efficiently by commercial optimizers, and numerical studies confirm the method’s effectiveness.

Authors

Institutions

Publication Details

Journal
Processes
Published
2025-11-29
DOI
https://doi.org/10.3390/pr13123859
Citations
1
Primary Topic
Optimal Power Flow Distribution
Type
article
Field-Weighted Citation Impact
0.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

MILP-Based Multistage Co-Planning of Generation–Network–Storage in Rural Distribution Systems

Liuzhu Zhu, Jun Xu, Tiancheng Shi, Xuli Wang et al.
1 citations
Processes
Optimal Power Flow Distribution
0.73
article

MILP-Based Multistage Co-Planning of Generation–Network–Storage in Rural Distribution Systems

Liuzhu Zhu, Jun Xu, Tiancheng Shi, Xuli Wang, Fan Zhou, Xin Yang, Fei Jiao
article en
1 citations

Abstract

A multistage coordinated expansion-planning framework for distribution systems is developed to jointly optimize investments in the network, distributed generation (DG), and energy storage systems (ESS). Network reinforcements select from multiple feeder and transformer candidates, while DG installations consider conventional and photovoltaic (PV) options. In this study, a set of candidate buses are considered for the installation of PVs and energy storage systems. Therefore, the expansion plan can determine the optimal installation locations and timing of these candidate assets. The objective minimizes total cost in net-present-value terms, covering investment, maintenance, generation, and operating components. Representative hourly load profiles are incorporated to capture ESS dispatch behavior and PV output variability; operating costs are modeled via piecewise linearization. To preserve connectivity and preclude islanding in the presence of DG and ESS, modified radiality constraints are imposed. The formulation is a mixed-integer linear program solvable efficiently by commercial optimizers, and numerical studies confirm the method’s effectiveness.

ProcessesVol. 13(12)
Anhui Jianzhu University (CN), Economic Research Institute (BG)
Openalex Percentile: Top 21%
Optimal Power Flow Distribution
0.73
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.