A multi-period MILP model for optimal integration of battery energy storage systems and distributed generation in power distribution systems

Optimal planning of distributed energy resources (DER), such as Battery Energy Storage Systems (BESS) and photovoltaic distributed generation (PV-DG), is essential to enhance the efficiency, operational performance, and sustainability of power distribution systems (PDS). However, DG placement often...

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Bibliographic Details
Published in:Results in engineering Vol. 27; p. 106806
Main Authors: Salazar Vanegas, Carlos E., Gallego Pareja, Luis A., Gómez Carmona, Oscar
Format: Journal Article
Language:English
Published: Elsevier B.V 01.09.2025
Subjects:
Battery energy storage systems
Distributed generation
Mix integer linear programming model
Power distribution systems
Battery energy storage systems
Distributed generation
Mix integer linear programming model
Power distribution systems
ISSN:2590-1230, 2590-1230
Online Access:Get full text
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Summary:Optimal planning of distributed energy resources (DER), such as Battery Energy Storage Systems (BESS) and photovoltaic distributed generation (PV-DG), is essential to enhance the efficiency, operational performance, and sustainability of power distribution systems (PDS). However, DG placement often depends on investor decisions and local constraints, sometimes lacking system-level coordination. Prior studies have primarily employed metaheuristic approaches, which, while flexible and widely used, do not provide formal convergence guarantees and therefore may not ensure a globally optimal solution. This paper proposes a novel mixed-integer linear programming (MILP) model for the simultaneous optimal placement, sizing, and hourly operation of BESS and PV-DG in the PDS. A key contribution of this work is the incorporation and linearization of voltage and current constraints, enabling the formulation of a rigorous MILP framework that ensures global optimality. The model also incorporates multi-period optimization and seasonal variations in load and generation. The optimization is implemented using AMPL and is solved with CPLEX, providing a reliable and scalable solution framework. The proposed MILP model is validated on 33-bus, 69-bus, and practical 136-bus test systems. The results demonstrate significant reductions in energy losses (up to 43.6%), peak demand (up to 30.8% in the 69-bus), and annual energy costs (up to 53.9%) in the 69-bus test system. Furthermore, the model achieves superior computational efficiency and reproducibility compared to metaheuristic methods. In conclusion, the MILP-based strategy offers a robust and computationally efficient approach to integrate BESS and PV-DG into modern distribution systems. Facilitates optimal coordination of distributed energy resources, improves overall system performance, and paving the way for future scalable applications in larger networks. [Display omitted] •Mixed-Integer Linear Programming (MILP) model for planning of BESS and PV-DG.•Multi-period optimization considers daily active and reactive power demand curves.•The MILP model ensures global optimality, surpassing traditional non-linear methods.•The MILP model is validated on the 33-bus, 69-bus, and 136-bus test systems.•The MILP model can be implemented using commercial optimization software.
ISSN:2590-1230
2590-1230
DOI:10.1016/j.rineng.2025.106806