Hierarchical Energy Planning and Control of DGs, BESS, and D-STATCOMs in Unbalanced Non-Interconnected Distribution Networks | Zendy

Jhony Andres Guzman-Henao | Zendy; Ruben Ivan Bolanos | Zendy; Luis Fernando Grisales-Norena | Zendy; Oscar Danilo Montoya | Zendy; J.C. Hernandez | Zendy

Open Access

Hierarchical Energy Planning and Control of DGs, BESS, and D-STATCOMs in Unbalanced Non-Interconnected Distribution Networks

Author(s) -

Jhony Andres Guzman-Henao,

Ruben Ivan Bolanos,

Luis Fernando Grisales-Norena,

Oscar Danilo Montoya,

J.C. Hernandez

Publication year - 2025

Publication title -

ieee access

Language(s) - English

Resource type - Magazines

SCImago Journal Rank - 0.587

H-Index - 127

eISSN - 2169-3536

DOI - 10.1109/access.2025.3610528

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

Access to reliable and economically viable electricity services remains a major challenge in non-interconnected zones (NIZs), particularly in developing countries. To address this issue, this study proposes a comprehensive methodology for the simultaneous planning and intelligent operation of distributed energy resources (DERs), specifically distributed generation (DG) units, battery energy storage systems (BESS), and Distribution Static Synchronous Compensators (D-STATCOMs), within unbalanced three-phase distribution systems. The proposed approach is formulated as a mixed-integer nonlinear programming (MINLP) model aimed at minimizing total system costs over a 20-year planning horizon, while accounting for technical and operational constraints under dynamic conditions in both renewable generation and electricity demand. To solve the model, three metaheuristic optimization techniques were implemented: the Chu–Beasley Genetic Algorithm (CBGA), the Vortex Search Algorithm (VSA), and the Black Widow Optimization Algorithm (BWOA). Each algorithm was independently executed 100 times in two representative test scenarios: a 25-bus system based on the distribution network of Leticia, and a 37-bus system derived from the San Andrés Island network. This evaluation enabled a statistical comparison of performance, convergence behavior, and repeatability. Results indicate that BWOA achieved the greatest cost reductions, with savings of 26.9304% and 35.6691% in Leticia and San Andrés, respectively. The selected configurations complied with all voltage and current constraints, while significantly reducing reliance on conventional diesel-based generation. These findings confirm the technical and economic viability of the proposed approach for the simultaneous integration and operation of DERs in isolated power systems.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research