A hybrid optimization approach based on human memory optimization algorithm and differential evolution for optimal DG placement and sizing under diverse load models and loading conditions

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10259312" target="_blank" >RIV/61989100:27240/25:10259312 - isvavai.cz</a>

Alternative codes found

RIV/61989100:27730/25:10259312

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S2772671125002554" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2772671125002554</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.prime.2025.101139" target="_blank" >10.1016/j.prime.2025.101139</a>

Result language

angličtina

Original language name

A hybrid optimization approach based on human memory optimization algorithm and differential evolution for optimal DG placement and sizing under diverse load models and loading conditions

Original language description

The transformation of passive distribution networks into microgrid-oriented active systems enables the integration of diverse distributed generation (DG) units. However, the benefits of DGs, such as improved voltage profile, reduced losses, and enhanced reliability, are not fully realized without optimal placement and sizing, especially under varying loading conditions. With this motivation, the present study proposes a novel hybrid optimization technique, termed HMOADE, which synergistically combines the Human Memory Optimization Algorithm (HMOA) and Differential Evolution (DE) to address the Optimal Distributed Generation Placement and Sizing Problem (ODGPSP). The algorithm leverages human memory-inspired learning, retention, and recall mechanisms alongside DE&apos;s robust global search capabilities. Furthermore, the approach introduces adaptive parameter tuning and dual-phase search strategies to enhance both exploration and exploitation during the optimization process. The ODGPSP is formulated as a single-objective problem, focusing on minimizing active power loss, subject to operational constraints such as voltage limits, line capacities, DG generation bounds, and power balance equations. The study incorporates multiple static load models, constant power (CP), constant current (CI), constant impedance (CZ), and ZIP (composite), to realistically reflect real-world demand characteristics under light, full, and heavy loading scenarios. A cost-benefit analysis is also performed, assessing the reduction in energy loss and the costs of DG generation. The proposed HMOADE algorithm is validated on IEEE 69-bus and IEEE 85-bus radial distribution systems, demonstrating its robustness, accuracy, and computational efficiency. Simulation results reveal significant improvements in voltage profile, reductions in active power losses (up to ∼90 %), and substantial cost savings, with Type-III DGs showing the most favourable performance. A comparative analysis with higher accuracy, reduced computational time, simplified formulation, and consistency confirms the superiority of HMOADE, particularly in handling complex, nonlinear, and load-sensitive scenarios, over existing techniques. © 2025 The Author(s)

Czech name

—

Czech description

—

Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

—

OECD FORD branch

20200 - Electrical engineering, Electronic engineering, Information engineering

Project

<a href="/en/project/TN02000025" target="_blank" >TN02000025: National Centre for Energy II</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

e-Prime - Advances in Electrical Engineering, Electronics and Energy

ISSN

2772-6711

e-ISSN

2772-6711

Volume of the periodical

101139

Issue of the periodical within the volume

12/2025

Country of publishing house

GB - UNITED KINGDOM

Number of pages

54

Pages from-to

1-54

UT code for WoS article

—

EID of the result in the Scopus database

2-s2.0-105025546958