Ahmad Fudholi

Work place: National Research and Innovation Agency (BRIN) of Republic of Indonesia

E-mail: a.fudholi@ukm.edu.my

Website: https://orcid.org/0000-0002-9528-7344

Research Interests:

Biography

Ahmad Fudholi is an Associate Professor at the Solar Energy Research Institute (SERI), Universiti Kebangsaan
Malaysia (UKM), Bangi. He earned his Ph.D. in Renewable Energy from SERI-UKM in 2012, following his
Master's in Energy Technology in 2005. His research specialization encompasses solar drying technologies, solar
collectors, photovoltaic/thermal (PV/T) systems, and energy harvesting applications. With an exceptional 11,338
citations (Scopus ID: 57195432490, ORCID: 0000-0002-9528-7344), Dr. Fudholi is internationally recognized
in renewable energy research. He serves as an affiliated reviewer for prestigious Q1 journals including
Renewable & Sustainable Energy Reviews, Applied Energy, and Energy Conversion and Management. His
pioneering work on solar-assisted drying systems for agricultural and marine products has significantly
contributed to sustainable food preservation technologies in Malaysia and Southeast Asia. His research group has
designed and constructed commercial-scale solar dryers and conducted extensive experimental and analytical studies on thermal efficiency and exergy analysis of various solar energy systems.

Author Articles
Identifying Optimal Wind Penetration for Agricultural Distribution Networks: Integrated Power Quality and Reliability Analysis

By Sofyan Sofyan Jasrul Jamani Jamian Norazliani Md Sapari Ahmad Fudholi Muhira Dzar Faraby

DOI: https://doi.org/10.5815/ijem.2026.02.01, Pub. Date: 8 Apr. 2026

This research presents a systematic analysis framework for wind farm integration in scaled IEEE 33-bus agricultural distribution systems (×26.38, representing 98 MW peak agricultural load), focusing on comprehensive power quality, reliability, and economic assessment. The scaled system exhibits baseline voltage violations (24 buses) characteristic of extended radial distribution topologies serving concentrated agricultural loads, consistent with real utility system characteristics in Indonesian agricultural regions. Four wind penetration scenarios (0%, 15%, 30%, 45%) are evaluated using an integrated backward-forward sweep methodology coupling fundamental power flow with empirical harmonic calculations validated against full harmonic load flow analysis (±0.3% accuracy). The analysis employs realistic harmonic injection models for VFD-dominated agricultural loads and full-converter wind turbines, time-domain operational profiles capturing diurnal variations, and revised reliability modeling incorporating protection coordination constraints and battery energy storage system limitations. Results demonstrate that 30% penetration achieves optimal multi-objective performance validated through systematic sensitivity analysis across 10-45% penetration levels: active power loss reduction of 35.5% (210.9 kW to 136.1 kW), harmonic distortion mitigation up to 46.1% THD_V reduction at the wind connection point (1.52% to 0.82%), and realistic reliability improvements of 5.0% SAIDI reduction (8.52 to 8.09 hours/year) accounting for islanding effectiveness constraints (19% successful islanding events with proper battery energy storage and protection infrastructure). The 45% penetration scenario introduces voltage regulation challenges (V_max = 1.052 p.u.) that offset incremental benefits. Economic analysis reveals that system-wide benefits (loss reduction: $670,000/year) substantially exceed agricultural productivity gains ($4,800/year with realistic nonlinear yield models), positioning wind integration as primarily a power quality and efficiency enhancement with supplementary agricultural reliability benefits. Practical implementation requires comprehensive voltage regulation equipment ($2.1-2.5M investment), harmonic filters for VFD-dominated buses ($240,000), and advanced protection schemes for islanding operation ($450,000-$700,000). The integrated analysis framework provides utilities and agricultural operators with quantitative guidance for optimal distributed generation deployment, balancing technical performance, economic viability, and operational constraints.

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