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All Journal Indonesian Journal of Electrical Engineering and Computer Science International Journal of Renewable Energy Development
Wijaya, Prima Trie
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Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering

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Renewable energy in sustainable cities: Challenges and opportunities by the case study of Nusantara Capital City (IKN) Yudiartono, Yudiartono; Santosa, Joko; Fitriana, Ira; Wijaya, Prima Trie; Rahardjo, Irawan; Abdul Wahid, La Ode Muhammad; Siregar, Erwin; Hesty, Nurry Widya; Fithri, Silvy Rahmah; Sugiyono, Agus
International Journal of Renewable Energy Development Vol 13, No 6 (2024): November 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60390

Abstract

This study explores strategies for optimizing energy consumption in Indonesia's New Capital City (IKN) to achieve net zero emissions by 2045, focusing on energy efficiency, sustainable mobility, and renewable energy through the Low Emissions Analysis Platform (LEAP) model. Sustainable cars, such as renewable-energy-powered electric and green hydrogen-powered vehicles, can reduce energy consumption by 43% in 2045 and 33% in 2060, respectively, compared to BAU. GHG emissions per capita will drop 70% in 2045 and 63% in 2060. In NZE scenario, IKN can reach 100% green energy by 2045 with a 4.4 GW solar power plant, a 0.92 GWh BESS, and a full load hour capability of 4 hours. By 2045, 1.1 GW of hydropower and 143 MW of wind power are expected to be utilized. In 2060, hydropower will be 2.8 GW, wind power will be 184 MW, and solar power will be 8 GW with 1.6 GWh of BESS. Lack of legislation, technical expertise, high prices, inadequate grid infrastructure, and renewables shortfalls restrict Indonesia's BESS. Solar installation criteria, subsidies, and off-grid project incentives can all help ease BESS use. Forecasts predict 0.53 GW of rooftop solar PV capacity by 2045 and 3.35 GW by 2060. Net metering and solar tariffs boost rooftop solar system profitability. One ton of green hydrogen production requires 55.7 MWh from a solar power plant. Solar power plant capacity will rise to 0.49 GW by 2045, producing 19,359 tons of green hydrogen, and almost quintuple to 89,594 tons by 2060. Hydrogen generation, storage, transit, and distribution require specific infrastructure due to high capital costs and a lack of networks, yet interest in them is growing.
Enhancing wind energy prediction accuracy with a hybrid Weibull distribution and ANN model: a case study across ten locations in Java Island, Indonesia Fithri, Silvy Rahmah; Hesty, Nurry Widya; Wijayanto, Rudi P.; Pranoto, Bono; Wijaya, Prima Trie; Faqih, Akhmad; Kusuma, Wisnu Ananta; Nurrohim, Agus; Sugiyono, Agus; Yudiartono, Yudiartono
Indonesian Journal of Electrical Engineering and Computer Science Vol 41, No 1: January 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v41.i1.pp180-190

Abstract

Accurate wind speed forecasting is essential for optimizing renewable energy (RE) systems, especially in coastal and island regions with high variability. This study proposes a hybrid predictive model that combines Weibull distribution parameters with artificial neural networks (ANN) to enhance forecasting accuracy. Using ten years of hourly NASA POWER data from 10 locations across Java Island, 24 scenarios were tested with varying combinations of Weibull and meteorological variables. Results demonstrate that incorporating both Weibull shape (k) and scale (c) parameters significantly improves performance, with the best configuration (Scenario 1) achieving a MAPE of 0.44% in Garut. Excluding one or both parameters sharply reduced accuracy, with errors rising up to 35.12%. Beyond technical accuracy, the findings emphasize the practical relevance of Weibull-informed ANN models for energy planning. Reliable forecasts support better wind resource assessment, grid integration, and investment decisions, reducing uncertainties that often hinder wind power deployment. By providing accurate and stable predictions across diverse locations, this approach offers policymakers and planners a robust tool to accelerate RE development and meet national energy targets.
Co-Authors Abdul Wahid, La Ode Muhammad agus Nurrohim Agus Sugiyono Akhmad Faqih Erwin Siregar Fithri, Silvy Rahmah fitriana, ira Hesty, Nurry Widya Joko Santosa, Joko Pranoto, Bono Rahardjo, Irawan Wijayanto, Rudi P. Wisnu Ananta Kusuma yudiartono, yudiartono