Most inhabited islands in Indonesia are powered by expensively known diesel generators and isolated from the primary grid due to either geographical or economic reasons. Meanwhile, the diesel generator can be combined with a photovoltaic (PV) system and Battery Energy Storage (BES) system to form a hybrid power generation system to reduce the energy cost and increase renewable energy penetration. For this, proper sizing of each power generation component is required, one of which is influenced by the applied control strategy. This paper proposes an optimal BES dispatch (OBD) control strategy that optimizes the power generation components’ sizing. The method examines the shortcomings of the other popular control strategies, such as load following, cycle charging, or combination. The optimization objectives are to minimize the Levelized Cost of Energy (LCOE) and maximize the renewable energy (RE) penetration, which can be achieved by prioritizing the BES to supply the load over other available generations and charge the BES every time the generator operates. The proposed method is implemented at two different systems with different load profiles. As a result, the proposed control strategy provides lower LCOE while maintaining higher RE penetration than the other control strategies in both locations.

Renewable energy sources have become one of the important roles for sustainable energy development. One of the promising mechanisms to deploy renewable energy is through a Virtual Power Plant (VPP), which can integrate various distributed renewable energy resources into a single controllable and deployable entity. This paper examines the opportunity for VPP adoption in Indonesia, which investigates the minimum implementation criteria, provides a gap analysis for VPP implementation, and proposes recommendations for VPP implementation in Indonesia. The implementation criteria are obtained from the literature review, including the lessons learned from other countries, and categorized into four aspects: regulatory, technical, economic, and social. The gap analysis is performed by evaluating the current state of Indonesia’s utility network in correlation with the VPP minimum implementation criteria and then provides a scoring matrix for each criterion. Lastly, the recommendations are arranged to narrow these gaps, organized into ten key focus points, and divided into four phases, initiation, preparation, piloting, and deployment, across a ten-year timeframe.

Integrating renewable energy through inverter-based generators has decreased the power system’s inertia. Reduced inertia may lead to frequency instability during power imbalance disturbances, particularly in an isolated power system with limited inertia. The Battery Energy Storage System (BESS) and a virtual inertia (VI) emulation control system have become popular to mitigate this issue. Nonetheless, the BESS utilization for VI emulation is highly dependent on the availability of BESS capacity, which may affect the energy cost. Therefore, developing a VI emulation control strategy that requires less energy and can recover the state of charge (SoC) to a desired level to optimize BESS utilization is required. This paper proposes a VI control with an SoC recovery strategy through coordination with the generators’ secondary frequency control. Instead of relying on the frequency, such as in the conventional approach, the controlled signal of the generators’ secondary frequency control also includes the VI power and BESS SoC. Hence, the generators can contribute to lowering the VI required energy and recovering the BESS SoC. The results show that the proposed method outperforms the conventional method by requiring around 36% lower energy and the ability to maintain the BESS SoC.

The accurate estimation of solar radiation is crucial for optimizing solar energy deployment and advancing the global energy transition. This study pioneers the development of a hybrid model combining Recurrent Neural Networks (RNNs) and the Weather Research and Forecasting (WRF) model to estimate solar radiation in tropical regions characterized by scarce and low-quality data. Using datasets from Sumedang and Jakarta across five locations in West Java, Indonesia, the RNN model achieved moderate accuracy, with R² values of 0.68 and 0.53 and RMSE values of 159.87 W/m² and 125.53 W/m², respectively. Additional metrics, such as Mean Bias Error (MBE) and relative MBE (rMBE), highlight limitations due to input data constraints. Incorporating spatially resolved GHI data from the WRF model into the RNN framework significantly enhanced accuracy under both clear and cloudy conditions, accounting for the region’s complex topography. While the results are not yet comparable to best practices in data-rich regions, they demonstrate promising potential for advancing solar radiation modeling in tropical climates. This study establishes a critical foundation for future research on hybrid solar radiation estimation techniques in challenging environments, supporting the growth of renewable energy applications in the tropics.

Accurate estimation of global horizontal irradiance (GHI) is essential for optimizing photovoltaic (PV) systems, particularly in regions with distinct climatic characteristics. Geostationary satellites, such as GK2A and COMS, provide consistent and spatially extensive data, offering a practical alternative to ground-based measurements. However, the performance of semi-empirical GHI models has been sparsely evaluated across diverse geographic zones. This study aimed to conduct a comparative analysis of four semi-empirical models—Beyer, Rigollier, Hammer, and Perez—applied to two contrasting locations: Seoul, South Korea (temperate) and Jakarta, Indonesia (tropical). Using satellite-derived cloud indices and ground-based pyranometer data, model performance was evaluated via RMSE, MBE, and their relative metrics. Results indicate that the Hammer model achieves the best performance in Seoul (RMSE: 103.92 W/m²; MBE: 0.09 W/m²), while the Perez model outperforms others in Jakarta with the lowest relative RMSE of 58.69%. The analysis outlines the limitations of transferring models calibrated in temperate climates to tropical settings without regional adaptation. This study provides critical insights for improving satellite-based GHI estimation and supports the development of region-specific forecasting tools essential for expanding solar infrastructure in Southeast Asia.

The need for electricity that continues to increase requires increasing electricity generation capacity and building comparable transmission and distribution systems and a smarter system for dealing with increasingly complex forms of electricity production and consumption. Renewable energy, such as solar and wind, are ones of the solutions to increase electricity generation capacity but has problems with its intermittent and other grid related problems, which can be solved by using Power Electronic Interfaces (PEIs), i.e., Battery Energy Storage Sytems or converter of renewable energy sources (RES), to keep the quality and stability of the power system. However, the increasing penetration rate of RES, which gather several different types of energy sources and generations system, in an electrical power system will make need a more complex system control. Objective of this research was to study the effects of RES integration on frequency dynamics in microgrid to further develop and increase its stability and quality by modeling and simulation using MATLAB/Simulink software.