In recent years, the goal of lowering emissions to minimize the harmful impacts of climate change has emerged as a consensus objective among members of the international community through the increase in renewable energy sources (RES), as a step toward net-zero emissions. The drawbacks of these energy sources are unpredictability and dependence on nature, leading to unstable load power supply risk. One way to overcome instability in the power supply is by using a battery energy storage system (BESS). Therefore, this study provides a detailed and critical review of sizing and siting optimization of BESS, their application challenges, and a new perspective on the consequence of degradation from the ambient temperature. It also reviews advanced battery optimization planning that considers battery degradation, technologies, degradation, objective function, and design constraints. Furthermore, it examines the challenges encountered in developing the BESS optimization model and evaluates the scope of the proposed future direction to improve the optimized BESS, especially its battery.

The increasing integration of renewable energy sources is reshaping power systems from centralized, synchronous generator-based architectures to more inverter-dominated and decentralized architectures. This transition, however, results in a significant reduction in system inertia, posing challenges to frequency stability. To address this issue, various control strategies have been proposed to emulate the inertial response of traditional synchronous generators—commonly known as virtual inertia. This study reviews inverter-based virtual inertia and related control strategies that replicate or extend synchronous generator dynamics, covering five main approaches: droop control, synchronverters, virtual synchronous generators (VSGs), the swing equation-based approach, and data-driven grid-forming (GFM) methods. While all approaches enhance frequency nadir and RoCoF, they differ in complexity, robustness, and adaptability. Droop control offers simplicity but lacks true inertia support, whereas synchronverter and swing equation-based controls provide closer emulation of synchronous behavior for grid-forming or islanded systems. VSG offers a more practical grid-following solution, and data-driven GFM introduces adaptability through learning-based mechanisms. Overall, this study contributes to a comprehensive understanding of how these control strategies can be implemented through inverter control to maintain frequency stability in renewable-dominated power systems.

Energy sustainability has become one of the main issues in power system planning in the Indonesian archipelago system, which has many small, isolated systems. For that purpose, green and sustainable generation expansion planning (GEP) procedures based on local energy resources is required. GEP is a necessary procedure for fulfilling electricity demand, which determines the generating units to be installed within a specified time horizon with minimal total costs as the objective function. This study uses GEP considering the interconnection option among the existing small scattered generation systems in Maluku: the isolated Ambon, Seram, Haruku, and Saparua systems. With interconnection, the utilization of local renewable energy sources would be increased, especially biomass, which has abundant potential in these areas. The GEP was simulated in the PLEXOS environment using mixed-integer linear programming (MILP). For comparison purposes, there were interconnection and isolated system scenarios. The results showed that the interconnection system would have a high share of a renewable energy source (RES) of up to 54% in 2050, most of which is biomass as the primary local energy source. The interconnection system scenario met the LOLP criteria and had a lower reserve margin and total costs than the isolated scenario, with USD 773.7 million.

The use of renewable energy is becoming the most suitable solution to meet the growing energy needs in developing and developed countries. This is because fossil fuel-based energy sources significantly contribute to greenhouse gas emissions. As an alternative solution to fossil fuel, microgrids with hybrid renewable energy sources are being built to electrify isolated locations where distribution network expansion is not practical or cost-effective. Despite this, hybrid renewable energy systems face numerous challenges concerning resource variability, load demand assessments, and economic trade-offs to guarantee the effective and sustainable sizing of resources. This study aimed to determine the ideal hybrid using solar, diesel, hydro, and battery energy sources to address the load requirements of Anggi District, Indonesia. The experiment was carried out using HOMER software to size the main electricity components, analyze economics, and estimate greenhouse gas emissions. The best model was evaluated using the Net Present Cost (NPC), the Cost of Energy (COE), the Renewable Fraction (RF), excess energy, and fuel cost. A detailed sensitivity analysis was also conducted using fossil fuel costs, as well as flow, discount, and inflation rates to examine model variations. Different configurations of hybrid renewable energy systems, such as Diesel Generator (DG) Only, DG/Hydro, DG/Photovoltaic (PV)/Battery, DG/Hydro/PV/Battery, and PV/Hydro/Battery, are examined and contrasted through the optimization of diverse energy sources. The results showed that the off-grid DG/Hydro/PV/Battery hybrid system was the most technically, economically, and environmentally optimal configuration, comprising 450 kW DG, 157 kW hydro, 15.7 kW PV, and 7 battery storage. The system had the lowest value across all variables, including RF of 67.7%, NPC, and COE at $6.30M and $0.311/kWh. It also emitted 4,372 kg/year less than the DG system, serving as a greener system. Hybrid Renewable Energy System (HYRES) improved energy access, jobs, education, public health, economic, and social fairness. In conclusion, the proposed hybrid system showed the potential to be implemented in rural areas as well as in any location worldwide.

The increased use of electrical energy will encourage the installation of more power transformers in residential areas as well as in industrial areas. Each power transformer, in its operation, will generate noise that can interfere with comfort and, at some level, cause health problems. The design of the power transformer currently focuses on optimizing its economic side, so noise has not been considered at this design stage. This research is about optimizing the low noise transformer design. The main goal is to obtain a low noise power transformer with low production costs. The method used in this optimization is particle swarm optimization with a multi-objective function. The objective function consists of the minimization of load noise, core weight, and winding weight. In this study, 11 optimized variables were used. Some variables that are optimized must be in the form of integers. Therefore, the optimization process needs a mechanism for mapping variables. The results showed that a low noise power transformer could be designed at optimal cost. Design validation was performed analytically and numerically with COMSOL software. The optimization results showed a decrease in load noise, core, and winding weight by 0.86 dB, 2.12%, and 47.46%, respectively. The results of this optimization are better than the designs used regularly in the industry.

For generating electricity, direct-drive wave energy converters (WECs) with linear permanent magnet generators (LPMGs) have advantages in terms of efficiency, simplicity, and force-to-weight ratio over WEC with rotary generators. However, the converter’s work under approaching-real wave conditions should be investigated. This paper studies the performance of a pico-scale WEC with two different LPMGs under unidirectional long-crested random waves. Different significant wave heights (using data in the Southern Ocean of Yogyakarta, Indonesia) and peak frequencies are tested. The JONSWAP energy spectrum is used to extract the wave elevations, while the MSS toolbox in MATLAB Simulink is employed to solve the floater’s dynamic responses. Next, the translator movements are extracted and combined with the flux distribution from FEMM simulation and analytical calculation, and the output powers are obtained. An experiment is conducted to test the output under constant speed. The results show for both designs, different tested significant wave height values produce higher output powers than peak frequency variation, but there is no specific trend on them. Meanwhile, the peak frequency is inversely proportional to the output power. Elimination of the non-facing events results in increasing output power under both parameters’ variation, with higher significant wave height resulting in a bigger increase. The semi iron-cored LPMG produces lower power loss and higher efficiency.