In 2019, Indonesia’s electricity consumption exceeded 278 TWH, or about 1.08 MWh/capita. This value shows a considerable increase in electricity consumption which has doubled in just a decade. Previous studies have shown that the proportion of electricity consumption used for lighting needs is correlated to the country’s GDP. This is generally around 20 to 50% of electricity production but can go up to 86% in the case of Tanzania. Indonesia is the 4th country in the world in terms of population and its lighting market as well as its lighting-related energy consumption has a strong impact on several levels: societal, environmental but also economic and energy. Having a knowledge of the lamps used by the Indonesian people is therefore particularly interesting and important, in particular in the context which presents a great societal diversity but also in a context of energy saving. Indonesia is an archipelagic country made up of 5 large islands and over 17,000 small islands with widely varying levels of population density. This island geography leads Indonesia to face challenges in the distribution and production of electrical energy, which affects the use of lamps in various types of regions. The overview of this study was done by collecting data from various sources, especially BPS (Biro Pusat Statistik/Statistic Center Bureau of Indonesia), CLASP (an NGO for clean energy), the Ministry of Energy and Mineral Resources of Indonesia (ESDM), PLN (Indonesian Electrical Company), etc. The data obtained from these sources provides several descriptions of general lighting conditions in Indonesia viewed from several angles, such as growth of lamp market, use of lamp types, percentage of use of lamps with energy saving (ESL), etc. Considering that Indonesia has various regional characteristics, in this study, the survey of a total of 394 respondents was conducted on the use of lamps by creating regional categories based on electrical conditions, power consumption, and electricity per capita, among others. The categories of areas observed fall into 5 types based on their population and geography: large cities, small towns, rural/village areas, islands and remote areas. The results of compiling data from these various sources show that the types of lamps used by Indonesians follow the lighting trend in the world. The use of LED lamps has a utilization percentage of around 52%, much higher than other types of lamps such as CFL, fluorescent or incandescent. Based on the survey conducted, it is known that the widely used LED power is between 1 and 10 watts with a usage time of 8 to 12 h per day. In the next few years, it is estimated that the use of LEDs in Indonesia will increase as the government has prepared various regulations and policies related to energy saving, one of which relates to lighting.

Intentional physical attacks on a wide-ranging transmission network may result in load shedding or outages in the electrical grid. This vulnerability can be mitigated through modern transmission expansion planning that takes into account grid risk and renewable energy penetration. This research introduces a novel approach to optimally reduce the network’s vulnerability to intentional transmission attacks by combining game-theoretic sequential attacker-defender model analysis with power flows and probabilistic risk analysis. This innovative method allocates defender resources based on location and size optimization under a budget constraint. The defender or network planner utilizes renewable energy technologies, such as photovoltaics and batteries, as non-wire expansion alternatives based on their power system reliability and environmental friendliness. This research was implemented on three modified IEEE bus test systems: the 14-bus, 39-bus, and 118-bus test systems. In Case 1, an investment in photovoltaics outperforms Case 2, where the defender integrates photovoltaics with batteries. In the 14-bus scenario of Case 1, the network vulnerability risk is reduced from 112.3 MW to 58.78 MW; in the 39-bus scenario, it decreases from 298.78 MW to 79.9 MW, and in the 118-bus scenario, it drops from 48.3 MW to 29.81 MW. The study demonstrates that the optimal allocation of defender resources can reduce the risk in exponential cost models. Integrating renewable energy at the grid scale will be crucial for the future expansion of power grids.

In Indonesia, the power generation sector is the primary source of carbon emissions, largely due to the heavy reliance on coal-fired power plants, which account for 60% of electricity production. Reducing these emissions is essential to achieve national clean energy transition goals. However, achieving this initiative requires careful consideration, especially regarding the complex interactions among multiple stakeholders in the Indonesian electricity market. The electricity market in Indonesia is characterized by its non-competitive and heavily regulated structure. This market condition often requires the PLN, as the system operator, to address multi-objective and multi-constraint problems, necessitating optimization in the generation dispatch scheduling scheme to ensure a secure, economical, and low-carbon power system operation. This research introduces a multiparadigm approach for GS optimization in a regulated electricity market to support the transition to clean energy. The multiparadigm integrates multi-agent system and system dynamic paradigms to model, simulate, and quantitatively analyze the complex interactions among multiple stakeholders in the Indonesian regulated electricity market. The research was implemented on the Java–Madura–Bali power system using AnyLogic 8 University Researcher Software. The simulation results demonstrate that the carbon policy scheme reduces the system’s carbon emissions while increasing the system’s cost of electricity. A linear regression for sensitivity analysis was conducted to determine the relationship between carbon policies and the system’s cost of electricity. This research offers valuable insights for policymakers to develop an optimal, acceptable, and reasonable power system operation scheme for all stakeholders in the Indonesian electricity market.

This study focuses on analyzing switching transients in the upcoming 500 kV Java-Bali Connection (JBC) hybrid OHL and submarine cable project using DIgSILENT PowerFactory software, based on a realistic power system model. Distributed-parameter models with constant parameters of the Bergeron model are utilized. Analysis of the traveling wave effect on the line is conducted, and the integration time step based on the time of the traveling wave is carefully selected. Statistical distributions of energization are produced by varying the circuit configuration and system short-circuit power. It is found that the Switching Withstand Voltage (SWV) during the energization process remain below 1175 kV. The probability distribution is fitted to a normal distribution, with the skewness and kurtosis shown to be skewed to the right and having a lower peak than that of the normal distribution, respectively. When a three-phase short-circuit at the line breaker is induced, the rate of rise of recovery voltage (RRRV) exceeds the IEC standard envelope if only one circuit is operating. In this contribution, switching analysis during no-load energization and de-energization in the planning stage of the mixed OHL-submarine cable is examined.

By the Electric Vehicle penetration, there will be additional new loads on the customer service transformer side. This paper will discuss the impact of Electric Vehicle penetration on the peak load on the 100 KVA Residential Area Transformer and also offers three strategies for charging the Electric Vehicle battery to reduce the peak load on these transformers. In this study, the Residential Area Transformers will be penetrated by the Electric Vehicle loads in stages 5, 10, 15, 20, 25, 30 EVs. This article will observe the impact of the penetration on the peak load of the transformers. There is a quite high increase in the penetration of EVs of 15, 20, 25, and 30 EVs. With the penetration of 30 EVs, the peak load on the transformers will increase to 123.6 KVA. This means that the 30 EV penetration exceeds the 100 KVA Transformer Residential capacity limit. Of the three EV charging strategies tested, with sequences per group of 4, 3, and 2 EV, it has been found that the best charging strategy to reduce the peak load of the transformer by shifting the peak load to the valley is charging strategy 2 with sequencing per group of 2 EV. By implementing the charging strategy 2 with sequencing per 2 EV groups, the peak EV load on uncontrolled charging is reduced from 123.6 KVA to 66.03 KVA, and there is a decrease in peak load by 46.59 percent.