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.

The rapid development of RES technology produces cheaper and compact devices. This condition has attracted the household to install the RES devices on their premises. Hence, the household has changed from the passive electricity consumer into the active prosumer. The active prosumer not only consumes the electricity but also have the capability to produce electricity. However, the electricity produced by RES devices is intermittence and unstable. Moreover, the behavior of the inhabitants of the prosumer also changes over time. Hence, a smart energy management system is needed by the prosumer to maintain the balance of its electricity demand and supply. In this paper, we explore the integration of the Machine-learning based on the prosumer's EMS to address the uncertainty problem in the prosumer.

Indonesia is a country that has tropical climate with average temperature vary in between 27°C until 37°C. BLDC motor industry is not common in Indonesia so that has to be imported from another country mostly subtropical countries. BLDC motor is built according to subtropical characteristics. Therefore, BLDC motor performance is changing in Indonesia due to the temperature differences. The following methods are used in the study: laboratory experiment and field test using electrical vehicle. The temperature in laboratory is in range between 23°C up to 55°C. However the field temperature varies from 27.7°C and 34, 2°C. The increasing temperature inside the motor in laboratory and field experiments conducts modification of BLDC motor parameters. The rising motor temperature degrades the current and torque of motor, but increasing the rotation velocity of the motor.

Government of Indonesia have target to achieve 23% share of renewable energy in National energy mix by 2025. As a part of the target, solar energy needs to contribute as much as 6.5 GW installed capacity in 2025. Therefore, Government of Indonesia develop policy to promote renewable energy, especially solar energy. In 2013, Ministry of Energy and Mineral Resources launched High Tariff Regulation for Solar PV Power Plant. The 5 MW Kupang Solar PV Power Plant is one of the result of the policy. It was the biggest Solar PV Power Plant project in Indonesia. This project located in Oelpuah District, Kupang Regent, in East Nusa Tenggara. This Solar PV Power Plant consist of 2,208 units of 230 Wp solar PV module manufactured by state owned company namely PT. LEN Industry and 250 units of grid inverter manufactured by SMA. Started operation in March 2016, this Solar PV Power Plant already contribute in national renewable energy share. By using the recorded data, evaluation of power plant performance conduct by using Performance Ratio calculation. During March 2016 to December 2019, the Plant have produced 25.3 GWh of electricity. Based on IEC 61724 methodology, daily Performance Ratio is between 0.7 and 0.9. In additionally, economic analysis of this Plant was calculated based on realization of project income. It shows that the investment will be returned by 8th year of the Plant operation.

The modern overhead lines with High Capacity Low Sag (HCLS) conductors can be operated at higher current carrying capacity. The main advantage of HCLS conductors is the special design of operating conditions, which cause the transformation of the mechanical pull load from the conductors to the reinforcing core. This transformation is called “knee point temperature”. This study aims to determine the knee point temperature and the effect on sag HCLS conductors. The simulation will be conducted on the HCLS conductors, namely ACCC/TW LISBON (310), which stretches between a span of 100meters. The electrical loading of conductors is gradually giving until a temperature of 180oC is reached. From the simulation results, we can determine the knee point temperature of the ACCC/TW LISBON (310) conductor is around 60-62oC. The value of the sag after the knee point temperature tends to be stable even though the ampacity loading is increased.