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 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.

Wheeling is a solution to the complexity of transmission network constructing problem. With the wheeling concept, a power plant owner can deliver electricity to its load without having to construct a transmission network. The owner of the power plant can utilize the transmission network belonging to other entities. The wheeling concept is an interesting thing in terms of increasing current renewable energy penetration. This is due to the construction of the transmission network, which is one of the obstacles in increasing renewable energy penetration. Fairness of wheeling costs is still one important topic. The discussion regarding wheeling costs emphasizes that the costs charged to each party involved can meet the fairness principle, which is in accordance with their respective contributions to the implementation of wheeling. Broadly speaking, research related to wheeling can be grouped into research for developing wheeling cost calculation methods and research for developing wheeling cost allocation methods. The development of the wheeling cost calculation method also includes the development of cost components that can be included in the cost calculation. This study summarizes the discussion of wheeling costs on three aspects, namely calculation methods, cost components, and cost allocation mechanisms.

Power transformer noise is one of the contributors to noise pollution in the environment. The dominant component of power transformer noise is no-load noise, which is a noise that appears when a power transformer is connected to a voltage source and is not connected to other electrical loads. The amount of no-load noise must be predicted at the design stage so that the noise does not exceed consumers’ standards or criteria. In this study, the prediction of no-load noise was conducted involving rated power, magnetic flux density, and geometry factor. Based on the measurement results from industrial testing and the multiple linear regression method, no-load noise prediction formula results with better accuracy are obtained.

Unlike non-variable renewable energy (VRE) generators, VRE generators have site-specific, various, and uncertain characteristics that require different approaches for power wheeling cost calculations. The conventional power wheeling method cannot be used to accommodate the variability and site specificity of VRE. This study aims to develop a power wheeling calculation method that accommodates the variability and site specificity of VRE by comparing the postage stamp and MW mile methods in a multi-period optimal power flow simulation. The impact of line contingencies on the total power wheeling cost is also assessed. The simulation uses a modified IEEE 39 bus system as the test network, with three study cases centered on assessing the impacts of variability, site specificity, and line contingency. Based on the simulation, it is understood that the pivotal power wheeling cost is the line used by power wheeling actors, as there are cheaper and more expensive lines. Therefore, the total power wheeling cost is less affected by variability and more affected by the site specificity of VRE. On the other hand, because of the meshed network being employed as the test case, line contingency results in a lower cost for power wheeling actors to use fewer and cheaper lines.

Power system reliability must be considered in the site planning and operation of electric power system. Referring to “Rencana Usaha Penyediaan Tenaga Listrik PLN 2016-2025” document, the annual growth of Jawa Bali System is 8.4%. The growth of the load will increase the power flow in the 500 kV Jawa Bali System in which affects the index value of composite reliability. This study calculates reliability index value at the hierarchy level II that is EENS in 500 kV Jawa Bali System that describes energy that is not served for one year (MWh/year). The simulation results show that the EENS value of 500 kV Jawa Bali System in 2015 is 18,281.23 MWh/year. The transmission release will affect the EENS value of the composite system. The largest EENS value occurred when scenario 6, the Ungaran-Mandirancan transmission is removed with a 2% load decreament in region 1 and 2 which was 1,238,817.20 MWh/year. While the smallest EENS value occurred when scenario 3, the Kediri-Pedan transmission is removed was 17,870.76 MWh/year. In order to anticipate the growth of the load will be an addition of plants, substation (GITET) and transmission lines to reduce the value of EENS. The smaller value of EENS represent a more reliable system. The EENS value for 2016 is 17,171.62 MWh/year, while EENS 2017 is 13,432.09 MWh/year and EENS 2018 is 11,637.7 MWh/year.