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Charge scheduling can mitigate against issues arising from excessive electric vehicle (EV) charging loads and is commonly implemented using time-of-use pricing. A charge scheduling strategy to suit vertically structured power systems without relying on time-of-use pricing has not yet been reported, despite being needed by industry. Therefore, a novel charge scheduling strategy to meet this need is proposed in this paper. Key aspects include the provision of a decision-making framework that accommodates for the considerations of transmission and distribution network operators, and the allowance for dynamically changing charging loads through timely forecast updates with reduced communication requirements. A case study based on the Indonesian Java-Bali power system is undertaken to demonstrate the strategy’s effectiveness. Different and realistic EV uptake scenarios are considered, using probabilistic modeling, survey work, and a Monte Carlo modeling approach. Even under slow EV charging conditions case study results show assets are overloaded and high electricity production costs are incurred. These are alleviated through adopting the proposed strategy.

Utilizing energy storage systems equipped with virtual/synthetic inertia control has emerged as one of the solutions to solve low inertia issues in power systems with massive penetration of renewables. However, while the aspect regarding the control of the synthetic inertia control has been widely investigated, the optimal placement of synthetic inertia control is rarely investigated. Therefore, the optimal placement of energy storage system with synthetic inertia control based on swarm‐based mean‐variance mapping optimization is proposed. The performance of the proposed method is tested by considering several cases, both single and multiple contingencies. By utilizing the proposed method, the optimal placement of energy storage system equipped with synthetic inertia control could be obtained, in which the resulting frequency response is better compared to randomly placed ones. The proposed method could also be applied by considering multiple contingencies in different locations. Furthermore, the resulting fitness values for different independent optimization repetitions for various study cases are consistent, leading to the efficacy to be applied in the actual power system planning.

This paper aims to evaluate the photovoltaic (PV) nanogrid implementation and its risk for a project at a remote location. Unlike the normal approach, this approach is based on a discontinuity project. The main advantage of the model is the simplicity to compute the expected lifetime and display the reliability curve. The reliability is calculated using state space equation and a quantitative approach evaluates the risk of PV nanogrid scenarios based on costs. The MATLAB/Simulink simulates the scenarios including the basic scenario of a PV system that is a PV nanogrid consisting of a PV array and inverter, scenario 1 that is a PV nanogrid with a battery system, scenario 2 is an extension of scenario 1 with a battery repair, and scenario 3 is a PV nanogrid connected to the grid. The result indicates that adding a battery system increases the reliability and the expected lifetime of the system, and the battery system’s maintenance makes it higher. Scenario 3 shows high reliability and a longer expected lifetime. The risk matrix shows the position of reliability and its impact on each scenario. This work can be used in practice as an objective assessment to electrify frontier, remote, and disadvantaged (3T) areas beside levelized cost of energy (LCOE).

This paper will be focused on designing Special Protection System (SPS) for Batam-Bintan System in Indonesia. This study will conduct a method to design event-based and parameter-based SPS based on identified vulnerable points. The designed algorithm will be tested to the 24 hours load curve in a weekday and a weekend. Frequency Security Index (FSI) will be a main indicator to compare performance between SPS and existing protection scheme. From calculation, there are identified 8 contingency points that have a significant difference in vulnerability index (Vu) when compared to the Vu value during the normal operating conditions. After design process of SPS based on power balance between generation and load is conducted, the suitable algorithm for the loss of generator block is event-based and for the loss of lines is parameter-based. This paper also conducts a method to find an arming value for parameter-based algorithm based on frequency response after disturbance. From the simulation results, SPS could improve the FSI value of Batam-Bintan System for each vulnerable test point. It can be concluded that SPS could accelerate the power balance in the system, thus frequency stability can be achieved faster.

System reliability is the main factor that is maintained in the continuity of the electricity system operation. In the event of a major disruption to the power system, a defense scheme can work quickly and safely to restore the system. Existing defense systems and disruptions that can lead to instability consist of UFLS, OGS, and other schemes. This scheme describes the design of the Centralized Remedial Action Scheme for the existing scheme implemented in the defense scheme in the Batam-Bintan system. The CRAS scheme will use the HYPERSIM simulator with OPAL-RT as Hardware In The Loop to perform real-time simulations, the SEL-3530 RTAC as the main processor for the RAS algorithm, and SEL 751 as the mitigation relay IED to send digital output CB commands back to HYPERSIM, where all This security equipment will be connected using an ethernet cable and communicated using the IEC 61850 GOOSE Protocol. The 8 types of vulnerability in the system are implemented as an event-based algorithm that immediately executes through critical component CB status information, which is then effectively mitigated by using load shedding and generation steps. The results obtained are 8 types of vulnerability that can be overcome by minimizing load discharges or generations curtailment by equalizing the power deficit. The system frequency value can stabilize again within 5-8 seconds of the disturbance, and the transient response can return to a stable state value of 50 Hz. CRAS schemes can also be run by equipment with a duration of 30-40 ms from the start of the fault event to the CB opening command.

In a large and complex interconnected power system with long transmission lines, the inadequate damping scheme for the inter-area oscillations may lead to system instability. This issue is commonly solved by employing a power system stabilizer (PSS) to increase the system damping. However, the use of PSS encounters some limitations that include voltage fluctuation and poor performance in damping significant oscillations that result due to three-phase faults. To improve the damping of the inter-area oscillation modes, a unified power flow controller (UPFC) along with the PSS is proposed in this paper. Simultaneous utilization of PSS and UPFC calls for proper coordination to attain an optimal damping performance. Hence, a method to obtain optimal coordination between the PSS and UPFC by employing the Firefly algorithm is proposed. To verify the effectiveness of the proposed method, the performance of the proposed damping scheme is analyzed through simulation analysis. Simulation results show the effectiveness of the proposed method in damping low as well as large oscillations in the power systems.

Proper design of protection scheme is one of the problems that arise when distributed generation penetration increases. This is due to the changes in system condition from previously radial to multi-source causing modifications of the magnitude and flow of the fault current. Therefore, the conventional protection schemes that do not consider the direction of the current flow become insufficient to protect the system. Therefore, adaptive protection scheme that can adjust its settings dynamically depending on the condition of the system is needed to keep the system safe. The proposed adaptive protection scheme is tested on the IEEE 3-bus test system on two conditions, the absence and presence of distributed generation. The algorithm is implemented on MATLAB and then verified on Power Factory 2020 to test its effectivity to clear the 3 phases, 2 phases, phase-ground and 2 phases – ground fault current. This algorithm also uses current contribution to prevent the occurrence of protection blinding and sympathetic tripping on this protection scheme. The proposed protection scheme is able to maintain the selectivity of relay operations despite changes in system topology, especially due to distributed generation.

This paper discusses an integration between SCADA and DIgSILENT PowerFactory. This integration allows near real time data transfer for further analysis purposes. The communication protocol used is OPC. The main software used are DIgSILENT PowerFactory and MatrikonOPC Explorer, as the OPC clients, and MatrikonOPC Server for Simulation, as an OPC server. State estimation, which is the key calculation of power system analysis, will be conducted and validated. The data used to simulate the measurement values are the results of the load flow analysis, with some level of errors. The results of state estimation show that the average differences between the state estimation results and the original load flow calculation values, the average deviations and the IISEA are less than 10% for variations of error less than 10% and 5% no meters. A simulation of redundant meters shows that the average difference is 10,16% and the average deviation is 4,11%, while the IISEA is 3,71%. In addition, contingency analysis can provide an index for a component outage and load flow analysis can be used to check the highest PI value, simulate transformer tap changes. The SE process takes 31 seconds, contingency analysis takes 12 seconds, and load flow analysis takes 1 second.

An electric power system is expected to continuously operate in safe conditions at all times and in all configurations. Modern electric power systems have dynamic characteristics with varying generation compositions, load types and network topologies. The dynamic changes of the electric power system require a fast, accurate, and efficient power system operation assessment. Conventional power system assessment mechanism is carried out by simulating contingency analysis with sampling testing on the network topology and generation and load profiles. Its processes also depend on the operator's expertise and experience in analyzing simulation data results, involving many variables and parameters. It is a time-consuming process and has a potential of human error. This gap can be reduced with random forest approach in power system assessment. Digsilent Power factory and python software are used for efficiently generating normal operation and N-1 contingency load flow simulation data with different loads: 50%-150% from the baseload as the datasets. The datasets are then used for training models based on a random forest algorithm for assessing the power system operation status. Finally, the proposed method will be tested on IEEE 14 and 39 test systems with various types of datasets training data to measure the level of accuracy and error proposed model. The simulations have shown that the proposed method has an MSE value of 0.0007 and 0.0005 for static security index prediction on IEEE 14 and IEEE 39, respectively and has an accuracy value of 100.0% and 99.97% for static security operation status classification on IEEE 14 and IEEE 39, respectively. With this level of accuracy, the proposed model may serve as a useful and efficient tool for power system assessment.

PLN Batam targeted to achieve 23% of renewable energy mix in 2025. However, PLN Batam only schedules 3x10 MW undefined renewable energy power plant in 2025 through to three connected substations: Sei Harapan, Nagoya, and Panaran in 2025. This condition encourages to conduct maximum renewable energy penetration assessment. Refer to solar potency in Batam-Bintan and global capital cost trend, this paper justifies optimized allocation for solar photovoltaic (PV) in Batam-Bintan 2021-2025 from three consideration aspects: electric, finance and geographic. This paper calculates that 654 MW-minimum midday load in Batam-Bintan 2025 then elaborated with 322 MW as Technical Minimum Loading (TML) system. Thus, maximum solar PV penetration capacity defined as 332 MW. Furthermore, since system strength of Batam-Bintan 2025 about 36 MW and grid code requires normal operation frequency range within 50±0.2 Hz, maximum capacity for one solar PV power plant about 7 MW. Then, Batam-Bintan geographical condition deliver 3 substations that deal with two adjacent solar PV power plants at 12 km. Therefore, frequency and geographic consideration obtain 3x7 MW as optimized capacity from connected substations: Batu Besar, Sri Bintan, and Kijang. Cost optimization using HOMER software then clarifies that 21 MW solar PV in 2025 may produces cost saving $ 2.7 million. Subsequently, grid impact analysis justifies that 21 MW installed capacity in 2025 that deliver no issue. Finally, this paper proposes different solar PV allocation from RUPTL PLN Batam. The difference as product of cascading stages that projected to be novelty in renewable energy penetration assessment.

To boost renewable energy utility for achieving the target of 23% renewable energy mix by 2025, PT PLN (Persero) launches the diesel conversion to renewable energy program that well-known as Dedieselization program. For the first phase, PLN locks target to convert 225 MW of diesel power plant in 200 locations to the renewable energy power plant. To align renewable energy potential utilization with affordable cost and to qualify with data confidentiality, this paper will figure out optimized hybrid power system configuration for three sampling islands: Island A, Island B, and Island C. These three islands will deal with three considered aspects: low Levelized Cost of Electricity (LCOE), less capacity shortage, and less land utilization. Simulation using HOMER Pro for configuration without diesel utilization deliver results that capacity shortage still occurs. Meanwhile, a hybrid configuration that utilizes a diesel plant delivers zero capacity shortage. Furthermore, scoring that refer to simulation result and optimized parameter conclude that Hybrid PV/BESS/Diesel is the most optimized configuration for Island A and Island B. Otherwise, Island C has Hybrid PV/Diesel as the most optimized configuration. Finally, this paper concludes that any dependency on diesel utilization to succeed Dedieselization program to deals with low LCOE, zero capacity shortage, and less land utilization.

Electricity generation in Indonesia is still dominated 43.64% by coal power plants, most of which operate on the island of Java but use coal transported from other islands. As an archipelagic country, sea condition often contributes to the non-optimal scheduling of power plant operations. Because of that, a new algorithm that consider coal delivery constraints is introduced. The algorithm optimizes maintenance schedule of the power plants to coal supply that affected by sea condition. The algorithm will be implemented using PyPSA – an open-source library for power system analysis based on Python programming language. When applied on IEEE 9-bus system within a year period, system with newly added algorithm provides 6.29% cheaper generation cost and more optimal coal power plants utilization.

Penelitian ini membahas mengenai penentuan prediksi margin kestabilan tegangan (voltage stability margin - VSM) dengan model regresi berganda yang menguhubungkan sisa daya reaktif dengan margin kestabilan tegangannya. Selain itu, penelitian ini juga membahas mengenai penentuan prediksi margin kestabilan tegangan dengan didasarkan pada pengukuran lokal yang memakai ekivalen thevenin untuk representasi sistem. Data-data yang diperoleh untuk perhitungan baik untuk model regresi berganda maupun prediksi didasarkan pada pengukuran lokal pada implementasinya akan diambil dari data phasor measurement unit (PMU) yang menyediakan fasor tegangan dan arus.

One of the methods to reduce peak-time generation costs is by using a battery energy storage system (BESS). To effectively utilize BESS, its installation must be considered carefully since incorrect site placement will increase grid losses and reduce BESS's benefits. This paper presents the application of loss sensitivity factor (LSF) to obtain BESS's optimal placement. The approach will be based on a novel approach considering the charging and discharging period of BESS. The optimization process aims to minimize grid losses when BESS is installed. The performance of the proposed method is validated by using IEEE RTS-96 24 bus system. The results obtained show that this novel approach can significantly minimize the grid losses compared to the conventional LSF approach.

Setting values (parameter values) of equipment (motor, generator, transformer, bus, and line) and system protection coordinations are not optimal (selective) cause a not expected disturbance on an electrical power system. These problems can be seen on many distribution and transmission systems (20 and 70 kV) disturbances that caused circuit breakers of generator tripped, so power plants could not be operated island or house loads. The parameter value problems because there are not protection experts or can use a protection consultant to optimize the parameter values. However, by using the consultant will spend much money. Therefore, for accomplishing the parameter value problems can use an expert system application that works based on knowledgebases of the protection experts, so do not need to spend much money to pay the consultant. The application has to work automatically, so it can eliminate human errors and cost of the consultant. The parameter values will be changed automatically when there are protected equipment or system topology changes.

This research optimises the mix and structure of Generation Companies (GenCos) in the Sumatra power system, Indonesia. Market power, indicating the ability to raise prices profitably above the competitive level, tends to be a significant problem in the aftermath of electricity market restructuring. In the process of regulatory reform and the development of competitive electricity markets, it is desirable and practical to establish an efficient number of competitor GenCos. Simulations of a power system account for multi-plant mergers of GenCos subject to a regulatory measure of the Residual Supply Index and the influence of direct current load flow and the topology of the system. This study simulates the Sumatra power system in order to determine the following: optimal market structure, efficient GenCo generation mix, and the optimal number of competitive GenCos. Further, this study seeks to empirically optimise the electricity generation mix and electricity market structure of the Sumatra power system using DC load flow optimisation, market power index, and multi-plant monopoly analysis. The simulations include generation and transmission constraints to represent network constraints. This research is the first to analyse the Sumatra power system using imperfect (Cournot) competition modelling. Furthermore, this study is the first kind to optimise the mix and structure of the Sumatra generation power market. The guidelines and methodology in this research can be implemented in other countries characterised by a monopoly electricity utility company.

Based on Electricity Supply Business Plan 2019– 2028, Indonesia targets energy mix of 23% for renewable energy. As Indonesia lies in equator line, the development of photovoltaic (PV) is promising in the future. The utilization of PV can be implemented by installing rooftop PV as it can supply electricity independently. Due to the falling price of PV, the user of rooftop PV is predicted to rise significantly. This paper aims to forecast rooftop PV installment in Indonesia from 2020 to 2030. Firstly, the savings bill if installing rooftop PV is calculated. The higher the capacity of rooftop PV is installed, the higher the savings by customers will be made. Prediction of rooftop PV adoption is then calculated using Bass diffusion model. It uses the historical data from three years ago while considering the effect of PV falling price. As the price goes lower, the adoption of rooftop PV is faster each year. Because of the presence of rooftop PV in the system, the annual production of energy can be reduced as the users can generate their own electricity. Consequently, the total production cost can be lower, leading to generation cost change each year.

The regulation of Indonesian Minister of Energy and Mineral Resources No. 4 of 2009 encourages many mining and mineral companies in Indonesia to build smelters. Electric arc furnaces used in the smelting process are non-linear loads that consume large amounts of power and change very quickly over time. The characteristics of electric arc furnaces that fluctuate rapidly may cause several problems such as system frequency instability. To compensate the intermittency of an electric arc furnace, a Static Watt Compensator (SWC) or Battery Energy Storage System (BESS) can be used. This paper discusses the comparison between the Static Watt Compensator and Battery Energy Storage System in terms of performance, sizing, and cost. The modeling and the simulation will be carried out with DIgSILENT PowerFactory, a power system analysis software. The performance of SWC and BESS will be compared by using the Integral Square Error (ISE) method. The results show that SWC maintains system frequency by absorbing active power and can only overcome the system's over-frequency condition, whereas BESS maintains system frequency by supplying or absorbing active power so that it can overcome both over-frequency and under-frequency conditions. However, the use of SWC increases system losses, which causes the total cost of SWC slightly higher than BESS.