This paper investigates the utilization of idle capacity within coal-fired steam power plants (CFSPPs) by implementing power-to-gas technology. The study aims to improve the technical performance and economic viability of underutilized capacity within the grid. Power-to-gas technology uses surplus electricity to convert excess power into alternative fuels, notably hydrogen, which can be utilized in various applications. The research employs specific simulation methods including load profile analysis to assess CFSPP performance across different capacity classes commonly found in the J ava-Madura-Bali (Jamali) electricity grid. The results demonstrate significant potential for performance improvements through power-to-gas implementation, particularly in optimizing the utilization of idle capacity from CFSPP. Findings suggest that integrating power-to-gas technology enhances the performance of CFSPPs, particularly as base load power plants, contributing to grid stability and reliability. Notably, the 600 MW type CFSPPs exhibit the most substantial performance improvements, about 15.27% from the usual dispatch, indicating scalability across different plant sizes with LCOH (Levelized Cost of Hydrogen) is USD 2.7 4/kgH2. Furthermore, implementing power-to-gas technology indirectly reduces production costs by optimizing plant performance and revenue generation. Converting excess electricity into valuable fuels like hydrogen offers a pathway towards sustainable energy utilization, contributing to the broader discourse on energy conversion strategies and the transition towards a net-zero emissions economy. Furthermore, the implementation of the power-to-gas scheme in Jamali, as demonstrated in this study, effectively utilizes excess capacity and significantly contributes to Indonesia's energy transition initiatives.

Integrating renewable energy sources (RES) into island microgrids is usually done to provide a cost-effective electricity supply. The integration process is carried out by scheduling generating unit operations with a unit commitment (UC) scheme to ensure low system operating costs. This article discusses developing a UC optimization method for integrating solar photovoltaic plants in Indonesia’s Eastern Sumba microgrid power system. The scope of this study is the optimization algorithm of the UC, which consists of a priority list (PL) for the UC stage and an economic dispatch (ED) that relies on a genetic algorithm (GA) to minimize total operating costs (TOC). The results show that the PL-GA algorithm performs better than the extended priority list (EPL), and combinations of genetic algorithm and Lagrange, by applying continuous problem dispatch and improved binary GA hourly dispatch to meet ramping constraints. The application of RES incentive programs, such as carbon taxes and incentives for RES generation in calculating the TOC, shows an improvement in the financial feasibility analysis of the internal rate of return (IRR) and net present value (NPV) of actual projects in Indonesia.

Primary energy supply arrangements play a crucial role in the planning and scheduling power plants to meet varying electricity demands. The primary energy supply arrangements also include the quantity, specification, and delivery time of the primary energy supply. When the delivery times of primary energy supplies become unpredictable or unreliable, it can negatively impact the planning and scheduling process. This study aims to develop the best primary energy supply arrangement method by optimizing the primary energy supply delivery time to each power plant in the power system. Data processing in this research uses descriptive analysis methods combined with Genetic algorithms (evolutionary), followed by a numerical simulation process to obtain a primary energy supply schedule. The simulation results show that the descriptive analysis combined with the Genetic Algorithm performs better than the existing methods by applying the manual descriptive analysis method to meet the best delivery time and various required constraints. From the simulation results, a deviation of 13% was obtained compared to the actual data for January-April 2023. This optimization method has been simulated at three power plants in the Java-Bali area with a significant supply contribution to the electric power system. To improve accuracy in making predictions about the delivery time of primary energy supplies, it is necessary to do data processing by adding factors such as weather, sea wave height, and other factors.

The utility companies' main steps in the digital transformation process are asset life cycle management and grid optimization. At these points, efforts to improve the efficiency of the electric power grid are a significant concern. For this reason, utility companies are expected to be able to monitor their operating flow to increase the efficiency of electricity distribution, one of which is by monitoring the losses of the electric power system network. This paper discusses a method for developing an integrated utility end-to-end energy loss monitoring system that monitors the electricity transmission and distribution system online. The method used is to develop an electric power measurement platform according to the local electric power system and consolidate electrical power measurements from measurement points of electric generators, power transmission systems, power transformers, and distribution line feeders. This platform has data communication channels, efficient traffic flow, and high-end database management. The event-driven streaming platform method is a platform that connects all services/ applications in a single data channel (data bus). The advantage of this platform is that it has the capacity for large volumes of data to be communicated in complex systems. On the other hand, it simplifies the communication chain.

Integration of renewable energy generators with existing electrical power systems is an effective strategy to strengthen energy security in islands and remote areas. However, in the case of high penetration of renewable energy sources (RES), operations and economic aspects must be considered. One of the power plant integration schemes is the Unit Commitment (UC), a daily scheduling method to achieve optimization goals while still meeting various operational, environmental, and technical constraints. However, the existing UC method is a generic one, therefore it is necessary to develop an optimization method with a new approach based on improved PL-GA to manage the generation scheduling in microgrid power systems. The proposed solution method is the PL-GA Algorithm, an improvement from the previous studies, with optimization on economic dispatch using GA. This algorithm uses a simple and fast PL technique for the generation scheduling and dispatch stages to obtain the initial population. Then, an accurate and more flexible GA technique is used for the economic dispatch stage to avoid local optima to get the lowest total operating costs. This method has been simulated on the electricity system in Eastern Indonesia, a developing electricity system with intermittent RES power plants with good results.

Knowledge of solar power prediction is an important aspect for power generation planning as well as supporting operations in grid area that apply photovoltaic (PV) generators. Such an aspect is even more critical in the case of limited availability of measurement data. This paper presents a novel model for predicting daily specific solar radiation using predetermined artificial neural networks. Daily meteorological data are used to enrich the conventional artificial neural networks technique. For simulation purposes, solar data was collected at two locations with different meteorological conditions, namely Kupang, Timor Island and Waingapu, Sumba Island, both in East Nusa Tenggara province, Indonesia. Finally, the proposed method shows good performance so as to achieve the above mentioned prediction purposes.

In recent years, utility companies have transformed from using automated meter reading (AMR) technology to Advanced Metering Infrastructure (AMI) in line with digital transformation program to develop energy measurement systems. The AMI energy measurements can be more accurate, real-time, efficient, and provide customer access. Operational reliability and security of measurement devices, communication facilities, data analytics, and other related AMI devices must be integrated, managed, and monitored using a monitoring system that continuously ensures all processes run well and detect any peculiar conditions. The AMI ecosystem is critical to consolidate all measurement points of energy transactions from the generation, transmission, and distribution sectors. AMI also manages all measurement points at substations, distribution substations, and all major customers to ensure accuracy and transparency of electrical energy distribution in the distribution sector. Therefore, a meter operation center is needed to operate and monitor the electric power measurement system working in a good performance. This paper discusses designing a meter operation center as part of the AMI program. The MOC development is carried out in stages using rapid application development, enriched with several improvements from the previous centralized AMR system. The implementation has shown a well-functioning MOC system with complete measurement parameters, large capacity end-devices connected, energy measurement forecasting, demand-side management, and the ability to monitor grid voltage, power interruptions, and power quality. The performance of this MOC will significantly help achieve the implementation and execution of AMI to provide an accurate, precise, and fast energy measurement system and guarantee utility revenue.

Building an accurate, precise, fast, and extensive capacity metering system is mandatory for electricity utility companies. Therefore, several years ago, utilities have built automated meter reading (AMR) systems to run energy measurement business processes to help companies earn revenue. With the growing demand for utilities for detailed and real-time energy measurements at customers, utility companies need to migrate technology from AMR to Advance Metering Infrastructure (AMI). This effort will require the development of information technology and supporting equipment. One of them is the Meter Data Management System (MDMS). It is an essential part of the AMI system to handle the utility company's business processes and the Service Level Agreement (SLA). This paper discusses developing an MDMS for an electricity company's AMI energy measurement system using an IoT-based approach. It leads to a massive meter reading in a certain interval period and handling such conditions required implementing the event-based streaming architecture. The Head-End System (HES) uses the enhanced AMR-based one. The measurement results of the proposed MDMS-HES for AMI show the reading process can handle massive meter reading precisely and detect any abnormal measurement quantities. The reading interval only takes 37.5% of the SLA required by the utility company to read 100% of the meter population. This advanced capability can guarantee better measurement results and guarantee the certainty of the company's revenue.

Integrating intermittent renewable energy power plants into the power system has always been an important issue to research. One method for system integration is to schedule the operation of the generating unit to meet the electrical load. The challenge faced is to adjust the balance between generation and electricity load by considering the intermittent characteristics of NRE generators. One of the isolated electric power systems in Indonesia supplied by the RES plant is the Netemnanu area in the Kupang Region with a photovoltaic power plant. The existing electrical power system in operation is the Oepoli electrical system, which consists of a diesel generator. The integration between the photovoltaic power plant and the Oepoli electrical system will be implemented to strengthen the electricity supply in the area and improve the continuity of the electricity supply. An appropriate method is needed to integrate renewable energy power plants and existing electric power systems so that electricity can be channeled adequately, stably, and continuously. In this study, a method for integrating intermittent EBT generators is discussed in the existing power system. The integration study is carried out by applying the operating scheduling of existing generating units in the electric power system. The challenge faced is regulating the stability of parallel operation between solar power plants and diesel generators. Initial results indicate that the RES plant integration is progressing well with a continuous supply of electric power. This paper also discusses and proposes a business model for cooperation and technology to use government electricity installations with a utility company.

In recent years, efforts to build electricity supplies for islands and remote areas have been carried out by developing renewable energy sources (RES) and integrated into existing electrical systems. For this reason, it is necessary to apply a method of regulating electricity supply. Unit Commitment (UC) is daily scheduling of power generation units to achieve optimization goals while still meeting various operational, environmental, and technical constraints. With a significant increase of the operation of the RES intermittent power plant in the power system, the development of the UC method becomes more necessary, to maintain system stability and resilience, and minimum operating costs. Therefore, new optimization methods need to be developed to be applied to the UC scheme for microgrid electric power systems.This paper discusses alternative optimization methods to optimize UC solutions in microgrid power systems with intermittent RES plant. In this paper, a comparison of the strengths and weaknesses of each optimization technique is discussed, with the intent and purpose of finding the most appropriate optimization technique to utilize. The problem in the UC scheme has been studied by experts using numbers of methods. The combination of mathematical techniques and stochastic / meta-heuristic techniques is proven to provide better optimization solutions. This study is aimed at optimizing UC in electric power systems with intermittent RES power plants. In particular, the power system under study is a developing electricity system, for islands or remote areas. The proposed method is the enrichment of existing optimization techniques, with additional innovations in analytical methods to improve the performance of the UC schemes applied to the microgrid system.

With the development of technology, renewable energy sources (RES) have been developed on islands and electricity systems in isolated areas, including RES which have intermittent characteristics. Those variable renewable energy power plants are operated by integration into existing power systems. The rapid increase of variable RES power plants integration into electricity network has given effect on the development of unit commitment (UC) schemes which aimed to ensure the operation of electric power systems stability, resilience, and with minimum operating cost can be maintained. To achieve these goals, it is necessary to develop optimization methods to be applied to the UC scheme for the island's electricity system.This paper discusses the most suitable optimization methods for the inclusion of renewable energy power generation using a unit commitment scheme in the microgrid electricity system. The methods here are a hybrid technique which combines enhanced priority list method for accurate generation unit scheduling and genetic algorithm (GA) technique for an optimum search for the lowest operational cost. The capacity of generating units to operate per capability segment is also taken into account in operating scheduling and affects the number of iterations in the operation of genetic algorithm techniques. This method has been simulated on the Timor electricity system, which is a growing power system and has an intermittent RES power plant. Implementation in other locations with other variable RES could provide better results. This method is an enrichment of hybrid techniques developed in previous studies. This enrichment is carried out on the calculation by segmenting the ability of generating units.

Electricity supply in microgrid power systems often faces limited power supply constraints. Besides adding more power generation and organizing power plants scheduling, efforts to balance supply and power requirements in the power system can be made by regulating the amount of electrical load. Demand side management (DSM) program can be done to control energy consumption and limit peak loads. The demand response (DR), as one of the DSM program, can be implemented to regulate the electric load to balance supply and demand Residential customers demand response is a program that aims to reduce peak load by shifting or shedding residential electricity loads. This load reduction method has been used to control the peak load to be able to adjust to power supply conditions. This paper presents a literature survey of articles that address the application of DR for residential customers. The study uses the assumption that majority of electrical loads in microgrid systems are residential customers. It is expected that a balance between supply and demand for electricity in the power system can be achieved through demand response activities for residential customers. Here, a review of effective demand response methods is performed to precisely and accurately regulate the use of electricity by residential customers to limit peak load and control electrical energy consumption. In the end, this paper also discusses the possible implementation of demand response method for residential customers on a microgrid system.

Southeast Asia's power systems face huge challenges – from reliability issues, over steeply growing energy demands to questions related to the change in the generation and demand matrix. In addition to these challenges, plans to integrate large amounts of intermittent renewable energy sources are put forward. Last but not least providing energy access for all citizens remains a challenge for many parts of the region. Smart-grid technologies can facilitate solutions for demand growth, energy access and renewable integration. This study presents the establishment of a smart grid roadmap for Indonesia's power system including a discussion on the applied method. Experiences and lessons learned are condensed to 10 key questions that utilities should be able to answer, when starting an energy transition programme. The presented method and insights can be helpful not only for Southeast Asia but also for any utility that aims to leverage smart grid technologies in an optimised way.

The rise of new electric customers with type of load of iron smelting electric furnace has made PLN prompted to prepare adequate power supply, improved reliability of electricity supply and fix the rules of on standards and control procedures of electric power quality on customer's side. Load type iron electric furnace or iron smelters, has been known to cause power quality problems, especially harmonics, which may cause disturbance to other consumers or to electrical power system. Therefore, procedures to supervise and to control customer's electrical load which causing power quality problems need to be developed and implemented to maintain the power system from voltage and current harmonic distortion problem and the influence of other power quality problems. Also, power quality standard as the major rules regarding the limitation of power quality distortions has to be established and consistenly implemented including on the letter of power purchase agreement between utility and electricity customer. This paper shows the efforts of PLN to develop supervision and control procedures and power quality standards for limiting the distortion power quality and also the preparatory steps for applying the rule on each electric power customer's. Implementation strategies for applying the power quality limitation rule to both news customers and existing customers are described in detail.

In the last three years, numbers of distribution transformer failure in Jakarta area were still deem high accounting for 54 units per year or 2 % of the total distribution transformer asset (2749 units) in Gambir Distribution System. Most of the faults were caused by isolation breakdown, mainly on the bushing, windings and insulation oil media, due to inadequate maintenance activities and also excessive loading of distribution transformer. The limited number and quality of human resources that are not proportional to power distribution assets and the limited operations and maintenance budget for distribution network have become the main cause of inadequate maintenance activities. Transformer’s excessive loading is due to high growth of electricity demand which is around 810% and worsened per year which could not be counterbalanced by limited investments in distribution equipments, delays in the development of power distribution systems and other technical matters. This paper presents the implementation of asset management program on distribution transformer operation and maintenance with the objective to decrease the rate of distribution transformer failures. The activities include capturing and collecting data of distribution substation and transformer, diagnosing of latest equipments conditions, enhancement of proper maintenance methodologies and implementation of integrated conditional based maintenance program (CBM). The implementation of integrated CBM is the most difficult part due to the fact that the process of updating the database was not optimal, limitation on human resource capabilities and there was is no integrated application system. The methodologies and procedures are also applied in technical system, management infrastructure and mindset capabilities and leadership. The early result shows that the number failures have been significantly declined approximately 10 % compared to the first quarter of 2010. Due to the profound result, this approach will be extended to the whole distribution network area.