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"This book makes use of existing scenarios to sketch a new structure for Germany's and Europe's electricity system that will be able to cope simultaneously with the fundamental demands for economic efficiency, environmental sustainability and supply security. "

"Sistem kelistrikan rumah tangga off-grid terus mengalami perkembangan. Dengan berkembangnya teknologi energi terbarukan, teknologi komputasi, teknologi informasi dan teknologi komunikasi, fungsi dan peran sistem kelistrikan rumah tangga dalam menurunkan emisi gas buang dan meningkatkan efisiensi semakin penting. Untuk merancang sistem kelistrikan rumah tangga diperlukan suatu alat. Saat ini pemodelan dan simulasi menjadi alat yang efektif untuk mendapatkan rancangan sistem yang diinginkan. Dalam penelitian ini, dirancang pemodelan dan simulasi sistem kelistrikan rumah tangga. Sistem ini terdiri dari panel surya, turbin angin, baterai dan beban yang terkoneksi melalui konverter. Pemodelan diturunkan dari model matematik sistem sedangkan simulasi menggunakan MATLAB/Simulink. Dalam penelitian ini, rancangan sistem kendali supervisi juga diimplementasikan. Kendali ini berfungsi menyeimbangkan antara pasokan energi dan beban yang terus berubah. Dari hasil simulasi yang dilakukan didapatkan bahwa model dan simulasi dapat bekerja dengan baik. Perubahan beban dan pasokan energi dapat diantisipasi dengan bekerjanya baterai dan juga fuel cell.

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The off-grid household electrical system continues to develop. With the development of renewable energy technology, computational technology, information technology and communication technology, the function and role of off-grid household electrical systems in reducing exhaust emissions and increasing efficiency are increasingly important. To design an off-grid household electrical system, a tool is needed. Currently modeling and simulation are effective tools to get the desired system design.

In this study, a household electrical system modeling and simulation was designed. This system consists of solar panels, wind turbines, fuel cells, batteries and loads connected through a converter. Modeling is derived from system mathematical models while the simulation uses MATLAB / Simulink. In this study, the design of the supervision control system was also implemented. This control functions to balance the energy supply and the ever-changing burden. From the results of the simulations carried out, it was found that the model and simulation could work well. Changes in load and energy supply can be anticipated by the operation of the battery and also the fuel cell."

"ABSTRAKModel optimisasi telah menjadi salah satu instrumen penting dalam menentukan bauran energi masa depan dan sebagian besar dibuat dalam pendekatan nasional. Indonesia memiliki sumber daya energi primer yang berlimpah, baik berupa energi fosil maupun energi terbarukan. Namun, tingginya disparitas kepadatan penduduk, infrastruktur, level ekonomi, dan perbedaan antara lokasi sumber energi dan konsumen energi antar dan intra-area berdampak pada ketimpangan performa sistem energi antara Indonesia bagian barat dan timur yang memicu ketidakberlanjutan sistem energi, dalam hal ini adalah listrik. Sehingga pada penelitian ini, analisis sistem ketenagalistrikan di Indonesia di masa depan hingga tahun 2050 dengan model optimisasi multi-objektif dilakukan dengan menggunakan indikator keberlanjutan. Penelitian diawali dengan mengembangkan model optimisasi pada pendekatan nasional dan spasial untuk menunjukkan besar deviasi antara pendekatan nasional dan spasial. Selanjutnya model optimisasi spasial digunakan untuk analisis lebih lanjut dengan memperhatikan perbedaan karakteristik regional dengan membagi Indonesia menjadi enam regional: Sumatera, Jamali, Kalimantan, Sulawesi, Maluku-Nusa Tenggara (Maluku & NT), dan Papua. Lima skenario tujuan pengembangan dianalisa: (a) BAU, (b) orientasi lingkungan secara pasif, (c) trade-off ekonomi-lingkungan, (d) perlindungan lingkungan secara aktif, dan (e) orientasi lingkungan hijau secara total. Hasil penelitian menunjukkan bahwa skenario orientasi lingkungan secara pasif menghasilkan performa indikator keberlanjutan terbaik. Skenario ini sangat sedikit mengorbankan aspek ekonomi energi untuk meningkatkan performa sistem ketenagalistrikan Indonesia pada apek lingkungan dan ketahanan sumber daya energi dengan meningkatnya penetrasi energi terbarukan dan tingkat keberagaman.

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ABSTRACTIn the present study, a multi-objective optimization model was developed to find the best scenario for Indonesian power generation planning up to 2050. Indonesia has abundant fossil and renewable energy resources. However, high disparity on population density, infrastructure, economic level, and the difference between energy source and energy consumer location among and inter-region inflict to discrepancy on electricity system performance between western and eastern part of Indonesia. In order to capture more accurately regional characteristics, the model was developed in spatial as well as national approach by dividing Indonesia become six regions: Sumatera, Java-Madura-Bali (Jamali), Kalimantan, Sulawesi, Maluku-Nusa Tenggara (Maluku & NT), and Papua. Five development objective scenarios were proposed: (A) business as usual, (B) passively environment oriented, (C) economic-environmental trade-off, (D) actively environment protection, and (E) totally towards green society. Energy mix, cost of generation, CO2 emission, and fuel consumption output from optimization model were inputted in sustainability indicator simulation which consist of eleven indicators which are represent three sustainability aspect: economic, social, and environment to be analyzed. The results show that national approach could utilize more renewable energy than spatial approach due to no limitation on potential coverage area. Passively environment oriented provide the best sustainable indicator performance. The scenario slightly compromise cost of electricity generation to highly increase social, environment, and resource security indicators by increasing penetration of renewable energy."

"In 2020, renewable energy sources contribution in Indonesia’s energy production mix had only reached 14,71%. The percentage was still far from Indonesia’s renewable energy mix target of 23% in 2025 and 31% in 2050 according to their own national energy plan. To enhance their progress in reaching those targets, one way that can be done is to benefit promising renewable energy potential in many areas, including coastal area such as Muara Bungin Beach located in Pantai Bakti Village, Bekasi. The village mentioned before have an average of 3,26-5,41 m/s wind speed and solar radiation of 5-5,4 kWh/m2/day. To utilize the area’s potential, three units of The Sky Dancer TSD-500 wind turbine and two monocrystalline solar panels with a total capacity of 1800 Watt peak have been installed in that area since 2014, making Muara Bungin Village mostly known as Bungin Techno Village to public. Sadly, the wind turbines have been removed recently in October 2021 due to poor physical condition, and the solar panels rarely being used and maintenanced. A revitalization plan can be done to keep Bungin Techno Village’s existance in utilizing their renewable energy potential alive.

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The revitalization plan will create huge project, which is to install renewable energy power plants that can serve Desa Pantai Bakti’s electricity demand. A modelling result by LEAP shows that Desa Pantai Bakti’s electricity demand will reach 1.965,1 kWh/day in 2031. The planned renewable energy power plants will handle electricity load of 1.021,85 kWh/day or 51,6% from the village’s total electricity demand. A solar power plant consisting 104 units of Monocrystalline Maysun Solar Cell 500 Wp Peak Power with a lifetime of 25 years, a wind power plant consisting 24 units of 2000 W/220 V capacity wind turbines with a lifetime of 20 years, and a waste-to-energy power plant consisting a TG30 gasification machine and a 200 kVa/160 kW capacity diesel genset Caterpillar with a lifetime of 20 years. The total cost for lifetime operation of the planned solar, wind, and waste-to-energy power plant is estimated to be around Rp1.519.049.423; Rp3.238.231.499; and Rp859.733.884 respectively. The investment for the renewable energy technology revitalization plan can be considered economically worthy, judging by the NPV and ROR of every single planned power plants showing positive values or greater than zero."

"Conservation Voltage Reduction (CVR) adalah metode untuk mengurangi konsumsi daya dan permintaan puncak. Ini bukan studi baru karena sudah banyak implementasi dan penelitian tentang CVR sebelumnya. CVR menyiratkan bahwa dengan mengurangi tegangan suatu perangkat atau sistem, daya yang dikonsumsi juga akan berkurang. Hal ini dapat dibuktikan dengan menggunakan persamaan daya listrik yang menyatakan bahwa daya sebanding dengan tegangan.Sistem energi terbarukan sedang meningkat karena semakin murah dan lebih efisien. Daya yang dikeluarkan oleh sistem energi terbarukan tergantung pada faktor sumbernya, apakah itu radiasi atau kecepatan angin. CVR memungkinkan pengurangan konsumsi daya beban. Ini membantu mengurangi beban sistem karena mereka tidak harus menghasilkan lebih banyak daya daripada kebutuhan beban.Sistem PV dan turbin angin mikro memiliki keluaran yang berbeda, tetapi keduanya perlu memasok beban yang sama dalam jaringan mikro. Kedua sistem pada akhirnya diubah menjadi daya AC untuk digunakan beban. Inverter digunakan di kedua sistem untuk membantu konversi. Inverter umum memiliki fluktuasi tegangan antara -20% dan +10% dari tegangan nominalnya. Sebuah sistem kontrol digunakan untuk mengatur tegangan keluaran inverter dan memastikan tidak mencapai kisaran tegangan maksimum. Sistem kontrol akan memungkinkan output inverter diatur lebih dekat ke tegangan nominal dan dengan demikian mengurangi tegangan berlebih.Sistem energi terbarukan menghasilkan tegangan yang lebih rendah setelah sistem kontrol diterapkan untuk mengatur keluaran inverter. CVR telah dicapai dalam sistem ini. Sistem telah mengurangi konsumsi daya dan dengan demikian menurunkan beban sistem. Sistem tidak menghemat energi dengan menerapkan CVR. Perangkat yang bergantung pada voltase masih akan membutuhkan lebih banyak daya jika voltase perangkat dinaikkan. Sistem PV dan turbin angin mikro dengan CVR memungkinkan beban mendapatkan input tegangan yang lebih sehat sekaligus mengurangi konsumsi daya.

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Conservation voltage reduction (CVR) is a method to reduce power consumption and peak demand. It is not a new study as there have been plenty of implementations and research regarding CVR for a long time. CVR implies that by reducing the voltage of a device or system, the power consumed will also be reduced. This can be proven using the electrical power equation where it states that power is proportional to voltage. Renewable energy systems are on the rise as they are getting cheaper and more efficient. The power outputted by a renewable energy system depends on their source factor whether it is irradiance or wind speed. Conservation voltage reduction allows the reduction of power consumption of the load. This helps decrease the burden of the system as they do not have to generate more power than the load needs.

PV systems and micro wind turbines have different outputs, but both need to supply the same load in a micro-grid. Both systems are eventually converted to AC power for the load to use. An inverter is used in both systems to help with the conversion. A common inverter has a voltage fluctuation between -20% and +10% of its nominal voltage. A control system is used to regulate the inverter’s output voltage and make sure it does not reach the maximum voltage range. The control system will allow the output of the inverter to be regulated much closer to the nominal voltage and thus decreasing excess voltage. The renewable energy system outputs a lower voltage after a control system has been applied to regulate the output of the inverter. Conservation voltage reduction has been achieved in this system. The system has reduced power consumption and thus lowering the burden of the system. The system does not save energy by implementing conservation voltage reduction. A voltage-dependent device will still demand more power if the voltage of the device is increased. The PV and micro wind turbine system with CVR allows the load to benefit healthier voltage input while having reduced power consumption."

"Negara kesatuan Republik Indonesia memiliki tujuh wilayah besar dengan karakteristik yang berbeda dalam system kelistrikan, perkembangan kebijakan kelistrikan di Indonesia dimulai pada abad ke-19 dan mulai berkembang dengan adanya pemberian hak konsesi oleh Pemerintah kolonial Hindia Belanda kepada swasta di beberapa daerah, kemudian ketika Jepang menguasai Indonesia, sektor kelistrikan berubah fungsi sebagai alat pertahanan dalam peperangan. Indonesia memperoleh kemerdekaan pada tahun 1945 dibarengi dengan proses nasionalisasi aset-aset yang dimiliki oleh Hindia-Belanda dan Jepang, kemudian sektor kelistrikan dikuasai sepenuhnya oleh Negara yang diamanahkan melalui Badan Usaha Milik Negara yaitu PLN. Pada tahun 1966, sektor ketenagalistrikan merupakan bagian dari proses pembangunan yang digaungkan dalam RPLT (Rencana Pembangunan Lima Tahun), di era tahun 1998 terjadilah pergolakan reformasi, yang berdampak pada kebijakan ketenagalistrikan, dimana porsi swasta/Independent Power Producer (IPP) meningkat signifikan menjadi 3.169 MW pada tahun 2003, rentan waktu era reformasi kebijakan sektor ketenagalistrikan mengalami 2 kali perubahan, konsepnya masih sama yaitu demonopolisasi, namun ada beberapa konsep yang diluruskan oleh Mahkamah Konstitusi, sehingga sektor ketenagalistrikan tetap menjadi bagian dari kontrol negara. Indonesia telah meratifikasi Paris Agreement, dimana konsep perencanaan kelistrikan akan berbasis pada energi baru terbarukan, berbagai skenario telah dipersiapkan pemerintah namun baru bersifat pemenuhan kebutuhan supply-demand dengan mengoptimalkan pemanfataan energi terbarukan untuk kebutuhan pembangkit listrik, belum ada kebijakan yang mengatur terkait agregasi energi terbarukan sehingga diperlukan proyeksi kebutuhan energi dengan alat bantu perangkat lunak Powersim dan Arena untuk menghitung kebutuhan energi secara skenario BAU (Business As Usual) dan skenario penambahan supply dari 20% dari PLTS Atap dan variabel lainnya dari PLT Energi Terbarukan sebesar 10 s.d 15 TWh dan penambahan demand dari adanya peningkatan penggunaan electric vehicle, kompor induksi dan ekspor listrik ke Singapura dan Timor Leste.

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The unitary state of the Republic of Indonesia has seven large regions with different characteristics in the electricity system, the development of electricity policy in Indonesia began in the 19th century and began to develop with the granting of concession rights by the Dutch East Indies colonial government to the private sector in some areas, then when Japan controlled Indonesia, the electricity sector changed its function as a means of defense in warfare. Indonesia gained independence in 1945 coupled with the process of nationalization of assets owned by the Dutch East Indies and Japan, then the electricity sector was fully controlled by the State mandated through state-owned enterprises, namely PLN. In 1966, the electricity sector was part of the development process echoed in the RPLT (Five-Year Development Plan), in the era of 1998 there was a reform upheaval, which had an impact on electricity policy, where the portion of private / Independent Power Producer (IPP) increased significantly to 3,169 MW in 2003, vulnerable when the era of electricity sector policy reform experienced 2 changes,  The concept is still the same as demonopolisation, but there are several concepts straightened out by the Constitutional Court, so that the electricity sector remains part of state control. Indonesia has ratified the Paris Agreement, where the concept of electricity planning will be based on new renewable energy, various scenarios have been prepared by the government but only meet the needs of supply-demand by optimizing the utilization of renewable energy for electricity generation needs, there is no policy that regulates the aggregation of renewable energy so that it requires the projection of energy needs with Powersim and Arena software tools for electricity generation.  Calculate the energy needs in the BAU (Business As Usual) scenario and the scenario of increasing supply from 20% of roofing power plants and other variables of renewable energy power plants of 10 to 15 TWh and the addition of demand from the increased use of electric vehicles, induction stoves and electricity exports to Singapore and Timor Leste."

"Energy has moved to the forefront in terms of societal and economic development. Modern energy markets is a comprehensive, economically oriented, exploration of modern electricity networks from production and distribution to deregulation and liberalization processes. Updating previous work by the authors, different aspects are considered resulting in a complete and detailed picture of the systems and characteristics of modern electricity markets.Modern energy markets provides clear detail whilst encompassing a broad scope of topics and includes :1. A method to model energy production systems including the main characteristics of future demand side management,2. Different applications of this model in nuclear and renewable energy scenarios,3. An analysis of Real-Time Pricing of electricity and its potential effects across the market, and,4. A discussion of the need for regulation in an easily monopolized industry.Engineering and economics students alike will find that modern energy markets is a succinct and informative resource, as will researchers interested in environmental and energy issues. The inclusion of timely and relevant issues related to economic decision will also be of value to industry and civil officials."

"ABSTRAKDalam pengoperasian sistem tenaga listrik untuk dapat menyediakan tenaga listrik di masa yang akan datang maka diperlukan suatu perencanaan operasi sistem tenaga listrik. Salah satu bagian utama yang harus disiapkan oleh penyedia tenaga listrik PLN adalah bagian pembangkitan, dalam merencanakan pembangkitan tenaga listrik harus selaras dengan besar beban puncak pada waktu tertentu. Kemudian, diperlukan pula suatu faktor keandalan yang berhubungan dengan pembangkitan dan besar beban puncak yaitu reserve margin, yang merupakan persentase besar cadangan pembangkit terhadap besar beban puncak. Dalam penelitian ini, penulis menemukan suatu permasalahan yaitu besar reserve margin yang sangat besar pada tahun 2019 dan pada tahun 2020 yaitu sebesar 55 dan 49 berdasarkan perencanaan PLN pada RUPTL 2017-2026. Oleh karena itu, penulis mencoba melakukan peramalan beban hingga tahun 2020 menggunakan Jaringan Syaraf Tiruan, lalu mencoba menentukan berapa reserve margin yang seharusnya diperlukan dan akan muncul berapa besar pembangkitnya sehingga perencanaan pembangkit dapat lebih efisien. Didapatkan hasil peramalan beban menggunakan JST pada tahun 2017 adalah 26,419 MW, tahun 2018 adalah 28,001 MW, lalu tahun 2019 adalah 29,716 MW, dan pada tahun 2020 adalah 30,779 MW. Dari beberapa variasi reserve margin, penulis memilih merekomendasikan reserve margin sebesar 30 . Sehingga, total pembangkit yang akan beroperasi pada tahun 2017 menjadi sebesar 34,345 MW, tahun 2018 sebesar 36,401 MW, lalu pada tahun 2019 sebesar 38,631 MW, dan pada tahun 2020 sebesar 40,013 MW.

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ABSTRACTIn the operation of electric power system to provide electric power in the future it is necessary to have a planning operation of electric power system. One of the main components that must be prepared by the provider of electricity PLN is the generation component, in planning the generation of electricity must be in line with the peak load at a certain time. Then, a reliability factor associated with the generation and the peak load called reserve margin, which is a percentage of the generating reserves against the peak load. In this study, the authors found a problem that is the value of the reserve margin is very large in 2019 and in the year 2020 that is equal to 55 and 49 based on PLN planning in RUPTL 2017 2026. Therefore, the author tries to forecast the load until 2020 using Artificial Neural Network ANN , then the author try to determine how much is the reserve margin should be required and how much is the power plants needed, so that the planning can be more efficient. After doing a forecast and calculation, it can obtained from load forecasting results using ANN in 2017 the peak load is 26,419 MW, 2018 is 28,001 MW, then year 2019 is 29,716 MW, and in the year of 2020 is 30,779 MW. From several variations of reserve margin, the author has choosen to use a reserve margin of 30 . Thus, the total power plant to be installed in 2017 will be 34,345 MW, in 2018 of 36,401 MW, then in 2019 by 38,631 MW, and by 2020 by 40,013 MW. "