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"Kronecker products are used to define the underlying Markov chain (MC) in various modeling formalisms, including compositional Markovian models, hierarchical Markovian models, and stochastic process algebras. The motivation behind using a Kronecker structured representation rather than a flat one is to alleviate the storage requirements associated with the MC. With this approach, systems that are an order of magnitude larger can be analyzed on the same platform. The developments in the solution of such MCs are reviewed from an algebraic point of view and possible areas for further research are indicated with an emphasis on preprocessing using reordering, grouping, and lumping and numerical analysis using block iterative, preconditioned projection, multilevel, decompositional, and matrix analytic methods. Case studies from closed queueing networks and stochastic chemical kinetics are provided to motivate decompositional and matrix analytic methods, respectively."

"This book summarizes a line of research that maps certain classical problems of discrete mathematics and operations research, such as the Hamiltonian cycle and the Travelling Salesman problems, into convex domains where continuum analysis can be carried out."

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Informasi mengenai penggunaan energi listrik merupakan salah satu elemen penting dalam hal pengaturan distribusi jaringan listrik pada jaringan pintar skala kecil (smart micro grid). Selain itu informasi pemakaian energi listrik dapat membantu konsumen melakukan proses evaluasi pemakaian energi listrik untuk menekan biaya tagihan pembayaran listrik yang secara tidak langsung berpengaruh pada efisensi energi keseluruhan. Salah satu metode dalam proses pemantauan pemakaian energi listrik adalah Non-Intrusive Load Monitoring (NILM). Permasalahan utama dalam NILM adalah mengetahui peralatan-peralatan elektronik yang ada dan mengetahui konsumsi energi listrik masing-masing peralatan dengan hanya melakukan proses pengambilan data hanya dari satu titik yang terhubung dengan semua peralatan elektronik pada jaringan listrik. Berdasarkan hasil pengujian menggunakan dataset AMPds dan REDD, nilai akurasi terendah yang didapatkan adalah sebesar 96,69% pada semua pengujian yang dilakukan.

 

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Information on electricity consumption is one of the essential elements in terms of regulating the distribution of electricity in smart micro grid. Besides, information on electricity consumption can help consumers carry out an evaluation process to reduce electricity bill costs, which indirectly affect overall energy efficiency. One method in the process of monitoring electricity consumption is Non-Intrusive Load Monitoring (NILM). The main problem in NILM is electronic disaggregation equipment that exists and determines the electrical energy consumption of each appliance by merely performing the retrieval of data from only one point connected with all the electronic devices on the electrical grid. Based on the results of tests conducted using the REDD and AMPds dataset, the lowest accuracy was 96.69% for all tests performed.

 

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"Transformator daya merupakan salah satu peralatan listrik yang sangat vital dalam menunjang performa pembangkit tenaga listrik. Alat ini dilengkapi dengan minyak yang berfungsi sebagai pendingin dan isolator. Kekuatan isolasi yang dimiliki oleh transformator daya dapat mengalami penurunan yang dipengaruhi oleh adanya gas-gas. Hal ini dapat menyebabkan terjadinya kegagalan operasi dan menurunnya sisa umur operasi transformator daya. Pemeliharaan prediktif dilakukan untuk mencegah dampak negatif dari penurunan kekuatan isolasi minyak transformator daya, salah satunya melalui teknik Dissolved Gas Analysis (DGA) yang dapat menganalisis kandungan gas terlarut dalam minyak transformator daya. Sesuai dengan standar yang ditetapkan dalam IEEE C57.104:2019 dan IEC 60599:2005, pengujian DGA dapat mendeteksi beberapa gas yang terlarut seperti H2, CH4, C2H4, C2H2, C2H6, dan CO di dalam minyak transformator daya. Pengujian DGA dilakukan menggunakan dua metode yaitu metode IEC ratio dan duval triangle untuk mengidentifikasi jenis kegagalan yang terjadi pada transformator daya BAT GT 1.1 dan 1.2 PT PLN Indonesia Power Priok PGU. Pengujian pada sampel pengukuran dari tahun 2018 hingga 2023 untuk kedua transformator menggunakan IEC ratio dan duval triangle didominasi dengan kegagalan termal di bawah 300 serta didapatkan diagnosa yang lebih spesifik menggunakan duval triangle yaitu pemanasan di bawah 250 . Kegagalan yang terjadi dapat mempengaruhi keandalan dan availability kondisi transformator daya. Melalui markov chain diprediksi transformator BAT GT 1.1 dan 1.2 mengalami penurunan keandalan sekitar 25% dalam waktu 30 hari beroperasi. Untuk mengoptimalkan keandalan kedua transformator dapat dilakukan pemeliharaan rutin pada hari kerja ke-90. Di sisi lain, transformator BAT GT 1.1 dan 1.2 tersedia dalam kondisi normal hingga hari ke-217 dan hari ke-185. Sehingga dapat dilakukan purifikasi pada masing – masing di transformator di hari kerja ke-218 dan ke-186 agar meminimalkan adanya partikel gas yang terlarut di isolasi minyak transformator.

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A power transformer is one of the electrical equipment that is very vital in supporting the performance of power plants. This tool is equipped with oil which functions as a coolant and insulator. The insulation strength of a power transformer can decrease due to the presence of gases. This can cause operational failure and reduce the remaining operating life of the power transformer. Predictive maintenance is carried out to prevent the negative impact of decreasing the insulation strength of power transformer oil, one of which is through the Dissolved Gas Analysis (DGA) technique which can analyze the dissolved gas content in power transformer oil. In accordance with the standards stipulated in IEEE C57.104:2019 and IEC 60599:2005, DGA testing can detect several dissolved gases such as H2, CH4, C2H4, C2H2, C2H6, and CO in power transformer oil. DGA testing was carried out using two methods, namely the IEC ratio and duval triangle methods to identify the type of failure that occurred in the PT PLN Indonesia Power Priok PGU BAT GT 1.1 and 1.2 power transformers. Tests on measurement samples from 2018 to 2023 for both transformers using the IEC ratio and Duval triangle were dominated by thermal failures below 300℃ and a more specific diagnosis was obtained using the duval triangle, namely heating below 250℃. Failures that occur can affect the reliability and availability of power transformers. Using the Markov chain, it is predicted that the BAT GT 1.1 and 1.2 transformers will experience a decrease in reliability of around 25% within 30 days of operation. To optimize the reliability of both transformers, routine maintenance can be carried out on the 90th working day. On the other hand, BAT GT 1.1 and 1.2 transformers were available in good condition on day 217 and day 185. Purification can be carried out on each component in the transformer on the 218th and 186th working days to minimize the presence of dissolved gas particles in the transformer oil insulation."

"This book focuses on the different steps involved in the conception, implementation and application of EDAs that use Markov networks, and undirected models in general. It can serve as a general introduction to EDAs but covers also an important current void in the study of these algorithms by explaining the specificities and benefits of modeling optimization problems by means of undirected probabilistic models.All major developments to date in the progressive introduction of Markov networks based EDAs are reviewed in the book. Hot current research trends and future perspectives in the enhancement and applicability of EDAs are also covered. The contributions included in the book address topics as relevant as the application of probabilistic-based fitness models, the use of belief propagation algorithms in EDAs and the application of Markov network based EDAs to real-world optimization problems. "