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"Pada pengoperasian sistem tenaga listrik untuk keadaan beban yang bagaimanapun, sumbangan daya dari tiap pembangkit harus ditentukan sedemikian rupa agar daya yang disuplai menjadi minimum. Biaya bahan bakar merupakan komponen biaya terbesar pada pembangkit thermis, oleh sebab itu maka biaya produksi tenaga listrik thermis, diusahakan menggunakan bahan bakar sehemat mungkin. Metode meminimasi biaya pembangkitan akan gagal, bila tidak mencakup rugi daya pada saluran transmisi, sebab meskipun biaya bahan bakar inkremental suatu pembangkit mungkin lebih rendah dari pembangkit lainnya, akan tetapi karena terletak jauh dari pusat beban, biaya rugi-rugi transmisinya besar. Untuk mengoptimalkan biaya bahan bakar dan rugi daya pada saluran, penyelesaiannya adalah dengan menggunakan persamaan koordinasi, karena pada persamaan ini biaya pembangkitan yang optimal akan tercapai bila biaya bahan bakar inkremental total dikalikan dengan faktor penalti bernilai sama untuk semua pembangkit. Dari hasil perhitungan optimasi didapatkan bahwa, pada beban sesaat yang sama didapatkan basil pembangkitan yang lebih rendah, hal ini disebakan karena adanya penurunan rugi daya pada saluran yang cukup signifikan, sehingga diperoleh penghematan biaya pembangkitan dibandingkan jika sistem dioperasikan manual, besar penghematan per kWh nya adalah Rp 17,0789 atau 12.97 % dari biaya pembangkitan sebelumnya, sedang rugi daya pada saat sebelum optimasi adalah 80.697 MW padasaat dioptimasi rugi dayanya sebesar 24.804 MW atau prosentasenya sebesar 225.30 %.

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In order to get a minimum generation-cost of interconnected power-plants, each power plant generated power should be adjusted at a certain value depending on the load of each substations at that time. Fuel cost is the main cost portion of a thermal power plant , so to achieve a minimum cost, the thermal power plantfue consumtion should be manage efficiently.

Calculation of generation cost optimation in between power plant connected over interconnected transmision line will not be accurate if not involving transmission linespower losses. Incremental fuel cost of a power plant may be lower then another, because its location is more far away from the load centre comparied to the another power plant, the total generation cost will be higher. To get an optimal generation cost involving transmission lines power losses a coordination equation will be used. By this equation we will get the optimum generation cost while the total fuel incremental cost multiplied by penalty factor has the same value for all power plants connected to results transmission lines.

From the optimation-calculations we get lower power generation comparied to manual adjustments by load dispatch center operators, because of decreasing total transmission lines losses, also total generation cost per kWh decrease significanly. The real saving generation cost by this optirnation is Rp 10,747.00 or 8.17 % as before."

"Dalam pengoperasian suatu sistem pembangkit tenaga listrik perlu ditentukan besarnya daya yang disalurkan oleh tiap unit pembangkit sehingga dapat beroperasi pada biaya pembangkitan yang minimum. Hal ini dapat dilakukan dengan optimasi pembebanan pada seluruh unit pembangkit tenaga listrik.Pada tesis ini akan dibahas mengenai optimasi pembagian beban pada unit pembangkit hidro dan termal dengan menggunakan metoda pengali Lagrange. Fungsi tujuannya adalah meminimalkan biaya pembangkitan dengan kendala kapasitas maksimum dan minimum unit pembangkit. Pembahasan tesis ini dibatasi pada optimasi pembangkit hidro termal area IV sistem kelistrikan Jawa-Bali, Perhitungan dilakukan dengan program Matlab yang dioperasikan pada komputer pribadi dan disertai dengan validasi program. Validasi program memperlihatkan bahwa program yang telah dibuat dapat digunakan untuk mengoptimalkan pembangkit hidro termal area IV sistem kelistrikan Jawa-Bali.

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The operating of an electric power generating system need to be determined power contribution of each unit with the result that it can be operated at a minimum generating cost. This case can be solved by the optimum loading of a power generating system.

This thesis is discussing about an optimum loading of the hydro thermal power generating system by Lagrange Multiplier Method which is limited at hydro thermal plants of Java-Bali fourth area. The objective function is to minimize the generating cost with maximum and minimum generating capacities as the constraint. The computation is being done by MatLab program which is operated on a personal computer along with validation program. The validation has shown that the program which is made, can be used for optimum loading of hydro thermal plants of Java-Bali fourth area."

"The systematic coordination of the operation of a system of hydroelectric generation plants is usually more complex than the scheduling of an all thermal generation system. The reason is both simple and important. In the operation of a hydroelectric power system, three general categories of problems arise. These depend on the balance between the hydroelectric generation, the thermal generation, and the load.

The transmission network's incremental power losses may cause a bias in the optimal economic scheduling of the generators. The coordination equations include the effects of the incremental transmission losses and complicate the development of the proper schedule. The network elements lead to two other, important effects: the total real power loss in the network increases the total generation demand, and the generation schedule may have to be adjusted by shifting generation to reduce flows on transmission circuits because they would otherwise become overloaded. It is the last effect that is the most difficult to include in optimum dispatching.

The requirements for the operation of hydroelectric plants, one must appreciate the limitations imposed on operation of hydro-resources by flood control, navigation, fisheries, recreation, and water supply. The largest category of hydrothermal systems includes those where there is a closer balance between the hydroelectric and thermal generation resources and those where the hydroelectric system is a small fraction of the total capacity. In these systems, the schedules are usually developed to minimize thermal generation production costs, recognizing all the diverse hydraulic constraints that many exist."

"Pemanfaatan Pembangkit Listrik Tenaga Surya (PLTS) telah meningkat dengan signifikan pada satu dekade terakhir. Pada tahun 2014, International Energy Agency (IEA) mencatat bahwa kapasitas pembangkitan PLTS diseluruh dunia telah mencapai 177 GWp, dimana 99%-nya merupakan PLTS on-grid. PLTS on-grid merupakan sistem pemasangan PLTS yang terhubung dengan jaringan utilitas, sehingga dibutuhkan beberapa studi untuk menentukan kapasitas dan lokasi optimal pemasangan PLTS. Pemasangan PLTS dengan kapasitas dan lokasi optimal dapat mengurangi rugi daya saluran sehingga sistem distribusi akan semakin efisien. Penelitian ini bertujuan untuk menginvestigasi karakteristik penurunan nilai rugi daya saluran akibat penetrasi PLTS pada beberapa sistem distribusi radial dan mengembangkan sebuah perhitungan nilai rugi daya saluran terkecil berdasarkan karakteristik tersebut untuk menentukan kapasitas dan lokasi pemasangan optimal PLTS pada sistem distribusi radial. Terdapat 7 sistem distribusi yang diinvestigasi, yaitu 2 sistem distribusi standar The Institute of Electrical and Electronics Engineer (IEEE) dan 5 sistem distribusi Perusahaan Listrik Negara (PLN). Simulasi aliran daya dilakukan pada ke-7 sistem distribusi tersebut dengan menggunakan perangkat lunak DIgSILENT Powerfactory 14.1, dimana data yang diambil adalah data rugi daya saluran. Penetrasi PLTS divariasikan 10% - 100% dan lokasi pemasangan PLTS divariasikan dari bus terdekat gardu induk (GI) sampai bus terjauh dari GI. Karakteristik rugi daya saluran seiring pergeseran lokasi pemasangan PLTS ke ujung penyulang menghasilkan grafik polinomial orde 2 (y = ax2 ? bx + c, a > 0) dan grafik fungsi x dengan pangkat negatif (y = ax-c), sementara seiring kenaikan kapasitas PLTS menghasilkan grafik polinomial orde 2 dengan nilai a > 0. Karakteristik tersebut digunakan pada perhitungan dengan pemrograman C untuk menentukan lokasi dan kapasitas optimal PLTS, dimana hasil penentuan titik optimalnya sesuai dengan hasil perhitungan DIgSILENT Powerfactory 14.1, akan tetapi memiliki perbedaan nilai rugi daya saluran sebesar 11.18%. Berdasarkan perhitungan DIgSILENT, lokasi optimal berada pada nomor bus dengan rentang 42.1% - 89.47% atau rata-rata pada nomor bus 67.25% dari bus GI dengan rentang kapasitas penetrasi optimal 80% - 90%.

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The utilization of photovoltaic (PV) has risen significantly over the last decade. In 2014, International Energy Agency (IEA) reported that the photovoltaic generation capacity had reached 177 GWp around the world, where 99% of it were on-grid. On-grid photovoltaic is a photovoltaic installation system that is connected to the utility grid, therefore some studies are required to determine the optimum photovoltaic capacity and location. An optimum photovoltaic capacity and its location can minimize line loss, therefore the distribution system become more efficient.

This research aims to investigate the line loss reduction characteristics due to photovoltaic penetration on radial distribution grids and develop a minimum line loss calculation based on that characteristics to determine an optimum photovoltaic penetration capacity and location on that grids. 7 distribution grids were investigated: 2 distribution grids from the Institute of Electrical and Electronics Engineer (IEEE) standard and 5 distribution grids from the National Electricity Company of Indonesia (Perusahaan Listrik Negara, PLN).

The load flow simulation was done on these 7 distribution grids by using software DIgSILENT Powerfactory 14.1, where in the line loss data were taken. The photovoltaic penetration was varied from 10% to 100% and the location was varied from the nearest bus until the farthest bus from the substation. The line loss characteristics, corresponding to the shift on photovoltaic location up to the edge of the feeder yields a 2nd order polynomial graph (y = ax2 ? bx + c, a > 0) and an x function graph with a negative order (y = ax-c), wherein corresponding to the rise in photovoltaic capacity yields a 2nd order polynomial graph with a > 0.

These characteristics were used as a reference for making a C programming calculation to determine an optimum photovoltaic capacity and location, wherein the optimum value from C calculation was equal with DIgSILENT calculation, but the line loss calculation has different value 11.18%. Based on DIgSILENT calculation, optimum photovoltaic location was on bus number from 42.1% up to 89.47% or in average was on bus number 67.25% from substation bus, with optimum photovoltaic capacity was from 80% up to 90%."