Stability Improvement of Single Machine using ANFIS-PSS Based on Feedback-linearization

Electrical power system (EPS) operation always follows load changes which occur within time. Load changes and disturbances cause EPS operation to find a new balance point and before can reach the new balance point, the rotor speed will swing around its synchronous speed. This phenomenon causes the stability of the EPS operation decrease significantly, moreover, when the disturbance is large the machine tend to become unstable. To overcome this problem, it is necessary to add a power system stabilizer (PSS). This research proposes ANFIS-PSS based on feedback-linearization to stabilize the EPS operation. Feedback-linearization is a nonlinear control technique which feedback and limits several outputs in order to make the nonlinear system acts as a linear system. Data from conventional PSS is used to train and to update ANFIS-PSS parameters. Simulation results show an improvement of the stability of single machine model such as decreasing in maximum magnitude of rotor speed at the value of 0.466 rad/s and to reduce the time settling to 5.6 s

GWO-based estimation of input-output parameters of thermal power plants

The fuel cost curve of thermal generators was very important in the calculation of economic dispatch and optimal power flow. Temperature and aging could make changes to fuel cost curve so curve estimation need to be done periodically. The accuracy of the curve parameters estimation strongly affected the calculation of the dispatch. This paper aims to estimate the fuel cost curve parameters by using the grey wolf optimizer method. The problem of curve parameter estimation was made as an optimization problem. The objective function to be minimized was the total number of absolute error or the difference between the actual value and the estimated value of the fuel cost function. The estimated values of parameter that produce the smallest total absolute error were the values of final solution. The simulation results showed that parameter estimation using gray wolf optimizer method further minimized the value of objective function. By using three models of fuel cost curve and given test data, parameter estimation using grey wolf optimizer method produced the better estimation results than those estimation results obtained using least square error, particle swarm optimization, genetic algorithm, artificial bee colony and cuckoo search methods

Dynamic Stability Improvement of Multimachine Power Systems using ANFIS-based Power System Stabilizer

Modern power system are very vurnerable to against load fluctuation during their operation. Load fluctuation identified as small disturbance is important to test dynamic (small signal) stability. This research is focused on improvement of multimachine dynamic stability by using ANFIS-based power system stabilizer (proposed PSS). ANFIS method is proposed because the ANFIS computation is more efective than Mamdani fuzzy computation. Simulation results show that the proposed PSS is able to maintain the dynamic stability by decreasing peak overshoot (Po) to the value -3,37´10-5 pu/pu and accelerating settling time (St) to the time 4.01 s for rotor speed deviation Machine-2. Also, the Po is decreased to the value -3,37´10-5 pu/pu and the St is accelerated to the time 3.98 s for rotor speed deviation Machine-3

Rekonfigurasi Jaringan Distribusi untuk Meminimisasi Rugi-Rugi pada Penyulang Kabut di Gardu Induk Teluk Betung Menggunakan Metode Binary Particle Swarm Optimization (BPSO)

Distribution network reconfiguration is needed to minimize losses, especially in densely populated areas. Various reconfiguration methods and techniques have been proposed for the purpose of minimizing power losses. This paper presents a reconfiguration of the distribution network using the binary particle swarm optimization (BPSO) with a case study in Kabut feeder at the Teluk Betung substation. Reconfiguration is performed only by creating new lines without changing the number of lines. The results showed that with the planned four new lines, BPSO method can find new configuration to further minimizes losses. Active power losses resulting from the new configuration is 47.1043 kW or decreased by 1.81% of active power losses before the reconfiguration, i.e. 47.9477 kW. Voltage profile on each bus is better than those of before reconfiguration, where the minimum voltage obtained is 0.98603 per unit compared with a minimum voltage of 0.98597 per unit prior to reconfiguration. However, the selection of the best initial position of the whole of particle swarms outside loop configuration formed by new lines may cause a failure to find the best configuration.Keywords : Reconfiguration, distribution network, loss minimization, BPSO, feederAbstrak—Rekonfigurasi jaringan distribusi sangat diperlukan untuk mengurangi rugi-rugi khususnya pada daerah yang berpenduduk padat. Berbagai metode dan teknik rekonfigurasi telah diusulkan untuk tujuan meminimalkan rugi-rugi daya. Makalah ini menyajikan rekonfigurasi jaringan distribusi dengan menggunakan metode binary particle swarm optimization (BPSO) dengan studi kasus penyulang Kabut di gardu induk Teluk Betung. Rekonfigurasi dilakukan hanya dengan membuat saluran baru tanpa merubah jumlah saluran. Hasil penelitian menunjukkan bahwa dengan merencanakan empat saluran baru, metode BPSO dapat menemukan konfigurasi baru yang lebih meminimalkan rugi-rugi. Rugi-rugi daya aktif yang dihasilkan dari konfigurasi baru sebesar 47,1043 kW atau berkurang sebesar 1,81% dari rugi-rugi daya aktif sebelum rekonfigurasi, yakni 47,9477 kW. Profil tegangan pada setiap bus juga lebih baik dari tegangan sebelum rekonfigurasi, dimana tegangan minimum yang diperoleh adalah sebesar 0,98603 per unit dibandingkan dengan tegangan minimum 0,98597 per unit sebelum rekonfigurasi. Namun pemilihan posisi awal terbaik dari seluruh kumpulan partikel di luar lup konfigurasi yang dibentuk oleh saluran baru dapat menyebabkan kegagalan untuk menemukan konfigurasi terbaik.Kata Kunci : Rekonfigurasi, jaringan distribusi, minimisasi rugi-rugi, BPSO, penyulan

Aplikasi Fuzzy Type-2 PSS untuk Perbaikan Stabilitas Dinamik Pembangkit Listrik Tenaga Mikro Hidro dan Diesel: Application of Fuzzy Type-2 PSS to Improve Dynamic Stability of Micro Hydro and Diesel Power Plants

Teknologi fuzzy tipe 2 (FT2) berkembang sangat pesat dan memasuki bidang stabilitas sistem tenaga listrik. Pembangkit listrik tenaga mikro hidro (PLTMH) dan diesel (PLTD) riskan terhadap gangguan perubahan beban. Studi stabilitas penting dikerjakan untuk memastikan bahwa operasi PLTMH-PLTD tetap stabil ketika dan setelah beban berubah. Maka power system stabilizer (PSS) berbasis FT2 diusulkan untuk perbaikan stabilitas sistem tersebut. FT2PSS didesain dengan input kecepatan rotor dan derivatifnya. Outputnya adalah sinyal stabilitas yang diumpankan pada sistem eksitasi. Hasilnya, FT2PSS mampu mereduksi overshoot -0,035 deg. Sedangkan overshoot untuk CPSS adalah -0,051 deg. FT2PSS juga dapat mempersingkat settling time dan mempercepat steady state. Stabilitas PLTMH-PLTD yang dilengkapi dengan FT2PSS diperbaiki secara significan

Perbaikan Stabilitas Dinamik Sistem Tenaga Terintegrasi Pembangkit Listrik Tenaga Mikro Hidro dan Diesel Menggunakan PSS Berbasis ANFIS

Power generating units should be built closed to load centers according to electric power company regulation. These units are generally small in capacity, so that makes power transfer among inter- and outer-areas is easier to be done. This study aims to improve dynamic stability of a Micro Hydro Power Plant (MHPP) on perspective of 5% load increased in Diesel Power Plant (DPP). The DPP is equipped by an ANFIS-based Power System Stabilizer (PSS) in this scheme. Two inputs with Gauss2mf membership function (MF) type and 5-number of the each MF are used to implement the ANFIS model. Simulation results show that overshoot of MHPP power angle deviation is reduced to the values of 0.023, 0.0138 and 0.0132°, for the DPP without PSS, conventional and ANFIS PSS, respectively.  Also, reduction in setting time is achieved at times >6, 4.051 and 3.553 s. It is shown that the ANFIS PSS is more effective to enhance the dynamic stability compared to other PS

Bauran Pemasaran Lobster Air Tawar pada Kelompok Petani Agro Crayfish di Denpasar

Marketing Mix of Crayfish on Agro Crayfish Farmers Group in Denpasar The purpose of this study was to determine the application of the marketing mix of crayfish, the obstacles faced, and the strategies in the implementation. This research is descriptive qualitative. Based on the result of research on Agro Crayfish Farmers Group found that the application of the marketing mix in terms of products which is products marketed crayfish includes crayfish for consumption, breeding and nursery transplant. Pricing method is a fixed price. Distribution is defined direct and indirect distribution. The promotion is done by personal selling. The obstacle in product is that many crayfish dies due to cannibalism which could be resolved by feeding regularly. The obstacle in price is when the feed price goes up while the company can't raise the determined price, and to cope with it the company has to get the consumers understanding. The obstacle in distribution is that during delivery there are some crayfish without claws or even dead, and to resolve it the company needs to limit the amount of crayfish per box. The obstacle in promotion is that the promotion done to market the product is not yet maximum, and to overcome it the promotion should be adjusted to the targeted market. Keyword: Marketing Mix, Crayfish, Farmers Grou

Strategy to reduce transient current of inverter-side on an average value model high voltage direct current using adaptive neuro-fuzzy inference system controller

Growing-up of high voltage direct current (HVDC) penetration into modern power systems (PS) makes difficulty on the PS operation. The HVDC produces high and slow transient current (TC) at start-time, especially for higher up-ramp rate (Urr>20 pu/s). Its condition makes the HVDC cannot be linked and synchronized into the PS rapidly. A strategy to reduce the TC is proposed by an adaptive network based fuzzy inference system (ANFIS) control on inverter HVDC-link to cope up this problem. The ANFIS control is tuned with the help of conventional control in various train-data by using offline mode. Response of ANFIS scheme is improved by suppressing TC at the values of 3.75% for the both phases (A and C), and 3.95% for phase B, for the Urr=30 pu/s. While the conventional control achieved at 9.1% for the both phases (A and B), and 9.2% for the phase C. The ANFIS control gives shorter settling time (0.553 s) than the conventional control (0.584 s) for all phases. The proposed control is more effective than the conventional control at all the scenario

PELATIHAN ARDUINO PADA SISWA SMA 1 MATARAM UNTUK MENGUKUR KADAR AMONIA DAN SUHU TUBUH VIA MODUL BLUETOOTH

SMAN 1 Mataram merupakan sekolah favorit di Lombok yang menetapkan visinya: “Mencetak pribadi berakhlak mulia yang unggul dalam prestasi dan berwawasan lingkungan”. Dalam rangka mengejar peningkatan prestasi siswa, sekolah memfasilitasi berbagai kegiatan ekstrakurikuler, dan salah satunya ekstrakurikuler Ristek. Dalam rangka memonitor tingkat pencemaran lingkungan diperlukan peralatan yang dapat mengukur kadar polusi udara. Bersama Mitra (SMAN 1 Mataram) tim Pengabdian Kepada Masyarakat memberikan pelatihan sistem komunikasi data dengan memanfaatkan koneksi Bluetooth untuk pengiriman data hasil pengukuran kadar amonia dan suhu tubuh ke terminal handphone. Tim pangabdian melakukan pendampingan pada siswa SMAN 1 Mataram, khususnya ekstrakurikuler Ristek. Kegiatan pendampingan diharapkan dapat meningkatkan ketrampilan siswa tentang Arduino. Metode yang digunakan dengan cara menyediakan modul peraga yang bersifat bongkar pasang dan praktik langsung mengenai perangkat keras dan perangkat lunak. Berdasarkan analisis instrumen kuisioner yang sudah diedarkan, terjadi peningkatan pengetahuan nilai antara pretest dan posttest 28 peserta. Rerata nilai pretest sebesar 44,29 dengan standar deviasi 11,60. Sedangkan nilai rerata posttest sebesar 73,79 dengan standar deviasi 11,71. Kemampuan keterampilan siswa secara individu dalam kesempatan ini tidak diamati, namun secara kelompok terlihat ada tambahan skill peserta. Antusias peserta cukup baik,  ditunjukkan dengan hasil kuisioner yang menyatakan sebanyak 11 peserta atau 39,29% menginginkan pelatihan lanjutan perangkat keras dan dasar pemrograman android. Ada 2 peserta yang menginginkan pelatihan coding/scrip pemrograman

Rancang Bangun Smart Energy Meter Berbasis UNO dan Raspberry Pi

Smart energy meter (SEM) is developed to the transparency goal of energy consumption by consumers for tariff strategy. The tariff strategy is designed based on the type of consumer load that per-kWh energy price difference for linear and nonlinear loads. Energy conscious awareness is built by displaying all load power consumption information from consumer loads such as voltage, current, power factor, load properties, load type, power, volt-ampere distortion, power factor distortion, THD, current and voltage waveforms, and harmonic frequency spectrum. The SEM is designed using ZMCT103C and ZMPT101B for current and voltage sensors, respectively. The SEM security function uses the SW420 vibrating sensor, open/close bolt sensor on the chasing and electronic lock. The results show that error measurement of the voltage sensor, current sensor, and power factor are 0.8%, 1.5%, and 1.0% respectively. The SEM security works well as the information on maintenance and criminal actions are informed on screen and buzzer sound for criminal acts. The tariff strategy for linear and nonlinear loads is used to calculate the energy cost per-kWh. The details of load energy consumption are stored in a database