Differential Protection Scheme for A Micro Grid with Inverter-Type Sources Based On Positive Sequence Fault Currents

There is a large difference in fault current level between the GC and IS mode for a microgrid (MG) with inverter-based distributed generators (IBDGs). The fault currents are minimal in the IS mode owing to the low current-carrying capacity of power electronics devices. Therefore, the coordination of traditional overcurrent (OC) protection is difficult for these two operation modes. Therefore, a comprehensive MG protection scheme should be established to safeguard MG against all kinds of faults. This paper proposes a positive sequence differential current protection scheme as the main protection. The envisioned concept can overcome the protective device coordination problems, and all fault types can be detected during both operation modes of MG, grid-connected (GC), and islanded (IS) for radial and loop configuration. The validation of the proposed design is performed using PSCAD/EMTDC software. The results show that the maximum fault clearing time for the main protection in GC mode and IS mode of 31.5 ms and 34 ms respectively. Compared with other schemes, the proposed scheme has a faster clearing time and is less expensive

Differential Protection Scheme for A Micro Grid with Inverter-Type Sources Based On Positive Sequence Fault Currents

There is a large difference in fault current level between the GC and IS mode for a microgrid (MG) with inverter-based distributed generators (IBDGs). The fault currents are minimal in the IS mode owing to the low current-carrying capacity of power electronics devices. Therefore, the coordination of traditional overcurrent (OC) protection is difficult for these two operation modes. Therefore, a comprehensive MG protection scheme should be established to safeguard MG against all kinds of faults. This paper proposes a positive sequence differential current protection scheme as the main protection. The envisioned concept can overcome the protective device coordination problems, and all fault types can be detected during both operation modes of MG, grid-connected (GC), and islanded (IS) for radial and loop configuration. The validation of the proposed design is performed using PSCAD/EMTDC software. The results show that the maximum fault clearing time for the main protection in GC mode and IS mode of 31.5 ms and 34 ms respectively. Compared with other schemes, the proposed scheme has a faster clearing time and is less expensive

Network reconfiguration for loss reduction with distributed generations using PSO

This paper presents an effective method based on Particle Swarm Optimization (PSO) to identify the switching operation plan for feeder reconfiguration and optimum value of DG size simultaneously. The main objective is to reduce the real power losses and improve the bus voltage profile in the system while satisfying all the distribution constraints. A method based on PSO algorithm to determine the minimum configuration is presented and their impact on the network real power losses and voltage profiles are investigated. To demonstrate the validity of the proposed algorithm, computer simulations are carried out on 33 bus systems and the results are presented and compare with the Genetic Algorithm (GA) method

Object oriented sparse linear solver component for power system analysis

Thls paper describes the develvpment of a sparse linear solver component for solving linear equation In power system analysis. The solver Is developed Into a component by using Object Oriented Programming and Component Based Development methodologies. This component Is then Integrated with the load flow and fault analysis components as power system analysis software. By developing the solver and the power system analyses Into a different component, the engineering analysis becomes Independent from the sparse linear solver. Therefore, the solver can be replaced with other solver, whlth may be proprietary code, or when better or Improved solver becomes available In future. The replacement will not cause any need to modify the load flow and fault analysls·components. By using Component OilSI'd Development, the software becomes flexible to be updated alad ex tended

An Improved Deep Learning Model for Electricity Price Forecasting

Accurate electricity price forecasting (EPF) is important for the purpose of bidding strategies and minimizing the risk for market participants in the competitive electricity market. Besides that, EPF becomes critically important for effective planning and efficient operation of a power system due to deregulation of electricity industry. However, accurate EPF is very challenging due to complex nonlinearity in the time series-based electricity prices. Hence, this work proposed two-fold contributions which are (1) effective time series preprocessing module to ensure feasible time-series data is fitted in the deep learning model, and (2) an improved long short-term memory (LSTM) model by incorporating linear scaled hyperbolic tangent (LiSHT) layer in the EPF. In this work, the time series pre-processing module adopted linear trend of the correlated features of electricity price series and the time series are tested by using Augmented Dickey Fuller (ADF) test method. In addition, the time series are transformed using boxcox transformation method in order to satisfy the stationarity property. Then, an improved LSTM prediction module is proposed to forecast electricity prices where LiSHT layer is adopted to optimize the parameters of the heterogeneous LSTM. This study is performed using the Australian electricity market price, load and renewable energy supply data. The experimental results obtained show that the proposed EPF framework performed better compared to previous techniques

A Smart Under-Frequency Load Shedding Scheme based on Takagi-Sugeno Fuzzy Inference System and Flexible Load Priority

This paper proposes a new smart under frequency load shedding (UFLS) scheme, based on Takagi-Sugeno (TS) fuzzy inference system and flexible load priority. The proposed scheme consists of two parts. First part consists of fuzzy load shed amount estimation module (FLSAEM) which uses TS-fuzzy to estimate the amount of load shed and sends its value to accurate load shedding module (ALSM) to perform accurate load shedding using flexible load priority. The performance of the proposed scheme is tested for intentional islanding case and increment of sudden load in the system. Moreover, the response of the proposed scheme is compared with adaptive UFLS scheme to highlight its advantages. The simulation results show that the proposed UFLS scheme provides the accurate load shedding due to advantage of flexible priority whereas adaptive UFLS scheme due to fixed load priority does not succeed to achieve accurate load shedding.fi=vertaisarvioitu|en=peerReviewed

Influence of Renewable Energy Sources on Day Ahead Optimal Power Flow Based on Meteorological Data Forecast Using Machine Learning: A case study of Johor Province

This article investigates a day ahead optimal power flow considering the intermittent nature of renewable energy sources that involved with weather conditions. The article integrates the machine learning into power system operation to predict precisely day ahead meteorological data (wind speed, temperature and solar irradiance) that influence directly on the calculations of generated power of wind turbines and solar photovoltaic generators. Consequently, the power generation schedulers can make appropriate decisions for the next 24 hours. The proposed research uses conventional IEEE -30-bus as a test system running in Johor province that selected as a test location. algorithm designed in Matlab is utilized to accomplish the day ahead optimal power flow. The obtained results show that the true and predicted values of meteorological data are similar significantly and thus, these predicted values demonstrate the feasibility of the presented prediction in performing the day ahead optimal power flow. Economically, the obtained results reveal that the predicted fuel cost considering wind turbines and solar photovoltaic generators is reduced to 645.34 USD/h as compared to 802.28 USD/h of the fuel cost without considering renewable energy sources. Environmentally, CO2 emission is reduced to 340.9 kg/h as compared to 419.37 kg/h of the conventional system. To validate the competency of the whale optimization, the OPF for the conventional system is investigated by other 2 metaheuristic optimization techniques to attain statistical metrics for comparative analysis

Pemodelan dan Analisis Fault Current Limiter Sebagai Pembatas Arus Hubung Singkat Pada GI Sengkaling Malang

Abstrak— Perkembangan penduduk dan peningkatan ekonomi masyarakat menjadi salah satu penyebab peningkatan kebutuhan energi listrik. Konsekuensinya, ketersediaan sumber dan prasarana penyaluran energi harus dapat memastikan kualitas catu daya listrik kepada pelanggan. Unjuk kerja sistem daya listrik  harus memenuhi standar teknis dan ekonomis yang menjamin keandalan dan penanggulangan gangguan, misalnya hubung singkat, yang mungkin terjadi. Beberapa peralatan yang dikenal dapat digunakan untuk menangani arus gangguan hubung singkat antara lain reaktor berinti udara, sekring, dan pemutus rangkaian.  Peralatan-peralatan proteksi tersebut pada umumnya hanya dapat merespon setelah dua atau tiga siklus dari saat terjadinya arus gangguan hubung singkat. Pada artikel ini dibahas pemodelan dan analisis unjuk kerja suatu peralatan yang dapat merespon arus gangguan dalam waktu kurang dari dua siklus, yaitu fault current limiter (FCL). Contoh penerapan alat ini disimulasikan pada sistem nyata Gardu Induk Sengkaling Malang. Pada kejadian gangguan satu fasa dan tiga fasa, terbukti alat ini dapat membatasi arus gangguan hubung singkat yang melewati saluran dalam setengah siklus awal.  Kata kunci—Fault Current Limiter, sistem distribusi, gangguan satu fasa, gangguan tiga fasa

An islanding detection strategy for distribution network connected with hybrid DG resources

The exponential growth in electricity demand has driven the Distributed Generation (DG) technology a boost in the power system. The use of DG is beneficial to power utilities, DG owners', and end-users in terms of reliability, power quality, and economics. However, to fully utilize the benefits of DGs, some technical issues need to be addressed. Islanding condition is one of the most important issue in this context. Until now, several islanding detection techniques have been proposed for detecting the islanding condition. This paper presents a brief overview of existing islanding detection techniques with their relative merits and demerits. Apart from this, the paper presents an islanding detection strategy suitable for hybrid DG resources of mini-hydro and Bio-Mass. The proposed strategy uses average rate of change of reactive power and load shift strategy to detect islanding of the distribution network. The performance of proposed strategy is validated on various islanding and non-islanding events. The results of proposed strategy are compared with other existing techniques in terms of fast islanding detection, and non-detection zone. The simulation results show that the proposed strategy is effective in detecting islanding phenomenon possesses fast detection and negligible non-detection zone region compared to existing islanding detection techniques. (C) 2015 Elsevier Ltd. All rights reserved