2021 9th IEEE International Conference on Power Systems (ICPS)最新文献_第7页

Solar Photovoltaic On Water Bodies in Rajasthan 拉贾斯坦邦水体上的太阳能光伏

2021 9th IEEE International Conference on Power Systems (ICPS) Pub Date : 2021-12-16 DOI: 10.1109/ICPS52420.2021.9670248

Vijaya S Kumar, K. Lata, R. Bhakar, Parul Mathuria

引用次数: 0

PSS Tuning of a Radially Connected Hydro Power Plant of Eastern India Using SMIB Model and Phase Compensation Technique 基于SMIB模型和相位补偿技术的东印度径向连接水电站PSS调谐

2021 9th IEEE International Conference on Power Systems (ICPS) Pub Date : 2021-12-16 DOI: 10.1109/ICPS52420.2021.9670011

Saibal Ghosh

{"title":"PSS Tuning of a Radially Connected Hydro Power Plant of Eastern India Using SMIB Model and Phase Compensation Technique","authors":"Saibal Ghosh","doi":"10.1109/ICPS52420.2021.9670011","DOIUrl":"https://doi.org/10.1109/ICPS52420.2021.9670011","url":null,"abstract":"Power systems are very often exposed to large disturbances such as loss of load, loss of transmission lines, and loss of large generating units. Now the main challenge in operating large power system is that running all the generators synchronously even after these disturbances. Generally following a large disturbance different generators respond differently to the disturbance and low frequency oscillation among the generators comes into the picture. Hydro power plants are generally located to very remote hilly area and connected to the electrical grid via long radial transmission lines. Small signal stability issue is sometimes get triggered following some disturbance or during system wide inter-area oscillation. In this paper a radially connected hydro generating station “A” of Sikkim having 3X170 MW installed capacity is studied. Generating station is connected to the grid at a pooling station via two 400 kV twin moose lines. Machine is currently equipped with static excitation and one simple Power system stabilizer model at the site. However excitation system has the provision of activating complex stabilizer model also. Analyzing various past disturbances and low frequency events in the Indian power grid it is found that the performance of the above mentioned generators in damping the local and inter-area oscillation is poor and ranges between 0 to 7 % damping for all the modes. This paper aims at improving the damping of oscillation to 15-25%.","PeriodicalId":153735,"journal":{"name":"2021 9th IEEE International Conference on Power Systems (ICPS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131673816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive Voltage Restrained Overcurrent Relaying for Protection of Distribution System with PV Plant 光伏电站配电系统自适应电压抑制过流继电保护

2021 9th IEEE International Conference on Power Systems (ICPS) Pub Date : 2021-12-16 DOI: 10.1109/ICPS52420.2021.9670077

P. Mishra, A. Pradhan, P. Bajpai

引用次数: 1

Simulation And Analysis Of Solar Based Water Pump System Using Separately Excited DC Motor With Different Converter Topologies 不同变换器拓扑下分励直流电动机太阳能水泵系统仿真与分析

2021 9th IEEE International Conference on Power Systems (ICPS) Pub Date : 2021-12-16 DOI: 10.1109/ICPS52420.2021.9670213

Kalyan Singh Malviya, S. Nema, S. Gawre

引用次数: 0

Stealth Attacks in Microgrids: Modeling Principles and Detection 微电网中的隐形攻击:建模原理与检测

2021 9th IEEE International Conference on Power Systems (ICPS) Pub Date : 2021-12-16 DOI: 10.1109/ICPS52420.2021.9670061

Devakumar Annavaram, Subham S. Sahoo, S. Mishra

引用次数: 1

Load Frequency Control of Two Area Microgrid Using Reinforcement Learning Controller 基于强化学习控制器的两区微电网负荷频率控制

2021 9th IEEE International Conference on Power Systems (ICPS) Pub Date : 2021-12-16 DOI: 10.1109/ICPS52420.2021.9670279

S. Beura, D. Soni, B. Padhy

引用次数: 0

An Improved Crow Search Algorithm to Control MPPT Under Partial Shading Conditions 一种改进的乌鸦搜索算法控制部分遮阳条件下的MPPT

2021 9th IEEE International Conference on Power Systems (ICPS) Pub Date : 2021-12-16 DOI: 10.1109/ICPS52420.2021.9670238

K. Swetha, Abin Robinson, V. Barry, Harish Kumar Varma Gadiraju

引用次数: 2

A hybrid wind speed forecasting model using complete ensemble empirical decomposition with adaptive noise and convolutional support vector machine 基于自适应噪声和卷积支持向量机的完全集合经验分解混合风速预报模型

2021 9th IEEE International Conference on Power Systems (ICPS) Pub Date : 2021-12-16 DOI: 10.1109/ICPS52420.2021.9670394

Vishalteja Kosana, Kiran Teeparthi, M. Santhosh

{"title":"A hybrid wind speed forecasting model using complete ensemble empirical decomposition with adaptive noise and convolutional support vector machine","authors":"Vishalteja Kosana, Kiran Teeparthi, M. Santhosh","doi":"10.1109/ICPS52420.2021.9670394","DOIUrl":"https://doi.org/10.1109/ICPS52420.2021.9670394","url":null,"abstract":"Wind energy is a clean, green energy source that is used effectively in power system grids. Wind forecasting is the key requirement for enhanced integration. Wind speed forecasting is more challenging due to the unpredictable and intermittent nature of the wind. As a result, a robust and novel frame-work is proposed by hybridizing complete ensemble empirical decomposition with adaptive noise (CEEMDAN), convolutional neural network (CNN), and support vector machine (SVM). The CEEMDAN algorithm is used to remove noise from the raw data. Then, to extract the dominating characteristics from the noiseless wind speed data, CNN is used. Finally, SVM forecasts the wind speed. The hybridization of CNN and SVM enhanced the computational efficiency as well as the performance. For comparative analysis, six different state-of-the-art forecasting approaches are employed. An experimental study is carried out utilising real-time 5-minute interval data obtained from Manhattan's Garden City. The proposed framework performance is assessed through various statistical metrics. With relatively low error metrics and higher R2 score, the proposed framework outperformed all other comparative models, according to the experimental results.","PeriodicalId":153735,"journal":{"name":"2021 9th IEEE International Conference on Power Systems (ICPS)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127553776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Analysis of Single and Multiple Line Contingency in a 62 Bus Indian Practical Power System using Track Structure Algorithm Approach 用轨道结构算法分析62母线印度实用电力系统的单线和多线事故

2021 9th IEEE International Conference on Power Systems (ICPS) Pub Date : 2021-12-16 DOI: 10.1109/ICPS52420.2021.9670240

Swasti Bachan Panda, S. Mohanty

引用次数: 0

Wind Power Forecasting using Generalized Autoregressive Score Model 基于广义自回归评分模型的风电预测

2021 9th IEEE International Conference on Power Systems (ICPS) Pub Date : 2021-12-16 DOI: 10.1109/ICPS52420.2021.9670026

Yash Pal, K. Sharma, Archee Gupta, Archita Vijayvargia, R. Bhakar

{"title":"Wind Power Forecasting using Generalized Autoregressive Score Model","authors":"Yash Pal, K. Sharma, Archee Gupta, Archita Vijayvargia, R. Bhakar","doi":"10.1109/ICPS52420.2021.9670026","DOIUrl":"https://doi.org/10.1109/ICPS52420.2021.9670026","url":null,"abstract":"Accurate Wind Power Forecasting (WPF) is essential for the economic operation and planning of electric power systems and electricity markets. Wind power forecasts up to few hours ahead (very short-term) are utilized for optimal operation of power systems. Several time-series models are proposed in the existing literature for Very Short-Term Forecasting (VSTF) of wind power. These include Autoregressive Integrated Moving Average (ARIMA), Generalized Autoregressive Conditional Heteroskedasticity (GARCH), Hybrid ARIMA-GARCH, etc. Although these models are mathematically well off and effective for short-term WPF but not accurate because of their fixed or time-independent parameters. Therefore, this paper presents a novel Generalized Autoregressive Score (GAS) model for WPF considering time-varying parameters. GAS model parameters are updated online for each forecasting lead time by a feedback system. The proposed model is implemented on three Australia-based wind farms and obtained results are compared to benchmark ARIMA and ARIMA-GARCH Hybrid models. The simulated results show that the GAS model has the highest accuracy and offers minimum error followed by ARIMA-GARCH Hybrid, and then ARIMA.","PeriodicalId":153735,"journal":{"name":"2021 9th IEEE International Conference on Power Systems (ICPS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125772551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0