2022 22nd National Power Systems Conference (NPSC)最新文献_第8页

A Direct Search Nelder Mead MPPT based Induction Motor Drive for Solar PV Water Pumping Systems 基于直接搜索Nelder Mead MPPT的太阳能光伏水泵系统感应电机驱动

2022 22nd National Power Systems Conference (NPSC) Pub Date : 2022-12-17 DOI: 10.1109/NPSC57038.2022.10069049

K. Swetha, Barry Venugopal Reddy, R. Jain

引用次数: 0

Development of Online Coherency Detection Algorithm 在线相干检测算法的发展

2022 22nd National Power Systems Conference (NPSC) Pub Date : 2022-12-17 DOI: 10.1109/NPSC57038.2022.10069075

Rutuja Powar, P. Gawande, S. Dambhare

引用次数: 0

Effective Reactive Power Reserve Procurement for Economic Operation of MTDC-AC Systems MTDC-AC系统经济运行的有效无功储备采购

2022 22nd National Power Systems Conference (NPSC) Pub Date : 2022-12-17 DOI: 10.1109/NPSC57038.2022.10069652

Suraj Kumar Gadari, Sumit Kumar, D. Kiran, Manmohan Singh

{"title":"Effective Reactive Power Reserve Procurement for Economic Operation of MTDC-AC Systems","authors":"Suraj Kumar Gadari, Sumit Kumar, D. Kiran, Manmohan Singh","doi":"10.1109/NPSC57038.2022.10069652","DOIUrl":"https://doi.org/10.1109/NPSC57038.2022.10069652","url":null,"abstract":"The reactive power reserve (RPR) procurement is essential in multi-terminal high-voltage direct current-alternating current (MTDC-AC) systems, considering the voltage source converter (VSC) stations, phase reactors and AC lines. Therefore, this paper proposes an optimal power flow (OPF) model for economical, effective reactive power reserve (EQR) procurement in the MTDC-AC systems. The model consists of two stages. The first stage generates economic active-power base-case dispatch points. The second stage is a multi-objective function that maximizes the EQR while minimizing the deviation of active power from its economic base case obtained in stage 1. Compared to the existing models, the constraints for this OPF model are simplified with a modified Y-Bus matrix. This modification includes the converter AC buses in the conventional Y-Bus matrix. Two variations of the proposed method are presented, one for constant reactive power reserve (CQR) and another for EQR. These two models are compared with three existing methods. The model is implemented on the IEEE 14-Bus system for validation.","PeriodicalId":162808,"journal":{"name":"2022 22nd National Power Systems Conference (NPSC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114883865","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

Day-ahead Solar Power Generation Forecasting using LSTM and Random Forest Methods for North Eastern Region of India 基于LSTM和随机森林方法的印度东北地区太阳能发电日前预测

2022 22nd National Power Systems Conference (NPSC) Pub Date : 2022-12-17 DOI: 10.1109/NPSC57038.2022.10069833

N. Roy, P. Tripathy, Samar Chandra De, Bimal Swargiary, Subhash Kumar, Sangita Das, Namrata Pathak

{"title":"Day-ahead Solar Power Generation Forecasting using LSTM and Random Forest Methods for North Eastern Region of India","authors":"N. Roy, P. Tripathy, Samar Chandra De, Bimal Swargiary, Subhash Kumar, Sangita Das, Namrata Pathak","doi":"10.1109/NPSC57038.2022.10069833","DOIUrl":"https://doi.org/10.1109/NPSC57038.2022.10069833","url":null,"abstract":"A tremendous increase in the renewable energy capacity addition worldwide has been observed in the recent times. India is also aiming to make renewables, the major source of power to meet its ever-increasing power demand. At present, while the total solar installed capacity of the country is around 58 GW with a daily average generation of around 200 MU, the North Eastern Region (NER) of the country has only 204 MW of solar power installed capacity as in the year 2022. Assam is one of the leading states in NER for installing solar photovoltaic (PV) independent solar parks connected to high voltage systems with an installed capacity of 199 MW. There is a huge potential in NER for adding more solar power capacity in the future. In this paper, Block-wise (15-minutes) Day ahead Solar Power generation is forecasted for Rowta PV plant in Assam using Long Short Term Memory (LSTM) and Random Forest (RF) methods for a week considering the available weather data of NER. The objective of this paper is to provide a reliable method of forecasting for System Operators and Generating utilities that can ease the process of day ahead solar power forecasting. In terms of overall forecasting error, LSTM emerges as the better forecasting technique compared to Random Forest method. The approach is validated through SCADA data from Rowta PV plant. The performance of LTSM method is further compared with NARX with exogenous input method, another popular ANN method in the field of forecasting. Forecast results by these two methods for a day have also been presented in this paper.","PeriodicalId":162808,"journal":{"name":"2022 22nd National Power Systems Conference (NPSC)","volume":"435 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133467408","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: 1

A Comparative Analysis of Hold Out, Cross and Re-Substitution Validation in Hyper-Parameter Tuned Stochastic Short Term Load Forecasting 超参数调优随机短期负荷预测的保留、交叉和再替代验证比较分析

2022 22nd National Power Systems Conference (NPSC) Pub Date : 2022-12-17 DOI: 10.1109/NPSC57038.2022.10069288

B. V. S. Vardhan, M. Khedkar, P. Thakre

{"title":"A Comparative Analysis of Hold Out, Cross and Re-Substitution Validation in Hyper-Parameter Tuned Stochastic Short Term Load Forecasting","authors":"B. V. S. Vardhan, M. Khedkar, P. Thakre","doi":"10.1109/NPSC57038.2022.10069288","DOIUrl":"https://doi.org/10.1109/NPSC57038.2022.10069288","url":null,"abstract":"Analysis of load plays an important role in the operation of modern power systems due to its highly intermittent nature. This manuscript proposes the best approach by comparing results of Hold out, Cross and Re-Substitution validation from hyperparameter tuned Short Term Load Forecasting (STLF). Tree, Neural Network and GPR (Gaussian Process Regression) are three stochastic regression methods used. Each validation procedure is compared with every considered regression method, leading to 9 such combinations. Each combination is analysed with statistical parameters like RMSE (Root Mean Square Error), R Squared, MSE(Mean Square Error), MAE (Mean Absolute Error) and training time. The best approach is further optimised by modifying hyper parameters using Bayesian, Grid Search, and Random Search and most suitable method is proposed. The simulations are performed in Python and MATLAB platforms. The best combination for computation of STLF is K-fold validation with Tree Regression The statistical parameters obtained from the combination are RMSE, R Squared, MSE, MAE and training time of 0.077, 0.88, 0.0059, 0.046, 1.2 respectively. The best method for hyper-parameter tuning is found out to be Grid search with a reduced MSE of 0.0023.","PeriodicalId":162808,"journal":{"name":"2022 22nd National Power Systems Conference (NPSC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122179750","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

TOU Price based Optimal Scheduling of EV Clusters 基于分时电价的电动汽车集群最优调度

2022 22nd National Power Systems Conference (NPSC) Pub Date : 2022-12-17 DOI: 10.1109/NPSC57038.2022.10069334

Abhishek Jain, Bhavana Jangid, Chandra Prakash Barala, R. Bhakar, Parul Mathuria

{"title":"TOU Price based Optimal Scheduling of EV Clusters","authors":"Abhishek Jain, Bhavana Jangid, Chandra Prakash Barala, R. Bhakar, Parul Mathuria","doi":"10.1109/NPSC57038.2022.10069334","DOIUrl":"https://doi.org/10.1109/NPSC57038.2022.10069334","url":null,"abstract":"The widespread adoption of Electric Vehicles (EVs) and their uncoordinated simultaneous charging puts additional stress on the grid due to an increase in peak load. The charging schedule of EVs can be coordinated by an EV Aggregator (EVA) through appropriate price signals. This paper presents an optimal scheduling framework for EV clusters using Time-of-use (TOU) price. Firstly, the EVA aggregates the total demand corresponding to the vehicle's arrival and departure times for optimal power scheduling using clustering algorithms. The accuracy of cluster-based aggregation plays a vital role, hence this study adopts the advanced clustering technique: spectral clustering algorithm, to accurately cluster the EVs. However, the optimal EV scheduling is motivated by dynamic prices like Real-Time Price (RTP) and Time of Use (TOU) but the acceptance rate of RTP is quite less due to its highly volatile nature. Hence, the proposed work focuses on the optimal scheduling of EV clusters based on TOU prices. For this, the historical data of RTPs are considered for TOU price design using hierarchical clustering. For the case study, 500 EVs are aggregated using spectral clustering and compared with the traditional k-means. The aggregation results are analyzed using Principal Component Analysis (PCA) decomposition; highlighting the increased accuracy of aggregation in terms of time. Further, the optimal scheduling of EV clusters is achieved based on the proposed pricing and aggregation strategies.","PeriodicalId":162808,"journal":{"name":"2022 22nd National Power Systems Conference (NPSC)","volume":"33 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123570270","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: 1

Coordinated Bidding Strategy of an Integrated Wind-Thermal-Solar System using Cooperative Game Theory 基于合作博弈论的风-热-太阳能一体化系统协同竞价策略研究

2022 22nd National Power Systems Conference (NPSC) Pub Date : 2022-12-17 DOI: 10.1109/NPSC57038.2022.10069215

Vikram Singh, M. Fozdar

引用次数: 0

Optimal Placement of DG for a Distribution System Operating under Regulated Monopoly 垄断管制下配电系统DG的最优配置

2022 22nd National Power Systems Conference (NPSC) Pub Date : 2022-12-17 DOI: 10.1109/NPSC57038.2022.10069966

Aprajay Verma, K. Swarup

引用次数: 0

Demand Response of HVAC Systems Using Data-Driven Approaches and Modelling Procedure 基于数据驱动方法和建模程序的暖通空调系统需求响应

2022 22nd National Power Systems Conference (NPSC) Pub Date : 2022-12-17 DOI: 10.1109/NPSC57038.2022.10069640

Rajat Agarwal, Chandra Prakash Barala, Parul Mathuria, R. Bhakar, Vinod Sahai Pareek

{"title":"Demand Response of HVAC Systems Using Data-Driven Approaches and Modelling Procedure","authors":"Rajat Agarwal, Chandra Prakash Barala, Parul Mathuria, R. Bhakar, Vinod Sahai Pareek","doi":"10.1109/NPSC57038.2022.10069640","DOIUrl":"https://doi.org/10.1109/NPSC57038.2022.10069640","url":null,"abstract":"Demand Response (DR) from Heating, Ventilation, and Air-Conditioning (HVAC) systems is quantified by studying performance of energy buildings. Physical models, hybrid methods and data-driven approaches are used to predict the performance of building energy. Physical models require numerical equations that account for specific physical attributes and characteristics of building envelope materials. While the physical models are advantageous in describing heat transfer mechanisms, they are time-consuming, require expertise, are difficult to make proper assumptions and may not adapt to environmental or socio-economic variabilities. Hybrid models have similar drawbacks as physical models and require expertise and improper assumptions. But, data-driven approaches build models based on statistical data and overcome the shortcomings of model-based and hybrid approaches. Due to these advantages, data-driven approaches have gained popularity in recent years. In this context, this paper attempts to summarise and develop an overarching view of data-driven approach for building DR. Moreover, this review highlights the comparison of model-based and data-driven approaches for building DR and highlights the key benefits of the data-driven approach for building DR in power systems.","PeriodicalId":162808,"journal":{"name":"2022 22nd National Power Systems Conference (NPSC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128036946","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

Sequence Current Components Based Directional Relaying Technique for Unsymmetrical Faults 基于顺序电流分量的非对称故障定向继电保护技术

2022 22nd National Power Systems Conference (NPSC) Pub Date : 2022-12-17 DOI: 10.1109/NPSC57038.2022.10069934

Akshat Saini, Suryanarayana Gangolu

{"title":"Sequence Current Components Based Directional Relaying Technique for Unsymmetrical Faults","authors":"Akshat Saini, Suryanarayana Gangolu","doi":"10.1109/NPSC57038.2022.10069934","DOIUrl":"https://doi.org/10.1109/NPSC57038.2022.10069934","url":null,"abstract":"The transmission line protection schemes should offer better reliability, sensitivity, selectivity, and stability and be economical with high operation speed. Directional relays play a vital role in protecting the transmission line. In this paper, a highly efficient current-based directional protection algorithm is introduced. The proposed technique does not use the pre-fault data, and only the post-fault current signal is utilized; hence, it can successfully work under CVT transients and close-in faults. In this technique, the ratio of negative to positive (RNP) sequence post-fault current phasor is defined for fault detection. The trajectory of the ratio outside the specified security region decides the occurrence of the fault, i.e., forward or reverse unsymmetrical faults. Simulation results are carried out considering the different values of fault resistance and fault location with various unsymmetrical faults. These simulation trials have been conducted using PSCAD and MATLAB 2019a software. The comparative analysis with previous similar proposed techniques is presented. Simulation results under various operating conditions confirm the effectiveness and accuracy of the proposed technique.","PeriodicalId":162808,"journal":{"name":"2022 22nd National Power Systems Conference (NPSC)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124230953","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