2022 26th International Electrical Power Distribution Conference (EPDC)最新文献_第2页

Improving the power quality of the distribution network using the optimal placement of the electric car parking 通过优化电动汽车停车位置，提高配电网电能质量

2022 26th International Electrical Power Distribution Conference (EPDC) Pub Date : 2022-05-11 DOI: 10.1109/epdc56235.2022.9817201

A. Seif

引用次数: 0

Double Learning for Suppliers' Bidding Strategy in the Electricity Market 电力市场中供应商竞价策略的双重学习

2022 26th International Electrical Power Distribution Conference (EPDC) Pub Date : 2022-05-11 DOI: 10.1109/epdc56235.2022.9817339

Amir Bayati, M. Naghibi-Sistani

{"title":"Double Learning for Suppliers' Bidding Strategy in the Electricity Market","authors":"Amir Bayati, M. Naghibi-Sistani","doi":"10.1109/epdc56235.2022.9817339","DOIUrl":"https://doi.org/10.1109/epdc56235.2022.9817339","url":null,"abstract":"In this article, we have simulated an agent-based model to investigate the bidding behavior of generation companies (GenCos) in the electricity market under different pricing rules. In a real electricity market, they do not have complete information about the behavior of competitors and therefore make their own decisions based on information that exists on the market-clearing price (MCP) from the past. So considering of high ability of reinforcement learning (RL) algorithms for making decisions on issues with incomplete information, the behavior of companies has been simulated with RL algorithms. In addition, to remove the maximization bias in usual algorithms, we have used the double learning technique for unbiased estimation. The results have shown that companies using Double Q-learning and Double SARSA algorithms, can gain optimal values with unbiased estimation. Furthermore, we investigated market-clearing mechanisms with different pricing rules under an equal rationing policy, in terms of competitiveness in the market and total profit of GenCos. The results showed that in terms of competitiveness, the uniform pricing rule causes more competitive bid prices. However, from the side of the total profit of GenCos, it was seen that with changing from the uniform pricing to the pay-as-bid (P AB), the total profit of companies would reduce.","PeriodicalId":395659,"journal":{"name":"2022 26th International Electrical Power Distribution Conference (EPDC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129800808","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

Energy Management System in Residential Microgrid Using MPC with Considering Uncertainties 考虑不确定性的MPC住宅微电网能源管理系统

2022 26th International Electrical Power Distribution Conference (EPDC) Pub Date : 2022-05-11 DOI: 10.1109/epdc56235.2022.9817190

Mohammad Amin Gharibi, H. Abyaneh

引用次数: 2

Condition Monitoring of Distribution Transformers Using Frequency Response Traces and Artificial Neural Network to Detect the Extent of Windings Axial Displacements 基于频率响应迹线和人工神经网络的配电变压器状态监测

2022 26th International Electrical Power Distribution Conference (EPDC) Pub Date : 2022-05-11 DOI: 10.1109/epdc56235.2022.9817296

Reza Behkam, H. Karami, M. S. Naderi, G. B. Gharehpetian

{"title":"Condition Monitoring of Distribution Transformers Using Frequency Response Traces and Artificial Neural Network to Detect the Extent of Windings Axial Displacements","authors":"Reza Behkam, H. Karami, M. S. Naderi, G. B. Gharehpetian","doi":"10.1109/epdc56235.2022.9817296","DOIUrl":"https://doi.org/10.1109/epdc56235.2022.9817296","url":null,"abstract":"Distribution transformers are of great importance in power systems regarding electrical power supply to the consumers. To have a reliable and continuous service, monitoring of transformers is a crucial issue. Maloperation or improper transportation can result in mechanical tension and stress on transformer windings. Axial displacement (AD) is one of the mechanical defects that can influence transformer operation through windings insulation degradation and short circuit faults. Frequency response analysis (FRA) is an efficient diagnostic technique widely used in transformers monitoring; however, interpretation of FRA results is complicated and is still under investigation. In this paper, AD faults are implemented on the 20 kV winding of a 1600 kV A distribution transformer. FRA traces are practically measured, and then the most sensitive and appropriate statistical indices such as cross-correlation factor (CCF), Lin's concordance coefficient (LCC), sum of errors (SE), and fitting percentage (FP) are employed to extract feature sets. All four components of the frequency responses, i.e., magnitude, phase, real and imaginary parts, are considered. Furthermore, an Artificial Neural Network using the obtained feature vectors is designed to detect the extent of the AD faults. The K-fold cross-validation method is used to evaluate the performance of the intelligent classifier. Both of the most suitable statistical indexes and frequency response components to detect the AD faults are determined.","PeriodicalId":395659,"journal":{"name":"2022 26th International Electrical Power Distribution Conference (EPDC)","volume":"352 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122842351","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

ELD of Power Network in Southwest of Iran (Khuzestan Province) Using JAY A Technique 基于JAY A技术的伊朗西南部胡齐斯坦省电网ELD研究

2022 26th International Electrical Power Distribution Conference (EPDC) Pub Date : 2022-05-11 DOI: 10.1109/epdc56235.2022.9817300

A. Sina, Mehdi Yavarirad, Damanjeet Kaur

{"title":"ELD of Power Network in Southwest of Iran (Khuzestan Province) Using JAY A Technique","authors":"A. Sina, Mehdi Yavarirad, Damanjeet Kaur","doi":"10.1109/epdc56235.2022.9817300","DOIUrl":"https://doi.org/10.1109/epdc56235.2022.9817300","url":null,"abstract":"Power load flow studies are the mainstays of analyzing and designing power systems, and doing so is essential for scheduling production between power companies and economic utilization. The distribution of economic load in today's world is the most important goal of energy distribution in dispatching centers. In industry, the production capacity of generators is usually much larger than the loads, so the allocation of loads in the generator can be varied. Since reducing the cost of electricity generation is important and the highest cost of production is related to the cost of fuel, so load sharing must be done economically. Finally, energy distribution professionals must take control of power plant production at the lowest cost. In this paper, the Economic Load Dispatch (ELD) problem of a sample power system is investigated by JA YA effective computational algorithm and the results are compared with Lambda iteration method. Theoretical backgrounds and mathematical formulations for these two methods are also provided. The power system studied in this research is the power network of southwestern Iran (Khuzestan province), which includes eight power plants. These calculations are performed by excluding network losses as well as by continuously assuming the cost function of power plants. Finally, the fuel cost of the power plants of the sample power system is compared using the JA YA algorithm and the classical Lambda iteration method. Comparison of the obtained results shows that these two methods are suitable in providing efficient solutions to economic load distribution problems in large electricity networks. All simulations have been performed in MATLAB software.","PeriodicalId":395659,"journal":{"name":"2022 26th International Electrical Power Distribution Conference (EPDC)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121457565","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