International Journal of Energy Optimization and Engineering最新文献_第4页

Identification of Most Significant Parameter of Impact of Climate Change and Urbanization on Operational Efficiency of Hydropower Plant 气候变化和城市化对水电厂运行效率影响的最显著参数辨识

IF 0.9

International Journal of Energy Optimization and Engineering Pub Date : 2019-07-01 DOI: 10.4018/IJEOE.2019070103

Priyanka Majumder, A. K. Saha

{"title":"Identification of Most Significant Parameter of Impact of Climate Change and Urbanization on Operational Efficiency of Hydropower Plant","authors":"Priyanka Majumder, A. K. Saha","doi":"10.4018/IJEOE.2019070103","DOIUrl":"https://doi.org/10.4018/IJEOE.2019070103","url":null,"abstract":"The operational performance of hydropower plants (HPPs) is largely affected as the output from the plant entirely depends on the rainfall and demand from consumers both of which are compromised due to the vulnerability in climatic patterns and rapid change in urbanization rate. Although, not all the parameters are equally affected and the present study aims to find the degree of impact on the various correlated parameters on which production efficiency of HPPs varies. In this aspect, a neural network concept was used as decision making tool to identify the most significant parameters with respect to change in climate, urbanization along with machine failure because as a combined effect of the first two parameters, the probability of machine failure will also increase. The result from the study provides an opportunity to mitigate the impact that can be caused as a result of climate change impact and change in rate of urbanization. According to the result it was found that Efficiency of Generators is the most significant parameter of impact of climate change and urbanization on operational efficiency of hydropower plant. The result from the scenario analysis suggested that if the A2 scenario becomes true in 2061-70 there will be a maximum decrease in the OE and if land use scenario: PR story line is found to be adopted in the future world of 2020-30 the change in OE will be the greatest (an increase of 6.056%) compared to any other scenario developed for the impact of urbanization followed by land use change scenario of the 2031-40 decade, which will be equal to an increase of 5.247% compared to the baseline.","PeriodicalId":43245,"journal":{"name":"International Journal of Energy Optimization and Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.9,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4018/IJEOE.2019070103","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42274869","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: 2

Location selection for Installation of Surface Water Treatment Plant by Applying a New Sinusoidal Analytical Hierarchy Process 应用新的正弦层次分析法选择地表水处理厂的安装位置

IF 0.9

International Journal of Energy Optimization and Engineering Pub Date : 2019-07-01 DOI: 10.4018/IJEOE.2019070102

Sudipa Choudhury, A. K. Saha

{"title":"Location selection for Installation of Surface Water Treatment Plant by Applying a New Sinusoidal Analytical Hierarchy Process","authors":"Sudipa Choudhury, A. K. Saha","doi":"10.4018/IJEOE.2019070102","DOIUrl":"https://doi.org/10.4018/IJEOE.2019070102","url":null,"abstract":"Water treatment plants (WTPs) are responsible for ensuring supply of healthy water to urban and rural consumers for drinking and other related purposes. But the arbitrary selection of a location for installation or relocation of WTPs often fails the purpose of the plant. Presently studies in location selection for water treatment plant are rare. Multi-criteria decision making (MCDM) methods and bagged polynomial neural networks (PNN) were found to be exemplary and easy to use tools for prediction, simulation and optimization of decision-making objectives. The present study tries to apply the advantages of MCDM and bagged PNNs in the identification of an ideal location for a surface water treatment plant. The most significant parameter is found to be WQI which represents the overall quality of water suitable for domestic use. The PNN models were developed with all the selected eight alternatives as input and output. The algorithms like GMDH, SFS, SMS, and QC were used to estimate the weight of connections in between the input and hidden; and hidden and output layers separately for each segment. The application of these two soft computation tools provides an opportunity to the decision maker in the selection of optimal location with the help of an objective and cognitive method.","PeriodicalId":43245,"journal":{"name":"International Journal of Energy Optimization and Engineering","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4018/IJEOE.2019070102","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42621856","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: 4

Maintaining a Constant Charging Duration Independent of Battery Capacity for Battery Pack by Designing a Fast DC Charger 通过设计快速直流充电器来保持电池组的恒定充电持续时间与电池容量无关

IF 0.9

International Journal of Energy Optimization and Engineering Pub Date : 2019-07-01 DOI: 10.4018/IJEOE.2019070106

Bassam Atieh, Mohammad Fouad Al-sammak

引用次数: 1

Application of Neurogenetic Modeling in Optimization of Water Treatment Plant Based on the Temporal Monitoring of Water Input Quality 神经遗传建模在水处理厂输入水质实时监测优化中的应用

IF 0.9

International Journal of Energy Optimization and Engineering Pub Date : 2019-07-01 DOI: 10.4018/IJEOE.2019070105

Paulami De

{"title":"Application of Neurogenetic Modeling in Optimization of Water Treatment Plant Based on the Temporal Monitoring of Water Input Quality","authors":"Paulami De","doi":"10.4018/IJEOE.2019070105","DOIUrl":"https://doi.org/10.4018/IJEOE.2019070105","url":null,"abstract":"This article addresses methods to adjust operating requirements in water treatment plants (WTPs) in order to increase the efficiency of water treatment plants based on the nature of the water inflows into the systems. In the past, various studies have suggested that the quality of water inflow into the WTP has an impact on the efficiency and economic viability of operating treatment plants. Among all other quality parameters, the concentration of dissolved oxygen (DO) is one of the basic indicators about the overall quality of the water. Identification of a temporal pattern can help the engineers to adapt the WTP operations and can save the unnecessary wasting of plant resources. That is why the present article has proposed a new model that can predict the temporal patterns of various chemical parameters with the help of an analytic neuronal network. The model was applied to the case of a WTP that responds to a peri-urban catchment, leading to regular variations in the DO of water inflow. According to the performance metrics utilized the model was able to predict the temporal pattern at a lag of 1 hour.","PeriodicalId":43245,"journal":{"name":"International Journal of Energy Optimization and Engineering","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4018/IJEOE.2019070105","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44385308","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

Economic Load Dispatch With Multiple Fuel Options and Valve Point Effect Using Cuckoo Search Algorithm With Different Distributions 基于不同分布布谷鸟搜索算法的多燃料选择和阀点效应的经济负荷调度

IF 0.9

International Journal of Energy Optimization and Engineering Pub Date : 2015-01-31 DOI: 10.4018/IJEOE.2020070102

C. Tran, Tam Thanh Dao, Ve Song Vo, T. Nguyen, Tan Phong Ward

引用次数: 19