Pub Date : 2019-03-01DOI: 10.1109/esars.2010.5665201
{"title":"Letter of acquisition","authors":"","doi":"10.1109/esars.2010.5665201","DOIUrl":"https://doi.org/10.1109/esars.2010.5665201","url":null,"abstract":"","PeriodicalId":130355,"journal":{"name":"2015 International Conference on Energy Economics and Environment (ICEEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130882445","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}
Pub Date : 2015-03-27DOI: 10.1109/ENERGYECONOMICS.2015.7235082
D. De, Olawole C. Olukunle
For efficient and cost effective utilization Solar energy solar concentrators are vital. These are finding increasing applications in many solar energy applications such as concentrated solar photovoltaics, solar steam power generation, solar energy storage, solar cooking etc. In this brief review we discuss the various types of solar concentrators, their current applications, advantages and disadvantages. We also suggest future new applications of solar concentrators.
{"title":"A brief review of solar concentrators","authors":"D. De, Olawole C. Olukunle","doi":"10.1109/ENERGYECONOMICS.2015.7235082","DOIUrl":"https://doi.org/10.1109/ENERGYECONOMICS.2015.7235082","url":null,"abstract":"For efficient and cost effective utilization Solar energy solar concentrators are vital. These are finding increasing applications in many solar energy applications such as concentrated solar photovoltaics, solar steam power generation, solar energy storage, solar cooking etc. In this brief review we discuss the various types of solar concentrators, their current applications, advantages and disadvantages. We also suggest future new applications of solar concentrators.","PeriodicalId":130355,"journal":{"name":"2015 International Conference on Energy Economics and Environment (ICEEE)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129365442","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}
Pub Date : 2015-03-27DOI: 10.1109/ENERGYECONOMICS.2015.7235075
S. Barpanda, S. C. Saxena, K. Dey, K. V. N. Pawan Kumar
Multiple Power Exchanges were introduced in India in 2008 and began with an hourly bidding structure. This paper details the impact of 15 minute bidding introduced in Power Exchanges in India from April, 2012 on the portfolio management of utilities. A literature survey of international practices has also been carried out. It is observed that the 15 minute bidding has modified the scheduling pattern, ramping behaviour, portfolio management of state utilities, price discovery and helped in integration of renewable energy in the Indian Electricity Market.
{"title":"Impact of sub-hourly bidding in power exchanges in India","authors":"S. Barpanda, S. C. Saxena, K. Dey, K. V. N. Pawan Kumar","doi":"10.1109/ENERGYECONOMICS.2015.7235075","DOIUrl":"https://doi.org/10.1109/ENERGYECONOMICS.2015.7235075","url":null,"abstract":"Multiple Power Exchanges were introduced in India in 2008 and began with an hourly bidding structure. This paper details the impact of 15 minute bidding introduced in Power Exchanges in India from April, 2012 on the portfolio management of utilities. A literature survey of international practices has also been carried out. It is observed that the 15 minute bidding has modified the scheduling pattern, ramping behaviour, portfolio management of state utilities, price discovery and helped in integration of renewable energy in the Indian Electricity Market.","PeriodicalId":130355,"journal":{"name":"2015 International Conference on Energy Economics and Environment (ICEEE)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124752898","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}
Pub Date : 2015-03-27DOI: 10.1109/ENERGYECONOMICS.2015.7235080
G. Tiwari, S. Tiwari, V. Dwivedi, S. Sharma, Vineet Tiwari
Sun is a great source of energy. Solar Energy is non-polluting and one of the most efficient and affordable energy alternatives available today. Solar energy can be utilised in two ways either in the form of thermal energy or electrical energy using photovoltaic (PV). The conversion efficiency of photovoltaic depends upon its operating temperature. The operating temperature of photovoltaic module is maintained as low as possible by withdrawing/utilizing the thermal energy associated with it. The thermal energy available on the PV module can be carried away by flowing any fluid (water, air etc.) above it. This type of system is known as hybrid photovoltaic thermal (PVT) system. In the present study, the analytical expressions for temperature dependent electrical efficiency have been derived for opaque and semitransparent PV module with water flow. Then comparison between efficiencies have been done for different climatic condition of New Delhi, India. Then it is observed that there is remarkable change in efficiency when water is flow on the top of the surface of PV module.
{"title":"Effect of water flow on PV module: A case study","authors":"G. Tiwari, S. Tiwari, V. Dwivedi, S. Sharma, Vineet Tiwari","doi":"10.1109/ENERGYECONOMICS.2015.7235080","DOIUrl":"https://doi.org/10.1109/ENERGYECONOMICS.2015.7235080","url":null,"abstract":"Sun is a great source of energy. Solar Energy is non-polluting and one of the most efficient and affordable energy alternatives available today. Solar energy can be utilised in two ways either in the form of thermal energy or electrical energy using photovoltaic (PV). The conversion efficiency of photovoltaic depends upon its operating temperature. The operating temperature of photovoltaic module is maintained as low as possible by withdrawing/utilizing the thermal energy associated with it. The thermal energy available on the PV module can be carried away by flowing any fluid (water, air etc.) above it. This type of system is known as hybrid photovoltaic thermal (PVT) system. In the present study, the analytical expressions for temperature dependent electrical efficiency have been derived for opaque and semitransparent PV module with water flow. Then comparison between efficiencies have been done for different climatic condition of New Delhi, India. Then it is observed that there is remarkable change in efficiency when water is flow on the top of the surface of PV module.","PeriodicalId":130355,"journal":{"name":"2015 International Conference on Energy Economics and Environment (ICEEE)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121859378","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}
Pub Date : 2015-03-27DOI: 10.1109/ENERGYECONOMICS.2015.7235081
D. De, Olawole C. Olukunle
In this paper Part I we consider the detailed energy dynamics of a thermionic converter heated by solar energy concentrated by a parabolic mirror and compute the total output power for different solar insolation, height of emitter, reflectivity of parabolic mirror, assuming no space charge effect initially. Our theoretical investigation gives for the first time the dependence of the output electric power on height h of the emitter from the base of the parabolic concentrator. The investigation discusses many novel ways the space-charge problem can be tackled and shows method of calculation of efficiencies which is also found to be dependent on solar insolation. Part II of the paper considers in details the effect of space charge on above calculations and the extent of space charge reduction following the novel ways such as gate, magnetic field etc.
{"title":"A theoretical study on solar thermionic (thermo electronic) power conversion with a parabolic concentrator","authors":"D. De, Olawole C. Olukunle","doi":"10.1109/ENERGYECONOMICS.2015.7235081","DOIUrl":"https://doi.org/10.1109/ENERGYECONOMICS.2015.7235081","url":null,"abstract":"In this paper Part I we consider the detailed energy dynamics of a thermionic converter heated by solar energy concentrated by a parabolic mirror and compute the total output power for different solar insolation, height of emitter, reflectivity of parabolic mirror, assuming no space charge effect initially. Our theoretical investigation gives for the first time the dependence of the output electric power on height h of the emitter from the base of the parabolic concentrator. The investigation discusses many novel ways the space-charge problem can be tackled and shows method of calculation of efficiencies which is also found to be dependent on solar insolation. Part II of the paper considers in details the effect of space charge on above calculations and the extent of space charge reduction following the novel ways such as gate, magnetic field etc.","PeriodicalId":130355,"journal":{"name":"2015 International Conference on Energy Economics and Environment (ICEEE)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124183990","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}
Pub Date : 2015-03-27DOI: 10.1109/ENERGYECONOMICS.2015.7235068
Kishan Bhushan Sahay, Vishesh Rana
Short-term load forecasting is an essential instrument in power system planning, operation & control. Many operating decisions are based on load forecasts, such as dispatch scheduling of generating capacity, reliability analysis & maintenance planning for the generators. This paper discusses significant role of artificial intelligence (AI) in short-term load forecasting (STLF), that is, the one hour-ahead forecast of the power system load. A new artificial neural network (ANN) has been designed to compute the forecasted load. Historical electricity load data has been used in the modeling of ANN. The ANN model is trained on hourly data from PJM Electricity Market & UPPCL and tested on out-of-sample data. Simulation results obtained have shown that one hour-ahead forecasts of load using proposed ANN is very accurate with very less error.
{"title":"One hour ahead load forecast of PJM electricity market & UPPCL","authors":"Kishan Bhushan Sahay, Vishesh Rana","doi":"10.1109/ENERGYECONOMICS.2015.7235068","DOIUrl":"https://doi.org/10.1109/ENERGYECONOMICS.2015.7235068","url":null,"abstract":"Short-term load forecasting is an essential instrument in power system planning, operation & control. Many operating decisions are based on load forecasts, such as dispatch scheduling of generating capacity, reliability analysis & maintenance planning for the generators. This paper discusses significant role of artificial intelligence (AI) in short-term load forecasting (STLF), that is, the one hour-ahead forecast of the power system load. A new artificial neural network (ANN) has been designed to compute the forecasted load. Historical electricity load data has been used in the modeling of ANN. The ANN model is trained on hourly data from PJM Electricity Market & UPPCL and tested on out-of-sample data. Simulation results obtained have shown that one hour-ahead forecasts of load using proposed ANN is very accurate with very less error.","PeriodicalId":130355,"journal":{"name":"2015 International Conference on Energy Economics and Environment (ICEEE)","volume":"340 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114809865","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}
Pub Date : 2015-03-27DOI: 10.1109/ENERGYECONOMICS.2015.7235086
N. Singh, Ashutosh Kumar Singh, M. Tripathy
Load forecasting plays a significant role in power system planning. In today's scenario of deregulated electricity market as existing in New South Wales (NSW) Australia, an extremely accurate load/ price forecasting model is required because of several economic and operational advantages. It helps in dealing with the problems of economic load dispatch, unit commitment, protection, etc. Research shows that most of the classical methods are incapable to forecast the load/ price with highest possible precision, as per the expectation of deregulated and complex electricity markets. In this paper, Artificial Neural Network (ANN)-based Short Term Load Forecasting (STLF) model, i.e., ELMAN Neural Network (ELMNN) is developed and tested on NSW Australia data. The performance of the ELMNN-based model is compared with Feed Forward Neural Network (FFNN) and Radial Basis Function Neural Network (RBFNN). It is observed that ELMNN-based load forecasting model produces superior results over other ANN-based models.
{"title":"Short-term load/price forecasting in deregulated electric environment using ELMAN neural network","authors":"N. Singh, Ashutosh Kumar Singh, M. Tripathy","doi":"10.1109/ENERGYECONOMICS.2015.7235086","DOIUrl":"https://doi.org/10.1109/ENERGYECONOMICS.2015.7235086","url":null,"abstract":"Load forecasting plays a significant role in power system planning. In today's scenario of deregulated electricity market as existing in New South Wales (NSW) Australia, an extremely accurate load/ price forecasting model is required because of several economic and operational advantages. It helps in dealing with the problems of economic load dispatch, unit commitment, protection, etc. Research shows that most of the classical methods are incapable to forecast the load/ price with highest possible precision, as per the expectation of deregulated and complex electricity markets. In this paper, Artificial Neural Network (ANN)-based Short Term Load Forecasting (STLF) model, i.e., ELMAN Neural Network (ELMNN) is developed and tested on NSW Australia data. The performance of the ELMNN-based model is compared with Feed Forward Neural Network (FFNN) and Radial Basis Function Neural Network (RBFNN). It is observed that ELMNN-based load forecasting model produces superior results over other ANN-based models.","PeriodicalId":130355,"journal":{"name":"2015 International Conference on Energy Economics and Environment (ICEEE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116887517","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}
Pub Date : 2015-03-27DOI: 10.1109/ENERGYECONOMICS.2015.7235071
Padmanabh Thakur, Ashutosh Kumar Singh
The precise diagnosis of power quality disturbances (PQDs) has now become a significant concern among the utility engineers as well as consumers due to the high cost of downtimes associated with it. Numerous methods, such as, Artificial Intelligence (AI), Signal Processing (SP), Space Vector Representation, Symmetrical Component, have been evaluated for the precise diagnosis of PQDs. Among these methods, AI and SP based techniques have received extensive attention by the researchers and industry engineers. This paper discusses the various AI and SP based methodologies currently used for the diagnosis of PQDs. Existing AI and SP based methods are critically reviewed to highlight their applications, merits, and shortfalls. It is revealed that, besides the numerous applications and merits of these methodologies, none of them is found proficient for the precise diagnosis of PQDs. Accurate recognition of PQDs is still a challenging task. Therefore, the need of incorporation of new techniques for the accurate estimation of PQDs has been asserted.
{"title":"Signal processing and AI based diagnosis of power quality disturbances: A review","authors":"Padmanabh Thakur, Ashutosh Kumar Singh","doi":"10.1109/ENERGYECONOMICS.2015.7235071","DOIUrl":"https://doi.org/10.1109/ENERGYECONOMICS.2015.7235071","url":null,"abstract":"The precise diagnosis of power quality disturbances (PQDs) has now become a significant concern among the utility engineers as well as consumers due to the high cost of downtimes associated with it. Numerous methods, such as, Artificial Intelligence (AI), Signal Processing (SP), Space Vector Representation, Symmetrical Component, have been evaluated for the precise diagnosis of PQDs. Among these methods, AI and SP based techniques have received extensive attention by the researchers and industry engineers. This paper discusses the various AI and SP based methodologies currently used for the diagnosis of PQDs. Existing AI and SP based methods are critically reviewed to highlight their applications, merits, and shortfalls. It is revealed that, besides the numerous applications and merits of these methodologies, none of them is found proficient for the precise diagnosis of PQDs. Accurate recognition of PQDs is still a challenging task. Therefore, the need of incorporation of new techniques for the accurate estimation of PQDs has been asserted.","PeriodicalId":130355,"journal":{"name":"2015 International Conference on Energy Economics and Environment (ICEEE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127659846","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}
Pub Date : 2015-03-27DOI: 10.1109/ENERGYECONOMICS.2015.7235117
J. Singh, C. Vishwakarma, K. Chatterjee
To reduce the order of the large-scale dynamic systems, a method has been proposed by merging improved modified pole clustering and Genetic Algorithm. Reduced order denominator and numerator polynomial is obtained via improved modified pole clustering technique and Genetic Algorithm respectively. The method produces `k' number of reduced order systems for kth - order reduction. A numerical example has been taken from the literature to show the viability of the proposed mixed method and also compared with existing order reduction methods.
{"title":"SISO method using improved modified pole clustering and genetic algorithm","authors":"J. Singh, C. Vishwakarma, K. Chatterjee","doi":"10.1109/ENERGYECONOMICS.2015.7235117","DOIUrl":"https://doi.org/10.1109/ENERGYECONOMICS.2015.7235117","url":null,"abstract":"To reduce the order of the large-scale dynamic systems, a method has been proposed by merging improved modified pole clustering and Genetic Algorithm. Reduced order denominator and numerator polynomial is obtained via improved modified pole clustering technique and Genetic Algorithm respectively. The method produces `k' number of reduced order systems for kth - order reduction. A numerical example has been taken from the literature to show the viability of the proposed mixed method and also compared with existing order reduction methods.","PeriodicalId":130355,"journal":{"name":"2015 International Conference on Energy Economics and Environment (ICEEE)","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134378369","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}
Pub Date : 2015-03-27DOI: 10.1109/ENERGYECONOMICS.2015.7235106
F. Brazier, H. la Poutré, A. Abhyankar, K. Saxena, S. Singh, K. Tomar
This paper proposes the concept of Distributed Energy Resource (DER) management, based on dynamic clustering of energy resources for better coordination of supply and demand. A review on load profiling and forecasting mechanisms is provided which to be utilised in building knowledge, needed for local and global coordination. To avoid large scale complexities, a decentralised control approach with Multi Agent System (MAS) is deployed. A review on MAS technologies and their application in power system is presented. With MAS we provide a framework for designing producer, consumer and cluster agents. These agents further negotiate Service Level Agreements for managing supply and demand and optimally utilizing the energy resources.
{"title":"A review of multi agent based decentralised energy management issues","authors":"F. Brazier, H. la Poutré, A. Abhyankar, K. Saxena, S. Singh, K. Tomar","doi":"10.1109/ENERGYECONOMICS.2015.7235106","DOIUrl":"https://doi.org/10.1109/ENERGYECONOMICS.2015.7235106","url":null,"abstract":"This paper proposes the concept of Distributed Energy Resource (DER) management, based on dynamic clustering of energy resources for better coordination of supply and demand. A review on load profiling and forecasting mechanisms is provided which to be utilised in building knowledge, needed for local and global coordination. To avoid large scale complexities, a decentralised control approach with Multi Agent System (MAS) is deployed. A review on MAS technologies and their application in power system is presented. With MAS we provide a framework for designing producer, consumer and cluster agents. These agents further negotiate Service Level Agreements for managing supply and demand and optimally utilizing the energy resources.","PeriodicalId":130355,"journal":{"name":"2015 International Conference on Energy Economics and Environment (ICEEE)","volume":"5 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134392084","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}
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