2016 IEEE Smart Energy Grid Engineering (SEGE)最新文献

{"title":"Economic and environmental impact of using hydrogen enriched natural gas and renewable natural gas for residential heating","authors":"S. Walker, Daniel van Lanen, M. Fowler","doi":"10.1109/SEGE.2016.7589528","DOIUrl":"https://doi.org/10.1109/SEGE.2016.7589528","url":null,"abstract":"Natural gas, a fuel source that provides power generation and heating application, offers significant emissions and efficiency improvements over coal. The majority of natural gas is obtained through non-renewable deposits; however, it is possible to generate methane through the creation of Renewable Natural Gas (RNG). RNG is generated when biogas composed of CO2 and CH4 is methanated through the addition of hydrogen. An alternative sustainable pathway, however, is the creation of Hydrogen Enriched Natural Gas (HENG). HENG is created from the addition of hydrogen, in low volume percentages, to create a blend that emits less greenhouse gasses per unit of energy. The hydrogen used to create RNG and HENG can be generated from electrolysis using surplus electricity. Using surplus electricity, during off-peak hours, helps a jurisdiction effectively manage the power grid. As demonstrated through this case study the use of RNG and HENG to be utilized within the natural gas network can create an overall positive impact in any jurisdiction.","PeriodicalId":222683,"journal":{"name":"2016 IEEE Smart Energy Grid Engineering (SEGE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115307688","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}

{"title":"Dynamic simulation of heat losses in a district heating system: A case study in Wales","authors":"Yu Li, Y. Rezgui, Hanxing Zhu","doi":"10.1109/SEGE.2016.7589537","DOIUrl":"https://doi.org/10.1109/SEGE.2016.7589537","url":null,"abstract":"District heating (DH) is a promising energy solution to alleviate environmental negative impacts caused by fossil fuels. Improving the performance of DH systems is one of the major challenges to promote larger scale adoption. This paper presents a dynamic simulation of a DH distribution network located in Ebbw Vale, south Wales. A numerical simulation model is developed in Simscape/Simulink to analyze heat losses in the distribution network at different periods of the week. Results show that heat losses in the network vary between 1-2% during weekday daytime, while they increase to 8-12% at night. Supply and return temperatures of each building are presented and simulation results are in line with measured data. In addition, node flow rates and node temperatures are analyzed. This model can be used to provide reference for selecting the best pipe configuration, including size and insulation materials to minimize heat losses.","PeriodicalId":222683,"journal":{"name":"2016 IEEE Smart Energy Grid Engineering (SEGE)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115640976","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}

{"title":"Direct control method for a PV system integrated in an Indirect Matrix Converter-based UPQC","authors":"Thomas Geury, S. Pinto, J. Gyselinck","doi":"10.1109/SEGE.2016.7589511","DOIUrl":"https://doi.org/10.1109/SEGE.2016.7589511","url":null,"abstract":"This paper proposes a direct control method for a three-phase Photovoltaic (PV) system integrated on the Low-Voltage grid, using an Indirect Matrix Converter (IMC)-based Unified Power Quality Conditioner topology. This topology adds enhanced Power Quality functionality to the PV inverter when connected to a sensitive non-linear load, such as load current harmonics mitigation and voltage sags, swells and harmonics compensation. The PV array is inserted in the DC link of the IMC, which is controlled with a direct sliding mode control method. This direct control allows using a specific modulation method for the shunt converter that guarantees the DC link voltage is adequate for the operation of the IMC. Simulation results are presented to confirm the proper operation of the system under a variety of operating conditions.","PeriodicalId":222683,"journal":{"name":"2016 IEEE Smart Energy Grid Engineering (SEGE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116959138","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}

{"title":"Optimal placement of data aggregators in smart grid on hybrid wireless and wired communication","authors":"Mahsa Tavasoli, M. Yaghmaee, A. Mohajerzadeh","doi":"10.1109/SEGE.2016.7589547","DOIUrl":"https://doi.org/10.1109/SEGE.2016.7589547","url":null,"abstract":"Advanced Metering Infrastructure (AMI) is one of the main applications of smart grids. AMI enables the transmission of commands to smart meters, that is, a two-way communication is established. The meters data is aggregated in some intermediate nodes called Data Aggregation Point (DAP) and then forwarded to the control center. DAP placement is one of the greatest challenges for the smart grid networks. The manual analysis of the best DAPs positions is costly and hard to execute in practice, especially in high-density neighborhoods. General formulation of this problem leads to an NP-hard problem. In the current study, first we investigate some of the existing literatures in this area and then present an optimization problem to find the best location for aggregators in a hybrid wireless and wired communication network including fiber optic and WIMAX. To the best of our knowledge, there is no work that presents an optimal placement of data aggregator in a hybrid wireless and wired network that helps the customers and the microgrid to communicate within themselves with less delay in getting energy services and less overhead to the data aggregator points. Numerical results show that our proposed communication network infrastructure and DAP placement model minimizes cost and data aggregator density.","PeriodicalId":222683,"journal":{"name":"2016 IEEE Smart Energy Grid Engineering (SEGE)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126932326","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}

{"title":"Personalized pricing: A new approach for dynamic pricing in the smart grid","authors":"M. Yaghmaee, Mikhak Samadi Kouhi, A. L. Garcia","doi":"10.1109/SEGE.2016.7589498","DOIUrl":"https://doi.org/10.1109/SEGE.2016.7589498","url":null,"abstract":"Among many key subjects in the smart grid technology, Demand Side Management (DSM) which is one of the common and popular subjects interests researchers on controlling and monitoring customers' consumption activities. In reality, DSM involves any activities that impress customer's consumption levels in a power grid system. This usually happens by means of employing new policies by utility companies, defining suitable pricing schemes that guarantee grid's continual working and using effective scheduling approaches to adjust hourly customer's consumption levels, especially on peak-time hours. Among them, pricing methods are very important and effective in controlling customer's consumption patterns. Real-Time Pricing (RTP) and Time of Use (TOU) pricing are common approaches which are being employed by many utility companies and are mostly dependent on the grid's dynamic load behavior. In addition, real-time pricing methods adjust real-time prices based on grid's real-time demand level dynamically. In this paper, we propose a new pricing method that not only makes use of grid's real-time consumption data but also considers consumption levels of each customer and define real-time prices individually (Personalized Pricing). This means that the consumption price for each individual customer will be adjusted by the changes that occur during the course of power consumption and also reflect each individual customer's habit of using electricity. In this way, our proposed method can consider both grid and individual customer's consumption level to adjust real-time prices. Generally personalized pricing is a type of an incentive-based DSM model that can impress customer's consumption levels by persuading them to decrease their consumption levels during peak-time hours and updating each customer's consumption prices individually. However, individual satisfaction is a more important capability that lies at the heart of Personalized Pricing. Our results also intensify that most of our customers in the grid will decrease their consumption levels during peak-time hours to reduce their electricity consumption costs.","PeriodicalId":222683,"journal":{"name":"2016 IEEE Smart Energy Grid Engineering (SEGE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117164461","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}

{"title":"A stochastic modelling framework to analyze smart grids control strategies","authors":"S. Chiaradonna, F. Di Giandomenico, Giulio Masetti","doi":"10.1109/SEGE.2016.7589512","DOIUrl":"https://doi.org/10.1109/SEGE.2016.7589512","url":null,"abstract":"Smart grids provide services at the basis of a number of application sectors, several of which are critical from the perspective of human life, environment or financials. It is therefore paramount to be assisted by technologies able to analyze the smart grid behavior in critical scenarios, e.g. where cyber malfunctions or grid disruptions occur. In this paper, we present a stochastic modelling framework to quantitatively assess representative indicators of the resilience and quality of service of the distribution grid, in presence of accidental faults and malicious attacks. The results from the performed analysis can be exploited to understand the dynamics of failures and to identify potential system vulnerabilities, against which appropriate countermeasures should be developed. The features of the proposed analysis framework are discussed, pointing out the strong non-linearity of the involved physics, the developed solutions to deal with control actions and the definition of indicators under analysis. A case study based on a real-world network is also presented.","PeriodicalId":222683,"journal":{"name":"2016 IEEE Smart Energy Grid Engineering (SEGE)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115726774","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}

{"title":"Fault diagnosis method of transformer based on cloud theory and entropy weight","authors":"Zhicheng Xie, Kun Yu, Shu Su, Zhengtian Li, Xiangning Lin, Weihong Xiong","doi":"10.1109/SEGE.2016.7589548","DOIUrl":"https://doi.org/10.1109/SEGE.2016.7589548","url":null,"abstract":"In this paper, we propose a method to identify potential faults in power transformers. Firstly, the cloud distribution model of gases under different fault types are established respectively, which are the basis for building the cloud knowledge base. Secondly, the membership grades between test sample and different fault types can be calculated by weighting the gases using entropy weight method. Finally, the effectiveness and the superior data learning ability of this method can be verified by comparing the diagnostic accuracy with three-ratio method introduced by IEEE and the existing cloud method under different amount of samples. The result of this method can provide effective reference for the maintenance planning of transformer.","PeriodicalId":222683,"journal":{"name":"2016 IEEE Smart Energy Grid Engineering (SEGE)","volume":"186 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126941819","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}

{"title":"Smart distribution system Volt/VAR control using the intelligence of smart transformer","authors":"H. Gabbar, K. Sayed","doi":"10.1109/SEGE.2016.7589499","DOIUrl":"https://doi.org/10.1109/SEGE.2016.7589499","url":null,"abstract":"This paper presents the dynamic performance of a smart distribution system. A detailed power distribution system model has been developed with a smart electronic transformer using the MATLAB/ Simulink power systems simulation package. The results are presented using this simulation to illustrate the capability of Smart transformer units to assist with voltage regulation of LV feeders. Low voltage distribution networks are recovered from minor and severe perturbations in the AC system is verified. Simulations conducted on case study network representing a typical 4-wire LV distribution system under different load/generation conditions. The LV network fed on 22 kV distribution system through a smart transformer. The results demonstrate the improving the network power quality levels and eliminate the voltage unbalance.","PeriodicalId":222683,"journal":{"name":"2016 IEEE Smart Energy Grid Engineering (SEGE)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123021339","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}

{"title":"Transient over-voltage protection in distributed generators systems","authors":"Lauren M. Qaisieh, Hazem W. Marar","doi":"10.1109/SEGE.2016.7589190","DOIUrl":"https://doi.org/10.1109/SEGE.2016.7589190","url":null,"abstract":"In distributed generators systems (DGs), islanding condition occurs when generators continue to energize a part of the power network while the main utility power is no longer available. In such situations, transient over-voltage condition might occur when the amount of generated power exceeds the load consumption and hence needs to be mitigated. In this paper, we are proposing a new system consisting of high power MOSFETs configured as a digital potentiometer along with a communication module. A pre-driver circuit is used to enhance the switching response of the system. The system represents a continuous method of dissipating extra power and synchronizes all network data with an online portal for further analysis and computations.","PeriodicalId":222683,"journal":{"name":"2016 IEEE Smart Energy Grid Engineering (SEGE)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134290697","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}

{"title":"Rated energy impact of BESS on total operation cost in a microgrid","authors":"K. Alqunun, P. Crossley","doi":"10.1109/SEGE.2016.7589540","DOIUrl":"https://doi.org/10.1109/SEGE.2016.7589540","url":null,"abstract":"Economic operation of a microgrid is becoming increasingly important due to the rapid increase in the number of microgrids now being investigated and deployed. Energy storage becomes an essential part in microgrids, not only to manage technical challenges, but also to provide economic benefits. A battery energy storage system (BESS) is used in this study, since it is the most flexible and reliable storage device now available in distribution networks. This paper presents an optimization method to minimize the economic operation of a microgrid with BESS. The proposed method defines the relation between the rated energy of the BESS and the total economic operation cost of a microgrid when operating in on-grid and off-grid modes. The optimization formulation applies economic dispatch and unit commitment techniques using mixed integer programming (MIP). The examples studied show the effectiveness of energy storage in the economic operation of a microgrid.","PeriodicalId":222683,"journal":{"name":"2016 IEEE Smart Energy Grid Engineering (SEGE)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131014492","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}