Pub Date : 2020-01-15DOI: 10.5772/intechopen.88812
N. Kannan
A microgrid has a group of electrical generation and various types of loads operated as single controllable power system. Microgrid is a best option for configuration of recent model power grids. Microgrids are capable of work in parallel with the existing grid as well as off grid as isolated mode. The microgrid enables the grid connection as either AC grid or DC grid and it provides connections of variable AC and DC sources with loads. Microgrid has modeled such a way that it avoids multiple reverse connections. Power electronic devices such as converters and inverters are ensures safe operation and control of the microgrid. The proper modeling and simulation results ensure the successful implementation of microgrid. The challenges involved in implementation and the modeling of AC/DC and hybrid grid in the tied mode have been discussed. The simulation modeling of the microgrid in MATLAB/SIMULINK platform is explained with neat circuit diagram. This chapter provides the readers complete and comprehen-sive overview about microgrids and their different modes of operations.
{"title":"Microgrid","authors":"N. Kannan","doi":"10.5772/intechopen.88812","DOIUrl":"https://doi.org/10.5772/intechopen.88812","url":null,"abstract":"A microgrid has a group of electrical generation and various types of loads operated as single controllable power system. Microgrid is a best option for configuration of recent model power grids. Microgrids are capable of work in parallel with the existing grid as well as off grid as isolated mode. The microgrid enables the grid connection as either AC grid or DC grid and it provides connections of variable AC and DC sources with loads. Microgrid has modeled such a way that it avoids multiple reverse connections. Power electronic devices such as converters and inverters are ensures safe operation and control of the microgrid. The proper modeling and simulation results ensure the successful implementation of microgrid. The challenges involved in implementation and the modeling of AC/DC and hybrid grid in the tied mode have been discussed. The simulation modeling of the microgrid in MATLAB/SIMULINK platform is explained with neat circuit diagram. This chapter provides the readers complete and comprehen-sive overview about microgrids and their different modes of operations.","PeriodicalId":158868,"journal":{"name":"Research Trends and Challenges in Smart Grids","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124374233","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 : 2020-01-15DOI: 10.5772/intechopen.86496
A. Vaccaro, Antonio Pepiciello, A. Zobaa
Modern power systems are facing several challenges related to the transition from a traditional, fossil fuel-based, and vertically integrated architecture to a smart, sustainable, renewable generation-based, and deregulated system. Smart grid is the key concept that allows this transition and enables a series of innovative applications thanks to the integration of information and communication technologies into power systems. Smart grids involve two-way electric and information flows across generation, transmission, distribution, and utilization systems, to improve their efficiency, sustainability, reliability, and resilience compared to traditional grids. The attribute “smart” reflects the layer of intelligence added to the power system that is able to sense power system’s conditions, interact with producers and users, and react to any unexpected conditions. Figure 1 describes the main differences between traditional and smart grids [1–3]. The concept of a smart grid was developed in order to reach a set of goals:
{"title":"Introductory Chapter: Open Problems and Enabling Methodologies for Smart Grids","authors":"A. Vaccaro, Antonio Pepiciello, A. Zobaa","doi":"10.5772/intechopen.86496","DOIUrl":"https://doi.org/10.5772/intechopen.86496","url":null,"abstract":"Modern power systems are facing several challenges related to the transition from a traditional, fossil fuel-based, and vertically integrated architecture to a smart, sustainable, renewable generation-based, and deregulated system. Smart grid is the key concept that allows this transition and enables a series of innovative applications thanks to the integration of information and communication technologies into power systems. Smart grids involve two-way electric and information flows across generation, transmission, distribution, and utilization systems, to improve their efficiency, sustainability, reliability, and resilience compared to traditional grids. The attribute “smart” reflects the layer of intelligence added to the power system that is able to sense power system’s conditions, interact with producers and users, and react to any unexpected conditions. Figure 1 describes the main differences between traditional and smart grids [1–3]. The concept of a smart grid was developed in order to reach a set of goals:","PeriodicalId":158868,"journal":{"name":"Research Trends and Challenges in Smart Grids","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117263939","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 : 2019-10-17DOI: 10.5772/intechopen.88718
S. Castaño-Solis, D. Serrano-Jiménez, J. Fraile-Ardanuy, David Jiménez-Bermejo, J. Sanz-Feito
In this chapter, a hybrid modeling procedure of Li-ion battery modules is presented. From experimental results, the parameters of an electrical circuit have been determined by means of time- and frequency-domain tests. In this way, the dynamic behavior of the battery-pack is modeled. The tests have been performed at the whole battery-pack, instead of a single-cell approach, in order to consider the packaging effects of multicell devices. The real performance of the battery-pack under dynamic applications associated with distribution grids has been simulated using a hardware-in-the-loop (HIL) experimental setup. According to simulation results, the hybrid model follows the battery-pack response with high accuracy.
{"title":"Hybrid Modeling Procedure of Li-Ion Battery Modules for Reproducing Wide Frequency Applications in Electric Systems","authors":"S. Castaño-Solis, D. Serrano-Jiménez, J. Fraile-Ardanuy, David Jiménez-Bermejo, J. Sanz-Feito","doi":"10.5772/intechopen.88718","DOIUrl":"https://doi.org/10.5772/intechopen.88718","url":null,"abstract":"In this chapter, a hybrid modeling procedure of Li-ion battery modules is presented. From experimental results, the parameters of an electrical circuit have been determined by means of time- and frequency-domain tests. In this way, the dynamic behavior of the battery-pack is modeled. The tests have been performed at the whole battery-pack, instead of a single-cell approach, in order to consider the packaging effects of multicell devices. The real performance of the battery-pack under dynamic applications associated with distribution grids has been simulated using a hardware-in-the-loop (HIL) experimental setup. According to simulation results, the hybrid model follows the battery-pack response with high accuracy.","PeriodicalId":158868,"journal":{"name":"Research Trends and Challenges in Smart Grids","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126570841","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 : 2019-05-22DOI: 10.5772/INTECHOPEN.85108
M. Azzouz
The intermittent nature of renewable power sources (RES) can significantly change the voltage profile of smart grids and adversely impact the conventional voltage control devices such as tap-changing transformers and capacitor banks. Furthermore, the growing penetration of plug-in electric vehicles (PEVs) can add high stress on voltage control devices due to the PEV stochastic and concentrated power profiles. Such power profiles may lead to high maintenance costs and reduced lifetimes for voltage control devices and limit actions on accommodation of high penetration levels of RES and PEVs. This chapter explains the basic background of voltage regulation in smart grids. The typical approaches, which are employed by utilities for voltage regulation, are reviewed. Then, the impact of RES and PEVs on voltage regulation is analyzed. Lastly, remedies for voltage violations in smart grids, such as optimal reactive power control and coordination between voltage control devices, are discussed.
{"title":"Voltage Regulation in Smart Grids","authors":"M. Azzouz","doi":"10.5772/INTECHOPEN.85108","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.85108","url":null,"abstract":"The intermittent nature of renewable power sources (RES) can significantly change the voltage profile of smart grids and adversely impact the conventional voltage control devices such as tap-changing transformers and capacitor banks. Furthermore, the growing penetration of plug-in electric vehicles (PEVs) can add high stress on voltage control devices due to the PEV stochastic and concentrated power profiles. Such power profiles may lead to high maintenance costs and reduced lifetimes for voltage control devices and limit actions on accommodation of high penetration levels of RES and PEVs. This chapter explains the basic background of voltage regulation in smart grids. The typical approaches, which are employed by utilities for voltage regulation, are reviewed. Then, the impact of RES and PEVs on voltage regulation is analyzed. Lastly, remedies for voltage violations in smart grids, such as optimal reactive power control and coordination between voltage control devices, are discussed.","PeriodicalId":158868,"journal":{"name":"Research Trends and Challenges in Smart Grids","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115071344","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 : 2019-03-20DOI: 10.5772/INTECHOPEN.84287
B. Vaidya, H. Mouftah
Transportation is the main cause of various harmful gases being released into the atmosphere. Due to dependency on fossil fuels, conventional internal-combustion engine vehicles cause major impacts on air pollution and climate change. Achieving greenhouse gas (GHG) reduction targets requires electrification of transportation at the larger scale. Zero-emission vehicles are developing rapidly with consequences for energy use and GHG emissions, and their penetration is rising throughout the world. Such vehicles are widely considered as a promising solution for GHG reduction and a key to low-carbon mobility future. Recent trend in transportation system is a rapid shift toward connected autonomous vehicles. Connected autonomous electric vehicle (CAEV) will play a vital role in emerging revolution in sustainable low-carbon mobility. They can result in major reductions in GHG emissions and be at the forefront of rapid transformation in transportation. CAEVs have great potential to operate with higher vehicle efficiency, if they are charged using renewable energy sources that will significantly reduce emissions and dependency on fossil fuels. This book chapter is intended not only to provide understanding of potential environmental implications of CAEV technologies by reviewing the existing studies and research works but also to discuss environmental impacts including GHG emissions and improvement of vehicle efficiency.
{"title":"Connected Autonomous Electric Vehicles as Enablers for Low-Carbon Future","authors":"B. Vaidya, H. Mouftah","doi":"10.5772/INTECHOPEN.84287","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.84287","url":null,"abstract":"Transportation is the main cause of various harmful gases being released into the atmosphere. Due to dependency on fossil fuels, conventional internal-combustion engine vehicles cause major impacts on air pollution and climate change. Achieving greenhouse gas (GHG) reduction targets requires electrification of transportation at the larger scale. Zero-emission vehicles are developing rapidly with consequences for energy use and GHG emissions, and their penetration is rising throughout the world. Such vehicles are widely considered as a promising solution for GHG reduction and a key to low-carbon mobility future. Recent trend in transportation system is a rapid shift toward connected autonomous vehicles. Connected autonomous electric vehicle (CAEV) will play a vital role in emerging revolution in sustainable low-carbon mobility. They can result in major reductions in GHG emissions and be at the forefront of rapid transformation in transportation. CAEVs have great potential to operate with higher vehicle efficiency, if they are charged using renewable energy sources that will significantly reduce emissions and dependency on fossil fuels. This book chapter is intended not only to provide understanding of potential environmental implications of CAEV technologies by reviewing the existing studies and research works but also to discuss environmental impacts including GHG emissions and improvement of vehicle efficiency.","PeriodicalId":158868,"journal":{"name":"Research Trends and Challenges in Smart Grids","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121301586","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 : 2019-02-19DOI: 10.5772/INTECHOPEN.84345
Fernando Vaca-Urbano, Manuel S. Alvarez‐Alvarado, Angel A. Recalde, Félix Moncayo-Rea
The rapid evolution of power electronic solutions in all around the globe brings a common problem, which is the adoption of nonlinear loads. This fact carries out a strong impact over the quality of power systems and consequently on energy efficiency, since nonlinear loads act as sources of harmonic currents that flow to other loads or even sources, causing non-optimal performance in their operation. Nowa-days, conventional transformers are limited to just manage (increase or decrease) voltage level, but they are not able to deal with power quality events, such as harmonics, sag, swell, among others. Hence, there is a need to incorporate a versa-tile smart device to deal with the challenges previously described for a smart grid environment. This chapter introduces a solid-state transformer (SST) with topology of multilevel cascade H bridge converter as a solution. SST is an emerging technology that has the advantages of low volume, low weight, fault isolation, and other management features. Within its fundamental operation, this chapter presents a detailed description of a SST system comprising communication and control, highlighting their main advantages in comparison with conventional transformer such as mitigation of waveform harmonic distortion, allowance of integration of distributed generation, and bi-directional power flow.
{"title":"Solid-State Transformer for Energy Efficiency Enhancement","authors":"Fernando Vaca-Urbano, Manuel S. Alvarez‐Alvarado, Angel A. Recalde, Félix Moncayo-Rea","doi":"10.5772/INTECHOPEN.84345","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.84345","url":null,"abstract":"The rapid evolution of power electronic solutions in all around the globe brings a common problem, which is the adoption of nonlinear loads. This fact carries out a strong impact over the quality of power systems and consequently on energy efficiency, since nonlinear loads act as sources of harmonic currents that flow to other loads or even sources, causing non-optimal performance in their operation. Nowa-days, conventional transformers are limited to just manage (increase or decrease) voltage level, but they are not able to deal with power quality events, such as harmonics, sag, swell, among others. Hence, there is a need to incorporate a versa-tile smart device to deal with the challenges previously described for a smart grid environment. This chapter introduces a solid-state transformer (SST) with topology of multilevel cascade H bridge converter as a solution. SST is an emerging technology that has the advantages of low volume, low weight, fault isolation, and other management features. Within its fundamental operation, this chapter presents a detailed description of a SST system comprising communication and control, highlighting their main advantages in comparison with conventional transformer such as mitigation of waveform harmonic distortion, allowance of integration of distributed generation, and bi-directional power flow.","PeriodicalId":158868,"journal":{"name":"Research Trends and Challenges in Smart Grids","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116456271","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 : 2019-02-01DOI: 10.5772/INTECHOPEN.84136
D. H. Nguyen, H. Tran, T. Narikiyo, M. Kawanishi
This chapter presents a distributed optimization method named sequential distributed consensus-based ADMM for solving nonlinear constrained convex optimization problems arising in smart grids in order to derive optimal energy management strategies. To develop such distributed optimization method, multi-agent system and consensus theory are employed. Next, two smart grid problems are investigated and solved by the proposed distributed algorithm. The first problem is called the dynamic social welfare maximization problem where the objective is to simultaneously minimize the generation costs of conventional power plants and maximize the satisfaction of consumers. In this case, there are renewable energy sources connected to the grid, but energy storage systems are not considered. On the other hand, in the second problem, plug-in electric vehicles are served as energy storage systems, and their charging or discharging profiles are optimized to minimize the overall system operation cost. It is then shown that the proposed distributed optimization algorithm gives an efficient way of energy management for both problems above. Simulation results are provided to illustrate the proposed theoretical approach.
{"title":"A Distributed Optimization Method for Optimal Energy Management in Smart Grid","authors":"D. H. Nguyen, H. Tran, T. Narikiyo, M. Kawanishi","doi":"10.5772/INTECHOPEN.84136","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.84136","url":null,"abstract":"This chapter presents a distributed optimization method named sequential distributed consensus-based ADMM for solving nonlinear constrained convex optimization problems arising in smart grids in order to derive optimal energy management strategies. To develop such distributed optimization method, multi-agent system and consensus theory are employed. Next, two smart grid problems are investigated and solved by the proposed distributed algorithm. The first problem is called the dynamic social welfare maximization problem where the objective is to simultaneously minimize the generation costs of conventional power plants and maximize the satisfaction of consumers. In this case, there are renewable energy sources connected to the grid, but energy storage systems are not considered. On the other hand, in the second problem, plug-in electric vehicles are served as energy storage systems, and their charging or discharging profiles are optimized to minimize the overall system operation cost. It is then shown that the proposed distributed optimization algorithm gives an efficient way of energy management for both problems above. Simulation results are provided to illustrate the proposed theoretical approach.","PeriodicalId":158868,"journal":{"name":"Research Trends and Challenges in Smart Grids","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115116075","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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