Pub Date : 2015-11-12DOI: 10.1109/SEGE.2015.7324584
Alberto Betancourt-Torcat, A. Almansoori
A mixed integer linear programming model for the optimal design of the United Arab Emirates power infrastructure under uncertainty is presented. The optimization objective is the minimization of the power generation costs in the UAE under techno-economic and environmental constraints. Uncertainty is considered in the carbon tax price and social benefits associated with the avoidance of air emissions. The optimization problem was formulated in the General Algebraic Modeling System (GAMS®). The novelty of the present work consists of determining the most suitable combination of power generation plants under uncertainty. This work also considers the introduction of alternative energy sources such as nuclear and renewables into the country's power fleet. Two case studies are solved to demonstrate the usefulness of the devised approach.
{"title":"Design optimization model for the United Arab Emirates power sector under uncertainty","authors":"Alberto Betancourt-Torcat, A. Almansoori","doi":"10.1109/SEGE.2015.7324584","DOIUrl":"https://doi.org/10.1109/SEGE.2015.7324584","url":null,"abstract":"A mixed integer linear programming model for the optimal design of the United Arab Emirates power infrastructure under uncertainty is presented. The optimization objective is the minimization of the power generation costs in the UAE under techno-economic and environmental constraints. Uncertainty is considered in the carbon tax price and social benefits associated with the avoidance of air emissions. The optimization problem was formulated in the General Algebraic Modeling System (GAMS®). The novelty of the present work consists of determining the most suitable combination of power generation plants under uncertainty. This work also considers the introduction of alternative energy sources such as nuclear and renewables into the country's power fleet. Two case studies are solved to demonstrate the usefulness of the devised approach.","PeriodicalId":409488,"journal":{"name":"2015 IEEE International Conference on Smart Energy Grid Engineering (SEGE)","volume":"13 25","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113973666","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 : 2015-11-12DOI: 10.1109/SEGE.2015.7324620
A. Zidan, H. Gabbar
In this paper, optimization scheme for microgrids is presented. In microgrids, the operational cost and greenhouse gas emissions are mainly depend on types and sizes of distributed generators (DGs) used. This paper aims to reduce the operational cost and the greenhouse gas emissions through evaluating the optimal output of each DG type. DGs operate within their respective capacity limits while satisfying the local energy demand (both electrical and thermal). The multi-objective optimization compromises between the operational cost and the emissions. The constraints include power and heat demands constraints, and DG capacity limits.
{"title":"Optimal planned scheduling of distributed generators in microgrids","authors":"A. Zidan, H. Gabbar","doi":"10.1109/SEGE.2015.7324620","DOIUrl":"https://doi.org/10.1109/SEGE.2015.7324620","url":null,"abstract":"In this paper, optimization scheme for microgrids is presented. In microgrids, the operational cost and greenhouse gas emissions are mainly depend on types and sizes of distributed generators (DGs) used. This paper aims to reduce the operational cost and the greenhouse gas emissions through evaluating the optimal output of each DG type. DGs operate within their respective capacity limits while satisfying the local energy demand (both electrical and thermal). The multi-objective optimization compromises between the operational cost and the emissions. The constraints include power and heat demands constraints, and DG capacity limits.","PeriodicalId":409488,"journal":{"name":"2015 IEEE International Conference on Smart Energy Grid Engineering (SEGE)","volume":"190 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114471160","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 : 2015-11-12DOI: 10.1109/SEGE.2015.7324617
S. Karimi, A. Rajabi-Ghahnavieh, H. Azad
Distributed Generation (DG) has received increasing attention during the last decade. Advantage and constraints of DG application are well known to both DG owner and electric utility. Various technologies are available for DG units among them gas GenSet is, in particular, more attractive to the investors as the technology provides the control on DG generation. However, there are various financial risks associated with dispatchable DG units that prohibit wide private investment in such technologies. This paper examines the use of financial tools to manage dispatchable DG economic risks. A comprehensive framework has been proposed to consider various economic risks to DG owner. Suitable models have been used to incorporate risk management tools, in particular the financial tools, in the problem. Optimal use of risk management tools has been determined based on conditional value-at-risk (CVaR) approach. The proposed approach has been applied to a test case and the effectiveness of the solution has been verified.
{"title":"Financial tools to manage dispatchable Distributed Generation economic risks","authors":"S. Karimi, A. Rajabi-Ghahnavieh, H. Azad","doi":"10.1109/SEGE.2015.7324617","DOIUrl":"https://doi.org/10.1109/SEGE.2015.7324617","url":null,"abstract":"Distributed Generation (DG) has received increasing attention during the last decade. Advantage and constraints of DG application are well known to both DG owner and electric utility. Various technologies are available for DG units among them gas GenSet is, in particular, more attractive to the investors as the technology provides the control on DG generation. However, there are various financial risks associated with dispatchable DG units that prohibit wide private investment in such technologies. This paper examines the use of financial tools to manage dispatchable DG economic risks. A comprehensive framework has been proposed to consider various economic risks to DG owner. Suitable models have been used to incorporate risk management tools, in particular the financial tools, in the problem. Optimal use of risk management tools has been determined based on conditional value-at-risk (CVaR) approach. The proposed approach has been applied to a test case and the effectiveness of the solution has been verified.","PeriodicalId":409488,"journal":{"name":"2015 IEEE International Conference on Smart Energy Grid Engineering (SEGE)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117296291","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 : 2015-11-12DOI: 10.1109/SEGE.2015.7324595
A. Eldessouky, H. Gabbar
Maintaining voltage level stability of islanded mode Micro Grids (MG) is a challenging objective due to the limited power flow between sources and loads. The objective of this work is to enhance the dynamic performance of islanded mode Micro grid in the presence of load disturbance using static VAR compensator (SVC). The contribution of this work is the implementation of PI fuzzy model reference learning controller (FMRLC) to SVC control loop. The control algorithm compensates for nonlinearity possessed by MG where fuzzy membership functions and implication imbedded in both controller and inverse model that achieve better presentation of both uncertainty and nonlinearity of the power system dynamics. Hence, MG keeps desired performance as required irrespective of the operating condition. In addition, learning capabilities of the proposed control algorithm compensates for grid parameter variation even with inadequate information about mathematical presentation of load dynamics. The reference model was designed to reject bus voltage disturbance, created by load and wind variation, with achievable desired performance. Accordingly, SVC with fuzzy controller was able to reject bus voltage disturbance by matching closely the reference model performance. Simulations were carried out to study the steady-state and transient performance of MG in islanded mode. The MG is composed of a PV bus supplied by wind turbine and induction generator, a PQ bus connected to nonlinear dynamic load and linear load, a single distribution line connecting the two buses, and SVC. The proposed control algorithm robustness was tested by providing load disturbance in different operating conditions and observing the system dynamic performance. The performance of the proposed controller is compared to a conventional PID controller using overshoot, transient oscillation, Integral-of-Time Multiplied Absolute Error (ITMAE), and integral square error (ISE) as performance parameters. Both ITMAE and ISE values for the proposed controller were much less than conventional PID controller. In addition, for the proposed controller, ITMAE values sustained stable increase while PID controller ITMAE values increased exponentially. These results indicates the progress achieved by proposed controller to enhance disturbance rejection with time due to learning process.
{"title":"Micro Grid stability enhancement using SVC with fuzzy model reference learning controller algorithm","authors":"A. Eldessouky, H. Gabbar","doi":"10.1109/SEGE.2015.7324595","DOIUrl":"https://doi.org/10.1109/SEGE.2015.7324595","url":null,"abstract":"Maintaining voltage level stability of islanded mode Micro Grids (MG) is a challenging objective due to the limited power flow between sources and loads. The objective of this work is to enhance the dynamic performance of islanded mode Micro grid in the presence of load disturbance using static VAR compensator (SVC). The contribution of this work is the implementation of PI fuzzy model reference learning controller (FMRLC) to SVC control loop. The control algorithm compensates for nonlinearity possessed by MG where fuzzy membership functions and implication imbedded in both controller and inverse model that achieve better presentation of both uncertainty and nonlinearity of the power system dynamics. Hence, MG keeps desired performance as required irrespective of the operating condition. In addition, learning capabilities of the proposed control algorithm compensates for grid parameter variation even with inadequate information about mathematical presentation of load dynamics. The reference model was designed to reject bus voltage disturbance, created by load and wind variation, with achievable desired performance. Accordingly, SVC with fuzzy controller was able to reject bus voltage disturbance by matching closely the reference model performance. Simulations were carried out to study the steady-state and transient performance of MG in islanded mode. The MG is composed of a PV bus supplied by wind turbine and induction generator, a PQ bus connected to nonlinear dynamic load and linear load, a single distribution line connecting the two buses, and SVC. The proposed control algorithm robustness was tested by providing load disturbance in different operating conditions and observing the system dynamic performance. The performance of the proposed controller is compared to a conventional PID controller using overshoot, transient oscillation, Integral-of-Time Multiplied Absolute Error (ITMAE), and integral square error (ISE) as performance parameters. Both ITMAE and ISE values for the proposed controller were much less than conventional PID controller. In addition, for the proposed controller, ITMAE values sustained stable increase while PID controller ITMAE values increased exponentially. These results indicates the progress achieved by proposed controller to enhance disturbance rejection with time due to learning process.","PeriodicalId":409488,"journal":{"name":"2015 IEEE International Conference on Smart Energy Grid Engineering (SEGE)","volume":"62 18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130376048","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 : 2015-11-12DOI: 10.1109/SEGE.2015.7324626
M. N. Mojdehi, P. Ghosh
Electric Vehicle (EV) becoming a promising reactive power service provider because of its short response time with no battery degradation during this service. Also EV would allow efficient adjustment of power flows in response to frequent changes in loads. In this paper we present a novel structure to evaluate the reactive power service potential of EVs. We formulate a linear program to minimize the operating cost of an EV that includes the battery degradation cost, under a range of practical constraints. These constraints include owner's desired state of charges and limitation in the current ripple from the DC-link capacitor of the EV charger. The developed optimization framework yields EV's optimal charging/discharging and reactive power service (injection/absorption) schedules. We also introduce an algorithm capable of determining the estimated compensation for the EV owner under different market structure and when real time events force the DSO to ask for more reactive power than pre-scheduled amount.
{"title":"Minimization of energy usage and cost for EV during reactive power service","authors":"M. N. Mojdehi, P. Ghosh","doi":"10.1109/SEGE.2015.7324626","DOIUrl":"https://doi.org/10.1109/SEGE.2015.7324626","url":null,"abstract":"Electric Vehicle (EV) becoming a promising reactive power service provider because of its short response time with no battery degradation during this service. Also EV would allow efficient adjustment of power flows in response to frequent changes in loads. In this paper we present a novel structure to evaluate the reactive power service potential of EVs. We formulate a linear program to minimize the operating cost of an EV that includes the battery degradation cost, under a range of practical constraints. These constraints include owner's desired state of charges and limitation in the current ripple from the DC-link capacitor of the EV charger. The developed optimization framework yields EV's optimal charging/discharging and reactive power service (injection/absorption) schedules. We also introduce an algorithm capable of determining the estimated compensation for the EV owner under different market structure and when real time events force the DSO to ask for more reactive power than pre-scheduled amount.","PeriodicalId":409488,"journal":{"name":"2015 IEEE International Conference on Smart Energy Grid Engineering (SEGE)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115559882","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 : 2015-11-12DOI: 10.1109/SEGE.2015.7324622
A. Eltamaly
Partial shading on PV modules reduces the generated power of the PV system than the maximum power generated from each module separately. The shaded PV module acts as a load to unshaded ones which can lead to hot-spot. To alleviate the effect of partial shading, bypass diodes should be connected across each PV modules. Connecting several PV modules together produces multiple peaks (One global peak (GP) and multiple local peaks (LP)) on partial shading conditions. Maximum power point tracker (MPPT) conventional techniques are designed to follow the GP but they stuck around LPs such as fuzzy logic controller (FLC). In this paper, modified particle swarm optimization (MPSO) using genetic algorism has been used to follow the GP under any operating conditions. MPSO has been studied and compared with FLC technique to show the superiority of this technique under all operating conditions. Co-simulation between Matlab/Simulink and PSIM has been used to model the PV system under partial shading conditions. The simulation results show that the MPSO technique is more effective than FLC in following the GP. The generated power increases considerably with MPSO than FLC technique in shading conditions.
{"title":"Performance of smart maximum power point tracker under partial shading conditions of PV systems","authors":"A. Eltamaly","doi":"10.1109/SEGE.2015.7324622","DOIUrl":"https://doi.org/10.1109/SEGE.2015.7324622","url":null,"abstract":"Partial shading on PV modules reduces the generated power of the PV system than the maximum power generated from each module separately. The shaded PV module acts as a load to unshaded ones which can lead to hot-spot. To alleviate the effect of partial shading, bypass diodes should be connected across each PV modules. Connecting several PV modules together produces multiple peaks (One global peak (GP) and multiple local peaks (LP)) on partial shading conditions. Maximum power point tracker (MPPT) conventional techniques are designed to follow the GP but they stuck around LPs such as fuzzy logic controller (FLC). In this paper, modified particle swarm optimization (MPSO) using genetic algorism has been used to follow the GP under any operating conditions. MPSO has been studied and compared with FLC technique to show the superiority of this technique under all operating conditions. Co-simulation between Matlab/Simulink and PSIM has been used to model the PV system under partial shading conditions. The simulation results show that the MPSO technique is more effective than FLC in following the GP. The generated power increases considerably with MPSO than FLC technique in shading conditions.","PeriodicalId":409488,"journal":{"name":"2015 IEEE International Conference on Smart Energy Grid Engineering (SEGE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128430183","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 : 2015-11-12DOI: 10.1109/SEGE.2015.7324615
O. Ur-Rehman, N. Zivic, C. Ruland
Intelligent buildings are not imaginable anymore without smart metering devices. Smart metering systems are used not only for the provisioning of instantaneous metering information on commodities, such as electricity, water and gas, to the service providers but also to make this information available to customers. This helps the customers in dynamically adapting their energy consumption behavior. The smart metering devices also help in balancing the power generation and distribution in a smart grid by tailoring the power generation according to the demand. However, the liberalization of the metering market requires few strong security and privacy requirements for the metering data. Smart metering raises many security and privacy concerns. There are worries that the personal information of consumers could be disclosed. There are also concerns about frauds exploiting security vulnerabilities in smart metering systems on a large scale, e.g., making smart meters provide false metering data to the service providers. From a macro perspective, the smart grids, including the smart metering systems and devices can be attacked to bring down the whole grid or at least some parts of the grid, which is a concern of national security. This paper focuses on the security and privacy aspects of the smart metering systems. Potential attackers, security threats and attacks on smart metering systems are listed and the security approaches to address the security issues are presented. A security by design approach for secure smart metering is discussed in the paper. The major results of a security by design approach for smart metering systems developed in the project, entitled “Trusted Computing Engineering for Resource Constraint Embedded Systems Applications”, funded by the European commission, are summarized in the end.
{"title":"Security issues in smart metering systems","authors":"O. Ur-Rehman, N. Zivic, C. Ruland","doi":"10.1109/SEGE.2015.7324615","DOIUrl":"https://doi.org/10.1109/SEGE.2015.7324615","url":null,"abstract":"Intelligent buildings are not imaginable anymore without smart metering devices. Smart metering systems are used not only for the provisioning of instantaneous metering information on commodities, such as electricity, water and gas, to the service providers but also to make this information available to customers. This helps the customers in dynamically adapting their energy consumption behavior. The smart metering devices also help in balancing the power generation and distribution in a smart grid by tailoring the power generation according to the demand. However, the liberalization of the metering market requires few strong security and privacy requirements for the metering data. Smart metering raises many security and privacy concerns. There are worries that the personal information of consumers could be disclosed. There are also concerns about frauds exploiting security vulnerabilities in smart metering systems on a large scale, e.g., making smart meters provide false metering data to the service providers. From a macro perspective, the smart grids, including the smart metering systems and devices can be attacked to bring down the whole grid or at least some parts of the grid, which is a concern of national security. This paper focuses on the security and privacy aspects of the smart metering systems. Potential attackers, security threats and attacks on smart metering systems are listed and the security approaches to address the security issues are presented. A security by design approach for secure smart metering is discussed in the paper. The major results of a security by design approach for smart metering systems developed in the project, entitled “Trusted Computing Engineering for Resource Constraint Embedded Systems Applications”, funded by the European commission, are summarized in the end.","PeriodicalId":409488,"journal":{"name":"2015 IEEE International Conference on Smart Energy Grid Engineering (SEGE)","volume":"84 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120810355","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 : 2015-11-12DOI: 10.1109/SEGE.2015.7324621
M. A. Mohamed, A. Eltamaly, Hassan M. H. Farh, A. Alolah
Smart grid is a concept by which the existing electrical grid infrastructure is being upgraded with integration of multiple technologies such as, two-way power flow, two-way communication, automated sensors, advanced automated controls and forecasting system. Smart grid enables interaction between the consumer and utility which allow the optimal usage of energy based on environmental, price preferences and system technical issues. This enables the grid to be more reliable, efficient and secure, while reducing greenhouse gases. This paper presents a survey of the recent literature on integrating renewable energy sources into smart grid system. Various management objectives, such as improving energy efficiency, maximizing utilization, reducing cost, and controlling emission have been explored.
{"title":"Energy management and renewable energy integration in smart grid system","authors":"M. A. Mohamed, A. Eltamaly, Hassan M. H. Farh, A. Alolah","doi":"10.1109/SEGE.2015.7324621","DOIUrl":"https://doi.org/10.1109/SEGE.2015.7324621","url":null,"abstract":"Smart grid is a concept by which the existing electrical grid infrastructure is being upgraded with integration of multiple technologies such as, two-way power flow, two-way communication, automated sensors, advanced automated controls and forecasting system. Smart grid enables interaction between the consumer and utility which allow the optimal usage of energy based on environmental, price preferences and system technical issues. This enables the grid to be more reliable, efficient and secure, while reducing greenhouse gases. This paper presents a survey of the recent literature on integrating renewable energy sources into smart grid system. Various management objectives, such as improving energy efficiency, maximizing utilization, reducing cost, and controlling emission have been explored.","PeriodicalId":409488,"journal":{"name":"2015 IEEE International Conference on Smart Energy Grid Engineering (SEGE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127292007","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 : 2015-11-12DOI: 10.1109/SEGE.2015.7324607
Kiyan Elyasibakhtiari, M. Azzouz, Elham Akhavan Rezai, E. El-Saadany
PEVs are going to heavily load future residential distribution grids, specifically; slow chargers are more expected in domestic areas. This paper presents the real-time simulation analysis of the unbalance issues associated with charging and discharging of the single-phase PEVs. Simulations are performed using a real-time simulator and PEV battery specifications that are available in market. The results of the case study indicate how single-phase charging of those PEVs could cause significant phase imbalance.
{"title":"Real-time analysis of voltage and current in low-voltage grid due to electric vehicles' charging","authors":"Kiyan Elyasibakhtiari, M. Azzouz, Elham Akhavan Rezai, E. El-Saadany","doi":"10.1109/SEGE.2015.7324607","DOIUrl":"https://doi.org/10.1109/SEGE.2015.7324607","url":null,"abstract":"PEVs are going to heavily load future residential distribution grids, specifically; slow chargers are more expected in domestic areas. This paper presents the real-time simulation analysis of the unbalance issues associated with charging and discharging of the single-phase PEVs. Simulations are performed using a real-time simulator and PEV battery specifications that are available in market. The results of the case study indicate how single-phase charging of those PEVs could cause significant phase imbalance.","PeriodicalId":409488,"journal":{"name":"2015 IEEE International Conference on Smart Energy Grid Engineering (SEGE)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133114448","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 : 2015-11-12DOI: 10.1109/SEGE.2015.7324580
A. Abdelsalam, A. Sharaf
This paper proposes a novel custom power device based on distribution static compensator (DSTATCOM) with PID controller driven by the unified error signal (UES) from a multi loop dynamic error controller scheme. Both DSTATCOM and UES are modified to meet the requirements for voltage stabilization, voltage waveform disturbance compensation and power factor improvement. A complete simulation model of the proposed system is developed in Matlab/Simulink Environment. The system is simulated with different control strategies under different operating conditions for comparison. The controllers and the control strategies are developed to have the novel DSTATCOM be operated for voltage stabilization, power factor improvement, energy losses reduction, power quality, and less harmonics distortion. The operational characteristics of a power system, supplying electrical power to hybrid loads consisting of linear and nonlinear and motorized loads, are investigated for better performance and higher power quality employing the proposed DSTATCOM and UES driven controllers.
{"title":"Improvement of power quality in distribution network using a novel DSTATCOM device","authors":"A. Abdelsalam, A. Sharaf","doi":"10.1109/SEGE.2015.7324580","DOIUrl":"https://doi.org/10.1109/SEGE.2015.7324580","url":null,"abstract":"This paper proposes a novel custom power device based on distribution static compensator (DSTATCOM) with PID controller driven by the unified error signal (UES) from a multi loop dynamic error controller scheme. Both DSTATCOM and UES are modified to meet the requirements for voltage stabilization, voltage waveform disturbance compensation and power factor improvement. A complete simulation model of the proposed system is developed in Matlab/Simulink Environment. The system is simulated with different control strategies under different operating conditions for comparison. The controllers and the control strategies are developed to have the novel DSTATCOM be operated for voltage stabilization, power factor improvement, energy losses reduction, power quality, and less harmonics distortion. The operational characteristics of a power system, supplying electrical power to hybrid loads consisting of linear and nonlinear and motorized loads, are investigated for better performance and higher power quality employing the proposed DSTATCOM and UES driven controllers.","PeriodicalId":409488,"journal":{"name":"2015 IEEE International Conference on Smart Energy Grid Engineering (SEGE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123468313","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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