Pub Date : 2018-04-16DOI: 10.1109/TDC.2018.8440136
F. Tuffner, Nikitha Radhakrishnan, Yingying Tang, K. Schneider
Microgrids provide the ability to maintain service to critical end-use loads when utility service is not available. Despite their ability to increase resiliency, they can have high capital and operating costs; this can be compounded by the complexities associated with low inertia systems. One option to mitigate the costs is to more effectively engage the assets within the microgrids, specifically the end-use loads. Previous work has shown that by using Grid Friendly™ Appliance controllers, it is possible to increase the dynamic stability of multiple microgrids during switching transients, without the need to oversize generation assets or to install energy storage devices. Building on the previous work, this paper will present a method for determining the set-points of decentralized controllers, accounting for the different characteristics and sizes of loads, to facilitate multiple microgrid switching operations. By effectively engaging the end-use load as a resource, the switching operations necessary to network low inertia microgrids for resiliency applications can be supported without the need to oversize generation assets or for energy storage.
{"title":"Grid Friendly Appliance Controllers to Increase the Dynamic Stability of Networked Resiliency-based Microgrids","authors":"F. Tuffner, Nikitha Radhakrishnan, Yingying Tang, K. Schneider","doi":"10.1109/TDC.2018.8440136","DOIUrl":"https://doi.org/10.1109/TDC.2018.8440136","url":null,"abstract":"Microgrids provide the ability to maintain service to critical end-use loads when utility service is not available. Despite their ability to increase resiliency, they can have high capital and operating costs; this can be compounded by the complexities associated with low inertia systems. One option to mitigate the costs is to more effectively engage the assets within the microgrids, specifically the end-use loads. Previous work has shown that by using Grid Friendly™ Appliance controllers, it is possible to increase the dynamic stability of multiple microgrids during switching transients, without the need to oversize generation assets or to install energy storage devices. Building on the previous work, this paper will present a method for determining the set-points of decentralized controllers, accounting for the different characteristics and sizes of loads, to facilitate multiple microgrid switching operations. By effectively engaging the end-use load as a resource, the switching operations necessary to network low inertia microgrids for resiliency applications can be supported without the need to oversize generation assets or for energy storage.","PeriodicalId":6568,"journal":{"name":"2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)","volume":"77 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2018-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90383666","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 : 2018-04-16DOI: 10.1109/TDC.2018.8440219
A. Rentschler, G. Kuhn, M. Delzenne, O. Kuhn
Particularly in Germany, but also in many other countries of the world, the electrical networks will change greatly in the future due to the integration of renewable energy generation. For a successful execution of this energy transition (German: Energiewende) the design and operation of the networks has to change in order to solve the new requirements of modern energy supply. Medium voltage direct current (MVDC) technology is an innovative solution to face some of these challenges. A new concept consisting in the down-scaling of a HVDC Modular Multilevel Converter (MMC) is presented. It combines the advantages from MMC such as low converter losses, fast active and reactive control and compact footprint to reduced acquisition costs. The technical implications of the construction of long distance medium voltage dc links are highlighted. Especially the losses in the DC line and the AC-Fault Ride Through capability are discussed.
{"title":"Medium Voltage DC, Challenges Related to the Building of Long Overhead Lines","authors":"A. Rentschler, G. Kuhn, M. Delzenne, O. Kuhn","doi":"10.1109/TDC.2018.8440219","DOIUrl":"https://doi.org/10.1109/TDC.2018.8440219","url":null,"abstract":"Particularly in Germany, but also in many other countries of the world, the electrical networks will change greatly in the future due to the integration of renewable energy generation. For a successful execution of this energy transition (German: Energiewende) the design and operation of the networks has to change in order to solve the new requirements of modern energy supply. Medium voltage direct current (MVDC) technology is an innovative solution to face some of these challenges. A new concept consisting in the down-scaling of a HVDC Modular Multilevel Converter (MMC) is presented. It combines the advantages from MMC such as low converter losses, fast active and reactive control and compact footprint to reduced acquisition costs. The technical implications of the construction of long distance medium voltage dc links are highlighted. Especially the losses in the DC line and the AC-Fault Ride Through capability are discussed.","PeriodicalId":6568,"journal":{"name":"2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)","volume":"20 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2018-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78882129","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 : 2018-04-16DOI: 10.1109/TDC.2018.8440531
B. Khaki, C. Chu, R. Gadh
Electric vehicles (EVs) are controllable loads from which distribution grid operator can benefit in order to minimize the load profile variations. In this paper, we proposed a hierarchical distributed optimization framework such that EV management system (EVMS), as a part of distribution grid management system, minimizes the load variance of the grid in communication with the EV aggregators which control EV charging load of the distribution system feeders. The hierarchical distributed framework, based on alternative direction method of multipliers (ADMM), increases the scalability of the EV charging infrastructure while decreases computational burden. In our proposed approach, each EV aggregator schedules the EV charging profiles of its feeder in a distributed fashion which avoids sharing the EV owners' desired charging profile information and enables privacy preserving. To show the performance of our approach, we apply it to a case study with 100% EV penetration, including 4 feeders and 60 EVs, and show how the load variance of the system and charging cost of individual EVs decrease.
{"title":"A Hierarchical ADMM Based Framework for EV Charging Scheduling","authors":"B. Khaki, C. Chu, R. Gadh","doi":"10.1109/TDC.2018.8440531","DOIUrl":"https://doi.org/10.1109/TDC.2018.8440531","url":null,"abstract":"Electric vehicles (EVs) are controllable loads from which distribution grid operator can benefit in order to minimize the load profile variations. In this paper, we proposed a hierarchical distributed optimization framework such that EV management system (EVMS), as a part of distribution grid management system, minimizes the load variance of the grid in communication with the EV aggregators which control EV charging load of the distribution system feeders. The hierarchical distributed framework, based on alternative direction method of multipliers (ADMM), increases the scalability of the EV charging infrastructure while decreases computational burden. In our proposed approach, each EV aggregator schedules the EV charging profiles of its feeder in a distributed fashion which avoids sharing the EV owners' desired charging profile information and enables privacy preserving. To show the performance of our approach, we apply it to a case study with 100% EV penetration, including 4 feeders and 60 EVs, and show how the load variance of the system and charging cost of individual EVs decrease.","PeriodicalId":6568,"journal":{"name":"2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)","volume":"44 1","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2018-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88141225","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 : 2018-04-16DOI: 10.1109/TDC.2018.8440480
Yinong Sun, W. Cole, V. Krishnan
Future electricity system portfolios will require strategic transmission expansions for economically integrating regionally dependent, high-quality renewable resources. In this context, accurate representation of transmission flows in large-scale electricity infrastructure capacity expansion planning problems is important. This paper describes an approximate linearized power flow transmission modeling method for such expansion problems and demonstrates the impact on planning solutions using the National Renewable Energy Laboratory's Regional Energy Deployment System (ReEDS) model. Results are compared against a pipe flow transmission representation, which is used in a number of large-scale planning models. We show that national-scale generation and transmission expansion is not substantially influenced by the power flow methodology but that the pipe flow representation does underestimate required transmission capacity and total system costs.
{"title":"Comparing Power Flow Approximations for Electricity Infrastructure Capacity Expansion Models with High Spatial Resolution","authors":"Yinong Sun, W. Cole, V. Krishnan","doi":"10.1109/TDC.2018.8440480","DOIUrl":"https://doi.org/10.1109/TDC.2018.8440480","url":null,"abstract":"Future electricity system portfolios will require strategic transmission expansions for economically integrating regionally dependent, high-quality renewable resources. In this context, accurate representation of transmission flows in large-scale electricity infrastructure capacity expansion planning problems is important. This paper describes an approximate linearized power flow transmission modeling method for such expansion problems and demonstrates the impact on planning solutions using the National Renewable Energy Laboratory's Regional Energy Deployment System (ReEDS) model. Results are compared against a pipe flow transmission representation, which is used in a number of large-scale planning models. We show that national-scale generation and transmission expansion is not substantially influenced by the power flow methodology but that the pipe flow representation does underestimate required transmission capacity and total system costs.","PeriodicalId":6568,"journal":{"name":"2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)","volume":"37 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2018-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74141539","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 : 2018-04-16DOI: 10.1109/TDC.2018.8440130
T. Magier, Andreas Dehler, H. Koch
The AC Gas-Insulated Transmission Lines (GIL) technology for high power underground transmission shows an ever-increasing usage worldwide. Today, the AC GIL transmission technology is entering densely populated areas where the desire for solutions of non-visible transmission lines is high. AC GIL provides a powerful solution for underground installations. The next step in development of AC GIL is focused on increasing the level of automated laying procedures using the mobile factory as a flexible and effective laying machine. The mobile factory contains the friction stir welding machine for high quality welding of the enclosure and conductor pipes. The laying efficiency of the AC GIL will be improved in total by 20–30% which will reduce the AC GIL project cost. The new concept is set up for long distance applications and allows the localization of major work to the installation site with pre-assembly, assembly and laying works.
{"title":"AC Compact High Power Gas-Insulated Transmission Lines","authors":"T. Magier, Andreas Dehler, H. Koch","doi":"10.1109/TDC.2018.8440130","DOIUrl":"https://doi.org/10.1109/TDC.2018.8440130","url":null,"abstract":"The AC Gas-Insulated Transmission Lines (GIL) technology for high power underground transmission shows an ever-increasing usage worldwide. Today, the AC GIL transmission technology is entering densely populated areas where the desire for solutions of non-visible transmission lines is high. AC GIL provides a powerful solution for underground installations. The next step in development of AC GIL is focused on increasing the level of automated laying procedures using the mobile factory as a flexible and effective laying machine. The mobile factory contains the friction stir welding machine for high quality welding of the enclosure and conductor pipes. The laying efficiency of the AC GIL will be improved in total by 20–30% which will reduce the AC GIL project cost. The new concept is set up for long distance applications and allows the localization of major work to the installation site with pre-assembly, assembly and laying works.","PeriodicalId":6568,"journal":{"name":"2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)","volume":"69 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2018-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76423781","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 : 2018-04-16DOI: 10.1109/TDC.2018.8440384
Kamel Alboaouh, S. Mohagheghi
Utilization of solar energy in distribution networks is on the rise, especially in the form of rooftop photovoltaic (PV) panels. Using smart inverters, it is now possible to allow PVs to inject both active and reactive power into the grid. However, high penetration of PVs can introduce operational challenges as it may cause voltage rise beyond the permissible limits and may lead to additional stress on system components. Also, if uncoordinated, injecting reactive power locally could interfere with the utility's efforts in controlling node voltages. Hence, a proper coordination among various electrical devices in the distribution system is necessary in order to pave the way for maximizing PV penetration and to minimize, concurrently, the overall system losses. In this paper an evolutionary algorithm (EA) is used in order to find the optimal settings of the controllable components in a distribution system in a centralized fashion. The control variables considered are PV active and reactive powers, load curtailment through demand response, tap positions of the voltage regulators (VRs), and status of switching capacitors (SC). The main objective of the proposed approach is to minimize system losses, operational variations of VRs and SCs, as well as curtailment in the PV active power. Two aspects are in particular investigated in this paper: the impact of PV reactive power support on the grid, and the effect of high PV integration on switching devices (SCs and VRs). The proof-of-concept simulation is conducted over a one-day period in order to assess the proposed optimal scheduling.
{"title":"Voltage and Power Optimization in a Distribution Network with High PV Penetration","authors":"Kamel Alboaouh, S. Mohagheghi","doi":"10.1109/TDC.2018.8440384","DOIUrl":"https://doi.org/10.1109/TDC.2018.8440384","url":null,"abstract":"Utilization of solar energy in distribution networks is on the rise, especially in the form of rooftop photovoltaic (PV) panels. Using smart inverters, it is now possible to allow PVs to inject both active and reactive power into the grid. However, high penetration of PVs can introduce operational challenges as it may cause voltage rise beyond the permissible limits and may lead to additional stress on system components. Also, if uncoordinated, injecting reactive power locally could interfere with the utility's efforts in controlling node voltages. Hence, a proper coordination among various electrical devices in the distribution system is necessary in order to pave the way for maximizing PV penetration and to minimize, concurrently, the overall system losses. In this paper an evolutionary algorithm (EA) is used in order to find the optimal settings of the controllable components in a distribution system in a centralized fashion. The control variables considered are PV active and reactive powers, load curtailment through demand response, tap positions of the voltage regulators (VRs), and status of switching capacitors (SC). The main objective of the proposed approach is to minimize system losses, operational variations of VRs and SCs, as well as curtailment in the PV active power. Two aspects are in particular investigated in this paper: the impact of PV reactive power support on the grid, and the effect of high PV integration on switching devices (SCs and VRs). The proof-of-concept simulation is conducted over a one-day period in order to assess the proposed optimal scheduling.","PeriodicalId":6568,"journal":{"name":"2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)","volume":"57 1","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2018-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79254171","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 : 2018-04-16DOI: 10.1109/TDC.2018.8440144
Syed Rahman, Haneen Aburub, Yemeserach Mekonnen, A. Sarwat
Recent changes to greenhouse gas emission policies are catalyzing the electric vehicle (EV) market making it readily accessible to consumers. While there are challenges that arise with dense deployment of EVs, one of the major future concerns is cyber security threat. In this paper, cyber security threats in the form of tampering with EV battery's State of Charge (SOC) was explored. A Back Propagation (BP) Neural Network (NN) was trained and tested based on experimental data to estimate SOC of battery under normal operation and cyber-attack scenarios. NeuralWare software was used to run scenarios. Different statistic metrics of the predicted values were compared against the actual values of the specific battery tested to measure the stability and accuracy of the proposed BP network under different operating conditions. The results showed that BP NN was able to capture and detect the false entries due to a cyber-attack on its network.
{"title":"A Study of EV BMS Cyber Security Based on Neural Network SOC Prediction","authors":"Syed Rahman, Haneen Aburub, Yemeserach Mekonnen, A. Sarwat","doi":"10.1109/TDC.2018.8440144","DOIUrl":"https://doi.org/10.1109/TDC.2018.8440144","url":null,"abstract":"Recent changes to greenhouse gas emission policies are catalyzing the electric vehicle (EV) market making it readily accessible to consumers. While there are challenges that arise with dense deployment of EVs, one of the major future concerns is cyber security threat. In this paper, cyber security threats in the form of tampering with EV battery's State of Charge (SOC) was explored. A Back Propagation (BP) Neural Network (NN) was trained and tested based on experimental data to estimate SOC of battery under normal operation and cyber-attack scenarios. NeuralWare software was used to run scenarios. Different statistic metrics of the predicted values were compared against the actual values of the specific battery tested to measure the stability and accuracy of the proposed BP network under different operating conditions. The results showed that BP NN was able to capture and detect the false entries due to a cyber-attack on its network.","PeriodicalId":6568,"journal":{"name":"2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)","volume":"20 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2018-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80646410","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 : 2018-04-16DOI: 10.1109/TDC.2018.8440376
Yanhong Yang, W. Pei, L. Kong, Tianjiao Pu, Shixiong Fan, Renle Huang
In this paper, a comprehensive optimization of load transfer strategy for distribution network with flexible interconnect device (FID) is discussed. FID with accurate control of power flow is versatile and increasingly being considered to transfer load without black-out in distribution system with high penetrations of distributed generation (DG). The interconnection structure and exact operating set-point of FID are discussed which realized loop closing operation of distribution system. Then, the non-linear combinational optimization problem models of load transfer with FID are established which considering separately different objectives and constraints. In order to solve these complicated optimization problems, hybrid coding based genetic algorithm (GA) mixed particle swarm algorithm (PSO) is used. A case study based on 3 terminal interconnection 10kV distribution network with FID is carried out for load transfer strategy verification. The results show that the FID and proposed comprehensive optimization method have stronger ability to improve the performance of distribution system with power loss reduction, feeder load balancing, and DG penetration increasing.
{"title":"A Comprehensive Optimization of Load Transfer Strategy for Distribution Network with Flexible Interconnect Device","authors":"Yanhong Yang, W. Pei, L. Kong, Tianjiao Pu, Shixiong Fan, Renle Huang","doi":"10.1109/TDC.2018.8440376","DOIUrl":"https://doi.org/10.1109/TDC.2018.8440376","url":null,"abstract":"In this paper, a comprehensive optimization of load transfer strategy for distribution network with flexible interconnect device (FID) is discussed. FID with accurate control of power flow is versatile and increasingly being considered to transfer load without black-out in distribution system with high penetrations of distributed generation (DG). The interconnection structure and exact operating set-point of FID are discussed which realized loop closing operation of distribution system. Then, the non-linear combinational optimization problem models of load transfer with FID are established which considering separately different objectives and constraints. In order to solve these complicated optimization problems, hybrid coding based genetic algorithm (GA) mixed particle swarm algorithm (PSO) is used. A case study based on 3 terminal interconnection 10kV distribution network with FID is carried out for load transfer strategy verification. The results show that the FID and proposed comprehensive optimization method have stronger ability to improve the performance of distribution system with power loss reduction, feeder load balancing, and DG penetration increasing.","PeriodicalId":6568,"journal":{"name":"2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)","volume":"14 1","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2018-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87193602","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 : 2018-04-16DOI: 10.1109/TDC.2018.8440235
Israel Akingeneye, Jingxian Wu
In this paper, we study bad data detection in a power system by strategically placing phasor measurement units (PMUs) at various buses across the power grid. We propose to optimize PMU placements by maximizing the probability of detecting bad data maliciously injected in the power grid. An optimum bad data detector is first developed by following the NeymanPearson criterion. The corresponding detection probability is shown to be an increasing function of the Kullback-Leibler (KL) divergence between the data distributions with and without bad data, respectively. Thus maximizing the detection probability is equivalent to maximizing the KL divergence. Since the bad data used in an attack is unknown, the PMU placement algorithm is developed by following a max-min criterion, that is, maximizing the minimum KL divergence under the assumption of the least detectable attack vector. Simulation results show that using the KL divergence as a design metric results in significant performance gains over existing methods that are developed based on critical measurements.
{"title":"PMU-Assisted Bad Data Detection in Power Systems","authors":"Israel Akingeneye, Jingxian Wu","doi":"10.1109/TDC.2018.8440235","DOIUrl":"https://doi.org/10.1109/TDC.2018.8440235","url":null,"abstract":"In this paper, we study bad data detection in a power system by strategically placing phasor measurement units (PMUs) at various buses across the power grid. We propose to optimize PMU placements by maximizing the probability of detecting bad data maliciously injected in the power grid. An optimum bad data detector is first developed by following the NeymanPearson criterion. The corresponding detection probability is shown to be an increasing function of the Kullback-Leibler (KL) divergence between the data distributions with and without bad data, respectively. Thus maximizing the detection probability is equivalent to maximizing the KL divergence. Since the bad data used in an attack is unknown, the PMU placement algorithm is developed by following a max-min criterion, that is, maximizing the minimum KL divergence under the assumption of the least detectable attack vector. Simulation results show that using the KL divergence as a design metric results in significant performance gains over existing methods that are developed based on critical measurements.","PeriodicalId":6568,"journal":{"name":"2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)","volume":"78 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2018-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76131350","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 : 2018-04-16DOI: 10.1109/TDC.2018.8440352
I. Ndiaye, E. Ahmed, C. Burns, Jonathan Nickerson, Michael Falls
Simulations using PSCAD have been performed to evaluate the impact of distributed solar photovoltaic (PV) systems on the performance of suburban feeders. Multiple scenarios including low, medium and high feeder loading as well as different PV generation levels and micro-inverters reactive power supports have been analyzed and compared to the baseline case referred to as no PV. Results showed at high PV generation feeder losses increases when load is below a medium level. They also consistently showed that the feeder performance, in particular the power factor at the feeder head, is deteriorated when no reactive power support is provided by the PV micro-inverters. Adjusting the micro-inverters power factor based on the generation level significantly improves the feeder performance. Alternately a fixed micro-inverter power factor of 0.9 will provided better performance relatively to the baseline.
{"title":"Impact of Distributed Solar PV Systems Operation on Residential Feeders Performance","authors":"I. Ndiaye, E. Ahmed, C. Burns, Jonathan Nickerson, Michael Falls","doi":"10.1109/TDC.2018.8440352","DOIUrl":"https://doi.org/10.1109/TDC.2018.8440352","url":null,"abstract":"Simulations using PSCAD have been performed to evaluate the impact of distributed solar photovoltaic (PV) systems on the performance of suburban feeders. Multiple scenarios including low, medium and high feeder loading as well as different PV generation levels and micro-inverters reactive power supports have been analyzed and compared to the baseline case referred to as no PV. Results showed at high PV generation feeder losses increases when load is below a medium level. They also consistently showed that the feeder performance, in particular the power factor at the feeder head, is deteriorated when no reactive power support is provided by the PV micro-inverters. Adjusting the micro-inverters power factor based on the generation level significantly improves the feeder performance. Alternately a fixed micro-inverter power factor of 0.9 will provided better performance relatively to the baseline.","PeriodicalId":6568,"journal":{"name":"2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)","volume":"381 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2018-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77673900","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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