Week of Events
ExComm October 2022 Meeting
ExComm October 2022 Meeting
Section Activities Agenda: Review Secretary and Treasury reports Discuss Affinity Group Activities - Consultant Networks, WIE, YP and PACE Review technical society activities - AP/MTT/UFFC, ComSoc/SP, Computyer/SMC, PES Review committee activities - Membership, Entrepreneur Society, IndustryLiason,, Student Activities Old Business New Business 1615 Stanley St, New Britain, Connecticut, United States, 06050, Virtual: https://events.vtools.ieee.org/m/324734
ExComm October 2022 Meeting
ExComm October 2022 Meeting
Section Activities Agenda: Review Secretary and Treasury reports Discuss Affinity Group Activities - Consultant Networks, WIE, YP and PACE Review technical society activities - AP/MTT/UFFC, ComSoc/SP, Computyer/SMC, PES Review committee activities - Membership, Entrepreneur Society, IndustryLiason,, Student Activities Old Business New Business 1615 Stanley St, New Britain, Connecticut, United States, 06050, Virtual: https://events.vtools.ieee.org/m/324734
ExComm October 2022 Meeting
ExComm October 2022 Meeting
Section Activities Agenda: Review Secretary and Treasury reports Discuss Affinity Group Activities - Consultant Networks, WIE, YP and PACE Review technical society activities - AP/MTT/UFFC, ComSoc/SP, Computyer/SMC, PES Review committee activities - Membership, Entrepreneur Society, IndustryLiason,, Student Activities Old Business New Business 1615 Stanley St, New Britain, Connecticut, United States, 06050, Virtual: https://events.vtools.ieee.org/m/324734
ExComm October 2022 Meeting
ExComm October 2022 Meeting
Section Activities Agenda: Review Secretary and Treasury reports Discuss Affinity Group Activities - Consultant Networks, WIE, YP and PACE Review technical society activities - AP/MTT/UFFC, ComSoc/SP, Computyer/SMC, PES Review committee activities - Membership, Entrepreneur Society, IndustryLiason,, Student Activities Old Business New Business 1615 Stanley St, New Britain, Connecticut, United States, 06050, Virtual: https://events.vtools.ieee.org/m/324734
ExComm October 2022 Meeting
ExComm October 2022 Meeting
Section Activities Agenda: Review Secretary and Treasury reports Discuss Affinity Group Activities - Consultant Networks, WIE, YP and PACE Review technical society activities - AP/MTT/UFFC, ComSoc/SP, Computyer/SMC, PES Review committee activities - Membership, Entrepreneur Society, IndustryLiason,, Student Activities Old Business New Business 1615 Stanley St, New Britain, Connecticut, United States, 06050, Virtual: https://events.vtools.ieee.org/m/324734
ExComm October 2022 Meeting
ExComm October 2022 Meeting
Section Activities Agenda: Review Secretary and Treasury reports Discuss Affinity Group Activities - Consultant Networks, WIE, YP and PACE Review technical society activities - AP/MTT/UFFC, ComSoc/SP, Computyer/SMC, PES Review committee activities - Membership, Entrepreneur Society, IndustryLiason,, Student Activities Old Business New Business 1615 Stanley St, New Britain, Connecticut, United States, 06050, Virtual: https://events.vtools.ieee.org/m/324734
ExComm October 2022 Meeting
ExComm October 2022 Meeting
Section Activities Agenda: Review Secretary and Treasury reports Discuss Affinity Group Activities - Consultant Networks, WIE, YP and PACE Review technical society activities - AP/MTT/UFFC, ComSoc/SP, Computyer/SMC, PES Review committee activities - Membership, Entrepreneur Society, IndustryLiason,, Student Activities Old Business New Business 1615 Stanley St, New Britain, Connecticut, United States, 06050, Virtual: https://events.vtools.ieee.org/m/324734
Underground Power Cable Grid Monitoring and Partial Discharge Characterization
Underground Power Cable Grid Monitoring and Partial Discharge Characterization
When it comes to electric power distribution, the fundamental goals of today’s electric utilities have not changed much in fifty years. They comprise a safer distribution system that poses minimal risks to the public and to utility workers, the reliable and stable delivery of power to critical, commercial, and residential customers, and economically sound business operations that meet both shareholder and ratepayer expectations. The challenges to these goals, however, have grown significantly over the past decade. Increasingly intense and frequent weather events raise the threat of outages and environmental risks; the process of shifting from a centralized to decentralized grid to meet decarbonization mandates creates complexities; and the integration of renewable energy sources and the proliferation of electric vehicles are escalating the demands on an aging distribution grid. This presentation gives an overview of how big these underground power grid challenges are and how machine learning and deep learning are tools to tackle some of these challenges. Co-sponsored by: Eversource Energy Center Speaker(s): Steffen Ziegler , Tim Morello Virtual: https://events.vtools.ieee.org/m/324708
Underground Power Cable Grid Monitoring and Partial Discharge Characterization
Underground Power Cable Grid Monitoring and Partial Discharge Characterization
When it comes to electric power distribution, the fundamental goals of today’s electric utilities have not changed much in fifty years. They comprise a safer distribution system that poses minimal risks to the public and to utility workers, the reliable and stable delivery of power to critical, commercial, and residential customers, and economically sound business operations that meet both shareholder and ratepayer expectations. The challenges to these goals, however, have grown significantly over the past decade. Increasingly intense and frequent weather events raise the threat of outages and environmental risks; the process of shifting from a centralized to decentralized grid to meet decarbonization mandates creates complexities; and the integration of renewable energy sources and the proliferation of electric vehicles are escalating the demands on an aging distribution grid. This presentation gives an overview of how big these underground power grid challenges are and how machine learning and deep learning are tools to tackle some of these challenges. Co-sponsored by: Eversource Energy Center Speaker(s): Steffen Ziegler , Tim Morello Virtual: https://events.vtools.ieee.org/m/324708
Underground Power Cable Grid Monitoring and Partial Discharge Characterization
Underground Power Cable Grid Monitoring and Partial Discharge Characterization
When it comes to electric power distribution, the fundamental goals of today’s electric utilities have not changed much in fifty years. They comprise a safer distribution system that poses minimal risks to the public and to utility workers, the reliable and stable delivery of power to critical, commercial, and residential customers, and economically sound business operations that meet both shareholder and ratepayer expectations. The challenges to these goals, however, have grown significantly over the past decade. Increasingly intense and frequent weather events raise the threat of outages and environmental risks; the process of shifting from a centralized to decentralized grid to meet decarbonization mandates creates complexities; and the integration of renewable energy sources and the proliferation of electric vehicles are escalating the demands on an aging distribution grid. This presentation gives an overview of how big these underground power grid challenges are and how machine learning and deep learning are tools to tackle some of these challenges. Co-sponsored by: Eversource Energy Center Speaker(s): Steffen Ziegler , Tim Morello Virtual: https://events.vtools.ieee.org/m/324708
Underground Power Cable Grid Monitoring and Partial Discharge Characterization
Underground Power Cable Grid Monitoring and Partial Discharge Characterization
When it comes to electric power distribution, the fundamental goals of today’s electric utilities have not changed much in fifty years. They comprise a safer distribution system that poses minimal risks to the public and to utility workers, the reliable and stable delivery of power to critical, commercial, and residential customers, and economically sound business operations that meet both shareholder and ratepayer expectations. The challenges to these goals, however, have grown significantly over the past decade. Increasingly intense and frequent weather events raise the threat of outages and environmental risks; the process of shifting from a centralized to decentralized grid to meet decarbonization mandates creates complexities; and the integration of renewable energy sources and the proliferation of electric vehicles are escalating the demands on an aging distribution grid. This presentation gives an overview of how big these underground power grid challenges are and how machine learning and deep learning are tools to tackle some of these challenges. Co-sponsored by: Eversource Energy Center Speaker(s): Steffen Ziegler , Tim Morello Virtual: https://events.vtools.ieee.org/m/324708
Underground Power Cable Grid Monitoring and Partial Discharge Characterization
Underground Power Cable Grid Monitoring and Partial Discharge Characterization
When it comes to electric power distribution, the fundamental goals of today’s electric utilities have not changed much in fifty years. They comprise a safer distribution system that poses minimal risks to the public and to utility workers, the reliable and stable delivery of power to critical, commercial, and residential customers, and economically sound business operations that meet both shareholder and ratepayer expectations. The challenges to these goals, however, have grown significantly over the past decade. Increasingly intense and frequent weather events raise the threat of outages and environmental risks; the process of shifting from a centralized to decentralized grid to meet decarbonization mandates creates complexities; and the integration of renewable energy sources and the proliferation of electric vehicles are escalating the demands on an aging distribution grid. This presentation gives an overview of how big these underground power grid challenges are and how machine learning and deep learning are tools to tackle some of these challenges. Co-sponsored by: Eversource Energy Center Speaker(s): Steffen Ziegler , Tim Morello Virtual: https://events.vtools.ieee.org/m/324708
Underground Power Cable Grid Monitoring and Partial Discharge Characterization
Underground Power Cable Grid Monitoring and Partial Discharge Characterization
When it comes to electric power distribution, the fundamental goals of today’s electric utilities have not changed much in fifty years. They comprise a safer distribution system that poses minimal risks to the public and to utility workers, the reliable and stable delivery of power to critical, commercial, and residential customers, and economically sound business operations that meet both shareholder and ratepayer expectations. The challenges to these goals, however, have grown significantly over the past decade. Increasingly intense and frequent weather events raise the threat of outages and environmental risks; the process of shifting from a centralized to decentralized grid to meet decarbonization mandates creates complexities; and the integration of renewable energy sources and the proliferation of electric vehicles are escalating the demands on an aging distribution grid. This presentation gives an overview of how big these underground power grid challenges are and how machine learning and deep learning are tools to tackle some of these challenges. Co-sponsored by: Eversource Energy Center Speaker(s): Steffen Ziegler , Tim Morello Virtual: https://events.vtools.ieee.org/m/324708
Underground Power Cable Grid Monitoring and Partial Discharge Characterization
Underground Power Cable Grid Monitoring and Partial Discharge Characterization
When it comes to electric power distribution, the fundamental goals of today’s electric utilities have not changed much in fifty years. They comprise a safer distribution system that poses minimal risks to the public and to utility workers, the reliable and stable delivery of power to critical, commercial, and residential customers, and economically sound business operations that meet both shareholder and ratepayer expectations. The challenges to these goals, however, have grown significantly over the past decade. Increasingly intense and frequent weather events raise the threat of outages and environmental risks; the process of shifting from a centralized to decentralized grid to meet decarbonization mandates creates complexities; and the integration of renewable energy sources and the proliferation of electric vehicles are escalating the demands on an aging distribution grid. This presentation gives an overview of how big these underground power grid challenges are and how machine learning and deep learning are tools to tackle some of these challenges. Co-sponsored by: Eversource Energy Center Speaker(s): Steffen Ziegler , Tim Morello Virtual: https://events.vtools.ieee.org/m/324708