Data mining is the process of turning raw data into useful information. Data mining has been empl... more Data mining is the process of turning raw data into useful information. Data mining has been employed in many different data-rich industries, including banking, healthcare, manufacturing, and telecommunications. With the additions of thousands of PMUs to the nation’s power grid, the power systems industry has the data necessary to take advantage of data mining techniques and gain actionable insights. This white paper discusses the following topics related to applying data mining to the power systems industry:
● provide a high level overview of data mining, ● review how data mining has been used in various industries, ● present common big data architecture and software languages and tools that facilitate data mining, and ● provide use cases that show how data mining has been applied in the power grid community.
The purpose of this white paper is to provide an introductory reference for industry and academic... more The purpose of this white paper is to provide an introductory reference for industry and academic practitioners interested in exploring the use of synchrophasors and other time-synchronized measurements for supporting power distribution system planning, operation, and research. This paper is motivated by the belief that effective measurement and analytics for the electric grid, including the distribution level, represent an important enabling technology for electric power quality, reliability, grid resilience, and sustainability – especially given the growing significance of diverse and renewable resources. Significant changes are occurring at the periphery of the grid – more distributed generation and storage on customer premises, more customer-initiated demand response, electric vehicles and other changing customer load characteristics -- that necessitate better situational awareness and insight into distribution system conditions and performance.
In recent years, advanced sensors, intelligent automation, communication networks, and informatio... more In recent years, advanced sensors, intelligent automation, communication networks, and information technologies have been integrated into the electric grid to enhance its performance and efficiency. Integrating these new technologies has resulted in more interconnections and interdependencies between the physical and cyber components of the grid. Natural disasters and man-made perturbations have begun to threaten grid integrity more often. Urban infrastructure networks are highly reliant on the electric grid and consequently, the vulnerability of infrastructure networks to electric grid outages is becoming a major global concern. In order to minimize the economic, social, and political impacts of power system outages, the grid must be resilient. The concept of a power system cyber-physical resilience centers around maintaining system states at a stable level in the presence of disturbances. Resilience is a multidimensional property of the electric grid, it requires managing disturbances originating from physical component failures, cyber component malfunctions, and human attacks. In the electric grid community, there is not a clear and universally accepted definition of cyber-physical resilience. This paper focuses on the definition of resilience for the electric grid and reviews key concepts related to system resilience. This paper aims to advance the field not only by adding cyber-physical resilience concepts to power systems vocabulary, but also by proposing a new way of thinking about grid operation with unexpected disturbances and hazards and leveraging distributed energy resources.
Data mining is the process of turning raw data into useful information. Data mining has been empl... more Data mining is the process of turning raw data into useful information. Data mining has been employed in many different data-rich industries, including banking, healthcare, manufacturing, and telecommunications. With the additions of thousands of PMUs to the nation’s power grid, the power systems industry has the data necessary to take advantage of data mining techniques and gain actionable insights. This white paper discusses the following topics related to applying data mining to the power systems industry:
● provide a high level overview of data mining, ● review how data mining has been used in various industries, ● present common big data architecture and software languages and tools that facilitate data mining, and ● provide use cases that show how data mining has been applied in the power grid community.
The purpose of this white paper is to provide an introductory reference for industry and academic... more The purpose of this white paper is to provide an introductory reference for industry and academic practitioners interested in exploring the use of synchrophasors and other time-synchronized measurements for supporting power distribution system planning, operation, and research. This paper is motivated by the belief that effective measurement and analytics for the electric grid, including the distribution level, represent an important enabling technology for electric power quality, reliability, grid resilience, and sustainability – especially given the growing significance of diverse and renewable resources. Significant changes are occurring at the periphery of the grid – more distributed generation and storage on customer premises, more customer-initiated demand response, electric vehicles and other changing customer load characteristics -- that necessitate better situational awareness and insight into distribution system conditions and performance.
In recent years, advanced sensors, intelligent automation, communication networks, and informatio... more In recent years, advanced sensors, intelligent automation, communication networks, and information technologies have been integrated into the electric grid to enhance its performance and efficiency. Integrating these new technologies has resulted in more interconnections and interdependencies between the physical and cyber components of the grid. Natural disasters and man-made perturbations have begun to threaten grid integrity more often. Urban infrastructure networks are highly reliant on the electric grid and consequently, the vulnerability of infrastructure networks to electric grid outages is becoming a major global concern. In order to minimize the economic, social, and political impacts of power system outages, the grid must be resilient. The concept of a power system cyber-physical resilience centers around maintaining system states at a stable level in the presence of disturbances. Resilience is a multidimensional property of the electric grid, it requires managing disturbances originating from physical component failures, cyber component malfunctions, and human attacks. In the electric grid community, there is not a clear and universally accepted definition of cyber-physical resilience. This paper focuses on the definition of resilience for the electric grid and reviews key concepts related to system resilience. This paper aims to advance the field not only by adding cyber-physical resilience concepts to power systems vocabulary, but also by proposing a new way of thinking about grid operation with unexpected disturbances and hazards and leveraging distributed energy resources.
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This white paper discusses the following topics related to applying data mining to the power systems industry:
● provide a high level overview of data mining,
● review how data mining has been used in various industries,
● present common big data architecture and software languages and tools that facilitate data mining, and
● provide use cases that show how data mining has been applied in the power grid community.
This white paper discusses the following topics related to applying data mining to the power systems industry:
● provide a high level overview of data mining,
● review how data mining has been used in various industries,
● present common big data architecture and software languages and tools that facilitate data mining, and
● provide use cases that show how data mining has been applied in the power grid community.