This Article Collection deals with innovative data-driven solutions for smart grids. The integration of communication systems and smart metering in power system has led, in recent years, to capability to measure quantities and communicate measurements with a precision, a sampling rate and a bandwidth that were unimaginable just a few years ago. The potential for this amount of information is huge but the power system industry and community have not yet fully exploited such a capability.
In this complex data-rich, but information-limited domain, the data streaming generated by the pervasive grid sensors do not always provide smart grids operators with the necessary information to react to external disturbances in a timely manner. Even if fast computing algorithms are utilized to convert data into information, smart grid operators face the challenge of not having the full picture of the information context and, therefore, the obtained information cannot be deployed with a high degree of confidence.
To address this complex issue, the most promising research directions are oriented toward the conceptualization of improved information processing paradigms and smart decision support systems aimed at enhancing standard operating procedures, based on pre-defined grid conditions and static operating thresholds, with a set of interactive information services, which could promptly provide the right information at the right moment to the right decision maker. To effectively support the deployment of these services in modern smart grids it will be incumbent upon the scientific community to develop advanced techniques and algorithms for reliable power system data acquisition and processing, which should support semantics and content-based data extraction and integration from heterogeneous sensor networks.
We welcome theoretical and proof-of-concept works on specific aspect of measurements of electrical quantities, the issues related to communicate and store such measurements and the processing of data for the operation, control and planning of the grid. At the same time, we are also very much interested in practical applications and field trials that showcase the potential of big data in power systems. Finally, significant examples of creation of open data lakes devoted to energy and their integration to other social, environmental and economic data are also welcome to highlight the importance of data reuse.
The goal of this collection is to provide the community with a broad view of the trends and opportunities that the availability of large sets of measurement data offer to the power system community and, ultimately, to the society as a whole.
We are looking for high-quality breakthrough contributions on any aspect related to big data, smart grids and energy systems, covering but not limited to the following:
• System monitoring
• State estimation
• On-line centralized and decentralized controls
• Smart metering
• Smart building
• Energy communities
• Provision of ancillary services
• Management and control of distributed resources (renewable energy sources, energy storage systems, microgrids, etc.)
• Management and control of large-scale electric vehicle chargers
• Virtual power plants
• Social impact of energy policies.
This Article Collection deals with innovative data-driven solutions for smart grids. The integration of communication systems and smart metering in power system has led, in recent years, to capability to measure quantities and communicate measurements with a precision, a sampling rate and a bandwidth that were unimaginable just a few years ago. The potential for this amount of information is huge but the power system industry and community have not yet fully exploited such a capability.
In this complex data-rich, but information-limited domain, the data streaming generated by the pervasive grid sensors do not always provide smart grids operators with the necessary information to react to external disturbances in a timely manner. Even if fast computing algorithms are utilized to convert data into information, smart grid operators face the challenge of not having the full picture of the information context and, therefore, the obtained information cannot be deployed with a high degree of confidence.
To address this complex issue, the most promising research directions are oriented toward the conceptualization of improved information processing paradigms and smart decision support systems aimed at enhancing standard operating procedures, based on pre-defined grid conditions and static operating thresholds, with a set of interactive information services, which could promptly provide the right information at the right moment to the right decision maker. To effectively support the deployment of these services in modern smart grids it will be incumbent upon the scientific community to develop advanced techniques and algorithms for reliable power system data acquisition and processing, which should support semantics and content-based data extraction and integration from heterogeneous sensor networks.
We welcome theoretical and proof-of-concept works on specific aspect of measurements of electrical quantities, the issues related to communicate and store such measurements and the processing of data for the operation, control and planning of the grid. At the same time, we are also very much interested in practical applications and field trials that showcase the potential of big data in power systems. Finally, significant examples of creation of open data lakes devoted to energy and their integration to other social, environmental and economic data are also welcome to highlight the importance of data reuse.
The goal of this collection is to provide the community with a broad view of the trends and opportunities that the availability of large sets of measurement data offer to the power system community and, ultimately, to the society as a whole.
We are looking for high-quality breakthrough contributions on any aspect related to big data, smart grids and energy systems, covering but not limited to the following:
• System monitoring
• State estimation
• On-line centralized and decentralized controls
• Smart metering
• Smart building
• Energy communities
• Provision of ancillary services
• Management and control of distributed resources (renewable energy sources, energy storage systems, microgrids, etc.)
• Management and control of large-scale electric vehicle chargers
• Virtual power plants
• Social impact of energy policies.
