Some problems of smart meter algorithms for electric power quality measurements

Lipsky, A.; Miteva, N.

doi:10.1109/smfg.2011.6125765

Cited by 6 publications

(1 citation statement)

References 2 publications

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“…For those near real-time critical applications (five minutes, quarterly hours, half hours, hourly intervals), such as fault identification and localization on MV and LV networks to ensure faster intervention and reduced outage duration, monitoring power quality, acting remotely managing peaksaving, forecasting network conditions, facilitation of integration of renewable energy and PHEVs into the grid, smart meters can help [6]. Examples include the measurement of voltage distortion (harmonic voltages and voltage unbalance) [72] using smart meter data to derive a dynamic model for improving volt-var control [73], as well as controlling congestion and stability in a power market [74]. Metering data can be also used to derive the knowledge of the power flows at and near the low voltage end of the distribution networks so that the loading and losses of the network can be known more accurately.…”

Section: E Metering Intelligence To Support Real-time Operationsmentioning

confidence: 99%

Smart Electricity Meter Data Intelligence for Future Energy Systems: A Survey

Alahakoon

2016

IEEE Trans. Ind. Inf.

462

170

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Smart meters have been deployed in many countries across the world since early 2000s. The smart meter as a key element for the smart grid is expected to provide economic, social and environmental benefits for multiple stakeholders. There has been much debate over the real values of smart meters. One of the key factors that will determine the success of smart meters is smart meter data analytics which deal with data acquisition, transmission, processing, and interpretation that bring benefits to all stakeholders. This paper presents a comprehensive survey of smart electricity meters and their utilization focusing on key aspects of metering process, the different stakeholder interests and technologies used to satisfy stakeholder interests. Furthermore the paper highlights the challenges as well as opportunities arising due to the advent of big data and the increasing popularity of the cloud environments.time pricing schemes, and demand-response for energy saving and efficient use of energy generated.The research and development in smart meters and their applications have been progressed rapidly in recent years and many methods and techniques have been developed. The technological scope relating to smart meters covers a diverse range of ICT technologies, such as electronics and communication, and there have already been several surveys done, e.g.[7] looks into the different applications of smart grids focusing on the communication needs and also on communication requirements of smart meters for integration into power grids.[8] is a comprehensive survey of communication technologies for smart meters which could be used to satisfy the identified needs.[9] introduces a novel smart meter communication technology, [10] examines the web and data service aspect of smart meter networks, and [11] proposes a framework for smart meter privacy. In this paper, we examine these developments from a holistic data analytic viewpoint. We will also outline potential future applications and challenges that lie ahead. As a foundation for our holistic approach the key components of electricity meter intelligence is shown as in Figure 1. The three key components capture the aspects of data, technology and stakeholders. These aspects and the role they play in smart meter intelligence is discussed in section 2.

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Section: E Metering Intelligence To Support Real-time Operationsmentioning

confidence: 99%