Abstract
Abstract. Information from existing smart metering infrastructure, mainly used for billing purposes can also be utilised to monitor and control state of the grid. To add functionalities such as fault detection and real-time state estimation, data from smart meters should be accessed with increased frequency during run time. The data collection system should adapt to changing dynamics of the communication network and electrical grid. This paper first introduces adaptation functionalities for the data collection mechanism. To study and analyse the influence of configuration parameters that can be utilised for adaptation, a two-layer smart meter data access infrastructure is presented. An information quality metric, Mismatch Probability (mmPr) is introduced for the quantitative analysis of the two-layer data access system implemented in MATLAB based discrete event simulation study.
Original language | English |
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Title of host publication | SGIoT : The 1st EAI International Conference on Smart Grid Assisted Internet of Things |
Publisher | EAI - European Alliance for Innovation |
Publication date | 1 May 2017 |
ISBN (Electronic) | 978-1-63190-159-1 |
Publication status | Published - 1 May 2017 |
Event | The 1st EAI International Conference on Smart Grid Assisted Internet of Things - Sault Ste. Marie, Canada Duration: 11 Jul 2017 → 13 Jul 2017 http://sgiot.org/2017/show/home |
Conference
Conference | The 1st EAI International Conference on Smart Grid Assisted Internet of Things |
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Country/Territory | Canada |
City | Sault Ste. Marie |
Period | 11/07/2017 → 13/07/2017 |
Internet address |
Keywords
- Adaptive Data Collection, Network QOS, Smart Metering Infrastructures, Distribution Grid Monitoring, Information Quality