State estimation of distribution networks through the real-time measurements of the smart meters

Leite, Jônatas Boás; Mantovani, José Roberto Sanches

doi:10.1109/ptc.2013.6652170

Cited by 11 publications

(11 citation statements)

References 6 publications

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“…The varieties of the load behaviors are ideal for the study of new tools that can be used towards the operation of the modern distribution system. For example, in Leite and Mantovani (2013) a state estimator algorithm was developed and evaluated that should work at the analysis layer from the reference model of the smart grid.…”

Section: Discussionmentioning

confidence: 99%

Development of a Smart Grid Simulation Environment, Part I: Project of the Electrical Devices Simulator

Leite

Mantovani

2014

J Control Autom Electr Syst

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A smart grid is an electric power system with high levels of automation, dispersed generation, intelligent monitoring and control; however, because the distribution networks in operation today do not have these characteristics, studies concerning the control, planning and operation of the smart grid are difficult to perform. To overcome these practical difficulties, studies investigating the smart grid can be conducted in computational environments that are able to reproduce meticulously the electrical and communicational behaviors expected by the smart grid. Therefore, in this paper, the development of a platform to simulate the advanced distribution management system from a reference model for smart grid, which has seven layers, is proposed. Part I of this paper is dedicated to formulating mathematically the three lower layers that make up the electrical devices simulator. The analysis of the results revealed the capability of the simulator to generate scenarios with a wide range of power demand that is ideal for developing new operation, planning and control tools for a smart grid.

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Section: Discussionmentioning

confidence: 99%

Development of a Smart Grid Simulation Environment, Part I: Project of the Electrical Devices Simulator

Leite

Mantovani

2014

J Control Autom Electr Syst

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“…This can help to prevent overloading components (transformers and lines) and to avoid power quality deviations [75]. Another example is the state estimation using smart meter data which may provide an alternative economical way of estimating states of MV and LV networks [76,77]. Smart meter data can also be used to enhance overcurrent protection [78] and load disaggregation [79].…”

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.

449

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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“…Agents in the analysis layer give support to the coordinator agents in the intelligence layer through the processing of historical and real-time data provided by agents in the lower layers. For example, the analysis agent can employ the Hamiltonian path theory and Kirchhoff's laws to produce a calculation scheme that allows the real-time estimation of the unknown states using the metering data from local agents [17], [18]. The addition of the calculated network states with the information from the energy market produces a global view of the distribution network that is utilized in load forecasting to obtain the normal, short-circuit and restorative operation conditions.…”

Section: Analysis Agent For State Estimationmentioning

confidence: 99%

“…In this way, proposed self-healing strategy should be integrated with the dynamic coloring tool that permits to the system operator monitor the energy quality delivered to the end consumers using the monitoring of the voltage profile [26]. The dynamic coloring tool uses several resources from the advanced distribution management system such as geo-referenced topological diagrams in multiple layers and the results of the real-time state estimation that employs the smart meter data [17], [18]. If the voltage ranges are standardized and associated with a specific color, each drawn branch should have a color in the topological diagram in accord with the voltage profile provided by the state estimation.…”

Section: A Location Of the Faulted Line-sectionmentioning

confidence: 99%

Development of a Self-Healing Strategy With Multiagent Systems for Distribution Networks

Leite

Mantovani

2017

IEEE Trans. Smart Grid

Self Cite

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The increase in information and communication technologies in the electric power system has led the distribution network to a new evolutionary stage known as a smart grid. In this scenario, automatic local switching plans based on an understanding of the network topology and load behavior allow the implementation of self-healing strategies. Self-healing aims at the minimization of the number of switching operations within the shortest time interval to restore the maximum load affected by a fault and to preserve distribution network operation limits. In this paper, multiagent system concepts are employed to develop a self-healing strategy, where all switching local agents have some awareness regarding the current network state and work cooperatively to reach the global purpose of distribution network automatic restoration.

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State estimation of distribution networks through the real-time measurements of the smart meters

Cited by 11 publications

References 6 publications

Development of a Smart Grid Simulation Environment, Part I: Project of the Electrical Devices Simulator

Development of a Smart Grid Simulation Environment, Part I: Project of the Electrical Devices Simulator

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

Development of a Self-Healing Strategy With Multiagent Systems for Distribution Networks

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