Application of Data Mining in Smart Grid Technology

Application of Data Mining in Smart Grid Technology

Lipi Chhaya (Researcher, University of Petroleum and Energy Studies, India), Paawan Sharma (Pandit Deendayal Petroleum University, India), Adesh Kumar (University of Petroleum and Energy Studies, India) and Govind Bhagwatikar (Sany Wind Energy India Private Limited, India)
Copyright: © 2021 |Pages: 13
DOI: 10.4018/978-1-7998-3479-3.ch056

Abstract

Smart grid technology is a radical approach for improvisation in existing power grid. Some of the significant features of smart grid technology are bidirectional communication, AMI, SCADA, renewable integration, active consumer participation, distribution automation, and complete management of entire grid through wireless communication standards and technologies. Management of complex, hierarchical, and heterogeneous smart grid infrastructure requires data collection, storage, processing, analysis, retrieval, and communication for self-healing and complete automation. Data mining techniques can be an effective solution for smart grid operation and management. Data mining is a computational process for data analysis. Data scrutiny is unavoidable for unambiguous knowledge discovery as well as decision making practices. Data mining is inevitable for analysis of various statistics associated with power generation, distribution automation, data communications, billing, consumer participation, and fault diagnosis in smart power grid.
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Introduction

Smart grid technology is a radical and creative approach for improvisation in existing passive power grid. Assimilation of power and communication infrastructures is inevitable for the design and deployment of an imminent smart grid technology. The grid is called ‘Smart’ as it is accomplished with intelligent devices for decision making. Some of the substantial features of smart grid technology are bidirectional communication, renewable integration, active consumer participation, distribution automation, advanced metering infrastructure, supervisory control and data acquisition and complete management of entire power grid through wireless communication protocols and technologies. Smart grid communication infrastructure is a gigantic architecture with massive amount of data communication between various hierarchical network layers (Farooq & Jung, 2014). Full duplex data communication is required for monitoring, control, security, management and fault diagnosis of entire power grid (Mahmood et al., 2015). Management of complex, hierarchical and heterogeneous smart grid communication infrastructure necessitates data collection, storage, processing, analysis, retrieval and communication for self-healing and complete automation. Collection, interpretation and analysis of massive quantity of data generated in smart grid operation are critical, inevitable and complex tasks (Gungor et al., 2010). Data mining techniques can be an effective solution for smart grid operation and management. Data mining is essential for converting information into knowledge (Wijaya, T., 2013). Knowledge discovery and data mining are interdisciplinary tasks in the context of smart grid network. Database management and data mining are the two significant aspects of a database system. Database management deals with processing and storage of data and data mining deals with discovery and abstraction of knowledge for the purpose of decision making. Data mining is a computational process for data scrutiny and analysis. Data analysis is unavoidable for unambiguous knowledge discovery as well as decision making practices. Data mining is necessary for analysis of various statistics associated with power generation, distribution automation, data communications, billing, consumer participation, and fault diagnosis in smart power grid. In Smart grid, accumulation of real time data is inevitable. Data mining techniques are required when data is continuously collected on real time basis (Atzmueller et al., 2013). The pattern of gigantic sets of data can be effectively extracted and scrutinized with the use of different data mining techniques for energy efficiency, reliability and real time decision making. This chapter is expected to serve as a comprehensive analysis and review of application of data mining techniques in generation, transmission, distribution and utilization of energy in smart grid infrastructure.

Key Terms in this Chapter

Data Mining: A process of extracting information from raw data sets.

Smart Grid: An electrical grid with an integration of power as well as information and communication infrastructure. It is characterized by full duplex flow of energy and information, advanced metering infrastructure, renewable energy resources, self-healing, active involvement of consumers, and Internet of things.

Wireless Sensor Network: A network comprising of sensor, communication transceivers, memory, processing unit and power supply. Wireless sensor network is useful to convey various parameters such as current, temperature, humidity etc. to the remote monitoring and control unit by using wireless communication technology.

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