Various Types of Smart Grid Techniques : A Review

For many years, there has been no reforms are done in the main architecture of the electric power grid. The twentieth century centrally controlled grids are unable to fulfill the need of 21st century requirements. Smart grid is introduced to address the challenges of the previous grid. The smart grid is a modernized infrastructure of electric power grid that use high power converters, automation control, modernized communication architecture, smart metering technologies, modernized energy management techniques, network and energy availability to enhance the reliability and efficiency of the electric power grid. Communication architecture and correct information are main two components of the current electric power systems, but smart grid need much larger and more complex communication architecture for power systems. This paper deals with the different techniques that are used in smart grid to enhance its infrastructure and functionality. Our main focus in this paper is to provide the contemporary look at the different techniques that are currently used in smart grid to make him more efficient and reliable. It is expects that this paper will bring a better understating of the different techniques, to overcome the smart grid potential advantages and research challenges and raise interest in the research community to explore this research area. Keywords– Distributed Generation (DG), Demand Side Management (DSM), Renewable Energy Sources (RES), Home Area Network (HAN), General Packet Radio Service (GPRS) and Auto Regressive Integrated Moving Average (ARIMA)

[1]  Wenye Wang,et al.  Review and evaluation of security threats on the communication networks in the smart grid , 2010, 2010 - MILCOM 2010 MILITARY COMMUNICATIONS CONFERENCE.

[2]  D.G. Infield,et al.  Potential for Domestic Dynamic Demand-Side Management in the UK , 2007, 2007 IEEE Power Engineering Society General Meeting.

[3]  Paula Gomes Mian,et al.  Systematic Review in Software Engineering , 2005 .

[4]  Avelino J. Gonzalez,et al.  Short-term electrical load forecasting using a fuzzy ARTMAP neural network , 1998, Defense, Security, and Sensing.

[5]  John Brooke,et al.  A Realistic ICT Network Design and Implementation in the Neighbourhood Area of the Smart Grid , 2013 .

[6]  Siu-Ming Yiu,et al.  Privacy-preserving advance power reservation , 2012, IEEE Communications Magazine.

[7]  Peter Palensky,et al.  Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads , 2011, IEEE Transactions on Industrial Informatics.

[8]  J. Contreras,et al.  ARIMA Models to Predict Next-Day Electricity Prices , 2002, IEEE Power Engineering Review.

[9]  Barbara A. Kitchenham,et al.  Systematic review in software engineering: where we are and where we should be going , 2012, EAST '12.

[10]  S. J. Kiartzis,et al.  A neural network short term load forecasting model for the Greek power system , 1996 .

[11]  A. Goh,et al.  Support vector machines: Their use in geotechnical engineering as illustrated using seismic liquefaction data , 2007 .

[12]  Michele Zorzi,et al.  The Deployment of a Smart Monitoring System Using Wireless Sensor and Actuator Networks , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[13]  Nada Golmie,et al.  NIST Framework and Roadmap for Smart Grid Interoperability Standards, Release 3.0 , 2014 .

[14]  R. Engle,et al.  Modelling peak electricity demand , 1992 .

[15]  Thomas J. Overbye,et al.  Smart Grids and Beyond: Achieving the Full Potential of Electricity Systems , 2012, Proceedings of the IEEE.

[16]  Sachin Tajane,et al.  Assessment of System Vulnerability for Smart Grid Applications , 2016, 2016 IEEE International Conference on Engineering and Technology (ICETECH).

[17]  Chi Zhou,et al.  Developing ZigBee Deployment Guideline Under WiFi Interference for Smart Grid Applications , 2011, IEEE Transactions on Smart Grid.

[18]  Ward Jewell,et al.  Wireless AMI application and security for controlled home area networks , 2011, 2011 IEEE Power and Energy Society General Meeting.

[19]  Frank C. Lambert,et al.  A survey on communication networks for electric system automation , 2006, Comput. Networks.

[20]  Prashant J. Shenoy,et al.  Private memoirs of a smart meter , 2010, BuildSys '10.

[21]  Alfredo Vaccaro,et al.  A Decentralized and Cooperative Architecture for Optimal Voltage Regulation in Smart Grids , 2011, IEEE Transactions on Industrial Electronics.

[22]  Taskin Koçak,et al.  Smart Grid Technologies: Communication Technologies and Standards , 2011, IEEE Transactions on Industrial Informatics.

[23]  Viktor K. Prasanna,et al.  Accurate and efficient selection of the best consumption prediction method in smart grids , 2014, 2014 IEEE International Conference on Big Data (Big Data).

[24]  T.G. Habetler,et al.  Power line sensornet - a new concept for power grid monitoring , 2006, 2006 IEEE Power Engineering Society General Meeting.

[25]  Georgios Kalogridis,et al.  Smart Grid Privacy via Anonymization of Smart Metering Data , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[26]  Xiaohui Liang,et al.  EPPA: An Efficient and Privacy-Preserving Aggregation Scheme for Secure Smart Grid Communications , 2012, IEEE Transactions on Parallel and Distributed Systems.

[27]  Mohamed Mohandes,et al.  Support vector machines for short‐term electrical load forecasting , 2002 .

[28]  Giacomo Verticale,et al.  Privacy-preserving smart metering with multiple data Consumers , 2013, Comput. Networks.