Computational awareness for smart grid: a review

Smart grid has been an active research area in recent years because almost all the technologies required to build smart grid are mature enough. It is expected that not only can smart grid reduce electricity consumption, but it can also provide a more reliable and versatile service than the traditional power grid can. Although the infrastructure of smart grid all over the world is far from complete yet, there is no doubt that our daily life will benefit a lot from smart grid. Hence, many researches are aimed to point out the challenges and needs of future smart grid. The question is, how do we use the massive data captured by smart meters to provide services that are as “smart” as possible instead of just automatically reading information from the meters. This paper begins with a discussion of the smart grid before we move on to the basic computational awareness for smart grid. A brief review of data mining and machine learning technologies for smart grid, which are often used for computational awareness, is then given to further explain their potentials. Finally, challenges, potentials, open issues, and future trends of smart grid are addressed.

[1]  Robert Schober,et al.  Optimal and autonomous incentive-based energy consumption scheduling algorithm for smart grid , 2010, 2010 Innovative Smart Grid Technologies (ISGT).

[2]  Farid Farahmand,et al.  Energy-awareness in dynamic traffic grooming , 2010, 2010 Conference on Optical Fiber Communication (OFC/NFOEC), collocated National Fiber Optic Engineers Conference.

[3]  Yang Xiao,et al.  A survey of communication/networking in Smart Grids , 2012, Future Gener. Comput. Syst..

[4]  Anil K. Jain,et al.  Data clustering: a review , 1999, CSUR.

[5]  Elaine J. Weyuker,et al.  Locating where faults will be [software testing] , 2005, 2005 Richard Tapia Celebration of Diversity in Computing Conference.

[6]  Georgios Kalogridis,et al.  Privacy for Smart Meters: Towards Undetectable Appliance Load Signatures , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[7]  Christoph Flath,et al.  Cluster Analysis of Smart Metering Data , 2012, Business & Information Systems Engineering.

[8]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[9]  Walid G. Morsi,et al.  Voltage collapse detection using ant colony optimization for smart grid applications , 2010, 2010 IEEE Electrical Power & Energy Conference.

[10]  R. Harley,et al.  Computational Intelligence in Smart Grids , 2011 .

[11]  Wencong Su,et al.  Performance evaluation of a PHEV parking station using Particle Swarm Optimization , 2011, 2011 IEEE Power and Energy Society General Meeting.

[12]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[13]  Abbe E. Forman,et al.  Smart Grid , 2013, Int. J. E Politics.

[14]  Jason Lines,et al.  Classification of Household Devices by Electricity Usage Profiles , 2011, IDEAL.

[15]  Rui Xu,et al.  Survey of clustering algorithms , 2005, IEEE Transactions on Neural Networks.

[16]  A. Feliachi,et al.  Multi-Agent systems hardware development and deployment for smart grid control applications , 2011, 2011 IEEE Power and Energy Society General Meeting.

[17]  S. Dreyfus,et al.  Thermodynamical Approach to the Traveling Salesman Problem : An Efficient Simulation Algorithm , 2004 .

[18]  Hamid Lesani,et al.  AAHES: A hybrid expert system realization of Adaptive Autonomy for smart grid , 2010, 2010 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe).

[19]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1992, Artificial Intelligence.

[20]  Farrokh Rahimi,et al.  Demand Response as a Market Resource Under the Smart Grid Paradigm , 2010, IEEE Transactions on Smart Grid.

[21]  Anton Gustafsson,et al.  The power-aware cord: energy awareness through ambient information display , 2005, CHI Extended Abstracts.

[22]  F. Glover,et al.  Handbook of Metaheuristics , 2019, International Series in Operations Research & Management Science.

[23]  Claudio Carpineto,et al.  A Survey of Automatic Query Expansion in Information Retrieval , 2012, CSUR.

[24]  Yi Xu,et al.  A survey on the communication architectures in smart grid , 2011, Comput. Networks.

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

[26]  Andries P. Engelbrecht,et al.  Computational Intelligence: An Introduction , 2002 .

[27]  J. G. Slootweg,et al.  Incorporating solar home systems for smart grid applications , 2012, 2012 47th International Universities Power Engineering Conference (UPEC).

[28]  Mo-Yuen Chow,et al.  A Survey on the Electrification of Transportation in a Smart Grid Environment , 2012, IEEE Transactions on Industrial Informatics.

[29]  Seema Singh,et al.  Application of computational intelligence in emerging power systems , 2010 .

[30]  S. Postel,et al.  Carrying Capacity: Earth’s Bottom Line , 1994 .

[31]  Christian Blum,et al.  Metaheuristics in combinatorial optimization: Overview and conceptual comparison , 2003, CSUR.

[32]  Zhao Lei,et al.  Architecture Design For Smart Grid , 2012 .

[33]  Cheng Lin,et al.  Integrated Design and Implementation of Toronto's Smart Distribution Grid , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[34]  H. Morais,et al.  Technical and economic resources management in smart grids using heuristic optimization methods , 2010, IEEE PES General Meeting.

[35]  Ganesh K. Venayagamoorthy,et al.  Dynamic, Stochastic, Computational, and Scalable Technologies for Smart Grids , 2011, IEEE Computational Intelligence Magazine.

[36]  V. Cerný.  Thermodynamical approach to the traveling salesman problem: An efficient simulation algorithm , 1985 .

[37]  Tomonobu Senjyu,et al.  Optimal Operation by Controllable Loads Based on Smart Grid Topology Considering Insolation Forecasted Error , 2011, IEEE Transactions on Smart Grid.

[38]  Chang-Tien Lu,et al.  Activity analysis based on low sample rate smart meters , 2011, KDD.

[39]  Russell C. Eberhart,et al.  Parameter Selection in Particle Swarm Optimization , 1998, Evolutionary Programming.

[40]  Jing Xie,et al.  Classification of power quality disturbances using wavelet and fuzzy support vector machines , 2005, 2005 International Conference on Machine Learning and Cybernetics.

[41]  Iain MacGill,et al.  Coordinated Scheduling of Residential Distributed Energy Resources to Optimize Smart Home Energy Services , 2010, IEEE Transactions on Smart Grid.

[42]  Lingfeng Wang,et al.  Multi-agent control system with intelligent optimization for smart and energy-efficient buildings , 2010, IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society.

[43]  Philip S. Yu,et al.  A framework for resource-aware knowledge discovery in data streams: a holistic approach with its application to clustering , 2006, SAC '06.

[44]  Gregory D. Abowd,et al.  Towards a Better Understanding of Context and Context-Awareness , 1999, HUC.

[45]  Pierluigi Siano,et al.  An overview on the smart grid concept , 2010, IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society.

[46]  Mo-Yuen Chow,et al.  Performance Evaluation of an EDA-Based Large-Scale Plug-In Hybrid Electric Vehicle Charging Algorithm , 2012, IEEE Transactions on Smart Grid.

[47]  Peter Miller,et al.  The Smart Swarm: How Understanding Flocks, Schools, and Colonies Can Make Us Better at Communicating, Decision Making, and Getting Things Done , 2010 .

[48]  L. L. Lai,et al.  An initial study on computational intelligence for smart grid , 2009, 2009 International Conference on Machine Learning and Cybernetics.

[49]  Thomas Way,et al.  Methods, metrics and motivation for a green computer science program , 2009, SIGCSE '09.

[50]  Paul J. Werbos,et al.  Computational Intelligence for the Smart Grid-History, Challenges, and Opportunities , 2011, IEEE Computational Intelligence Magazine.

[51]  Francesco Grimaccia,et al.  Photovoltaic plants predictive model by means of ANN trained by a hybrid evolutionary algorithm , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

[52]  Hamid Aghvami,et al.  A Universal Resource Awareness Channel for Cognitive Radio , 2006, 2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications.

[53]  Anna Scaglione,et al.  For the Grid and Through the Grid: The Role of Power Line Communications in the Smart Grid , 2010, Proceedings of the IEEE.

[54]  Marco Mussetta,et al.  Information Processing in Smart Grids and Consumption Dynamics , 2011, Information Retrieval and Mining in Distributed Environments.

[55]  Maurice Clerc,et al.  The particle swarm - explosion, stability, and convergence in a multidimensional complex space , 2002, IEEE Trans. Evol. Comput..

[56]  Zhe Chen,et al.  Cognitive Radio for Smart Grid: Theory, Algorithms, and Security , 2011, Int. J. Digit. Multim. Broadcast..

[57]  Fernando G. Gonzalez.  An Intelligent Controller for the Smart Grid , 2013, CSER.

[58]  Hossam Afifi,et al.  A Survey on Personalized TV and NGN Services through Context-Awareness , 2012, CSUR.

[59]  Kemal Akkaya,et al.  A survey of routing protocols for smart grid communications , 2012, Comput. Networks.

[60]  James Kennedy,et al.  Particle swarm optimization , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

[61]  Andrea Tagarelli,et al.  Low-voltage electricity customer profiling based on load data clustering , 2009, IDEAS '09.

[62]  Luca Maria Gambardella,et al.  Ant colony system: a cooperative learning approach to the traveling salesman problem , 1997, IEEE Trans. Evol. Comput..

[63]  Haibo He,et al.  Toward a Smart Grid: Integration of computational intelligence into Power Grid , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

[64]  Carlos Ramos,et al.  AI in Power Systems and Energy Markets , 2011, IEEE Intell. Syst..

[65]  Tarlochan S. Sidhu,et al.  Opportunities and challenges of wireless communication technologies for smart grid applications , 2010, IEEE PES General Meeting.

[66]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[67]  Xinghuo Yu,et al.  Incremental pattern characterization learning and forecasting for electricity consumption using smart meters , 2011, 2011 IEEE International Symposium on Industrial Electronics.

[68]  George Karypis,et al.  A Comparison of Document Clustering Techniques , 2000 .

[69]  Pierre Kuonen,et al.  SmartGRID: A Fully Decentralized Grid Scheduling Framework Supported by Swarm Intelligence , 2008, 2008 Seventh International Conference on Grid and Cooperative Computing.

[70]  J. Randers,et al.  Tracking the ecological overshoot of the human economy , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[71]  B.F. Wollenberg,et al.  Toward a smart grid: power delivery for the 21st century , 2005, IEEE Power and Energy Magazine.

[72]  S. Chatterji,et al.  Artificial Intelligence Based Optimization Algorithm for Demand Response Management of Residential Load in Smart Grid , 2012 .

[73]  Marco Conti,et al.  Context and resource awareness in opportunistic network data dissemination , 2008, 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks.

[74]  Bing Liu,et al.  Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data , 2006, Data-Centric Systems and Applications.

[75]  Naoki Tanaka,et al.  Distributed non-intrusive load monitoring , 2011, ISGT 2011.

[76]  Jianhui Wang,et al.  Smart Transmission Grid: Vision and Framework , 2010, IEEE Transactions on Smart Grid.

[77]  J. C. Cepeda,et al.  Dynamic vulnerability assessment due to transient instability based on data mining analysis for Smart Grid applications , 2011, 2011 IEEE PES CONFERENCE ON INNOVATIVE SMART GRID TECHNOLOGIES LATIN AMERICA (ISGT LA).

[78]  Amit Jain,et al.  Fuzzy Modeling and Similarity Based Short Term Load Forecasting Using Swarm Intelligence-A Step Towards Smart Grid , 2012, BIC-TA.

[79]  Khosrow Moslehi,et al.  A Reliability Perspective of the Smart Grid , 2010, IEEE Transactions on Smart Grid.

[80]  Pramode K. Verma,et al.  A proposed communications infrastructure for the smart grid , 2010, 2010 Innovative Smart Grid Technologies (ISGT).

[81]  Yilu Liu,et al.  Visualization and Classification of Power System Frequency Data Streams , 2009, 2009 IEEE International Conference on Data Mining Workshops.

[82]  V. C. Gungor,et al.  Smart Grid and Smart Homes: Key Players and Pilot Projects , 2012, IEEE Industrial Electronics Magazine.

[83]  S. Karnouskos,et al.  Smart Houses for a Smart Grid , 2009 .

[84]  Fred W. Glover,et al.  Tabu Search - Part I , 1989, INFORMS J. Comput..

[85]  Prakash Ranganathan,et al.  Agent-Oriented Designs for a Self Healing Smart Grid , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[86]  Ghadir Radman,et al.  Survey on Smart Grid , 2010, Proceedings of the IEEE SoutheastCon 2010 (SoutheastCon).

[87]  Mohamed Medhat Gaber,et al.  Enabling Resource-Awareness for In-Network Data Processing in Wireless Sensor Networks , 2008, ADC.

[88]  H. T. Mouftah,et al.  Prediction-based charging of PHEVs from the smart grid with dynamic pricing , 2010, IEEE Local Computer Network Conference.

[89]  Gyung-Leen Park,et al.  Design of an Energy Consumption Scheduler Based on Genetic Algorithms in the Smart Grid , 2011, ICCCI.

[90]  Jiawei Han,et al.  Data Mining: Concepts and Techniques , 2000 .

[91]  Andries Petrus Engelbrecht,et al.  Fundamentals of Computational Swarm Intelligence , 2005 .

[92]  C. Reeves.  Modern heuristic techniques for combinatorial problems , 1993 .

[93]  Padhraic Smyth,et al.  From Data Mining to Knowledge Discovery in Databases , 1996, AI Mag..

[94]  Xinghuo Yu,et al.  Semi-supervised classification of characterized patterns for demand forecasting using smart electricity meters , 2011, 2011 International Conference on Electrical Machines and Systems.

[95]  Lingfeng Wang,et al.  Smart meters for power grid — Challenges, issues, advantages and status , 2011 .

[96]  Muhammad Ramzan,et al.  Fault aware routing algorithm to enhance network resiliency & achieve load balancing in Hybrid Wireless Optical Broadband Access Network , 2010, 7th International Symposium on High-capacity Optical Networks and Enabling Technologies.

[97]  Chu-Sing Yang,et al.  Classification algorithms for interactive multimedia services: a review , 2011, Multimedia Tools and Applications.

[98]  Nikhil R. Devanur,et al.  A computational theory of awareness and decision making , 2009, TARK '09.

[99]  Seung-Hwan Choi,et al.  A study for clustering method to generate Typical Load Profiles for Smart Grid , 2011, 8th International Conference on Power Electronics - ECCE Asia.

[100]  Fred Glover,et al.  Tabu Search - Part II , 1989, INFORMS J. Comput..

[101]  Tatsuya Yamazaki,et al.  AERO: extraction of user's activities from electric power consumption data , 2010, IEEE Transactions on Consumer Electronics.

[102]  Pedro Faria,et al.  Intelligent energy resource management considering vehicle-to-grid: A Simulated Annealing approach , 2012, 2012 IEEE Power and Energy Society General Meeting.

[103]  Valeriy Vyatkin,et al.  Towards intelligent Smart Grid devices with IEC 61850 Interoperability and IEC 61499 open control architecture , 2010, IEEE PES T&D 2010.

[104]  G. Pastuszak,et al.  Multi-Path Adaptive Computation-Aware Search Strategy for Block-Based Motion Estimation , 2007, EUROCON 2007 - The International Conference on "Computer as a Tool".

[105]  Ahmed Yousuf Saber,et al.  Intelligent unit commitment with vehicle-to-grid —A cost-emission optimization , 2010 .

[106]  Olfa Nasraoui,et al.  Web data mining: exploring hyperlinks, contents, and usage data , 2008, SKDD.

[107]  Abdalkarim Awad,et al.  Self-Organizing Smart Grid Services , 2012, 2012 Sixth International Conference on Next Generation Mobile Applications, Services and Technologies.

[108]  Yuan Ye,et al.  Power quality disturbances classification Based on multi-class classification SVM , 2009, 2009 2nd International Conference on Power Electronics and Intelligent Transportation System (PEITS).

[109]  Kendall Nygard,et al.  Smart grid data analytics for decision support , 2011, 2011 IEEE Electrical Power and Energy Conference.

[110]  Edward Curry,et al.  System of systems information interoperability using a linked dataspace , 2012, 2012 7th International Conference on System of Systems Engineering (SoSE).

[111]  Jun Zhu,et al.  A Data-Driven Approach to Interactive Visualization of Power Systems , 2011, IEEE Transactions on Power Systems.

[112]  M. Manic,et al.  Improving cyber-security of smart grid systems via anomaly detection and linguistic domain knowledge , 2012, 2012 5th International Symposium on Resilient Control Systems.

[113]  Rajiv Kapoor,et al.  Classification of power quality events – A review , 2012 .

[114]  Zhenhua Jiang,et al.  Computational Intelligence Techniques for a Smart Electric Grid of the Future , 2009, ISNN.