A Fuzzy-Multiagent Service Restoration Scheme for Distribution System With Distributed Generation

This paper proposes a new multiagent control system (MACS) for service restoration in distribution systems with integrated distributed generation (DG) units. First, the MACS detects and locates faults, then decides the optimal reconfiguration of the network for restoring de-energized loads, and finally regulates the nodes voltages. Unintentional islanding operation of DG units is avoided and different postfault response modes of DG unit are addressed in the MACS design. The MACS has a hybrid centralizeddecentralized structure where agents are arranged in two layers with different responsibilities and communication capabilities. Agents at load buses in the first layer can only communicate directly with its next neighbor load agents on the same feeder and to its feeder agent, whereas the higher level agents in the second layer can communicate directly with each other. This MACS structure reduces the possibilities of control system failures for a moderate communication network infrastructure. Full dynamic simulation model for evaluating the MACS is implemented.

[1]  Aggelos S. Bouhouras,et al.  Cost/worth assessment of reliability improvement in distribution networks by means of artificial intelligence , 2010 .

[2]  Yuan-Kang Wu,et al.  Study of Reconfiguration for the Distribution System With Distributed Generators , 2010, IEEE Transactions on Power Delivery.

[3]  J. J. Grainger,et al.  Distribution feeder reconfiguration for loss reduction , 1988 .

[4]  Y.-T. Hsiao,et al.  Enhancement of restoration service in distribution systems using a combination fuzzy-GA method , 2000 .

[5]  Hsiao-Hwa Chen,et al.  Smart Grid Communication: Its Challenges and Opportunities , 2013, IEEE Transactions on Smart Grid.

[6]  Sebastien Grenard,et al.  Distribution automation: The cornerstone for smart grid development strategy , 2009, 2009 IEEE Power & Energy Society General Meeting.

[7]  Cuong P. Nguyen,et al.  Agent Based Restoration With Distributed Energy Storage Support in Smart Grids , 2012, IEEE Transactions on Smart Grid.

[8]  Pascal Benoit,et al.  Design of a Multiagent‐Based Voltage Control System in Peer‐to‐Peer Networks for Smart Grids , 2014 .

[9]  Taskin Koçak,et al.  A Survey on Smart Grid Potential Applications and Communication Requirements , 2013, IEEE Transactions on Industrial Informatics.

[10]  Dipti Srinivasan,et al.  An Introduction to Multi-Agent Systems , 2010 .

[11]  Kevin Tomsovic,et al.  A heuristic search approach to feeder switching operations for overload, faults, unbalanced flow and maintenance , 1991 .

[12]  Y. Shoham.  Introduction to Multi-Agent Systems , 2002 .

[13]  Bin Song,et al.  Multi-agent approach for service restoration of microgrid , 2010, 2010 5th IEEE Conference on Industrial Electronics and Applications.

[14]  Ehab F. El-Saadany,et al.  A Novel Cooperative Protocol for Distributed Voltage Control in Active Distribution Systems , 2013, IEEE Transactions on Power Systems.

[15]  Hiroshi Sasaki,et al.  An efficient algorithm for distribution network restoration , 2001, 2001 Power Engineering Society Summer Meeting. Conference Proceedings (Cat. No.01CH37262).

[16]  K.Y. Lee,et al.  A multi-agent system-based intelligent identification system for power plant control and fault-diagnosis , 2006, 2006 IEEE Power Engineering Society General Meeting.

[17]  G.T. Heydt,et al.  Optimal Restoration of Distribution Systems Using Dynamic Programming , 2008, IEEE Transactions on Power Delivery.

[18]  Cui-Ru Wang,et al.  DISTRIBUTION NETWORK RECONFIGURATION BASED ON MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM , 2006 .

[19]  Smarajit Ghosh,et al.  Multi-Agent Systems (MAS) controlled Smart Grid – A Review , 2013 .

[20]  Mike Barley,et al.  Intelligent Agents and Multi-Agent Systems , 2003, Lecture Notes in Computer Science.

[21]  Minjie Zhang,et al.  A Hybrid Multiagent Framework With Q-Learning for Power Grid Systems Restoration , 2011, IEEE Transactions on Power Systems.

[22]  Abder Koukam,et al.  Multi-agent systems for grid energy management: A short review , 2010, IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society.

[23]  Amany El-Zonkoly.  Fault Diagnosis in Distribution Networks with Distributed Generation , 2011 .

[24]  T. Nagata,et al.  A Multiagent Approach to Power System Restoration , 2002, IEEE Power Engineering Review.

[25]  F. Milano,et al.  An open source power system analysis toolbox , 2005, 2006 IEEE Power Engineering Society General Meeting.

[26]  Seon-Ju Ahn,et al.  Operation Schemes of Smart Distribution Networks With Distributed Energy Resources for Loss Reduction and Service Restoration , 2013, IEEE Transactions on Smart Grid.

[27]  Quang-Thuy Ha,et al.  Intelligent Agents and Multi-Agent Systems , 2008, Lecture Notes in Computer Science.

[28]  C. H. Wang,et al.  A Multi-Agent Based Service Restoration in Distribution Network with Distributed Generations , 2009, 2009 15th International Conference on Intelligent System Applications to Power Systems.

[29]  Zeng Xiangjun,et al.  Multi-agents based protection for distributed generation systems , 2004, 2004 IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies. Proceedings.

[30]  J.A. Momoh,et al.  Optimal Reconfiguration of the Navy Ship Power System using Agents , 2006, 2005/2006 IEEE/PES Transmission and Distribution Conference and Exhibition.

[31]  Mingtian Zhou,et al.  The Future-Oriented Grid-Smart Grid , 2011, J. Comput..

[32]  Xi Fang,et al.  3. Full Four-channel 6.3-gb/s 60-ghz Cmos Transceiver with Low-power Analog and Digital Baseband Circuitry 7. Smart Grid — the New and Improved Power Grid: a Survey , 2022 .

[33]  Ward Jewell,et al.  Wireless communication for smart grid applications at distribution level — Feasibility and requirements , 2011, 2011 IEEE Power and Energy Society General Meeting.

[34]  Adisa A. Jimoh,et al.  Fuzzy multi-agent based voltage and reactive power control , 2011 .

[35]  Dheeraj Kumar Khatod,et al.  Optimal allocation of combined DG and capacitor for real power loss minimization in distribution networks , 2013 .

[36]  Chen-Ching Liu,et al.  A Petri net algorithm for scheduling of generic restoration actions , 1997 .

[37]  N.N. Schulz,et al.  A Multi-Agent Solution to Distribution Systems Restoration , 2007, IEEE Transactions on Power Systems.

[38]  Alagan Anpalagan,et al.  Handbook of Green Information and Communication Systems , 2012 .

[39]  S. S. Venkata,et al.  An expert system operational aid for restoration and loss reduction of distribution systems , 1988 .

[40]  Chia-Hung Lin,et al.  A multiagent‐based distribution automation system for service restoration of fault contingencies , 2011 .

[41]  S. K. Basu,et al.  A new algorithm for the reconfiguration of distribution feeders for loss minimization , 1992 .

[42]  Agostino Poggi,et al.  Developing Multi-agent Systems with JADE , 2007, ATAL.

[43]  Ehab F. El-Saadany,et al.  A Cooperative Multiagent Framework for Self-Healing Mechanisms in Distribution Systems , 2012, IEEE Transactions on Smart Grid.

[44]  James R. McDonald,et al.  Automating power system fault diagnosis through multi-agent system technology , 2004, 37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the.

[45]  Y. Kumar,et al.  Multiobjective, Multiconstraint Service Restoration of Electric Power Distribution System With Priority Customers , 2008, IEEE Transactions on Power Delivery.

[46]  Michael Wooldridge,et al.  Introduction to Multi-Agent Systems , 2016 .

[47]  Tsutomu Oyama.  Restorative planning of power system using genetic algorithm with branch exchange method , 1996, Proceedings of International Conference on Intelligent System Application to Power Systems.

[48]  Robin Roche,et al.  Agent-Based Architectures and Algorithms for Energy Management in Smart Gribs : Application to Smart Power Generation and Residential Demand Response , 2012 .