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Combining Power and Communication Network Simulation for Cost-Effective Smart Grid Analysis
Open accessAbstract
Today's electricity grid is transitioning to a so-called smart grid. The associated challenges and funding initiatives have spurred great efforts from the research community to propose innovative smart grid solutions. To assess the performance of possible solutions, simulation tools offer a cost effective and safe approach. In this paper we will provide a comprehensive overview of various tools and their characteristics, applicable in smart grid research: we will cover both the communication and associated ICT infrastructure, on top of the power grid. First, we discuss the motivation for the development of smart grid simulators, as well as their associated research questions and design challenges. Next, we discuss three types of simulators in the smart grid area: power system simulators, communication network simulators, and combined power and communication simulators. To summarize the findings from this survey, we classify the different simulators according to targeted use cases, simulation model level of detail, and architecture. To conclude, we discuss the use of standards and multi-agent based modeling in smart grid simulation.
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Leszczyna et al. proposed MAlSim, a malware attack simulator for testing SCADA systems under controlled environments.
“A malware attack simulator for testing SCADA system under controlled environments, Mobile Agent Malware Simulator MAlSim has been proposed by Leszczyna et al. [63].”
From Assessing and augmenting SCADA cyber security: A survey of techniques (2017) · cites this paper as [63]
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Research works printed but not linked: 102
- 10.1109/EUROCON.2011.5929279 · DOI
- 10.1109/TSG.2011.2166412 · DOI
- 10.1109/TPWRD.2008.917693 · DOI
- siaterlis, 2012, On the use of Emulab testbeds for scientifically rigorous experiments, IEEE Comm Surveys & Tuto, pp, 1
- 10.1145/1065579.1065669 · DOI
- 10.1109/TSG.2010.2055905 · DOI
- luo, 2012, A network based protection scheme of distribution system, 2012 IEEE International Conference on Power System Technology (POWERCON), 1
- 10.1109/TSG.2012.2185073 · DOI
- pandya, 2008, A survey of optimal power flow methods, J Theoretical and Applied Information Technology, 4, 450
- blanger, 2010, The what, where and why of real-time simulation, IEEE PES General Meeting, 25
- 10.1109/ESTS.2011.5770857 · DOI
- 10.1109/PES.2007.386202 · DOI
- 10.4108/icst.simutools.2012.247730 · DOI · Paper page
- 10.1109/SGMS.2011.6089027 · DOI
- 10.1109/EnergyTech.2011.5948542 · DOI
- 10.1109/ISGTEUROPE.2010.5638890 · DOI
- 10.1109/SMARTGRID.2010.5622057 · DOI
- 10.1109/SGMS.2011.6089201 · DOI
- 10.1109/PESGM.2012.6345649 · DOI
- 10.1109/37.856179 · DOI
- 10.1109/MCOM.2010.5621968 · DOI
- 10.1109/NAPS.2012.6336408 · DOI
- 10.1109/ISAP.2011.6082173 · DOI
- 10.1109/APEC.2002.989281 · DOI
- 10.1109/ISGTEurope.2012.6465670 · DOI
- 10.1109/TPWRS.2003.821001 · DOI
- anwar, 2011, Loss reduction of power distribution network using optimum size and location of distributed generation, Proc 21st Australasian Universities Power Engineering Conference (AUPEC '11), 1
- kreckelbergh, 2012, Sizing and dynamic analyses of a micro-grid supplying a harbor industrial area, Proc 16th Int Conf on System Theory Control and Computing 2012 (ICSTCC '12), 1
- chen, 2010, Transient stability analyses of micro-grids with multiple distributed generations, Proc 2010 Int Conf Power System Technology (POWERCON), 1
- 10.1002/bltj.20450 · DOI
- 10.1109/TSG.2012.2191805 · DOI
- 10.1109/TPWRD.2012.2230344 · DOI
- 10.1109/PES.2011.6039456 · DOI
- mehra, 2013, Analysis of PCA based compression and denoising of smart grid data under normal and fault conditions, Proc IEEE Int Conf Electronics Computing and Commun Technol 2013 (CONECCT '13), 1, 10.1109/CONECCT.2013.6469311 · DOI
- 10.1016/j.jpowsour.2004.12.025 · DOI · Paper page
- 10.1109/PTC.2011.6019227 · DOI
- 10.1109/ISIEA.2011.6108766 · DOI
- 10.1109/DEXA.2012.9 · DOI
- 10.1016/j.epsr.2010.08.001 · DOI
- andren, 2011, Frame-work for co-ordinated simulation of power networks and components in smart grids using common communication protocols, Proc 37th Annu IEEE Conf Ind Electron Soc (IECON'11), 2700
- hansen, 2003, Dynamic wind turbine models in power system simulation tool DlgSILENT, Tech Rep
- sachs, 2012, Smart grid offering within PSS®SINCAL, Tech Rep
- 10.1109/ISGT-Asia.2011.6167120 · DOI
- 10.1109/GLOCOM.2013.6831526 · DOI
- 10.1109/JCN.2012.00029 · DOI
- lin, 2011, Power system and communication network co-simulation for smart grid applications, Proc IEEE/PES Innovative Smart Grid Technol 2011 (ISGT '11), 1, 10.1109/ISGT.2011.5759166 · DOI
- 10.1049/cp.2009.0710 · DOI
- mora, 2009, Communications architecture of smart grids to manage the electrical demand, 3rd Workshop on Power Line Communications
- 10.4108/ICST.SIMUTOOLS2008.3027 · DOI
- 10.1109/CAMAD.2011.5941119 · DOI
- muller, 2010, A system design framework for scalability analysis of geographic routing algorithms in large-scale mesh networks, Proc 3rd Int ICST Conf on Simulation Tools and Techniques (SIMUTools '10) ICST, 1
- 10.4108/icst.simutools.2012.247729 · DOI
- 10.1109/TPWRS.2005.851911 · DOI
- 10.1109/TPWRS.2003.821016 · DOI
- kwok, 0, Power system toolbox (PST), Rensselaer Polytech c Inst
- 10.1109/TPWRS.2002.807117 · DOI
- 10.1109/TE.2006.879798 · DOI
- 10.1109/PES.2009.5275920 · DOI
- 10.1109/SmartGridComm.2012.6485988 · DOI
- 10.1109/SmartGridComm.2012.6485992 · DOI
- 10.1109/TII.2012.2218253 · DOI
- henderson, 2008, Network simulations with the ns-3 simulator, Proc ACM Conf Special Interest Group on Data Commun 2008 (SIGCOMM '08), 527
- 10.1109/MPE.2009.934876 · DOI
- 10.1109/ISGT.2011.5759169 · DOI · Paper page
- 10.1109/NAPS.2006.359615 · DOI
- 10.1109/TPWRS.2002.804957 · DOI
- 10.1109/EMS.2012.21 · DOI
- 10.1109/PSCE.2009.4840078 · DOI
- schutte, 2011, Composition of simulations for the analysis of smart grid scenarios, Energinet Tech Rep
- 10.1109/TDC.2008.4517260 · DOI
- 10.1109/SGMS.2011.6089203 · DOI
- brown, 2012, Performance comparison of LTE FDD and TDD based smart grid communications networks for unlink biased traffic, Proc 3rd IEEE Int Conf Smart Grid Commun 201 (SmartGridComm '12), 276
- 10.1109/WSC.2003.1261545 · DOI
- 10.1109/SmartGridComm.2012.6486070 · DOI
- 10.1109/SmartGridComm.2012.6486049 · DOI
- 10.1109/ISAP.2009.5352933 · DOI
- 10.1109/PSCE.2009.4840087 · DOI
- 10.1109/EMS.2009.53 · DOI
- schutte, 2012, Smart grid simulation platform architecture & requirements specification, Tech Rep
- 10.1109/SGMS.2011.6089204 · DOI
- paolone, 2013, A hardware-in-the-loop test platform for the realtime state estimation of active distribution networks using phasor measurement units, Cigr� SC6 Colloquium
- 10.1109/PES.2010.5589594 · DOI
- 10.1016/j.jpowsour.2004.12.022 · DOI · Paper page
- 10.1109/SMARTGRID.2010.5622032 · DOI
- 10.1109/MPAE.2005.1507024 · DOI
- 10.1109/JPROC.2011.2116110 · DOI
- 10.1109/TPWRS.2006.873129 · DOI
- 10.1109/SmartGridComm.2012.6485994 · DOI
- 10.1109/WESCAN.1995.494045 · DOI
- konnerth, 2012, Integration of simulations and MAS for smart grid management systems, Proc 3rd Int Workshop on Agent Technologies for Energy Systems (ATES 2012) at 11th Int Conf on Autonomos Augents and Multiagent Systems (AAMAS '12)
- 10.1109/SGMS.2011.6089202 · DOI
- 10.4108/icst.simutools.2011.238604 · DOI
- 10.1109/MPE.2011.943205 · DOI
- 10.1109/SmartGridComm.2011.6102303 · DOI
- 10.1109/ICC.2009.5198657 · DOI
- 10.1109/SMFG.2011.6125758 · DOI
- 10.1109/SMARTGRID.2010.5622054 · DOI
- 10.1109/SmartGridComm.2012.6485981 · DOI
- aparicio, 2011, Scalable smart grid simulations in OPNET Modeler, Proc OPNETWORK 2011 Tech Rep
- 10.1109/TPWRD.2006.886788 · DOI
- 10.1109/TPWRD.2011.2160879 · DOI
- 10.1109/APPEEC.2010.5448248 · DOI
Cited by
Sorted by citations
Assessing and augmenting SCADA cyber security: A survey of techniques
Nazir, S., Patel, S., & Patel, D. (2017) · Computers & Security · doi:10.1016/j.cose.2017.06.010 · Cited by 167
“Smart Grid simulators [32] provide a useful reference for simulation tools but do not address SCADA or cyber security.”
Background
Metadata
- Authors
- Mets, K., Ojea, J. A., & Develder, C.
- Affiliations
- Ghent University (BE)
- Venue
- IEEE Communications Surveys & Tutorials
- Published
- 2014
- Volume
- 16
- Issue
- 3
- Pages
- 1771-1796
- ISSN
- 1553-877X (ISSN-L)
- OpenAlex
- W2053264041
- Cited by
- 239
- References
- 0
- Citations by year
- 2026: 1 · 2025: 7 · 2024: 12 · 2023: 15 · 2022: 14 · 2021: 15 · 2020: 14 · 2019: 24 · 2018: 31 · 2017: 38 · 2016: 34 · 2015: 27 · 2014: 7
- FWCI
- 18.77
- Type
- journal article
- Language
- en
- Open access
- green
- zenodo.org
- Locations
- IEEE Communications Surveys & Tutorials (publishedVersion)
- Ghent University Academic Bibliography (Ghent University) (submittedVersion)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, other-oa)
- Funders
- European Commission (FP7 ICT, 318708, ICT-2011, FP7‐ICT‐2011‐8, FP7‐ICT‐2011)
- FP7 Information and Communication Technologies (FP7-ICT-2011-8)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid and Power Systems
- Physical Sciences › Engineering › Control and Systems Engineering › Smart Grid Security and Resilience
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Power Systems and Technologies
- Keywords
- smart grid, power system simulation, communication network simulation, ICT infrastructure, multi-agent simulation, simulation standards, level of detail
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