Developing a multiagent model of an integrated energy supply system in AnyLogic simulation software
https://doi.org/10.21285/1814-3520-2020-5-1080-1092
Abstract
The purpose of this work is to develop a multi-agent model of an integrated energy supply system in the AnyLogic simulation software and to conduct a research on the operation and interaction of objects in this system using the obtained model. A multi-agent approach is proposed to study integrated energy supply systems as it enables to carry out a detailed research of interaction and coordination mechanisms of various elements and subsystems (energy sources, transport subsystems, active consumers, etc.) of the object under investigation. The model is implemented in AnyLogic simulation software that supports designing, development and documenting of the created models, carrying out computer experiments, parameter optimization according to some criterion that enables visualization of the mechanisms of interaction and connection between the agents. A multi-agent model of the integrated power supply system has been developed. Agent state diagrams that take into account the operation of its elements have been created and the principles of their interaction and coordination have been analyzed. The structure of the developed model of an integrated power supply system contains four types of agents and connections between them. An experiment has been conducted on the basis of the developed model, in which the optimal solution was found for energy supply of consumers. The results of the conducted computational experiment show that the specified conditions and restrictions are met; messages and parameters are correctly transmitted between the agents and the agents perform the assigned functions in the system. The results obtained will allow to model real power supply systems of any complexity in order to study the properties and improve the efficiency of these systems. The developed model enables the possibility to model complex processes in an integrated energy supply system which relate to production, transport, distribution and consumption of energy.
Keywords
About the Authors
V. A. StennikovRussian Federation
Valery A. Stennikov, Corresponding Member RAS, Director
130, Lermontov St., Irkutsk 664033
E. A. Barakhtenko
Russian Federation
Evgeny A. Barakhtenko, Cand. Sci. (Eng.), Associate Professor, Senior Researcher
130, Lermontov St., Irkutsk 664033
G. S. Mayorov
Russian Federation
Gleb S. Mayorov, Postgraduate student
130, Lermontov St., Irkutsk 664033
References
1. Voropai NI, Stennikov VA, Barakhtenko EA. Methodological principles of constructing the integrated energy supply systems and their technological architecture. Journal of Physics: Conference Series. 2018. https://doi.org/10.1088/1742-6596/1111/1/012001
2. Voropai N, Stennikov V, Senderov S, Barachtenko E, Kovernikova L, Voytov O, еt al. Integrated infrastructural energy systems of regional and interregional level. Energeticheskaya politika. Seriya: Regional'naya energetika: novye tendencii I podhody = Energy Policy. Series: Regional energy: new trends and approaches. 2015;3:24– 32. (In Russ.)
3. Voropai NI, Stennikov VA. Integrated smart energy systems. Izvestiya Akademii nauk. Energetika. 2014;1:64–73. (In Russ.)
4. Verhoeven R, Willems E, Harcouët-Menou V, De Boever E, Hiddes L, Veld PO, et al. Minewater 2.0 project in Heerlen the Netherlands: transformation of a geothermal mine water pilot project into a full scale hybrid sustainable energy infrastructure for heating and cooling. Energy Procedia. 2014;46:58–67. https://doi.org/10.1016/j.egypro.2014.01.158
5. Ran Xiaohong, Zhou Renjun, Yang Yuwei, Lin Lvhao. The multi-objective optimization dispatch of Combined Cold Heat and Power based on the principle of equal emission. In: IEEE Power and Energy Society General Meeting. 2012. https://doi.org/10.1109/PESGM.2012.6345053
6. Anvari-Moghaddam A, Rahimi-Kian A, Mirian MS, Guerrero JM. A multi-agent based energy management solution for integrated buildings and microgrid system. Applied Energy. 2017;203:41–56. https://doi.org/10.1016/j.apenergy.2017.06.007
7. Bünning F, Wetter M, Fuchs M, Müller D. Bidirectional low temperature district energy systems with agent-based control: performance comparison and operation optimization. Applied Energy. 2018;209:502–515. https://doi.org/10.1016/j.apenergy.2017.10.072
8. Ren Yi, Fan Dongming, Feng Qiang, Wang Zili, Sun Bo, Yang Dezhen. Agent-based restoration approach for reliability with load balancing on smart grids. Applied Energy. 2019;249:46–57. https://doi.org/10.1016/j.apenergy.2019.04.119
9. Wooldridge M, Jennings NR. Intelligent agents: theory and practice. The Knowledge Engineering Review. 1995;10(2):115–152. https://doi.org/10.1017/S0269888900008122
10. Mayorov G, Stennikov V, Barakhtenko E. Application of the multiagent approach to the research of integrated energy supply systems. In: Energy Systems Research 2019: International Conference of Young Scientists: E3S Web of Conferences. 2019;114. https://doi.org/10.1051/e3sconf/201911401006
11. Antonova VM, Grechishkina NA, Kuznetsov NA. Analysis of the modelling results for passenger traffic at an underground station using AnyLogic. Information Processes. 2018;18(1):35–39.
12. Zhang Yongan, Wang Ying, Wu Long. Research on demand-driven leagile supply chain operation model: a simulation based on anylogic in system engineering. Systems Engineering Procedia.2012;3:249– 258. https://doi.org/10.1016/j.sepro.2011.11.027
13. Mokshin VV, Kirpichnikov AP, Maryashina DN, Stadnik NA, Zolotukin AV. Comparison of structural and simulation modelling systems of Stratum 2000, Simulink, and AnyLogic.Vestnik Kazanskogo tekhnologicheskogo universiteta. 2019;22(4):144–148.(In Russ.)
14. Mezentsev KN. Modeling of digital control circuits in AnyLogic. Nauka Rossii: tseli I zadachi: trudy IX Mezhdunarodnoi nauchnoi konferentsii = Russian science: goals and objectives: Proceedings of IX International scientific conference. 10 June 2018, Yekaterinburg. Yekaterinburg: Moscow Automobile and Road Construction State Technical University; 2018, p. 15–19. (In Russ.) https://doi.org/10.18411/sr-10-06-2018-03
15. Lyubchenko AA, Kopytov EY, Bogdanov AA. Statistical modeling of quality measures of operation and preventive maintenance of railway telecommunication equipment in AnyLogic. Doklady Tomskogo gosudarstvennogo universiteta system upravleniya I radioelektroniki = Proceedings of Tomsk State University of Control Systems and Radioelectronics. 2018;21(4):98–108. (In Russ.) https://doi.org/10.21293/1818-0442-2018-21-4-98-108
16. Elufereva YuS, Palmov SV. Simulation of railway station operation using AnyLogic means. Mezhdunarodnyj nauchno-issledovatel'skij zhurnal = International research Journal. 2018;12(1):121–127. (In Russ.) https://doi.org/10.23670/irj.2018.78.12.021
17. Volodarets NV, Belousova TP. Simulation of working processes in a transport node under the operating conditions on the basis of AnyLogic. Sovremennye innovacionnye tekhnologii podgotovki inzhenernyh kadrov dlya gornoj promyshlennosti I transporta. 2018; 1(4):244–248. (In Russ.)
18. Sharnin LM, Kirpichnikov AP, Zaliaev BM, Vasiliev VD, Shaikhutdinov ShA, Nitshaev RA. Modeling the problem of product manufacturing in AnyLogic. Vestnik Kazanskogo tekhnologicheskogo universiteta. 2019;22(4):153–157. (In Russ.)
19. Abramov VI, Kudinov AN, Evdokimov DS. Application of social modeling using agent based approach in scientific and technical development, implementation of R&D and maintenance of innovative potential. Vestnik Voronezhskogo gosudarstvennogo universiteta inzhenernyh tehnologij = Proceedings of the Voronezh State University of Engineering Technologies. 2019;81(3):339–359. https://doi.org/10.20914/2310-1202-2019-3-339-357
20. Makoveev VN. Using agent-based models in the analysis and forecast of socio-economic development of territories. Economic and Social Changes: Facts, Trends, Forecast. 2016;5:272–289. https://doi.org/10.15838/esc/2016.5.47.15
Review
For citations:
Stennikov V.A., Barakhtenko E.A., Mayorov G.S. Developing a multiagent model of an integrated energy supply system in AnyLogic simulation software. Proceedings of Irkutsk State Technical University. 2020;24(5):1080-1092. (In Russ.) https://doi.org/10.21285/1814-3520-2020-5-1080-1092