Power converter within the multi-agent system of a spacecraft power supply system

Аuthors

Dyakin N. V.^*, Dyakin S. V.^**, Volsky S. I.^***

Moscow Aviation Institute (National Research University), 4, Volokolamskoe shosse, Moscow, А-80, GSP-3, 125993, Russia

*e-mail: dyakin.nikolay@gmail.com
**e-mail: dyakin.s@gmail.com
***e-mail: volsky-s@yandex.ru

Abstract

The spacecraft power supply system as well as ground-based power supply system provides transmission and redistribution of electric energy from power sources to consumers. One of the major requirements claimed to power supply systems is to keep electric energy at specified level in the course of one or more primary energy sources failure.

Currently, two types of supplying electric power to consumers exist: centralized and decentralized. The structure of the centralized power supply system has the Central Switch Gear (SSG) that collects electric energy from all primary and secondary power sources.

The main advantage of such systems is the stable feeding of consumers due to required power extraction from all electric power sources. On the other hand, the centralized electric power system has relatively low power grid mass and size figures, as well as comparatively low reliability due to the presence of single distribution gear.

The prospective trend, with the presence of a number of primary and secondary power sources in particular, is implementation of decentralized electrical power supply system, having several small SSGs, which potentially increases reliability and scalability.

The article introduced the concept of an agent and multi-agent power supply system that provide the operation, storage of information in the database, as well as exchange of information with other agents that allows implementation of the decentralized power supply system.

Consumers, sources and energy storage units are the main elements of the system. We suggest designing a separate agent for each element, which will provide — functionality, information storage in database, as well as information exchange with other agents to provide their effective operation.

We identified the following agents: a load agent (LA), an environment agent (ENVA), a photoelectric converter agent (PHCA), a fuel cell agent (FCA), a battery agent (BA), a simulation agent (SA) and a database agent (DBA).

The article also presents a power circuit of a static electric energy converter based on modern RB-IGBT transistors and method for synchronizing the output AC voltage with other power sources. It allows improve conversion efficiency of the energy generated by solar cells (this is one of the agents of the decentralized systems), reduces the mass and size parameters of the converter.

Keywords:

photoelectric converter, boost converter, three-level inverter, inverter synchronization, agent, multi-agent system

References

1. Grigoryan V.G., Evdokimov K.V. Energoustanovki kosmicheskikh letatel’nykh apparatov (Spacecraft Energy unis), Moscow, MAI, 2007, 84 p.

2. Bideev A.G., Semin A.Yu., Kuznetsov A.V., Akhmedov M.R. Kosmicheskaya tekhnika i tekhnologii, 2015, no. 2, pp. 64-74.

3. Teodorescu Remus, Liserre Marco, Rodrнguez Pedro. Grid Converters for Photovoltaic and Wind Power Systems. John Wiley & Sons, Ltd., United Kingdom, 2011, 398 p.

4. Gupta Atul, Porippireddi Anurag, Uppuluri Srinivasa Venu, Sharma Akash, Kadam Mangesh. Comparative Study of Single Phase PLL Algorithms for Grid Synchronization Applications. International Journal of electronics and communication technology, October December 2012, vol. 3, issue 4, pp. 237-245.

5. Adzic Evgenije, Porobic Vlado, Dumnic Boris, Celanovic Nikola, Katic Vladimir. PLL synchronization in gridconnected converters.The 6th PSU-UNS International Conference on Engineering and Technology (ICET-2013), University of Novi Sad, Faculty of Technical Sciences, Serbia, May 15-17, 2013, pp. 1-5.

6. Kalachev Yu.N. Vektornoe regulirovanie. Zametki praktika (Vector regulation. Practice notes), available at: www.privod-news.ru/docs/Vector_Kalachev.pdf, 2013 (accessed 01.06.2015).

7. Kalyaev I.A., Gaiduk A.R. Modeli i algoritmy kollektivnogo upravleniya v gruppakh robotov (Models and collective control algorithms for groups of robots), Moscow, Fizmatlit, 2009, 280 p.

8. Russell S., Norvig P. Artificial Intelligence a Modern Approach. Second Edition, Pearson Education, Inc., USA, 2003, 1082 p.