Optimal Operation Control of PV-Biomass Gasifier-Diesel-Hybrid Systems Using Reinforcement Learning Techniques

Alexander N. Kozlov, Nikita V. Tomin, Denis N. Sidorov, Electo E. S. Lora and Victor G. Kurbatsky
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Alexander N. Kozlov: Energy Systems Institute of Siberian Branch of Russian Academy of Sciences, 664033 Irkutsk, Russia
Nikita V. Tomin: Energy Systems Institute of Siberian Branch of Russian Academy of Sciences, 664033 Irkutsk, Russia
Denis N. Sidorov: Energy Systems Institute of Siberian Branch of Russian Academy of Sciences, 664033 Irkutsk, Russia
Electo E. S. Lora: Mechanical Engineering Institute, Federal University of Itajuba, Itajuba 37500-103, Brazil
Victor G. Kurbatsky: Energy Systems Institute of Siberian Branch of Russian Academy of Sciences, 664033 Irkutsk, Russia

Energies, 2020, vol. 13, issue 10, 1-20

Abstract: The importance of efficient utilization of biomass as renewable energy in terms of global warming and resource shortages are well known and documented. Biomass gasification is a promising power technology especially for decentralized energy systems. Decisive progress has been made in the gasification technologies development during the last decade. This paper deals with the control and optimization problems for an isolated microgrid combining the renewable energy sources (solar energy and biomass gasification) with a diesel power plant. The control problem of an isolated microgrid is formulated as a Markov decision process and we studied how reinforcement learning can be employed to address this problem to minimize the total system cost. The most economic microgrid configuration was found, and it uses biomass gasification units with an internal combustion engine operating both in single-fuel mode (producer gas) and in dual-fuel mode (diesel fuel and producer gas).

Keywords: biomass; operations research; machine learning; microgrids; optimization; CO 2 reduction; mixed integer linear programming; reinforcement learning (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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