Power and Energy Management of a DC Microgrid for a Renewable Curtailment Case Due to the Integration of a Small-Scale Wind Turbine

Jamila Aourir, Fabrice Locment and Manuela Sechilariu
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Jamila Aourir: AVENUES, Université de Technologie de Compiègne, Centre Pierre Guillaumat-CS 60 319, 60203 Compiègne, France
Fabrice Locment: AVENUES, Université de Technologie de Compiègne, Centre Pierre Guillaumat-CS 60 319, 60203 Compiègne, France
Manuela Sechilariu: AVENUES, Université de Technologie de Compiègne, Centre Pierre Guillaumat-CS 60 319, 60203 Compiègne, France

Energies, 2022, vol. 15, issue 9, 1-24

Abstract: Economic dispatch optimization and power management are the main concerns for a microgrid (MG). They are always studied and are considered to achieve an efficient operation of the MG by simplifying the control process and decreasing losses. The integration of a small-scale wind turbine (SSWD) into a direct current (DC) MG has an impact on its power and energy management. Excess power produced by renewable energy sources (RESs) is one of the problems that face the reliability of the MG and should be resolved. For this reason, a supervisory system is suggested to manage the excess of power. During the supervision process, some criteria, such as the physical limits and tariffs of the components are taken into account. Then, the suggested power management strategy aims to achieve an instantaneous power balance considering a rule-based power and depends on the above-mentioned criteria. To better meet the power balance, it is necessary to explore the constraints related to the control and supervision of the studied DC MG. Performance measures include the overall system energy cost and renewable curtailment (renewable energy that cannot be utilized and should be limited). Thus, the power limitation strategy consists of using two types of “shedding coefficients”, α and γ , to calculate the power that should be limited from each RES in the case of energy surplus. Simulation tests are carried out using two power management strategies: optimization and without optimization (i.e., storage priority). The results reveal that the coefficient γ reduces the overall energy cost and whatever the applied coefficient, optimization still provides good performances and significantly reduces the global energy cost.

Keywords: DC microgrid; small-scale wind turbine; energy management; power management; supervisory system; optimization; shedding constraints (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: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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