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Optimal sizing and economic assessment of diesel and solar mills for cereal milling in rural areas of Senegal Diop, Moustapha; Ndiaye, Mouhamadou Falilou; Gueye, Ibrahima; Kebe, Abdoulaye; Dia, Omar
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i4.pp2526-2534

Abstract

This paper aims at using life cycle costing (LCC) to assess the economic viability of solar and diesel mills for cereal milling, adopting several scenarios of village sizes in Senegal and time perspectives. This work is intended to provide decision-makers and stakeholders with valuable information for selecting optimal milling systems, taking into account both economic and village size considerations. The methodology adopted is based on system specifications and daily cereal consumption profiles. To determine the economic performance of systems, three types of villages are evaluated and analyzed in detail from short, medium, and long-term perspectives. The results indicate that solar mills are the most economical systems for milling cereals in remote villages in the long term, with a potential economic gain of 10%, 31%, and 41% for small, medium, and big villages respectively, compared to diesel mills. However, solar mills are less promising in the short term.
Evaluation of sensorless VF-MRAS and FOC-MRAS of IM electrical drive system Diop, Moustapha; Kebe, Abdoulaye; Gueye, Ibrahima
International Journal of Applied Power Engineering (IJAPE) Vol 14, No 3: September 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v14.i3.pp513-521

Abstract

This paper evaluates the performance of sensorless vector and scalar control methods, namely field-oriented control-based model reference adaptive system (FOC-MRAS) and voltage frequency-based model reference adaptive system (VF-MRAS), applied to an induction motor (IM) driven by a space vector modulation inverter. In motorized systems, conventional control methods use mechanical sensors, which can be cumbersome and costly. To overcome these limitations, sensorless control techniques based on speed estimation have been introduced. In this paper, MRAS-based sensorless speed control for IM drives using rotor flux is used. This adaptive system uses a reference model based on rotor flux and implements closed-loop control. The estimated speed derived from the current and voltage models is compared to the desired speed and adjusted by the proportional-integral (PI) controllers. The performances of the approaches are evaluated in terms of speed regulation and minimization of electromagnetic torque and rotor flux ripples, through a comparative analysis of sensor and sensorless controls under various operating conditions, including variable loads and speed reversal. The simulation results obtained, using consistent criteria for both methods, confirm the effectiveness of sensorless control.