Improvement of techno-economic optimal sizing of a hybrid off-grid micro-grid system

2021 
Abstract This paper deals with an improvement of a techno-economic optimal sizing of a hybrid off-grid micro-grid system in order to minimize the cost of produced energy and the reliability level required by customers. The used iterative approach is based on a recursive algorithm in combination with robust energy management. In fact, to study the system reliability, the Deficiency of Power Supply Probability (DPSP) is used. For the cost of the system study, two economic criteria are used; the total net present cost and the energy cost. In the literature, this approach has been widely used. However, the unpredictable weather circumstances, such as the irradiation conditions and/or low wind speed, present the most drawbacks of renewable energy. In our proposed paper, the sizing of two micro-grid system configurations ((1) a Photovoltaic Panel (PVP) and a battery, and (2) a PVP, wind and a battery) is studied while considering the autonomy days. We measure the size of both systems without taking into account the autonomy days, where DPSP = 0. When we consider the autonomy days, the dimensioned battery becomes unable to cover the load demand, so DPSP≠0. Accordingly, it is difficult to ensure the power supply reliability of a system with insufficient capacity. Moreover, by increasing the number of the autonomy days (from 1 to 5 days), the system cost will increase. Actually, it becomes as 16 times and 6 times as the initial cost for the PVP and battery system and the PVP, wind and battery system, respectively. Thus, to overcome this aforementioned problem, we use a diesel generator as a secondary power supply thanks to its efficiency at covering the load demand and its low cost when compared to the battery capacity. The obtained results are verified carrying out Matlab simulation using real weather data.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    68
    References
    3
    Citations
    NaN
    KQI
    []