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Since Jordan started the solar PV installation in 2012, the demand for solar PV operation and maintenance (O&M) services increased, driven by aging systems requiring inverter replacements (every 8-10 years) and system optimization.
According to annual reports by Jordan’s grid operators, the total installed on-grid solar PV capacity reached 2,073.86 MW by the end of 2024. This capacity is divided as follows: Distribution System Operators (DSOs): 1,081.86 MW across 74,145 projects. Transmission System Operator (TSO): 992 MW. The largest DSO-managed installations were by:
The commercial sector faces higher grid fees of 13 JD ($18.3 USD) per kWac/month, reducing the economic viability of installations. In September 2024, Jordan’s Council of Ministers lifted the cap on solar PV project sizes, enabling large-scale installations.
Jordan’s geographical location has a substantial impact on its potential for harnessing renewable energy, particularly solar energy. Positioned at the heart of the Middle East, Jordan benefits from its strategic placement in a region abundant in solar irradiance .
L. Prakash et al. (Shah et al., 2022) created an independent photovoltaic stimulated strong wind electrical generator for off-grid applications in India that reduces system costs and improves hybrid model system performance.
“Scrutiny of PV biomass stand-alone hybrid system for rice mill electrification,” in Deregulated electricity market (Apple Academic Press), 135–152. Sawle, Y., Gupta, S. C., and &Bohre, A. K. (2017). Optimal sizing of standalone PV/Wind/Biomass hybrid energy system using GA and PSO optimization technique.
The abundance of availability of renewable energy in the environment in distinct forms like solar, wind, and biomass can be configured with battery banks that enhance the hybrid system’s efficiency and dependability (Diaf et al., 2007).
In this study, an off-grid PV-wind-biomass hybrid model for the remote community of Barwani, Madhya Pradesh, India, is explored for the best solution and innovative proper evaluation with two alternative methods (demand flowing and cycle charging) using GA and particle swarm optimization (PSO).
