研究目的
To assess the solar energy potential in the Gaza Strip-Palestine, summarize its current status and future potential, and propose scenarios to address the electricity crisis using solar energy systems.
研究成果
The study concludes that Gaza Strip has significant solar energy potential, with PV systems being the most feasible due to low LCOE and flexibility. An urgent scenario proposes building 555 MWp of PV systems on rooftops at a cost of $800 million, reducing electricity costs by four times. Solar energy can enhance energy security, reduce dependence on imports, and support economic and social development in Palestine.
研究不足
The results are sensitive to economic parameters (e.g., capital cost, interest rate), thermal and electrical characteristics of PV modules, shadow cast, and meteorological data uncertainty. Political instability and limited uninhabited land in Gaza Strip also limit investment in solar energy.
1:Experimental Design and Method Selection:
The study uses solar radiation data from Meteoblue AG for 15 years (2000-2015) for five cities in Gaza Strip. The System Advisor Model (SAM) software from NREL is employed to evaluate solar energy potential and analyze financial feasibility for PV and concentrating solar systems.
2:Sample Selection and Data Sources:
Solar radiation data is hourly time-series for Jabalia, Gaza, Deir-Albalah, Khan-Yunis, and Rafah. Electricity consumption data is sourced from Palestinian Central Bureau of Statistics (PCBS) and Palestinian Energy and Natural Resources Authority (PENRA).
3:List of Experimental Equipment and Materials:
No specific equipment or materials are listed; the study relies on software simulations and data analysis.
4:Experimental Procedures and Operational Workflow:
Data is treated and reformatted using FORTRAN software to fit SAM input requirements. SAM is used to simulate and analyze renewable energy systems, including PV and concentrating solar technologies, with economic parameters adjusted.
5:Data Analysis Methods:
Results include system nameplate size, annual energy, capacity factor, energy yield, LCOE, and net capital cost for different scenarios and modes (fixed, 1-axis tracking, 2-axis tracking).
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