研究目的
This work analyzes the potential of photovoltaic self-consumption systems as a function of the array power, array tilt, and orientation angles to face the electric consumption in olive mills.
研究成果
The study concludes that photovoltaic self-consumption systems without storage can be suitable for olive mills, achieving high self-consumption indices (>80%) and self-sufficiency indices ranging from 20% to 30% for the olive harvest period. The study also highlights the importance of array tilt and orientation angles in maximizing self-sufficiency indices and the minimal impact of recording intervals on the estimation of photovoltaic energy consumed.
研究不足
The study focuses on direct self-consumption systems without storage, which may limit the applicability of the findings to systems with energy storage. Additionally, the study is based on data from a specific location (Jaén, Spain), which may not be representative of all olive mills.
1:Experimental Design and Method Selection:
The study analyzes the potential of photovoltaic self-consumption systems in olive mills, focusing on the impact of array orientation and tilt angles on self-sufficiency and self-consumption indices. The methodology includes the use of Performance Ratio (PR) for estimating the output power of solar photovoltaic systems.
2:Sample Selection and Data Sources:
The study uses irradiance data with a recording interval of one minute and one hour, and load consumption data from an olive mill in Jaén, Spain, with a recording interval of 15 minutes.
3:List of Experimental Equipment and Materials:
The study mentions the use of a meteorological station located in Jaén for irradiance data collection and a smart meter for measuring the active and reactive energy in the olive mill.
4:Experimental Procedures and Operational Workflow:
The study involves estimating photovoltaic generation profiles considering different combinations of array tilt and orientation angles, and analyzing the matching capability between load consumption and photovoltaic generation profiles.
5:Data Analysis Methods:
The study uses statistical techniques to analyze the error when matching the olive mill load consumption and photovoltaic generation profiles with different recording intervals.
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