Efficient operation of residential solar panels with determination of the optimal tilt angle and optimal intervals based on forecasting model

• Published in: IET renewable power generation Vol. 11; no. 10; pp. 1261 - 1267
• Main Authors: Akhlaghi, Shahrokh, Sangrody, Hossein, Sarailoo, Morteza, Rezaeiahari, Mandana
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 16.08.2017
• Subjects: bee algorithm; forecasting model; load forecasting; optimal intervals; optimal tilt angle determination; optimisation; optimisation problem; residential solar panels; solar energy; solar panel tilt angle; solar power generation; solar power stations; solar radiation; solar tracking system; Special Issue: Performance Assessment and Condition Monitoring of Photovoltaic Systems for Improved Energy Yield; stopping criterion; sunlight; residential solar panels; solar power stations; solar energy; solar power generation; solar radiation; bee algorithm; optimal intervals; optimisation problem; optimisation; sunlight; solar tracking system; forecasting model; load forecasting; stopping criterion; optimal tilt angle determination; solar panel tilt angle
• ISSN: 1752-1416; 1752-1424; 1752-1424
• DOI: 10.1049/iet-rpg.2016.1033

A solar panel tilt angle plays a great role in the performance of the solar panel which is either fixed at an optimal tilt angle or continuously adjusted using a solar tracking system. Solar tracking systems are not cost efficient especially for residential usage. On the other hand, a fixed tilt angle results in a huge loss of solar energy. One resort to solve this problem is to adjust the tilt angle a limited number of times. In this paper, a novel procedure is proposed to select the number of intervals and their durations by solving an optimisation problem. The proposed algorithm is consisted of four major steps. First, the solar radiation of the next year is predicted using historical data. Second, using a bee algorithm the optimal tilt angle of each interval is computed. Third, an optimisation problem is solved to get new periods for each interval. Finally, a stopping criterion is checked to decide whether the previous step should be repeated or the algorithm has been converged. The effectiveness of the proposed approach is studied at nine different locations across the US. The results show improvement of the solar power generation by using the optimal intervals.