Solar energy technologies play an important role in shaping a sustainable energy future, and generating clean, renewable, and widely distributed energy sources. This paper determines the optimum tilt angle and optimum azimuth angle of photovoltaic (PV) panels, employing the harmony search (HS) meta-heuristic algorithm. In this study, the ergodic method is first conducted to obtain the optimum tilt angle and the optimum azimuth angle in several cities of China based on the model of Julian dating. Next, the HS algorithm is applied to search for the optimum solution. The purpose of this research is to maximize the extraterrestrial radiation on the collector surface for a specific period. The sun's position is predicted by the proposed model at different times, and then solar radiation is obtained on various inclined planes with different orientations in each city. The performance of the HS method is compared with that of the ergodic method and other optimization algorithms. The results demonstrate that the tilt angle should be changed once a month, and the best orientation is usually due south in the selected cities. In addition, the HS algorithm is a practical and reliable alternative for estimating the optimum tilt angle and optimum azimuth angle of PV panels.

Abstract:The tilt angle with the horizon (with respect to the ground) of the solar energy system affects the amount of solar radiation received. This paper suggests a simple and universal method to obtain the optimum tilt angles by estimating the monthly mean daily global solar radiation on tilted surfaces facing directly towards the equator, which is based on monthly average daily global solar radiation data produced from Typical Meteorological Year (TMY) data. The monthly, seasonal, and yearly optimum tilt angles for photovoltaic panels are calculated at six stations of different climatic types (Tropical Zone (TZ), Subtropical Zone (SZ), Warm Temperate Zone (WTZ), Mid Temperate Zone (MTZ), Cold Temperate Zone (CTZ) and Tibetan Plateau Zone (TPZ)). The results indicate that changing the monthly, seasonal, and yearly optimum tilt angles causes a significant yearly gain in the solar radiation for the region. In addition, general correlations are generated to estimate the optimum tilt angle of solar collectors at six typical climatic stations of China. The performances of the proposed models are compared using statistical error tests such as the mean absolute bias error (MABE), the root mean square error (RMSE) and the correlation coefficients (R).

Accurate short-term wind power forecasting is important for improving the security and economic success of power grids. Existing wind power forecasting methods are mostly types of deterministic point forecasting. Deterministic point forecasting is vulnerable to forecasting errors and cannot effectively deal with the random nature of wind power. In order to solve the above problems, we propose a short-term wind power interval forecasting model based on ensemble empirical mode decomposition (EEMD), runs test (RT), and relevance vector machine (RVM). First, in order to reduce the complexity of data, the original wind power sequence is decomposed into a plurality of intrinsic mode function (IMF) components and residual (RES) component by using EEMD. Next, we use the RT method to reconstruct the components and obtain three new components characterized by the fine-to-coarse order. Finally, we obtain the overall forecasting results (with preestablished confidence levels) by superimposing the forecasting results of each new component. Our results show that, compared with existing methods, our proposed short-term interval forecasting method has less forecasting errors, narrower interval widths, and larger interval coverage percentages. Ultimately, our forecasting model is more suitable for engineering applications and other forecasting methods for new energy.

No abstract

We have applied our precision disk tester and noise measurement procedures to perpendicular media. We look at the randomness of dc media noise from write to write, quantify the deterministic component of this noise, and investigate the head noise and dc track edge noise of perpendicular heads and media. These results are compared with those obtained for longitudinal media. We observe lower correlation coefficients than those for longitudinal media, suggesting that there is more randomness associated with the reversal mechanisms involved in our experiment. We also see that the dc track edge noise is imperceptibly small using our testing operation, implying that double-layered perpendicular dc track edges are of a different form than those of thin film longitudinal single-layered media.