Study on Critical Factors Affecting Tidal Current Energy Exploitation in the Guishan Channel Area of Zhoushan

Abstract

As a new type of clean and renewable energy, tidal current energy has attracted more and more attention from scholars. The Zhoushan Guishan Channel area (GCA) is an important part of the East China Sea port area, with strong currents due to its special terrain. In order to more comprehensively evaluate the characteristics of tidal energy development near the GCA, this paper uses the MIKE21 FM hydrodynamic model to simulate the tidal hydrodynamic process in the Zhoushan sea area and verifies the reliability of the model through the measured data. Based on the results of numerical simulations, the energy flow density, frequency of flow rate occurrence, flow asymmetry, flow rotation, and effective flow time that can be exploited are considered as the key factors affecting the development of tidal current energy. The distribution characteristics of each influencing factor in the region and the different influences on tidal current energy development are analyzed. Numerical simulations show that the average high-tide velocity in the GCA is lower than the ebb-tide velocity, and the duration of the high tide is also shorter than that of the ebb tide, which has a higher flow velocity than the surrounding area. The annual average energy flow density in the GCA is the highest at 4520 W/m2, and the spatial distribution is uneven. The resource level in the central part is much higher than that at both ends of the waterway. Three sections, i.e., A-A′, B-B′, and C-C′, with different key influence factors are selected for specific analysis, and it is concluded that the tidal energy development conditions are relatively superior near the B-B’ section in the middle of the GCA, and the exploitable power calculated using the Flux method is about 24.19 MW. The discussion of the results provides a certain reference for the development of local tidal current energy. These key factors affecting tidal current energy development can also be applied to assess the suitability of tidal current energy resource development in other regions.

Predicting renewable energy production outputs from climate factors: A machine learning approach

“…Therefore, both short and long-term forecasting are required to meet the demand for energy using alternative sources when the generated power through wind turbines is expected to be insufficient. Finally, in terms of tidal power, frequency of tidal current speeds, density, flow asymmetry, effective flow time available, and flow rotation are among the factors influencing the production capacity of tidal turbines [4].…”

“…) 𝑑𝑒𝑑𝑤 𝑒 𝑤 (4) where P (E,W) is the joint probability density function of E and W, and P (E) and P (W) are the marginal probability density functions of E and W, respectively.…”