# Modeling and Test Results of an Innovative Gyroscope Wave Energy Converter
###### Abstract
However, one of the shortcomings of these devices is that the areas with high wave energy density are far away from the power grid, thus increasing the proportion of cable installation and maintenance costs in the investment of water conservancy projects and increasing commercial costs. From the economic point of view, the nearshore wave energy resources cannot be ignored, because the shallower waters and islands associated with the nearshore are critical to the operation and economic costs of certain WECs [23]. Japan does not have a substantial amount of wave power, but a WEC was developed successfully in the full-scale test [24]. Therefore, the current wave energy development and test power stations are mainly related to the coastal waters, and the development of small-scale wave energy has become a research hotspot in some coastal countries [25]. Therefore, in recent years, nearshore enclosed WECs have become more popular with the conversion systems not in contact with water [26,27]. The main advantage is that there are no moving parts in the water with survivability, and the purely mechanical device is friendly to the ocean. The University of Rome has developed a new type of wave energy device, which is especially suitable for enclosed sea areas with moderate wave power [4]. Kobe University applied the gyroscope principle to extract wave energy in the low-energy density ocean and successfully developed a 5.5 kW WEC in 2003 [28]. The gyroscope principle is used by the above two WECs to convert wave energy into electricity. Compared with other WECs with different structures or conversion principles, these WECs have the advantages of high reliability, low construction and maintenance costs, and easy implementation of active control strategies [29]. The design of WEC is quite different in the method of energy extraction, but all of them require a core of the WEC, called the power take-off (PTO) system, to convert the mechanical motion of the primary wave interface into a stable energy output. Additionally, there is an optimal damping point under different sea conditions for the PTO system, so the PTO can be controlled by the maximum power point (MPP) tracking (MPPT) control algorithms to improve the generated power of the system [30]. MPPT is an adaptive control strategy, which has been widely used in renewable energy such as wind and solar energy [31]. In the application of renewable energy, the duty cycle of the voltage converter is usually applied to adjust the load resistance in the generator. At present, MPPT methods are mainly divided into two categories, namely conventional methods and soft computing methods. The methods based on software calculations such as artificial neural networks, fuzzy algorithms, and particle swarm algorithms have excellent steady-state performance but have not been widely recognized due to their slow calculation speed. The conventional algorithms are perturb and observe (P&O) and incremental conductance, especially P&O, which is the most extensively used due to its simplicity and low cost [32; 33]. However, there are two main problems with these methods. Firstly, the MPPT controller occasionally makes the system deviate from the optimal operating point when the external conditions change rapidly. Another disadvantage is that when the MPP is approached, the system will continuously oscillate around the MPP [34]. One of the most significant parameters of P&O is the length of perturbation. A smaller value will result in slower tracking performance and poor dynamic response, while a larger one will cause steady-state oscillation and energy waste [35]. Therefore, the adjustable perturbation step size can simultaneously meet the system's requirements for dynamic tracking and steady-state characteristics. Several MPPT techniques have been investigated for creating adaptive perturbing step size to enhance MPPT control [36], but these methods are limited to specific conditions [37; 38; 39]. Therefore, solving the two shortcomings has become the key to improving the P&O method.