Many sources of renewable energy, including solar, wind, and ocean wave, offer significant advantages such as no fuel costs and no emissions from generation. However, in most cases these renewable power sources are variable and nondispatchable. The utility grid is already able to accommodate the variability of the load and some additional variability introduced by sources such as wind. However, at high penetration levels, the variability of renewable power sources can severely impact the utility reserve requirements. This paper presents an analysis of the interaction between the variability characteristics of the utility load, wind power generation, solar power generation, and ocean wave power generation. The results show that a diversified variable renewable energy mix can reduce the utility reserve requirement and help reduce the effects of variability.

This paper presents the application of nonlinear model predictive control (NMPC) to a point absorber wave energy converter (WEC). Model predictive control (MPC) is generally a promising approach for WECs, since system constraints and actuator limits can be taken into account. Moreover, it provides a framework for defining optimal energy capture and it can benefit from predictions. Due to possible nonlinear effects, such as the mooring forces, an NMPC is proposed in this paper, whose performance is compared to that of a linear MPC. Both controllers are supposed to control a nonlinear point absorber model. Computer simulations show that the proposed NMPC is able to optimize the energy capture while satisfying system limits.

This paper presents the development of Model Predictive Control (MPC) for ocean wave energy applications; specifically for a point absorber Wave Energy Converter (WEC). MPC has several features that make it very attractive for ocean wave energy, in particular the ability to consider constraints on the system forces and limitations in system velocity and position in the context of current future desired velocity or position. The results show that MPC coupled with forecasting can allow the system to optimize energy capture while respecting system limits.

Many forms of renewable energy exist in the world's oceans, with ocean wave energy showing great potential. However, the ocean environment presents many challenges for cost-effective renewable energy conversion, including optimal control of a wave energy converter (WEC). This paper presents a maximum power point tracking (MPPT) algorithm for control of a point absorber WEC. The algorithm and testing hardware are presented in detail, as well as simulated and laboratory test results. The results show that MPPT applied to ocean wave energy is an effective and promising control strategy.