Dynamic analysis and performance assessment of the Inertial Sea Wave Energy Converter (ISWEC) device via harmonic balance

Given the particular energy-maximising performance objective, wave energy converter (WEC) systems are prone to exhibit highly nonlinear behaviour. We present, in this paper,a detailed dynamic analysis and control synthesis for the Inertial Sea Wave Energy Converter (ISWEC) system, deriving and considering a comprehensive associated nonlinear model. In particular, we adopt a harmonic balance (HB) method to achieve this objective, producing the so-called amplitude-frequency curves (AFC) for the corresponding ISWEC nonlinear model,derived via a Lagrangian approach. We demonstrate that the system can present a variety of different behaviours which are completely neglected by its linear model counterpart. Leveraging both the efficiency, and convenient representation of the HB method, we synthesise so-called‘passive’ (i.e. proportional) energy-maximising controllers using a variety of input conditions.We provide a comparison of the obtained control parameters with those arising from standard linear modelling, showing a consistent improvement in performance by effectively considering the relevant nonlinear ISWEC dynamics

Empowering wave energy with control technology: Possibilities and pitfalls

With an increasing focus on climate action and energy security, an appropriate mix of renewable energy technologies is imperative. Despite having considerable global potential, wave energy has still not reached a state of maturity or economic competitiveness to have made an impact. Challenges include the high capital and operational costs associated with deployment in the harsh ocean environment, so it is imperative that the full energy harnessing capacity of wave energy devices, and arrays of devices in farms, is realised. To this end, control technology has an important role to play in maximising power capture, while ensuring that physical system constraints are respected, and control actions do not adversely affect device lifetime. Within the gamut of control technology, a variety of tools can be brought to bear on the wave energy control problem, including various control strategies (optimal, robust, nonlinear, etc.), data-based model identification, estimation, and forecasting. However, the wave energy problem displays a number of unique features which challenge the traditional application of these techniques, while also presenting a number of control ‘paradoxes’. This review articulates the important control-related characteristics of the wave energy control problem, provides a survey of currently applied control and control-related techniques, and gives some perspectives on the outstanding challenges and future possibilities. The emerging area of control co-design, which is especially relevant to the relatively immature area of wave energy system design, is also covered

Towards data-driven and data-based control of wave energy systems: Classification, overview, and critical assessment

Currently, a significant effort in the world research panorama is focused on finding efficient solutions to a carbon-free energy supply, wave energy being one of the most promising sources of untapped renewable energy. However, wave energy is not currently economic, though control technology has been shown to significantly increase the energy capture capabilities. Usually, the synthesis of a wave energy control strategy requires the adoption of control-oriented models, which are prone to error, particularly arising from unmodelled hydrodynamics, given the complexity of the hydrodynamic interactions between the device and the ocean. In this context, data-driven and data-based control strategies provide a potential solution to some of these issues, using real-time data to gather information about the system dynamics and performance. Thus motivated, this study provides a detailed analysis of different approaches to the exploitation of data in the design of control philosophies for wave energy systems, establishing clear definitions of data-driven and data-based control in this field, together with a classification highlighting the various roles of data in the control synthesis process. In particular, we investigate intrinsic opportunities and limitations behind the use of data in the process of control synthesis, providing a comprehensive review together with critical considerations aimed at directly contributing towards the development of efficient data-driven and data-based control systems for wave energy devices

Intuitive LTI energy-maximising control for multi-degree of freedom wave energy converters: The PeWEC case

Energy-maximising wave energy conversion control strategies are commonly based upon direct optimal control theory, where the control problem is discretised and transcribed into a nonlinear programme, and a solution is found via numerical routines. Though appealing from an optimality viewpoint, the real-time application of such strategies to realistic (complex) wave energy systems, such as the PeWEC device, can become potentially challenging, due to its intrinsic multiple degree-of-freedom (DoF) nature. Furthermore, this pendulum-based system is not only multi-DoF in its nature, but also underactuated, i.e. only one mode, associated to the pendulum mechanism installed inside the wave-excited floating body, can be effectively actuated. We propose, in this paper, a set of four simple and intuitive energy-maximising controllers for the PeWEC system based, upon linear time-invariant (LTI) systems. We achieve this by deriving the so-called impedance-matching conditions for the PeWEC, and extending well-established LTI controllers, originally designed for fully actuated single-DoF systems, to this multi-DoF underactuated case. In particular, we explore, design, and synthesise both feedback, and feedforward configurations, making explicit emphasis in their main characteristics. Furthermore, we provide a performance assessment for each of the proposed controllers, showing their energy-maximising capabilities for the wave resource characterising the Mediterranean Sea

The wave energy converter control competition (WECCCOMP): Wave energy control algorithms compared in both simulation and tank testing

The wave energy control competition established a benchmark problem which was offered as an open challenge to the wave energy system control community. The competition had two stages: In the first stage, competitors used a standard wave energy simulation platform (WEC-Sim) to evaluate their controllers while, in the second stage, competitors were invited to test their controllers in a real-time implementation on a prototype system in a wave tank. The performance function used was based on converted energy across a range of standard sea states, but also included aspects related to economic performance, such as peak/average power, peak force, etc. This paper compares simulated and experimental results and, in particular, examines if the results obtained in a linear system simulation are borne out in reality. Overall, within the scope of the device tested, the range of sea states employed, and the performance metric used, the conclusion is that high-performance WEC controllers work well in practice, with good carry-over from simulation to experimentation. However, the availability of a good WEC mathematical model is deemed to be crucial

Data-driven control of wave energy systems using random forests and deep neural networks

In the field of sustainable energy and alternatives to fossil fuels, wave energy is generating an increasing interest due to its untapped potential. However, the levelised cost of energy of wave energy systems is still not able to compete with other renewable technologies, mainly due to high costs associated with their conversion process. In this context, the development of energy-maximising control strategies plays an important role towards the economic viability of wave energy technology, by optimising the overall energy conversion, hence contributing towards minimising the associated cost of energy. State-of-the-art control systems for wave energy converters are mostly model-based, exploiting control-oriented models of the device to compute the applied control actions with a limited computational burden. Nevertheless, these representations of the system are simplified, and often based upon unrealistic assumptions, such as small motion around the zero equilibrium position, which are inherently invalidated during device operations and that can lead to large uncertainties, resulting in suboptimal power absorption. For these reasons, in this paper, a purely data-driven control strategy is developed. This strategy exploits random forests (RFs) and deep neural networks (DNNs) to gradually learn from real experiences towards an optimal proportional–integral control action. These structures are used as surrogate models (built upon the data coming from past experiences) to converge to the optimal control parameters in a surrogate-optimisation-like manner. To manage the exploration and exploitation needs of controllers based on this approach, a learning strategy is developed and presented. Some considerations are made on the choice of the input features of the surrogate structures, which deeply affect the control strategy learning results. To assess the performances of both the control and learning strategies, one year of operations has been simulated under control settings guided by the proposed data-driven approach, showing also the potential capabilities that the adoption of RFs and DNNs has in learning, even in sea conditions with a limited number of occurrences

An Anti-Windup Mechanism for State Constrained Linear Control of Wave Energy Conversion Systems:Design, Synthesis, and Experimental Assessment

Motivated by the necessity of suitable state constraint mechanisms within linear time-invariant (LTI) energy-maximising control of wave energy converters (WECs), we present, in this article, an anti-windup (AW) scheme for state constraint satisfaction, where the associated unconstrained controller is designed via impedance-matching theory for WEC systems. As in the standard (input) AW scenario, the adopted technique provides a mechanism for 'informing' the (unconstrained) controller when constraints are active, so that appropriate modifications to future control actions can be taken accordingly. The overall adopted AW technique is tested experimentally, on a prototype of the Wavestar WEC system, available at Aalborg University (Denmark). We explicitly demonstrate that the proposed AW scheme is able to consistently respect the defined state constraints, having a mild impact on overall energy absorption performance when compared to its unconstrained counterpart.</p