## 6 Conclusions  
This paper has proposed a lightweight SGD SARSA algorithm utilizing a Gaussian RBF approximation method to balance the trade-off between energy generation and power electronic converter lifetime in a marine HKT. The proposed control scheme was developed within a common k-omega-squared torque control framework, in which the RL agent varies the applied value of \(k\) depending on the state of the environment. The RL agent was trained using a reward function that estimated the net revenue of the turbine, considering both the income from the sale of energy in a dynamic energy market and the cost of operating the power electronic converter at a specific junction temperature. The training environment was derived from real-world flow velocity, flow temperature, and LMP data, creating a realistically difficult challenge for the RL agent to overcome. The results of the training protocol demonstrated that the RL agent achieved the greatest improvement with a higher cost of energy. Also, the training revealed the method's susceptibility to forgetfulness, which was solved by controlling the learning rate. The trained RL agent was then compared against an optimally tuned static k-omega-squared torque controller in two separate case studies. The case studies showed that the applied value of \(k\) (and, hence, the amount of power generated by the HKT) was directly related to the cost of energy at a given moment. Higher energy costs promoted the RL agent to maximize energy generation, while lower energy costs led to a reduction in energy generation to preserve the lifetime of the power electronics. In both case studies, it was also found that utilizing the proposed RL method reduced the mean junction temperature and the number of high-amplitude thermal cycles but increased the number of low-amplitude thermal cycles. As high-amplitude thermal cycles have more of an impact on life consumption, the RL-based scheme had less impact on the power electronic converter lifetime than the baseline controller. However, the reduction in thermal stress on the device also resulted in a non-negligible reduction in the cumulative energy harvested by the HKT. To quantify the relative improvements achieved by the proposed method, a custom estimate for net revenue considering the sale of energy and the cost of operating the power electronic converter was used. At the end of the case study, the improvements achieved by the proposed control method were determined by the state of the energy market. In the best case, the proposed adaptive control scheme increased the estimated net revenue by 45.4%. In the worst case, the RL-based method led to a net loss in revenue of 1.3%. These outcomes show that the RL method is more valuable in scenarios where the cost of energy is comparable to the cost of the converter such that decreasing the energy generated by the HKT to reduce the damage to the power electronic devices does not result in significant losses in revenue. Conceptualization, S.B., T.K.A.B. and Y.C. ; methodology, S.B. and T.K.A.B. ; writing--original draft preparation, S.B. ; writing--review and editing, T.K.A.B. and Y.C. ; supervision, T.K.A.B. and Y.C. ; project administration, T.K.A.B. and Y.C. ; funding acquisition, T.K.A.B. and Y.C. All authors have read and agreed to the published version of the manuscript. This work was supported in part by the US Department of Energy Advanced Research Projects Agency-Energy (ARPA-E) under Award DE-AR0001438 and in part by the US Department of Energy Water Power Technologies Office under Award DE-EE0011381. Not applicable. The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author. The authors declare no conflicts of interest. The following abbreviations are used in this manuscript: