Research
The Energy Control and Optimization (ECO) Lab develops advanced control and optimization methods to improve the reliability, resilience, and efficiency of modern energy systems. Our research spans renewable generation, energy storage, and smart grids. In ocean energy, we design intelligent control and co-design frameworks for wave energy converters, offshore microgrids, and Powering the Blue Economy (PBE) technologies that deliver power to ocean observation, aquaculture, desalination, and coastal resilience applications.
Control and Optimization of Energy Systems
We develop advanced control algorithms and optimization strategies to enhance the performance of ocean energy systems, particularly Wave Energy Converters (WECs). Our research explores cutting-edge techniques such as model predictive control, reinforcement learning, control co-design, and real-time simulation—focusing on maximizing energy capture, efficiency, and system reliability.
Related Publications
- Masood, U., Shabara, M., Grasberger, J., Wosnik, M., & Hasankhani, A. (2025). "Control Framework Design for WECs with Direct Drive Linear Generator-Based Power Take Off Systems." University Marine Energy Research Community (UMERC) 2025 Conference, USA.
- Hasankhani, A., Tang, Y., & VanZwieten, J. (2023). Integrated path planning and control through proximal policy optimization for a marine current turbine. Applied Ocean Research, 137, 103591. [doi]
- Hasankhani, A., Ondes, T. B., Tang, Y., Sultan, C., & Van Zwieten, J. (2022, June). “Integrated Path Planning and Tracking Control of Marine Current Turbine in Uncertain Ocean Environments.” In 2022 American Control Conference (ACC) (pp. 3106-3113). [doi]
- Hasankhani, A., Tang, Y., Snyder, A., VanZwieten, J., & Qiao, W. (2022). “Control Co-Design for Buoyancy-Controlled MHK Turbine: A Nested Optimization of Geometry and Spatial-Temporal Path Planning.” IEEE Conference on Control Technology and Applications (CCTA 2022). [doi]
Energy Solutions for the Blue Economy
We develop tunable wave energy converter reference models (WEC-RMs) to support blue economy applications such as aquaculture, ocean observation, and autonomous systems. This includes comprehensive modeling, lab-scale testing, and strategies for scale-up and deployment in real-world environments.
Related Publications
- Matamala, P., Wosnik, M., Fredriksson, D., & Hasankhani, A. (2025). "Wave Energy Converters (WECs) for Powering Offshore Aquaculture." University Marine Energy Research Community (UMERC) 2025 Conference, USA.
- Hasankhani, A., Ewig, G., McCabe, R., Won, E. T., & Haji, M. (2023, June). "Marine Spatial Planning of a Wave-Powered Offshore Aquaculture Farm in the Northeast US." In OCEANS 2023-Limerick (pp. 1-10). IEEE. [doi]
- Hasankhani, A., McCabe, R., Ewig, G., Won, E. T., & Haji, M. N. (2023, June). “Conceptual Design and Optimization of a Wave-Powered Offshore Aquaculture Farm.” In The 33rd International Ocean and Polar Engineering Conference. OnePetro. [doi]
Renewable Energy Integration into Smart Microgrids
Our lab investigates how marine energy sources, particularly wave energy, can be integrated into resilient, hybrid microgrids. We focus on dynamic modeling, hardware-in-the-loop validation, and control of distributed energy systems to support remote and islanded communities.
Related Publications
- Eghbali, N., Hakimi, S. M., Hasankhani, A., Derakhshan, G., & Abdi, B. (2022). “Stochastic energy management for a renewable energy based microgrid considering battery, hydrogen storage, and demand response.” Sustainable Energy, Grids and Networks, 30, 100652. [doi]
- Hakimi, S. M., Hasankhani, A., Shafie-khah, M., & Catalão, J. P. (2021). “Stochastic planning of a multi-microgrid considering integration of renewable energy resources and real-time electricity market.” Applied Energy, 298, 117215. [doi]
- Hasankhani, A., & Hakimi, S. M. (2021). “Stochastic Energy Management of Smart Microgrid with intermittent Renewable Energy Resources in Electricity Market.” Energy, 119668. [doi]