Zhenyun Zhu

Smart control of the driven power is one of the key issues of plasma source optimization. We present here, from code to device, a closed-loop optimization framework, to achieve in-situ plasma source control by dynamically adjusting the driven voltage parameters. The framework has been used in SDBD for hydrodynamics control in a turbulent flow wind tunnel and in DBD for chemical active species production.

ABSTRACT Power systems must address increasingly severe environmental challenges through an efficient low‐carbon transition. However, most current studies considered different single technology to achieve this transition. Research on the interactive mechanisms between different carbon reduction measures remains limited. This paper proposes a capacity expansion planning model for a low‐carbon power system that integrates multiple technologies, incorporating two complementary types of carbon reduction measures. Specifically, the technologies are categorized into two categories: direct CO 2 reduction measures (e.g., carbon capture and storage) and indirect CO 2 reduction measures (e.g., flexibility retrofit, energy storage system and wind expansion). Furthermore, a distributionally robust optimization method is developed to address the uncertainty of wind power. The column and constraint generation algorithm is employed to solve the model and derive the optimal planning scheme. Case studies based on the modified IEEE 24‐bus system and the IEEE 118‐bus system indicate that the proposed method significantly reduces both the system cost and carbon emissions. Additionally, the planning results demonstrate effective synergy between direct and indirect carbon reduction measures.