Tsinghua Sichuan Energy Internet Research Institute

Accurate assessment of source-load complementarity and system regulation capacity is critical for secure dispatch and planning in high-penetration renewable power systems. Addressing limitations of existing methods—which rely heavily on static metrics, struggle to capture temporal and tail dependence characteristics, and provide insufficient support for dispatch decisions—this paper proposes a multi-level integrated evaluation framework. First, from a source—load matching perspective, we develop a novel complementarity metric, integrating real-time rate of change, temporal consistency, and tail dependency. An improved adaptive noise-complete set empirical mode decomposition combined with a hybrid Copula model is employed to isolate noise and to precisely quantify dynamic dependency structures. Second, we introduce the Minkowski measure and construct a net load fluctuation domain accounting for extreme fluctuations and coupling relationships. Subsequently, combining the Analytic Hierarchy Process (AHP) with probabilistic convolution enables multi-level comparative quantification of resource capacity and fluctuation domain requirements under varying confidence levels. Simulation results demonstrate that the proposed framework not only provides a more robust assessment of source-load complementarity but also quantitatively outputs the adequacy and risk level of system regulation capacity. This delivers hierarchical, actionable decision support for dispatch planning, significantly enhancing the engineering applicability of evaluation outcomes.

To address the challenges posed by spatial constraints and fluid perturbations in underwater tunnels, this study proposes an efficient autonomous underwater vehicle (AUV) and introduces a tracking control strategy to tunnel conditions. First, the AUV integrates a modular buoyancy adjustment system, effectively mitigating the issues of large turning radii and loss of pitch control at low speeds typically encountered with conventional rudders. The Variable Look-Ahead Distance (VLAD) mechanism is integrated into the Adaptive Line-of-Sight (ALOS) guidance system to facilitate precise estimation of the angle of attack and ensure rapid convergence of tracking errors. In addition, a hyperbolic sliding mode switching controller (HSMC) is proposed, and its stability is rigorously analyzed. This approach dynamically adjusts the sliding mode surface based on the characteristics of the two hyperbolic functions, effectively reducing control buffering and improving the stability of wall tracking. Finally, the experimental results from both planar and curved wall tracking tests demonstrate that the proposed control strategy significantly reduces tracking errors while exhibiting superior resilience to interference.

VSC-HVDC systems based on overhead transmission lines suffer from transient DC short-current faults frequently, for which converters with DC-fault ride-through (DC-FRT) capability are required. This paper proposes a hybrid modular commutated converter (H-MCC) with DC-FRT capability. HMCC applies a hybrid DC switch to isolate fault lines and adopts an energy-absorption branch to facilitate rapid arc quenching. The control sequences and dynamic process of H-MCC during DC-FRT are analyzed in detail, deducing analytical model of electrical stress. On this basis, the parameter design methodology is presented, and a comprehensive comparison with the conventional hybrid MMC scheme shows that the proposed HMCC achieves notable improvements in power density, costeffectiveness, and operational efficiency. Finally, the feasibility of H-MCC is verified by simulation and experiment. The proposal offers a technically and economically attractive solution for power conversion in overhead-line-based VSC-HVDC systems.

Exploring demand-side flexibility through electricity pricing mechanisms is a core pathway to reducing costs in low-carbon power systems. While existing studies have confirmed differences in the effectiveness of various pricing mechanisms, they lack systematic quantitative analysis, making it difficult to support the optimization of pricing strategies. This paper constructs a bi-level simulation framework based on a comprehensive dataset from Anhui Province, China, to conduct empirical analysis of the system-level benefits of typical pricing mechanisms including Real-Time Pricing (RTP) and Time-of-Use Pricing (TOU) in exploring demand-side flexibility. The key findings reveal that from 2025 to 2050, as renewable energy penetration grows, RTP’s average daily cost savings compared to TOU increase from 70,000 Chinese yuan (CNY) to 393,000 CNY, whereas TOU’s efficiency index declines from 43.62% to 29.02%. Notably, the efficiency gap between RTP and TOU remains insignificant at present; yet as renewable energy penetration further increases, this gap will become far more pronounced. In practical terms, this implies TOU can serve as a short-term transitional mechanism, while the power market should gradually shift toward RTP in the long run to adapt to the rising penetration of renewable energy and fully tap into demand-side flexibility. This study provides empirical support for improving electricity market pricing mechanisms to unlock user-side flexibility resources.