This article proposes an efficient surrogate-assisted design optimization method based on a multicriteria optimal Latin hypercube design (LHD) for multi-objective optimization of a surface-mounted permanent-magnet vernier machine (SPMVM). An improved iterated local search (ILS) method is proposed to optimize the spatial distribution uniformity and orthogonality of LHDs so that the data feature over the wide ranges of optimization variables can be captured more efficiently. Using the optimal LHD, a highly generalizable surrogate model can be trained with fewer samples, thus greatly reducing the required number of finite element analysis (FEA) cases and improving the optimization efficiency. A prototype corresponding to the optimal design is built and measured to validate the proposed method.

A yolk–shell structured NiCo ₂ S ₄ is constructed to improve the cycling stability of rechargeable Mg batteries using a bimetallic synergistic effect.

The lack of suitable modeling methods for power systems with multiple doubly-fed induction generator-based wind turbines (DFIGWTs) integrated has left the analytical description of the boundary of the region of attraction (ROA) of such systems largely unexplored. To address this gap, this paper derives an ordinary differential equation (ODE) model for a power system with multiple DFIGWTs integrated. The proposed electromechanical model is validated in a single-machine-infinite-bus (SMIB) power system and a modified 3 machine 9 bus power system with root mean squared errors (RMSEs) of less than 9.5% for trajectory comparisons with the full model, demonstrating that it accurately captures the low-frequency dynamics of the full DFIGWT model. Subsequently, the ODE model is transformed into a polynomial differential-algebraic equation (DAE) model using a nonlinear coordinate transformation. To estimate the ROA, an enhanced expanding interior algorithm (EIA) based on sum of squares (SOS) programming is applied. The feasibility of the proposed model, along with the appropriate conservativeness of the improved EIA, is validated using two test systems that include multiple DFIGWTs and synchronous generators (SGs). By comparison, it is found that the time cost of the improved EIA is reduced by around 17% while maintaining the accuracy. These results demonstrate that the proposed approach has significant practical implications for the integration of wind farms into power systems, and offers an efficient tool for transient stability analysis.

In this article, an improved surrogate-assisted design optimization method is proposed and applied to the torque performance optimization of a five-phase surface-mounted permanent magnet machine with quasi-trapezoidal permanent magnets. It integrates the Taguchi and surrogate-assisted methods; the training data for surrogate models are generated by the Taguchi method to reduce reliance on the finite-element analysis (FEA), in turn, the local optimum problem caused by the Taguchi method is tackled by the surrogate model. The generalization ability of surrogate models is enhanced by the parameter transfer technique. Using the fuzzy best-worst method, the decision process of multiple solutions is placed before optimization so that the multiobjective optimization can be transformed into a single objective to facilitate the search process for the optimal design. The optimization results are validated by the test results from a prototype. Compared with the FEA-based parametric scanning method, the optimization cycle is shortened by 94% and a globally optimal design can be obtained.

The rapid development of ultra-high voltage direct current transmission systems has placed greater demands on the design optimization of transient parameters for large wound-field synchronous machines (WFSMs) in power systems, such as large synchronous condenser for dynamic reactive power compensation. This paper proposes a novel two-level surrogate-assisted multi-objective optimization method for WFSMs that can optimize transient parameters including per-unit reactance and time constants rapidly and accurately. To facilitate the manufacture of a prototype for verification, the proposed method is applied to the optimization of a WFSM for scale-down generator application. This method is employed to deal with the excessive number of design parameters, issues of multi-objective evaluation and strong coupling between objectives that either result in inaccuracy or become time-consuming by using conventional methods. To generate the training set for the surrogate model efficiently by finite element analysis, an improved arbitrary rotor position standstill time response (SSTR) method is employed to identify all transient parameters simultaneously in a single test, while Latin hypercube design is used to capture data features. The optimal WFSM designed by using the proposed method is prototyped and measured. It confirms that the proposed method can achieve high validity and high optimization efficiency simultaneously.

An erythrocyte-like CuS electrode delivers a high capacity, higher rate capability, and superior cycling stability in ans Mg ²⁺ /Li ⁺ complex electrolyte.