To improve the output characteristics of offshore wind power and to enhance the wind power accommodation, this paper analyzes its output characteristics along the southern coast in China, and then proposes an optimal sizing method of seawater pumped storage plant (SPSP) with variable-speed units in a connected mode on an islanded microgrid. Based on the constraints of variable-speed unit characteristics and power smoothness at the point of common coupling (PCC), the maximum static revenue as the objective function for the optimal sizing of SPSP is established. Notably, under an appropriate smoothness rate at PCC, the constraints that are mentioned above can adequately reflect the advantages of variable-speed units: fast power response and wide operating range. Additionally, they contain more concise models and variables than previously, which are friendly for optimizing the calculations. The results demonstrate that the proposed method is feasible and practical, by simulating and comparing in different scenarios.

Semiconductor ionic electrolytes, especially heterostructure composites, have a significant role in enhancing oxide ion conductivity and peak power density (PPD) because of their interfacial contact. In this work, the fluorite structure CeO₂ and spinel-based CoAl₂O₄ samples, as a heterostructure composite electrolyte, are successfully fabricated. The p-type CoAl₂O₄ and n-type CeO₂ heterostructure (CeO₂-CoAl₂O₄) used as an electrolyte exhibits a cell performance of 758 mW/cm² under fuel cell H₂/air conditions at 550 °C, which is quite higher than the pure CoAl₂O₄ and CeO₂ fuel cell devices. Scanning electron microscopy (SEM) and high-resolution transmission electron microscopy (HR-TEM) verified the heterostructure formation including the morphological analysis of the prepared heterostructure composite. The heterostructure-based CeO₂-CoAl₂O₄ composite achieved a higher ionic conductivity of 0.13 S/cm at 550 °C temperature, which means that the constructed device successfully works as an electrolyte by suppressing electronic conductivity. Meanwhile, the obtained results demonstrate the semiconductor ionic heterostructure effect by adjusting the appropriate composition to build heterostructure of the n-type (CeO₂) and p-type (CoAl₂O₄) components and built-in electric field. So, this work exhibits that the constructed device can be effective for energy conversion and storage devices.

The China Energy Administration has issued policies to encourage energy storage to participate in the electric auxiliary service market, which will provide ideas for electric vehicle charging stations (EVCSs) to collectively participate in peak‐regulation and frequency modulation (FM). Taking into account the benefits of EVs participating in peak‐regulation and FM, this paper studies expansion planning for EVCSs. First, the orderly scheduling strategy of EVs under vehicle‐to‐grid (V2G) technology is established in this paper. And a peak regulation method is proposed to maximize the economic benefits of charging and discharging during peak and valley periods. Second, based on the temporal and spatial prediction model of EV charging demand, the expansion planning model of EVCSs is constructed considering the benefits of peak‐regulation and FM. Aiming at minimizing the comprehensive annual social cost of charging stations, the expansion site selection and capacity scheme of EVCSs are obtained. Finally, taking the 24 nodes in Xiangzhou District of Zhuhai City as an example, the location and capacity of the final annual expansion plan are obtained. And the influence of main control parameters on the results of the whole model and method is analysed in detail, the feasibility and effectiveness of the whole model and method are verified.

To achieve economical compensation for the huge-capacity negative sequence currents generated by high-speed railway load, an electromagnetic hybrid compensation system (EHCS) and control strategy is proposed. The EHCS is made up of a small-capacity railway static power conditioner (RPC) and a large-capacity magnetic static var compensator (MSVC). Compared with traditional compensation methods, the EHCS makes full use of the SVC’s advantages of economy and reliability and of RPC’s advantages of technical capability and flexibility. Based on the idea of injecting a negative sequence, the compensation principle of the EHCS is analyzed in detail. Then the minimum installation capacity of an EHCS is theoretically deduced. Furthermore, a constraint optimization compensation strategy that meets national standards, which reduces compensation capacity further, is proposed. An experimental platform based on a digital signal processor (DSP) and a programmable logic controller (PLC) is built to verify the analysis. Simulated and experimental results are given to demonstrate the effectiveness and feasibility of the proposed method.

The high penetration and uncertainty of distributed energies force the upgrade of volt-var control (VVC) to smooth the voltage and var fluctuations faster. Traditional mathematical or heuristic algorithms are increasingly incompetent for this task because of the slow online calculation speed. Deep reinforcement learning (DRL) has recently been recognized as an effective alternative as it transfers the computational pressure to the off-line training and the online calculation timescale reaches milliseconds. However, its slow offline training speed still limits its application to VVC. To overcome this issue, this paper proposes a simplified DRL method that simplifies and improves the training operations in DRL, avoiding invalid explorations and slow reward calculation speed. Given the problem that the DRL network parameters of original topology are not applicable to the other new topologies, side-tuning transfer learning (TL) is introduced to reduce the number of parameters needed to be updated in the TL process. Test results based on IEEE 30-bus and 118-bus systems prove the correctness and rapidity of the proposed method, as well as their strong applicability for large-scale control variables.