The Z-Source Inverter (ZSI) has been reported suitable for residential PV system because of the capability of voltage boost and inversion in a single stage. Recently, four new topologies, the quasi-Z-Source Inverters (qZSI), have been derived from the original ZSI. This project analyzes one voltage fed topology of these four in detail and applies it to PV power generation systems. By using the new quasi-Z-Source topology, the inverter draws a constant current from the PV array and is capable of handling a wide input voltage range. It also features lower component ratings and reduced source stress compared to the traditional ZSI. A prototype which provides three phase 50-Hz, 230Vrms ac has been built in laboratory. It is demonstrated from the theoretical analysis and MATLAB/SIMULATION results that the proposed qZSI can realize voltage buck or boost and dc-ac inversion in a single stage with high reliability and efficiency, which makes it well suited for PV power systems.

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Ancillary services are critical to maintaining the safe and stable operation of power systems that contain a high penetration level of renewable energy resources. As a high-quality regulation resource, the regional integrated energy system (RIES) with energy storage system (ESS) can effectively adjust the non-negligible frequency offset caused by the renewable energy integration into the power system, and help solve the problem of power system frequency stability. In this paper, the optimization model aiming at regional integrated energy system as a participant in the regulation market based on pay-for-performance is established. Meanwhile YALMIP + CPLEX is used to simulate and analyze the total operating cost under different dispatch modes. This paper uses the actual operation model of the PJM regulation market to guide the optimal allocation of regulation resource in the regional integrated energy system, and provides a balance between the power trading revenue and regulation market revenue in order to achieve the maximum profit.

This paper documents the condition-based maintenance (CBM) of power transformers, the analysis of which relies on two basic data groups: structured (e.g., numeric and categorical) and unstructured (e.g., natural language text narratives) which accounts for 80% of data required. However, unstructured data comprised of malfunction inspection reports, as recorded by operation and maintenance of the power grid, constitutes an abundant untapped source of power insights. This paper proposes a method for malfunction inspection report processing by deep learning, which combines the text data mining-oriented recurrent neural networks (RNN) with long short-term memory (LSTM). In this paper, the effectiveness of the RNN-LSTM network for modeling inspection data is established with a straightforward training strategy in which we replicate targets at each sequence step. Then, the corresponding fault labels are given in datasets, in order to calculate the accuracy of fault classification by comparison with the original data labels and output samples. Experimental results can reflect how key parameters may be selected in the configuration of the key variables to achieve optimal results. The accuracy of the fault recognition demonstrates that the method we proposed can provide a more effective way for grid inspection personnel to deal with unstructured data.

Analyses of transformer electromagnetic vibration noise are presented in this study. A finite element model is established which combines transient electromagnetic field analysis, mechanical field analysis and acoustic analysis to calculate the sound pressure level of the radiated noise around the transformer. Transient electromagnetic field analysis is performed to get the Lorentz, reluctance magnetic forces and magnetostriction according to Maxwell theory and virtual displacement principle. Mutual influence of strain and magnetisation has been considered. The main frequency components of harmonic electromagnetic excitations are analysed by Fourier transformation so as to carry out the harmonic response analysis and obtain the nodes displacements of the windings and core. The noise distribution is further calculated by acoustic analysis based on the achieved vibration data. Comparison of calculated results and measured data verifies that the combined noise calculating model is applicable for transformer noise prediction.

Abstract:With a higher penetration of distributed generation in the power system, the application of microgrids is expected to increase dramatically in the future. This paper proposes a novel method to design optimal droop coefficients of dispatchable distributed energy resources for a microgrid in the Energy Internet considering the volatility of renewable energy generation, such as wind and photovoltaics. The uncertainties of renewable energy generation are modeled by a limited number of scenarios with high probabilities. In order to achieve stable and economical operation of a microgrid that is also suitable for plug-and-play distributed renewable energy and distributed energy storage devices, a multi-objective optimization model of droop coefficients compromising between operational cost and the integral of time-weighted absolute error criterion is developed. The optimization is solved by using a differential evolution algorithm. Case studies demonstrate that the economy and transient behavior of microgrids in the Energy Internet can both be improved significantly using the proposed method.

Overspeed is more likely to occur in the process of load rejection or large disturbances for nuclear steam turbines due to the large parameter range and low steam parameters, as well as the power of the low-pressure cylinder accounting for a high proportion of the total power. It is of great significance to study the overspeed characteristics of nuclear power plants (NPPs) to ensure the safe and stable operation of the unit and power grid. According to the characteristics of NPPs, the overspeed protection model and the super-acceleration protection model were established, which were added to the speed-governing system model. The response characteristics of the reactor, thermal system, steam turbine and speed-governing system in the process of load rejection or large disturbances of the power grid were analyzed and simulated. The results were compared using the simulation software personal computer transient analyzer (PCTRAN). The simulation results showed that quickly closing both the high and medium pressure regulating valves could effectively realize frequency control when load rejection or a large grid disturbance occurred. The over-acceleration protection cooperates with the super-acceleration protection to avoid the repeated opening/closing of the valves due to overspeed protection. This could effectively reduce the impact of large disturbances on the reactor, thermal system, and turbine.

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