Xiaolin Mao

A DC–DC Multiport-Converter-Based Solid-State Transformer Integrating Distributed Generation and Storage

The Solid-state transformer (SST) has been proposed by researchers to replace the regular distribution transformer in the future smart grid. The SST provides ports for the integration of storage and distributed generation (DG), e.g., photovoltaic (PV), and enables the implementation of power quality features. This paper proposes a SST topology based on a quad-active-bridge (QAB) converter which not only provides isolation for the load, but also for DG and storage. A gyrator-based average model is developed for a general multiactive-bridge (MAB) converter, and expressions to determine the power rating of the MAB ports are derived. These results are then applied to analyze the QAB converter. For the control of the dc-dc stage of the proposed QAB-based SST integrating PV and battery, a technique that accounts for the cross-coupling characteristics of the QAB converter in order to improve the regulation of the high-voltage-dc link is introduced. This is done by transferring the disturbances onto the battery. The control loops are designed using single-input single-output techniques with different bandwidths. The dynamic performance of the control strategy is verified through extensive simulation and experimental results.

Topology comparison for Solid State Transformer implementation

In this paper, a comparison of six representative topologies for the implementation of Solid State Transformers (SST) is performed. The objective is to help identify the most suitable topology capable of supporting additional functionalities as compared to a regular transformer, e.g. on-demand reactive power support to grid, voltage regulation, and current limiting. The comparison is based on switch loss, switch count, control characteristics and supported functionalities. It has been concluded that a three-stage configuration comprising distinct AC-DC, DC-DC and DC-AC stages results in the most suitable implementation. A Simulink model corresponding to this three-stage configuration is developed to demonstrate the desired characteristics and functionalities of the SST.

Optimal Variable Switching Frequency Scheme for Reducing Switching Loss in Single-Phase Inverters Based on Time-Domain Ripple Analysis

The choice of switching frequency for pulsewidth modulation single-phase inverters, such as those used in grid-connected photovoltaic application, is usually a tradeoff between reducing the total harmonic distortion (THD) and reducing the switching loss. This paper discusses an approach to minimize the switching loss while meeting a given THD requirement using variable switching frequency schemes (switching schemes with the switching frequency varying within a fundamental period). An optimal switching scheme is proposed based on time-domain current ripple analysis and the calculus of variations. The analysis shows that, to meet the same THD requirement, the optimal scheme has a significant saving on switching loss, compared to the fixed switching frequency scheme and the hysteresis control scheme, in addition to other benefits such as reduced peak switching loss and a spread spectrum of the current harmonics. The optimal scheme has been implemented in a prototype and the experimental results have verified the theoretical analysis. Also, a straightforward design method for designing filter inductors for single-phase converters is provided based on the time-domain current ripple analysis.

Hybrid Interleaved Space Vector PWM for Ripple Reduction in Modular Converters

This paper addresses the problem of optimizing space vector PWM (SVM) for interleaved, parallel-connected, three-phase voltage source converters to reduce total harmonic distortion (THD) of the total line current. A systematic approach is presented for designing hybrid SVM schemes involving multiple sequences, including those based on active state division, and different phase shifts to reduce current ripple. First, the effect of different phase shifts on the current ripple is investigated and it is shown that using standard phase shifts yields performance close to optimal. Second, a zone-division plot is generated based on all sequence-phase shift combinations. The plot shows spatial regions within a sector where a certain sequence-phase shift combination results in the lowest rms current ripple in one switching period, and thus represents the optimal hybrid scheme. Lastly, simplified, easy-to-implement quasi-optimal SVM schemes are derived from the zone-division plot based on specific application requirements, and their performances are compared with the optimal scheme. The application of the proposed approach to a two-converter case is discussed in detail. A simple, quasi-optimal SVM scheme is proposed for grid-connected applications with analytical and experimental results confirming significant reduction in current THD. Finally, extension to three- and four-converter cases is discussed.

Energy-based control design for a solid state transformer

This paper addresses the control design for a three-stage solid stage transformer (SST). When two or more independently controlled converter stages are cascaded, which is the case for the three-stage SST, the interaction among the stages can lead to instability. Normally, the input and output impedances of the cascaded stages need to be examined according to the impedance criterion to ensure stability. In this paper, a novel energy-based control design method is proposed for the three-stage SST that enables decoupled control design for the rectifier and DC-DC stages, which avoids the need for the impedance checking and hence significantly simplifies the control design. The energy-based concept also works well with the power control methods commonly used such as those based on the DQ frame or the instantaneous reactive power (IRP) p-q theory, which allows for simple reactive power or power factor control. The design of the various control loops of the SST is described in detail in this paper and validated through simulations.

Distribution system modeling using CYMDIST for study of high penetration of distributed solar photovoltaics

This paper discusses the detailed procedure for automated construction of a distribution system model using CYMDIST. Information about the distribution system equipments and lines is provided in geographic information system (GIS) data, and load and PV data is obtained by advanced metering infrastructure (AMI). Based on the given data, step by step method to construct the distribution system model is described. The model constructed includes single phase loads, high penetration of single phase solar photovoltaics (PV), and two large three-phase PV. CYMDIST has the ability to execute the three phase unbalanced power flow analysis on the model. Analysis results with and without PV in terms of voltage profiles, KW profiles and KVAR profiles are presented, in order to investigate the impact of high penetration of distributed solar photovoltaics.

Average and Phasor Models of Single Phase PV Generators for Analysis and Simulation of Large Power Distribution Systems

As the penetration of distributed PV generation increases, its impact on the stability and security of the power system will become more and more significant. Suitable models for the PV generators are needed for studying the dynamics in a power system containing many such distributed PV generators. In this paper, two dynamic models for residential single phase PV converters are developed for fast simulation of power distribution systems with multiple PV generators: a simplified average model and a phasor model. The former is useful for time-domain simulation. The latter is suitable for fast phasor simulation where only the magnitudes and phases at the line frequency of the voltages and currents in the power system network are of interest. Simulations are conducted to show the improved simulation speed and to validate the accuracy of the developed models.

Improving Reliability Assessment of Transformer Thermal Top-Oil Model Parameters Estimated From Measured Data

This paper presents a methodology for assessing the reliability of thermal-model parameters for transformers estimated from measured data. The methodology uses statistical bootstrapping to calculate confidence levels (CL) and confidence intervals (CI). Bootstrapping allows us to make a small dataset look statistically larger, which allows a precise estimate of the transformer thermal models reliability. The proposed methodology is tested on a 167-MVA oil-forced air-forced transformer. The CIs are evaluated with and without bootstrapping and the reliability indices are compared. The results show that the CI and CL values with bootstrapping are more consistently reproducible than the ones derived without bootstrapping.

Dead time effect in two-level space vector PWM voltage source inverters with large current ripple

The analysis of the effect of dead time in a PWM inverter is important to realize its impact on the low frequency harmonics in the inverter and for appropriate dead time compensator design. This paper analyzes the dead-time effect in space-vector PWM (SVM) inverters considering various SVM schemes that include some non-conventional SVMs and even hybrid SVMs. Also, the effect of the current zero-crossing zone in applications with large current ripple is considered in the analysis and it has been found that this inclusion is important. Experimental results are presented that agree with the analysis.

Simplified Solid State Transformer modeling for Real Time Digital Simulator (RTDS)

The Solid State Transformer will be an essential component in the smart grid and it would have made much more impact. This paper proposed a simplified model that is suitable for simulations in RTDS and it is also suitable for general power system studies. While most of the fast dynamics of SST is ignored, all the main control functionalities are kept in this model. The simplified model is tested and verified by comparing with a detail full switching model and cycle-by-cycle average model built in MATLAB and PLECS.