China Electric Power Research Institute

A synchronverter is an inverter that mimics synchronous generators, which offers a mechanism for power systems to control grid-connected renewable energy and facilitates smart grid integration. Similar to other grid-connected inverters, it needs a dedicated synchronization unit, e.g., a phase-locked loop (PLL), to provide the phase, frequency, and amplitude of the grid voltage as references. In this paper, a radical step is taken to improve the synchronverter as a self-synchronized synchronverter by removing the dedicated synchronization unit. It can automatically synchronize itself with the grid before connection and track the grid frequency after connection. This considerably improves the performance, reduces the complexity, and computational burden of the controller. All the functions of the original synchronverter, such as frequency and voltage regulation, real power, and reactive power control, are maintained. Both simulation and experimental results are presented to validate the control strategy. Experimental results have shown that the proposed control strategy can improve the performance of frequency tracking by more than 65%, the performance of real power control by 83%, and the performance of reactive power control by about 70%.

The battery energy storage station (BESS) is the current and typical means of smoothing wind- or solar-power generation fluctuations. Such BESS-based hybrid power systems require a suitable control strategy that can effectively regulate power output levels and battery state of charge (SOC). This paper presents the results of a wind/photovoltaic (PV)/BESS hybrid power system simulation analysis undertaken to improve the smoothing performance of wind/PV/BESS hybrid power generation and the effectiveness of battery SOC control. A smoothing control method for reducing wind/PV hybrid output power fluctuations and regulating battery SOC under the typical conditions is proposed. A novel real-time BESS-based power allocation method also is proposed. The effectiveness of these methods was verified using MATLAB/SIMULINK software.

The concept of the virtual synchronous generator (VSG) is emerging as an attractive solution for controlling the grid-connected inverter when the renewable energy has a high penetration level into the grid. This paper focuses on the small-signal modeling and parameters design of the power loop of the VSG, and points out that the bandwidth of the power loop should be far less than twice the line frequency for the purpose of avoiding the VSG output voltage to be severely distorted. Consequently, the line-frequency-averaged small-signal model of the VSG is derived for system analysis and parameters design. Based on the model, the decoupling conditions between the active power loops (APLs) and the reactive power loops (RPLs) of the VSG are given. Finally, a step-by-step parameters design method is proposed to facilitate the design of the control parameters of the VSG. A 10-kVA prototype is built and tested in the laboratory, and the experimental results are given to verify the effectiveness of the theoretical analysis and the proposed parameters design method.

Smart grids are the developmental trend of power systems and they have attracted much attention all over the world. Due to their complexities, and the uncertainty of the smart grid and high volume of information being collected, artificial intelligence techniques represent some of the enabling technologies for its future development and success. Owing to the decreasing cost of computing power, the profusion of data, and better algorithms, AI has entered into its new developmental stage and AI 2.0 is developing rapidly. Deep learning (DL), reinforcement learning (RL) and their combination-deep reinforcement learning (DRL) are representative methods and relatively mature methods in the family of AI 2.0. This article introduces the concept and status quo of the above three methods, summarizes their potential for application in smart grids, and provides an overview of the research work on their application in smart grids.

Subsynchronous resonance (SSR) was observed in wind farms located in North China. These wind farms prevailingly consist of doubly-fed induction generators (DFIGs) and are connected to series-compensated transmission lines. The observed resonant frequency is about 6 ~ 8 Hz, which is much lower than that of the reported SSR occurred in Texas. The frequency varies during the occurrence and this phenomenon is observed for the first time. The output power is usually within a certain range, when SSR occurs. Based on the practical system, an equivalent simulation system has been established, in which wind farms are modeled as many identical low rating DFIGs. Then, the SSR event is reproduced by simulations. Analysis results indicate that SSR happens even when the equivalent transmission system compensation level seen from wind farms is only 6.67%. Eigenvalue analysis shows that this phenomenon is an electrical resonance, and could be affected considerably by wind speed, number and control of DFIGs. The number of in-service DFIGs has a nonlinear impact on the damping of SSR. An equivalent electric circuit is deduced to intuitively explain why SSR happens and how the above factors affect it. Considering its features, this phenomenon is recognized as DFIG control participated induction generator effect.

An environmentally friendly leaching process for recycling valuable metals from spent lithium-ion batteries is developed. A sol–gel method is utilized to resynthesize LiNi1/3Co1/3Mn1/3O2 from the leachate. Lactic acid is chosen as a leaching and chelating agent. The leaching efficiency is investigated by determining the contents of metal elements such as Li, Ni, Co, and Mn in the leachate using inductively coupled plasma optical emission spectroscopy. The spent cathode materials for the pretreatment process and the regenerated and freshly synthesized materials are examined using X-ray diffraction and scanning electronic microscopy. The results show that the leaching efficiencies of Li, Ni, Co, and Mn reached 97.7, 98.2, 98.9, and 98.4%, respectively. The optimum conditions are lactic acid concentration of 1.5 mol L–1, solid/liquid ratio of 20 g L–1, leaching temperature of 70 °C, H2O2 content of 0.5 vol %, and reaction time of 20 min. The leaching kinetics of cathode scrap in lactic acid fit well to the Avrami equation. Electrochemical analysis indicate that the regenerated LiNi1/3Co1/3Mn1/3O2 cathode materials deliver a highly reversible discharge capacity, 138.2 mA h g–1, at 0.5 C after 100 cycles, with a capacity retention of 96%, comparable to those of freshly synthesized LiNi1/3Co1/3Mn1/3O2 cathodes.

This paper presents a hybrid modular multilevel converter (MMC), which combines full-bridge submodules (FBSM) and half-bridge submodules (HBSM). Compared with the FBSM-based MMC, the proposed topology has the same dc fault blocking capability but uses fewer power devices hence has lower power losses. To increase power transmission capability of the proposed hybrid MMC, negative voltage states of the FBSMs are adopted to extend the output voltage range. The optimal ratio of FBSMs and HBSMs, and the number of FBSMs generating a negative voltage state are calculated to ensure successful dc fault blocking and capacitor voltage balancing. Equivalent circuits of each arm consisting of two individual voltage sources are proposed and two-stage selecting and sorting algorithms for ensuring capacitor voltage balancing are developed. Comparative studies for different circuit configurations show excellent performance balance for the proposed hybrid MMC, when considering dc fault blocking capability, power losses, and device utilization. Experimental results during normal operation and dc fault conditions demonstrate feasibility and validity the proposed hybrid MMC.

Clarification of the responsibility for carbon emission is fundamental in a carbon-constrained world. Existing statistical methods for carbon emission estimation usually attribute the emission responsibility to the generation side. However, a growing number of analysis across different sectors has pointed out that “consumers” rather than “producers” should be responsible for the CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> emitted during the production. In power system, it is consumers that create the need for the combustion of fossil fuels and cause substantial carbon emission. In order to account carbon emission from the consumption-based perspective, carbon emission generated by various generators can be seen as a virtual attachment to the power flow and accumulated at the consumer's side. A novel analytical model for carbon emission flow (CEF) is proposed in this paper to quantify the carbon emission accompanying the power delivery process. The newly developed model of CEF can take into account the operational characteristics and the network features of power system, and elaborately characterize the relationship between power delivery and CEF. Some basic concepts of CEF in power networks are defined, and the fundamental characteristics and distribution principles of CEF are analyzed. Furthermore, a novel calculation model for CEF in power networks is proposed. A case study is conducted based on the IEEE 118 bus system to illustrate the calculation process and result of CEF in power system.

The emerging subsynchronous resonance (SSR) caused by the interaction of wind turbine generators (WTGs) with series compensation has aroused great concerns. For this particular issue, this paper is aimed to fill the gap between theoretical studies and actual observations. By analyzing the field data of 58 SSR events captured in a practical wind power system and examining the observed dynamics with previous theoretical results, the mechanism and characteristics of SSR are revealed in a more explicit and substantial way. The necessary conditions and dominant influential factors are identified and the underlying reasons are discovered. Theoretically derived as well as practically measured impedance models have demonstrated that the converter control of doubly fed induction generator (DFIG) produces negative resistance at the slip frequency and thus causes unstable SSR; while permanent magnet synchronous generators and self-excited induction generators are just passively engaged in those SSR incidents. The distribution of the oscillation frequency has also been examined with field measurements. It is discovered that WTGs at different locations participate into the same SSR mode and their frequencies are not fixed but keep changing with the time, the variation of grid topology, and the number of online generators.

Attention mechanisms are now widely used in image captioning models. However, most attention models only focus on visual features. When generating syntax related words, little visual information is needed. In this case, these attention models could mislead the word generation. In this paper, we propose Task-Adaptive Attention module for image captioning, which can alleviate this misleading problem and learn implicit non-visual clues which can be helpful for the generation of non-visual words. We further introduce a diversity regularization to enhance the expression ability of the Task-Adaptive Attention module. Extensive experiments on the MSCOCO captioning dataset demonstrate that by plugging our Task-Adaptive Attention module into a vanilla Transformer-based image captioning model, performance improvement can be achieved.

The change rate of the dc reactor voltage with predefined protection voltage thresholds is proposed to provide fast and accurate dc fault detection in a meshed multiterminal HVDC system. This is equivalent to the measurement of the second derivative of the dc current but has better robustness in terms of electromagnetic-interference noise immunization. In addition to fast dc fault detection, the proposed scheme can also accurately discriminate the faulty branch from the healthy ones in a meshed dc network by considering the voltage polarities and amplitudes of the two dc reactors connected to the same converter dc terminal. Fast fault detection leads to lower fault current stresses on dc circuit breakers and converter equipment. The proposed method requires no telecommunication, is independent of power-flow direction, and is robust to fault resistance variation. Simulation of a meshed three-terminal HVDC system demonstrates the effectiveness of the proposed dc fault detection scheme.

Existing enhancement methods are empirically expected to help the high-level end computer vision task: however, that is observed to not always be the case in practice. We focus on object or face detection in poor visibility enhancements caused by bad weathers (haze, rain) and low light conditions. To provide a more thorough examination and fair comparison, we introduce three benchmark sets collected in real-world hazy, rainy, and low-light conditions, respectively, with annotated objects/faces. We launched the UG2+ challenge Track 2 competition in IEEE CVPR 2019, aiming to evoke a comprehensive discussion and exploration about whether and how low-level vision techniques can benefit the high-level automatic visual recognition in various scenarios. To our best knowledge, this is the first and currently largest effort of its kind. Baseline results by cascading existing enhancement and detection models are reported, indicating the highly challenging nature of our new data as well as the large room for further technical innovations. Thanks to a large participation from the research community, we are able to analyze representative team solutions, striving to better identify the strengths and limitations of existing mindsets as well as the future directions.

Rapid development of renewable energy in China is driving a major shift in the characteristics and control requirements of the electricity grid. Since the best renewable energy resources are far away from load centers in the east and southeast, transmission over long distances is required. Over 20 high-voltage DC (HVDC) transmission lines, with a combined capacity exceeding 150 GW, are in operation or are currently under construction. This rapid expansion of new generation and transmission capacities based on power electronics starts to change the characteristics of the grid, especially in areas where they concentrate, creating new stability problems and operational challenges. New system theories and technologies are required to support the development and operation of a future grid that relies more and more on power electronics. This paper highlights the characteristics of power electronics as used in renewable energy generation and HVDC transmission systems, discusses the impacts of these power-electronics-based assets on grid stability and operational requirements, and identifies opportunities for the development of both new system theories and system technologies to support a national energy policy that emphasizes the use of clean energy.

Voltage-source converters (VSCs) are widely used in renewable energy sources as the grid interface, e.g., wind turbine generators and photovoltaics. These VSCs control the dc-link capacitor voltage and the reactive power output to track the reference values, which generally apply phase-locked loop (PLL) for grid synchronization. However, the dynamic performance of the conventional PLL can be deteriorated when the VSC is integrated into weak grids, which may even cause instability of the VSC. In this paper, a virtual synchronous control (ViSynC) is proposed for VSCs, which utilizes the dynamics of the dc-link capacitor to realize self-synchronization. Grid synchronization mechanism of the ViSynC-based VSC is particularly analyzed in this paper. The ViSynC-based VSC can provide inertial responses to the grid, and has the advantage that it can operate normally under weak grid conditions without any modification of the grid synchronization unit. Furthermore, virtual impedance and Q-V droop control can be easily implemented in the control structure of the ViSynC. Simulations based on MATLAB/ Simulink and hardware-in-the-loop real-time simulations based on RT-LAB verify the effectiveness of the proposed ViSynC.

Integrated energy system is important for the high-efficient utilization of multitype energy systems. In this paper, the stochastic optimal operation is investigated for the micro integrated electric power, natural gas, and heat delivery system (IPGHS). First, a low-carbon micro-IPGHS is proposed with the comprehensive consideration of renewable generation, carbon-capture-based power-to-gas technology, and the combined power and heat units. Second, a scenario-based optimal operation model for micro-IPGHS is proposed to handle uncertainties in energy demand and renewable generation. In the proposed model, energy transactions between micro-IPGHS and upstream energy systems as well as constraints for battery storage, natural gas storage, and heat storage systems are considered. Finally, a case study is used for the proposed low-carbon micro-IPGHS to validate the optimal stochastic operation approach. The proposed integrated system can effectively utilize the variable clean energy for optimizing the delivery of the green operation in micro-IPGHS.

A new type of subsynchronous resonance (SSR), namely, subsynchronous control interaction (SSCI), was recently observed in doubly-fed induction generators (DFIGs) interfaced with series-compensated power networks. In this paper, a more accurate method based on aggregated RLC circuit model is proposed to intuitively explain and quantitatively evaluate this type of SSR. For a practical power system containing multiple DFIGs and fixed series compensation, an improved impedance model (IM) is derived, which incorporates DFIG's full-scale control system. Around the series-resonant frequency, IM can be further represented with an aggregated RLC circuit model. Its equivalent parameters are worked out and then used for the quantitative assessment of potential SSR risk. The proposed method is applied for SSR analysis of a practical wind farm system in North China that experienced actual SSR incidents. The consistence between the obtained results and field measured data verifies its effectiveness very well. Further, its advantage in accuracy over existing impedance-based approaches is validated by both eigenvalue analysis and time-domain simulations. The method is also used to quantitatively investigate the impact on SSR stability from the various factors, including wind speed, number of online DFIGs and their control parameters.

This paper mainly focuses on the energy management of microgrids (MGs) consisting of combined heat and power (CHP) and photovoltaic (PV) prosumers. A multiparty energy management framework is proposed for joint operation of CHP and PV prosumers with the internal price-based demand response. In particular, an optimization model based on Stackelberg game is designed, where the microgrid operator (MGO) acts as the leader and PV prosumers are the followers. The properties of the game are studied and it is proved that the game possesses a unique Stackelberg equilibrium. The heuristic algorithm based on differential evolution is proposed that can be adopted by the MGO, and nonlinear constrained programing can be adopted by each prosumer to reach the Stackelberg equilibrium. Finally, via a practical example, the effectiveness of the model is verified in terms of determining MGO's prices and optimizing net load characteristic, etc.

Many utilities have the data quality problem with the geographical information system (GIS) records at distribution level. This affects many business functions of a utility, including asset management, outage response, and workforce safety. For correcting connectivity errors in the GIS representation of the distribution network topology, BC Hydro has developed an in-house algorithm. The algorithm leverages smart meter interval measurements and identifies the neighboring meters by voltage profile correlation analysis. It also predicts customers' upstream and downstream location relationship by voltage magnitude comparisons. The output of the algorithm is then compared with the existing GIS records to correct any errors in it. This paper presents in detail the algorithm and the promising testing results within the practical BC Hydro system. Challenges for underground services are demonstrated. The algorithm's potential use for phase detection by collectively leveraging smart meter and feeder meter data is explored. It shows encouraging results when applied in a downstream section of a large feeder.

As a flexible power source, energy storage has many potential applications in renewable energy generation grid integration, power transmission and distribution, distributed generation, micro grid and ancillary services such as frequency regulation, etc. In this paper, the latest energy storage technology profile is analyzed and summarized, in terms of technology maturity, efficiency, scale, lifespan, cost and applications, taking into consideration their impact on the whole power system, including generation, transmission, distribution and utilization. The application scenarios of energy storage technologies are reviewed and investigated, and global and Chinese potential markets for energy storage applications are described. The challenges of large-scale energy storage application in power systems are presented from the aspect of technical and economic considerations. Meanwhile the development prospect of global energy storage market is forecasted, and application prospect of energy storage is analyzed.

System control for dc microgrids with variable generations and energy storage is proposed in this paper. An autonomous three-level control strategy is proposed for dc microgrids with selective slack terminal(s) assigned to each operation level. The system operational status is acknowledged via the common dc voltage and the transitions between different operational levels are triggered by its variation. A four-terminal sample dc microgrid system with a grid-connected voltage-source converter, a wind turbine, an energy storage system, and dc loads are established and a specific control scheme is outlined to demonstrate the proposed strategy during various operating conditions, such as load step, generation fluctuation, islanding, grid reconnection, load shedding, and generation curtailment. The control strategy and the specific scheme are validated by experimental results conducted on a prototype dc microgrid system.