State Grid Corporation of China (China)

Abstract In the electrical energy transformation process, the grid-level energy storage system plays an essential role in balancing power generation and utilization. Batteries have considerable potential for application to grid-level energy storage systems because of their rapid response, modularization, and flexible installation. Among several battery technologies, lithium-ion batteries (LIBs) exhibit high energy efficiency, long cycle life, and relatively high energy density. In this perspective, the properties of LIBs, including their operation mechanism, battery design and construction, and advantages and disadvantages, have been analyzed in detail. Moreover, the performance of LIBs applied to grid-level energy storage systems is analyzed in terms of the following grid services: (1) frequency regulation; (2) peak shifting; (3) integration with renewable energy sources; and (4) power management. In addition, the challenges encountered in the application of LIBs are discussed and possible research directions aimed at overcoming these challenges are proposed to provide insight into the development of grid-level energy storage systems.

Recently, sustained power oscillation at subsynchronous frequency was captured in direct-drive permanent magnetic synchronous generator (PMSG) based wind farms in Xinjiang Uygur Autonomous Region, China. This new type of subsynchronous interaction (SSI) detected in practical systems has never been reported and analyzed before. Therefore, its mechanism and characteristics are not yet clearly clarified. In this paper, a simplified but representative system model with multiple PMSGs interfaced with AC networks is established first based on the actual system and the PMSG model provided by the manufacturer. Then, small-signal eigenanalysis, time-domain simulation, and impedance model analysis are carried out to investigate the interactive dynamics between them. The results show that such interaction between direct-drive PMSG wind farms and weak ac grids characterized by low short-circuit ratio would cause negative-resistance effect for the SSI mode, leading to unstable oscillation. In such cases, the controller of PMSG would saturate soon, resulting in sustained power oscillation in the system. If unfortunately the oscillation frequency matches the torsional mode of any nearby turbogenerator, severe torsional vibration would be excited on the shaft of the latter. The analysis results are finally validated with field measurements of an actual SSI event. To address the problem, a supplementary subsynchronous damping control loop is attached to the controllers of PMSGs to reshape the impedance and thus to stabilize the SSI.

A community integrated energy system (CIES) with an electric vehicle charging station (EVCS) provides a new way for tackling growing concerns of energy efficiency and environmental pollution, it is a critical task to coordinate flexible demand response and multiple renewable uncertainties. To this end, a novel bi-level optimal dispatching model for the CIES with an EVCS in multi-stakeholder scenarios is established in this paper. In this model, an integrated demand response program is designed to promote a balance between energy supply and demand while maintaining a user comprehensive satisfaction within an acceptable range. To further tap the potential of demand response through flexibly guiding users energy consumption and electric vehicles behaviors (charging, discharging and providing spinning reserves), a dynamic pricing mechanism combining time-of-use and real-time pricing is put forward. In the solution phase, by using sequence operation theory (SOT), the original chance-constrained programming (CCP) model is converted into a readily solvable mixed-integer linear programming (MILP) formulation and finally solved by CPLEX solver. The simulation results on a practical CIES located in North China demonstrate that the presented method manages to balance the interests between CIES and EVCS via the coordination of flexible demand response and uncertain renewables.

With the largest installed capacity in the world, wind power in China is experiencing a ~ 20% curtailment during operation. The large portion of the generation capacity from inflexible combined heat and power (CHP) is the major barrier for integrating this variable power source. This paper explores opportunities for increasing the flexibility of CHP units using electrical boilers and heat storage tanks for better integration of wind power. A linear model is proposed for the centralized dispatch for integrated energy systems considering both heat and power, with detailed modeling of the charging processes of the heat storage tanks. The model balances heat and power demands in multiple areas and time periods with various energy sources, including CHP, wind power, electrical boilers, and heat storage. The impact of introducing electrical boilers and heat storage systems is examined using a simple test system with characteristics similar to those of the power systems in Northern China. Our results show that both electrical boilers and heat storage tanks can improve the flexibility of CHP units: introducing electrical boilers is more effective at reducing wind curtailment, whereas heat storage tanks save more energy in the energy system as a whole, which reflect a different heating efficiency of the two solutions.

Non-lithium energy storage devices, especially sodium ion batteries, are drawing attention due to insufficient and uneven distribution of lithium resources. Prussian blue and its analogs (Prussian blue analogs [PBAs]), or hexacyanoferrates, are well-known since the 18th century and have been used for hydrogen storage, cancer therapy, biosensing, seawater desalination, and sewage treatment. Owing to their unique features, PBAs are receiving increasing interest in the field of energy storage, such as their high theoretical specific capacity, ease of synthesis, as well as low cost. In this review, a general summary and evaluation of the applications of PBAs for rechargeable batteries are given. After a brief review of the history of PBAs, their crystal structure, nomenclature, synthesis, and working principle in rechargeable batteries are discussed. Then, previous works classified based on the combination of insertion cations and transition metals are analyzed comprehensively. The review includes an outlook toward the further development of PBAs in electrochemical energy storage.

), critical scientific challenges remain in utilizing the advantages of existing semiconductor materials for more and wider applications while maintaining less complicated synthetic or device fabrication processes. DA complex materials have revealed new insight: their unique molecular packing and structure-property relationships. The combination of donors and acceptors could offer practical advantages compared with their unimolecular materials. First, growing crystals of DA complexes with densely packed structures will reduce impurities and traps from the self-assembly process. Second, complexes based on the original structural components could form superior mixture stacking, which can facilitate charge transport depending on the driving force in the coassembly process. Third, the effective use of organic semiconductors can lead to tunable band structures, allowing the operation mode (p- or n-type) of the transistor to be systematically controlled by changing the components. Finally, theoretical calculations based on cocrystals with unique stacking could widen our understanding of structure-property relationships and in turn help us design high-performance semiconductors based on DA complexes. In this Account, we focus on discussing organic DA complexes as a new class of semiconducting materials, including their design, growth methods, packing modes, charge-transport properties, and structure-property relationships. We have also fabricated and investigated devices based on these binary crystals. This interdisciplinary work combines techniques from the fields of self-assembly, crystallography, condensed-matter physics, and theoretical chemistry. Researchers have designed new complex systems, including donor and acceptor compounds that self-assemble in feasible ways into highly ordered cocrystals. We demonstrate that using this crystallization method can easily realize ambipolar or unipolar transport. To further improve device performance, we propose several design strategies, such as using new kinds of donors and acceptors, modulating the energy alignment of the donor (ionization potential, IP) and acceptor (electron affinity, EA) components, and extending the π-conjugated backbones. In addition, we have found that when we use molecular "doping" (2:1 cocrystallization), the charge-transport nature of organic semiconductors can be switched from hole-transport-dominated to electron-transport-dominated. We expect that the formation of cocrystals through the complexation of organic donor and acceptor species will serve as a new strategy to develop semiconductors for organic electronics with superior performances over their corresponding individual components.

Air filtration in the free molecular flow (FMF) regime is important and challenging because a higher filtration efficiency and lower pressure drop are obtained when the fiber diameter is smaller than the gas mean free path in the FMF regime. In previous studies, FMF conditions have been obtained by increasing the gas mean free path through reducing the pressure and increasing the temperature. In the case of carbon nanotubes (CNTs) with nanoscale diameters, it is possible to filtrate in the FMF regime under normal conditions. This paper reviews recent progress in theoretical and experimental studies of air filtration in the FMF regime. Typical structure models of high-efficiency particulate (HEPA) air filters based on CNTs are introduced. The pressure drop in air filters operated in the FMF regime is less than that predicted by the conventional air filtration theory. The thinnest HEPA filters fabricated from single-walled CNT films have an extremely low pressure drop. CNT air filters with a gradient nanostructure are shown to give a much better filtration performance in dynamic filtration. CNT air filters with a hierarchical structure and an agglomerated CNT fluidized bed air filter are also introduced. Finally, the challenges and opportunities for the application of CNTs in air filtration are discussed.

This paper studies the solution of joint energy storage (ES) ownership sharing between multiple shared facility controllers (SFCs) and those dwelling in a residential community. The main objective is to enable the residential units (RUs) to decide on the fraction of their ES capacity that they want to share with the SFCs of the community in order to assist them in storing electricity, e.g., for fulfilling the demand of various shared facilities. To this end, a modified auction-based mechanism is designed that captures the interaction between the SFCs and the RUs so as to determine the auction price and the allocation of ES shared by the RUs that governs the proposed joint ES ownership. The fraction of the capacity of the storage that each RU decides to put into the market to share with the SFCs and the auction price are determined by a noncooperative Stackelberg game formulated between the RUs and the auctioneer. It is shown that the proposed auction possesses the incentive compatibility and the individual rationality properties, which are leveraged via the unique Stackelberg equilibrium solution of the game. Numerical experiments are provided to confirm the effectiveness of the proposed scheme.

Transformerless inverters are widely used in grid-tied photovoltaic (PV) generation systems, due to the benefits of achieving high efficiency and low cost. Various transformerless inverter topologies have been proposed to meet the safety requirement of leakage currents, such as specified in the VDE-4105 standard. In this paper, a family of H6 transformerless inverter topologies with low leakage currents is proposed, and the intrinsic relationship between H5 topology, highly efficient and reliable inverter concept (HERIC) topology, and the proposed H6 topology has been discussed as well. One of the proposed H6 inverter topologies is taken as an example for detail analysis with operation modes and modulation strategy. The power losses and power device costs are compared among the H5, the HERIC, and the proposed H6 topologies. A universal prototype is built for these three topologies mentioned for evaluating their performances in terms of power efficiency and leakage currents characteristics. Experimental results show that the proposed H6 topology and the HERIC achieve similar performance in leakage currents, which is slightly worse than that of the H5 topology, but it features higher efficiency than that of H5 topology.

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.

Hydrogen is an ideal alternative energy carrier to generate power for all of society's energy demands including grid, industrial, and transportation sectors. Among the hydrogen production methods, water electrolysis is a promising method because of its zero greenhouse gas emission and its compatibility with all types of electricity sources. Alkaline electrolyzers (AELs) and proton exchange membrane electrolyzers (PEMELs) are currently used to produce hydrogen. AELs are commercially mature and are used in a variety of industrial applications, while PEMELs are still being developed and find limited application. In comparison with AELs, PEMELs have more compact structure and can achieve higher current densities. Recently, however, an alternative technology to PEMELs, hydroxide exchange membrane electrolyzers (HEMELs), has gained considerable attention due to the possibility to use platinum group metal (PGM)-free electrocatalysts and cheaper membranes, ionomers, and construction materials and its potential to achieve performance parity with PEMELs. Here, the state-of-the-art AELs and PEMELs along with the current status of HEMELs are discussed in terms of their positive and negative aspects. Additionally discussed are electrocatalyst, membrane, and ionomer development needs for HEMELs and benchmark electrocatalysts in terms of the cost-performance tradeoff.

The development of a large-scale high-voltage direct current (HVDC) power grid requires a reliable, fast, and low-loss circuit breaker. The load commutation switch (LCS) is an essential part of ABB's 1200-MW hybrid HVDC breaker concept, which builds up a low-loss conducting path for the load current. The technical requirements for the LCS are expressed in this paper by studying the operation principle of the hybrid HVDC breaker. The voltage stress over the LCS is determined based on a dc grid with 320 and 2 kA rated voltage and current. A system model of the hybrid HVDC breaker is developed in PSCAD/EMTDC to study the design criteria for snubber circuit and arrester blocks. It is observed that conventional snubber circuits are not suitable for a bidirectional LCS as the current of snubber capacitors prevent the fast interruption action. A modified snubber circuit is proposed in this paper along with two more alternatives for the LCS to overcome this problem. Moreover, the power loss model for a semiconductor device is discussed in this paper based on the 4.5-kV StakPak IGBT. The model is used to calculate the conduction power losses for different LCS topologies. Ultimately, a matrix of 3 X 3 IGBT modules is selected to provide a reliable LCS design which can handle several internal fault cases with no interruption of operation. A full-scale prototype has been constructed and tested in ABB HVDC Center, Ludvika, Sweden. The experimental test results are also included in the paper in order to verify the calculation and simulation study.

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.

This paper investigates the impact of powergrid strength and phase-locked loop (PLL) parameters on small signal stability of grid-connected doubly fed induction generator (DFIG)based wind farm. Modal analysis of the grid-connected DFIG wind turbine under different operating conditions and various power grid strengths are investigated at first. Modal analysis results reveal that the DFIG connected to a weak grid may easily lose stability under the heavy-duty operating conditions due to PLL oscillation. The object of this paper is to identify the PLL oscillation mechanism as well as influence factors and propose a damping solution for this oscillation mode. A simplified linear system model of the grid-connected DFIG wind turbine is proposed for analyzing the PLL oscillation. Through the complex torque coefficients method and using this model, the oscillation mechanism and influence factors including the power grid strength and the PLL parameters are identified. To suppress this PLL oscillation, a mixed H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> /H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> robust damping controller is proposed and designed for the DFIG. Electromagnetic transient simulation results of both singleDFIG system and multiply-DFIG system verify the correctness of the analysis results and effectiveness of the proposed damping controller.

The developments and current status of ultra high voltage (UHV) alternating current (AC) and direct current (DC) transmission in China were reviewed in this paper. The UHV transmission historical developments in the past twenty years; the demand of development UHV transmission; the research results of the UHV key technologies including electromagnetic environment, over-voltage and insulation coordination, lightning performance, live-line working and equipment manufacture recent years in China; the design parameters and construction of UHV AC, UHV DC test and demonstration transmission lines, UHV AC, DC test bases and state grid simulation center were introduced. The suggestions at the aspects of UHV transmission future design, construction, commercial operation and maintenance were simply presented and discussed. The review and discussion are important for the safe and reliable operation of UHV grid in China and can be a reference for other countries that want to develop UHV AC and DC transmission.

Model-predictive current control (MPCC) is widely recognized as a high-performance control strategy of permanent magnet synchronous machine (PMSM) drives due to its quick response and simple principle. It uses a cost function to select the best voltage vector minimizing the current error between the reference value and the feedback value. However, as only one voltage vector is applied during one control period, it fails to give satisfactory performance due to the limited voltage vectors, especially in the case of two-level converters. This paper proposes an improved MPCC strategy for PMSM drives, which first estimates the back electromotive force (EMF) based on the past value of stator voltage and currents and then applies the estimated EMF in the stator current prediction. To achieve steady-state performance improvement, a null vector along with the active vector obtained from conventional MPCC is applied during one control period. Two methods are proposed to achieve optimal vector selection and vector duration. The first one requires six predictions and the calculation of current differentiation, while the second one only requires one prediction to obtain the best voltage vector and its optimal duty can be obtained in a very efficient way. The proposed methods are comparatively studied and compared to conventional MPCC and deadbeat control with space vector modulation. Both simulation and experimental results confirm the effectiveness of the proposed methods in achieving good steady-state performance while maintaining quick dynamic response.

Electric vehicles (EVs) as distributed storage devices have the potential to provide frequency regulation services due to the fast adjustment of charging/discharging power. In our previous research, decentralized vehicle-to-grid (V2G) control methods for EVs were proposed to participate in primary frequency control. In this paper, our attention is on bringing a large number of EVs into the centralized supplementary frequency regulation (SFR) of interconnected power systems. An aggregator is the coordinator between EVs and the power system control center. The aggregator calculates the total frequency regulation capacity (FRC) and expected V2G (EV2G) power of EVs based on the data communicated between the aggregator and individual EVs or EV charging stations. With FRC and EV2G power, a V2G control strategy is proposed for the aggregator to dispatch regulation requirements to EVs and EV charging stations. In individual EV charging stations, the FRC is calculated on the basis of the V2G power at present time, and EV2G power is presented considering both frequency regulation and charging demands. Besides, V2G control strategies are developed to distribute regulation requirements to each EV. Simulations on an interconnected power grid based on a practical power grid in China have demonstrated the effectiveness of the proposed strategies.

Nowadays, electricity plays a vital role in national economic and social development. Accurate load forecasting can help power companies to secure electricity supply and scheduling and reduce wastes since electricity is difficult to store. In this paper, we propose a novel Deep Neural Network architecture for short term load forecasting. We integrate multiple types of input features by using appropriate neural network components to process each of them. We use Convolutional Neural Network components to extract rich features from historical load sequence and use Recurrent Components to model the implicit dynamics. In addition, we use Dense layers to transform other types of features. Experimental results on a large data set containing hourly loads of a North China city show the superiority of our method. Moreover, the proposed method is quite flexible and can be applied to other time series prediction tasks.

Edge computing provides a promising paradigm to support the implementation of Industrial Internet of Things (IIoT) by offloading computational-intensive tasks from resource-limited machine-type devices (MTDs) to powerful edge servers. However, the performance gain of edge computing may be severely compromised due to limited spectrum resources, capacity-constrained batteries, and context unawareness. In this article, we consider the optimization of channel selection that is critical for efficient and reliable task delivery. We aim at maximizing the long-term throughput subject to long-term constraints of energy budget and service reliability. We propose a learning-based channel selection framework with service reliability awareness, energy awareness, backlog awareness, and conflict awareness, by leveraging the combined power of machine learning, Lyapunov optimization, and matching theory. We provide rigorous theoretical analysis, and prove that the proposed framework can achieve guaranteed performance with a bounded deviation from the optimal performance with global state information (GSI) based on only local and causal information. Finally, simulations are conducted under both single-MTD and multi-MTD scenarios to verify the effectiveness and reliability of the proposed framework.