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The current monitoring of bundle conductors is essential for precisely locating operation failures in transmission lines, leading to a more stable and reliable power grid. This paper proposed a novel method for current reconstruction of bundle conductors, utilizing tunneling magnetoresistive (TMR) sensors. Both the normal and abnormal situations are discussed. The optimal and sub-optimal measurement points for sensors were obtained for concise current measurement with only one uniaxial TMR sensor. The current in each bundle conductor was calculated separately based on the comprehensive algorithm. Validation experiment indicated the error of the measurement and calculation system was no more than 10%, proving the robustness and feasibility of the measurement system and the algorithm. The reconstruction process takes full advantages of TMR sensors and provides a promising solution for transmission line monitoring in power grid.

Applicability problems of the widely-used aggregation-based representation of DFIG wind farms focus on the modelling “error and impact” in transient stability computation. In order to identify crucial LVRT behaviors of DFIGs, specifically in system-level analysis, control strategies including vector-orientation, closed-loop rotor-current regulation, and Crowbar protection are given a full consideration. It is proved that, the DFIG works with its electrical and mechanical dynamics decoupled, and the result is that the DFIG behaves as an ideal controlled-power source. The DFIG's power-modulation functions defined by the grid code distinguish it from the conventional synchronous generator, which also conveniently offers dominant dynamics for studying errors of aggregation. Next, errors caused by the coupling between distribution factors and LVRT behaviors of wind farms (but ignored in aggregation) are discussed. With some existing grid codes, these factors not only generate a distributive profile of residual voltages along the feeders, but more importantly nonuniform power responses among individual wind turbines. Impacts of aggregation's errors on transient stability of power systems are analyzed. The trend in the error and impact of aggregation is analytically surveyed in a rudimentary system, and further numerically verified in a multi-machine system.

Abstract In solid fuel (such as lignite) chemical looping combustion, solid fuels undergo pyrolysis and gasification. The volatiles from pyrolysis and the gasification product (CO/H 2 ) react with oxygen carriers. The gas conversion (to CO 2 /H 2 O) in the fuel reactor is a key point. However, char particles of different sizes and conversion ratios cause segregation in the fuel reactor, which influences the contact time between fuel gases and the carrier, thereby changing the gas conversion behavior. In order to gain information on obtaining a high gas conversion in the fuel reactor, this work focused on the effect of the char particle segregation on gas conversion. Different factors – the char particle size, the fluidizing gas velocity, and the oxygen carrier reactivity – were taken into account. Smaller char particles with low density would float on top of the fluidized bed, corresponding to a low gas conversion ( U mf in the Fe63Al bed) can reduce the segregation effect, resulting in a higher CO conversion. High reactivity carriers can convert CO completely although segregation exists, whereas low reactivity carriers exhibit the segregation effect and thus corresponds to a low CO conversion.

Abstract With increasing prosumers employed with flexible resources, advanced demand-side management has become of great importance. To this end, integrating demand-side flexible resources into electricity markets is a significant trend for smart energy systems. The continuous double auction (CDA) market is viewed as a promising P2P (peer to peer) market mechanism to enable interactions among demand side prosumers and consumers in distribution grids. To achieve optimal operations and maximize profits, prosumers in the electricity market must act as price makers to simultaneously optimize their operations and trading strategies. However, the CDA-based market is difficult to model explicitly because of its information-based clearing mechanism and the stochastic bidding behaviors of its participants. To facilitate prosumers actively participating in the CDA market, this paper proposes a novel prediction-integration strategy optimization (PISO) model. A surrogate market prediction model based on Extreme Learning Machine (ELM) is developed, which learns the interaction relationship between prosumer bidding actions and market responses from historical transaction data. Moreover, the prediction model can be conveniently transformed and integrated into the prosumer operation optimization model in the form of constraints. Therefore, prosumer operations and market trading strategies can be jointly optimized through the proposed approach, facilitating the integration of flexible resources into electricity markets. Numerical studies demonstrate the effectiveness of the proposed model by comparing with existing CDA trading strategies under various market conditions.

Abstract China has the advantage of learning from the mistakes made by nations that have developed their nuclear power energy system in the last century. Such mistakes encompass the lack of sustainable development of the nuclear energy and poor planning in the back-end of the nuclear fuel cycle. The present paper studies the evolution of a double strata cycle with fast reactor gradually replacing the LWR. It starts from 2035 and covers the historical development of nuclear energy in China to the year 2100. The paper studies the ADS impact on the NFC and estimates the number and the deploying schedule of the ADS reactors to limit the accumulation of minor actinides. The other aspects considered here are natural uranium resources, fuel utilization efficiency, proliferation and diversion risks, spent fuel production and overall materials flow. Additionally, perturbation calculations were performed to evaluate the impact of the uncertainty on key parameters. The results are discussed in view of the Chinese nuclear fuel cycle plan and their policy implications are thoroughly evaluated.

High voltage direct current (HVDC) technology is the ideal solution for long distance bulk power transmission. However, different from AC systems, differential protection of HVDC lines still faces a lot of challenges. We claim that from the perspective of state estimation, the essence of differential protection is to estimate state variables using measured data, of which the validity indicates whether there is a fault. Therefore, the performance of the differential protection is highly related to the model accuracy. Using a detailed distributed parameter line model, this paper developed a novel differential protection method for HVDC lines based on traveling waves with high reliability. The optimal differential point is also discussed to enhance protection rapidity. Experiments demonstrate that the proposed protection could soon detect internal faults with high fault resistance while maintaining reliability when external faults occur.

Given the increased percentage of wind power in power systems, chance-constrained optimal power flow (CC-OPF) calculation, as a means to take wind power uncertainty into account with a guaranteed security level, is being promoted. Compared to the local CC-OPF within a regional grid, the global CC-OPF of a multi-regional interconnected grid is able to coordinate across different regions and therefore improve the economic efficiency when integrating high percentage of wind power generation. In this global problem, however, multiple regional independent system operators (ISOs) participate in the decision-making process, raising the need for distributed but coordinated approaches. Most notably, due to regulation restrictions, commercial interest, and data security, regional ISOs may refuse to share confidential information with others, including generation cost, load data, system topologies, and line parameters. But this information is needed to build and solve the global CC-OPF spanning multiple areas. To tackle these issues, this paper proposes a distributed CC-OPF method with confidentiality preservation, which enables regional ISOs to determine the optimal dispatchable generations within their regions without disclosing confidential data. This method does not require parameter tunings and will not suffer from convergence challenges. Results from IEEE test cases show that this method is highly accurate.

Abstract In the study, a three-dimensional CFD simulating model coupling with reasonable turbulent model and reduced chemical kinetic mechanism was established and validated. The auto-ignition development and knocking characteristics of a downsized spark-ignition (SI) gasoline rotary engine (RE) under different boosted conditions were numerically investigated. Results showed that as inlet pressure increased from 1.12 bar to 1.16 bar, the knocking intensity (KI) of the RE was enhanced gradually, and the knocking onset was advanced. However, with the further augment of inlet pressure, the KI did not further increase due to the larger heat dissipation loss caused by high turbulent kinetic energy in the long and narrow combustion chamber of the RE. This indicated that the structure of the downsized SI RE had a certain ability of knocking suppression when inlet pressure was sufficiently boosted. The KI of the RE was more serious in the trailing part of the combustion chamber as compared to other positions due to the unidirectional flow field, especially on both sides near the end cover in the trailing part of the combustion chamber. Therefore, it was concluded that strengthening the cooling of both sides near the end cover in the trailing part of the combustion chamber may be an effective way to reduce the KI of a downsized boosted SI RE. In addition, the KI is closely related to auto-ignition development processes, e.g. end-gas auto-ignition modes. Under the mass fraction of unburned mixtures at the moment of end-gas auto-ignition, the local KI caused directly by single hot-spot auto-ignition was higher than that caused by multiple hot-spots auto-ignitions, and the local KI caused by homogeneous auto-ignition was higher than that caused by multiple hot-spots auto-ignitions.