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In this work, using Neutron star Interior Composition Explorer and Insight-Hard X-ray Modulation Telescope observations, we present a study of the broad-band spectral and timing evolution of the source throughout the first reflare, which occurred about 4-month after the major outburst. Our findings suggest that during the reflare, below a critical luminosity Lcrit ∼ 2.5 × 1036 (D/2.2 kpc)2 erg s−1, the scale of the corona shrinks in the radial direction, whereas the inner radius of the disc does not change considerably; however, the inner radius of the disc starts to move inward when the source exceeds the critical luminosity. We conclude that at low luminosity the increase in accretion rate only heats up the inner zone of the accretion disc without the transfer of angular momentum which occurs above a certain luminosity.

We analyze three observations of GRS 1915+105 in 2017 by Insight–Hard X-ray Modulation Telescope when the source was in a spectrally soft state. We find strong absorption lines from highly ionized iron, which are due to absorption by disk wind outflowing at a velocity of ∼1000 km s−1 along our line of sight. Two of the three observations show large amplitude oscillation in their light curves and the variation pattern corresponds to state κ of GRS 1915+105. From time-averaged and flux-resolved analysis, we find that the variation in the ionization state of the disk wind follows the X-ray continuum on timescales from hundreds of seconds to months. The radial location of the disk wind is consistent with thermal driving. The mass-loss rate due to the outflowing wind is comparable to the mass accretion rate in the inner disk, which demonstrates the important role of the disk wind in the disk accretion system.

Type-C quasi-periodic oscillations (QPOs) in black hole X-ray transients can appear when the source is in the low-hard and hard-intermediate states. The spectral-timing evolution of the type-C QPO in MAXI J1535-571 has been recently studied with Insight-HXMT. Here we fit simultaneously the time-averaged energy spectrum, using a relativistic reflection model, and the fractional rms and phase-lag spectra of the type-C QPOs, using a recently developed time-dependent Comptonization model when the source was in the intermediate state. We show, for the first time, that the time-dependent Comptonization model can successfully explain the X-ray data up to 100 keV. We find that in the hard-intermediate state the frequency of the type-C QPO decreases from 2.6 Hz to 2.1 Hz, then increases to 3.3 Hz, and finally increases to ~ 9 Hz. Simultaneously with this, the evolution of corona size and the feedback fraction (the fraction of photons up-scattered in the corona that return to the disc) indicates the change of the morphology of the corona. Comparing with contemporaneous radio observations, this evolution suggests a possible connection between the corona and the jet when the system is in the hard-intermediate state and about to transit into the soft-intermediate state., 11 pages, 6 figures, accepted for publication in MNRAS

The low mass X-ray binary GX 339-4 went into a new outburst in 2021. At the end of the hard to soft transition of this outburst, Insight-HXMT found that the source rapidly alternated between low flux and high flux states on a timescale of hours. Two high flux states lasted only for a period comparable to the orbital period of the observatory. Time-resolved spectral analysis shows that the sudden changes of flux are confined in the hard X-ray band (>4 keV). The variable non-thermal emission, including the power-law continuum from the corona and the reflected emission from the inner accretion disk, is responsible for the observed variability. The strength of disk thermal emission and the inner radius of the accretion disk are consistent between the two flux states. Assuming the lamppost geometry, our best-fit disk reflection models suggest a very low corona height (within 3 $R_{\rm g}$) and there is no evidence of significant variation in the corona geometry either. The observed rapidly alternating flux states suggest that the intrinsic power of the corona must change during the state transition. We discuss possible mechanisms for the observed sudden changes in the coronal power of GX 339-4., 10 pages, 7 figures. v2: refereed version

We studied the millihertz quasi-periodic oscillation (mHz QPO) in the 2020 outburst of the Be/X-ray binary 1A 0535+262 using Insight-HXMT data over a broad energy band. The mHz QPO is detected in the 27-120 keV energy band. The QPO centroid frequency is correlated with the source flux, and evolves in the 35-95 mHz range during the outburst. The QPO is most significant in the 50-65 keV band, with a significance of ~ 8 sigma, but is hardly detectable (120 keV) energy bands. Notably, the detection of mHz QPO above 80 keV is the highest energy at which mHz QPOs have been detected so far. The fractional rms of the mHz QPO first increases and then decreases with energy, reaching the maximum amplitude at 50-65 keV. In addition, at the peak of the outburst, the mHz QPO shows a double-peak structure, with the difference between the two peaks being constant at ~0.02 Hz, twice the spin frequency of the neutron star in this system. We discuss different scenarios explaining the generation of the mHz QPO, including the beat frequency model, the Keplerian frequency model, the model of two jets in opposite directions, and the precession of the neutron star, but find that none of them can explain the origin of the QPO well. We conclude that the variability of non-thermal radiation may account for the mHz QPO, but further theoretical studies are needed to reveal the physical mechanism., 13 pages, 7 figures. Accepted for publication in MNRAS

Here we report the spectral-timing results of the black hole X-ray binary 4U 1630–47 during its 2021 outburst using observations from the Hard X-ray Modulation Telescope (Insight-HXMT). Type C quasi-periodic oscillations (QPOs) in ∼1.6–4.2 Hz and quasi-regular modulation (QRM) near 60 mHz are detected during the outburst. The mHz QRM has a fractional rms of ∼10%–16% in the 8–35 keV energy band with a Q factor (frequency/width) of ∼2–4. Benefiting from the broad energy band of Insight-HXMT, we study the energy dependence of the ∼60 mHz QRM in 1–100 keV for the first time. We find that the fractional rms of the mHz QRM increases with photon energy, while the time lags of the mHz QRM are soft and decrease with photon energy. Fast recurrence of the mHz QRM, in a timescale of less than 1 hr, has been observed during the outburst. During this period, the corresponding energy spectra moderately change when the source transitions from the QRM state to the non-QRM state. The QRM phenomenon also shows a dependence with the accretion rate. We suggest that the QRM could be caused by an unknown accretion instability aroused from the corona.

Acquisition granularity and acquisition span are two important indexes to analyze the active power of renewable energy power stations, and it is important for the analysis of the intermittent energy output power to determine the acquisition granularity of the data. An acquisition granularity calibration method of the photovoltaic output power based on data mining technology is proposed in this paper. The sensitivity changing characteristics of the time series and the sum of the output power are respectively extracted by the multi-scale descriptive statistical analysis and interpolation method. A “power trapezoidal continuous changing state” method is proposed to establish a multi-objective optimization model for the acquisition granularity calibration of the photovoltaic output power. Genetic algorithm (GA) and Particle swarm optimization (PSO) algorithm are respectively used to solve the model and determine the optimal acquisition granularity of the photovoltaic output power. The sensitivity of the acquisition granularity of the data to the capacity of the energy storage system is analyzed, and the energy storage system with the optimal acquisition granularity can’t only effectively smooth the fluctuation of the photovoltaic output power but also keep the main information of the data. The simulation tests of the annual actual operation data at a photovoltaic power station with the installed capacity of 14 MW in China verify the validity of the model. The simulation results show when the acquisition granularity of the photovoltaic output power takes 45 s, it can satisfy the accuracy of the required data for the capacity configuration of the energy storage system. The method proposed in this paper provides a theoretical basis for the intermittent energy applications and has a certain engineering application prospects.

Summary The acquisition granularity (time feature quantity) and sampling span (spatial feature quantity) of the data are the feature factors to analyze the active power of renewable energy power stations. According to the time and space characteristics of photovoltaic (PV) power stations, the acquisition granularity and sampling span calibration methods of PV output power based on data mining technology are proposed this paper. The initial range of the acquisition granularity is determined by analyzing the maximum-order difference components of the PV output power. Through deeply mining the continuous change state of the PV output power, an acquisition granularity calibration method of the PV output power based on the multiobjective optimization model is proposed from time characteristics. The particle swarm optimization algorithm is used to solve the model to obtain the optimal the acquisition granularity of the PV power station. Through the analysis of the sample information entropy change trend of the PV output power, a sampling span calibration method of the PV output power based on the information entropy theory is proposed from space characteristics. The sensitivity analysis of the acquisition granularity and sampling span of the data to the capacity of energy storage systems is realized by the smooth control of the PV output power using first-order low filters. The simulation tests of the annual history operating data at a PV power station with the installed capacity of 40 MW in China verify the validity of the provided methods. The simulation results show when the acquisition granularity takes 60 seconds and the sampling span takes 33 days, it can satisfy the accuracy of the required data of energy storage systems to realize the smooth control of the PV output power.

Key management is the key to ensuring the information security of the intelligent distribution network. Based on the analysis of the communication characteristics and key management requirements of the intelligent distribution network, this paper proposes a lightweight intelligent distribution network key management scheme DNKMS. According to the storage and computing capabilities of power distribution terminals, electronic distribution stations and power distribution master stations, task distribution is optimized, and the design idea of the scheme and the process of key generation, distribution, update, and destruction are described in detail. The analysis results show that the proposed scheme has less time overhead and higher efficiency, can reduce the communication and calculation load required in key management, and meet the security requirements of key management in smart distribution networks.

The development of Power Internet of Things has brought a variety of access requirements for massive collecting terminals. Based on the characteristics of security attributes of Power Internet of Things, this paper proposes a secure access protocol based on symmetric cryptographic algorithm for the large number of collecting terminals with limited manufacturing cost, computing power and storage resources. This protocol only uses the symmetric cryptographic algorithm which has the fast computing speed and low resource consumption, and the protocol can realize two-way identity authentication between the collecting terminal and master station. At the same time, combined with the historical access mechanism, it improves the access efficiency of the collecting terminals, and realizes the safe and fast access of the collecting terminal. Finally, compared with other protocols, the proposed protocol is also effective in security and performance.

In this paper, the H65∞65 optimal control for a class of continuous-time nonlinear systems is investigated using event-triggered method. First, the H65∞65 optimal control problem is formulated a

A study of the acoustic characteristics of the Zeng Hou Yi chime bells from the fifth century BC during the Chinese Bronze Age.