基于长短期记忆网络的新能源电网电量分时计度方法

针对新能源接入电量不稳定,电量分时计度的负荷曲线优化效果较差的问题,设计一种基于长短期记忆网络的新能源电网电量分时计度方法。设计新能源电网的短期电力负荷预测模型,实施短期电力负荷预测。结合接入新能源的特征与用户需求,利用模糊隶属度函数计算新能源接入下负荷曲线上的谷时段隶属度、峰时段隶属度,通过聚类分析的方式归类峰谷时段。基于长短期记忆网络探索新能源电网电量分时计度中的目标函数、约束条件,构建新能源电网电量分时计度模型,实现新能源电网的电量分时计度。在某地区新能源电网测试设计方法的性能,测试结果表明,该方法在较大需求价格弹性、较小单时段响应系数下能够实现更好的负荷曲线优化效果。

利用感应型电度表实现分时计度电能的方法

采用分时计度电能是一种节能技术,复费率电度表是一种能对高峰负荷和低谷负荷所消耗的电能分别计量的电度表,本文介绍的分时计度表,是将带微处理器的分时脉冲计度表与原感应系电度表联机而成。本文介绍了这种分时计度表的原理、结构、线路和技术指标。

用带钟计算器制作的分时计度电度表

本文介绍了用两只带钟袖珍电子计算器制作的分时计度电度表,它可用作高峰、低谷电量计数,促使用户重视低谷用电,改善电网负荷,利于调荷节电,并讨论了制作条件、工作原理及注意事项等。

一种可实现分时计度电能的方法

分时计度电能是一种节能技术。复费率电度表是一种能对高峰负荷和低谷负荷所消耗的电能分别计量的电度表。本文介绍的分时计度表,是将带微处理器的分时脉冲计度表与原感应系电度表联机而成,文中介绍了这种计度表的原理、结构、线路和技术指标等。

Scheduling optimization problem considering time-of-use tariffs and piece-rate machine maintenance in EAF steelmaking

An operating schedule of the parallel electric arc furnaces(EAFs)considering both productivity and energy related criteria is investigated.A mathematical model is established to minimize the total completion time and the total electricity cost.This problem is proved to be an NP-hard problem,and an effective solution algorithm,longest processing time-genetic(LPT-gene)algorithm,is proposed.The impacts of varied processing energy consumption and electricity price on the optimal schedules are analyzed.The integrated influence of the different weight values and the variation between the peak price and the trough price on the optimal solution is studied.Computational experiments illustrate that considering the energy consumption costs in production has little influence on makespan;the computational performance of the proposed longest processing time-genetic algorithm is better than the genetic algorithm(GA)in the issue to be studied;considerable reductions in the energy consumption costs can be achieved by avoiding producing during high-energy price periods and reducing the machining energy consumption difference.The results can be a guidance for managers to improve productivity and to save energy costs under the time-of-use tariffs.

Novel Distributed Fiber Bragg Grating Sensing System Based on M-Z Interferometer

One of the problems in using grating sensors is how to measure a small Bragg wavelength shift accurately. Nowadays demodulation techniques are mainly based on the edge filter, tunable filter, or interferometric scanning methods. Interferometric demodulation is widely accepted as the technology which can provide the high sensitivity. An interrogation system using the interferometric scanning method is presented, in which an unbalanced fiber M-Z interferometer is used as the wavelength scanner for temperature measurement. A novel fiber Bragg grating sensor system based on M-Z interferometric demodulation technique is presented in this paper. The temperature sensitivity measured in the experiment is almost consistent with that obtained from the theoretic calculation.

Modeling a magneto-rheological soft starter for use with belt conveyors

The theory of magnetic circuit design, the constitutive equations of a magneto-theological fluid, and the load properties of belt conveyors were used to design a magneto-rheological soft starter test-bed. The magnetic field distribution in the working gap was analyzed and the current-speed relationship was investigated. A mathematical model for the time response was deduced. The results show that a linear relationship between current and magnetic field is seen when the magnetic materials are not saturated and the magnetic field is uniform in the working section. The rotation speed of the driven shaft changes linearly with increasing time. The response is rapid and can be as short as milliseconds. This meets the starting requirements of belt conveyors.

Signal Separation and Instantaneous Frequency Estimation Based on Multi-scale Chirplet Sparse Signal Decomposition

An approach based on multi-scale ehirplet sparse signal decomposition is proposed to separate the malti-component polynomial phase signals, and estimate their instantaneous frequencies. In this paper, we have generated a family of multi-scale chirplet functions which provide good local correlations of chirps over shorter time interval. At every decomposition stage, we build the so-called family of chirplets and our idea is to use a structured algorithm which exploits information in the family to chain chirplets together adaptively as to form the polyncmial phase signal component whose correlation with the current residue signal is largest. Simultaueously, the polynomial instantaneous frequency is estimated by connecting the linear frequency of the chirplet functions adopted in the current separation. Simulation experiment demonstrated that this method can separate the camponents of the multi-component polynamial phase signals effectively even in the low signal-to-noise ratio condition, and estimate its instantaneous frequency accurately.

Influence of solar wind dynamic pressure on geomagnetic Dst index during various magnetic storms

The Dst index,designed as a proxy of ring current intensity,is known to be also affected by other magnetospheric current systems,e.g.magnetopause current.The pressure-corrected Dst index is obtained by removing the effects of the solar wind dynamic pressure and the quiet time ring current.However,all previous studies treated the correction coefficient as an averaged parameter for storms of different intensity.In this paper,based on the Burton's equations and employing two independent methods,we will show a positive correlation between pressure-correction coefficient b and the intensity of the storms.We divided our storm database(872 storms in total) into three categories according to the intensity of storms.In order to improve the accuracy of calculating,we also used the higher-resolution SYM-H index data instead of Dst index to compute the corrected Dst index during different storms.Furthermore,we are able to provide corrected magnetic storm index with high-time resolution(-1 min).

Dense gas-particle flow in vertical channel by multi-lattice trajectory model

A multi-lattice deterministic trajectory(MLDT) model is developed to simulate dense gas-particle flow in a vertical channel.The actual inter-particle collision and particle motion are treated by a Lagrangian model with three sets of lattices to reduce computational time.Cluster formation and motion near the wall are successfully predicted with mean particle volume fraction and velocity,showing quantitatively agreement with experimental results.The mechanism of particles concentrated near the wall is investigated by considering effects of gravity,particle-wall collisions,inter-particle collisions and velocity profiles of the gas phase.It is shown that the inter-particle collision and gas-phase velocity distribution are the essential factors for cluster formation near the wall,while gravity and particle-wall collision only have minor effects on particle concentration near the wall.Particles are unable to remain in the high velocity region due to the strong inter-particle collisions,while they tend to stay in the low velocity region for weak inter-particle collisions.In addition,the effects of channel width and particle sizes on cluster formation are also investigated and it is found that particle concentration near the wall reduces with the decrease of channel width and increase of particle size.