基于电锅炉的火电机组灵活性改造技术研究

为有效解决东北电力产能过剩,促进风电、核电等清洁能源消纳问题,提升燃煤供热机组的灵活性,针对东北地区某热电厂,通过对热电解耦时间、电锅炉型式以及不同电锅炉容量配置对机组实际发电负荷的影响等灵活性改造关键技术进行研究,确定了最佳电锅炉容量,提出了电锅炉装设方案,并对改造前后机组的调峰能力和性能指标进行对比分析。研究表明:随着电锅炉容量增长,抵减电锅炉用电后机组实际发电负荷率显著降低,提升火电机组灵活性改造后,电厂调峰能力显著提升,考虑以全厂172 MW发电负荷运行,电厂调峰能力在采暖初末期增加了368 MW,采暖中期增加了528 MW;全厂供热标煤耗由39.7 kg/GJ降低至34.3 kg/GJ,降低了5.4 kg/GJ;经济效益显著,扣除电锅炉用电成本后1个采暖季的调峰辅助服务补贴收益为1.47亿元;同时,电锅炉投运后可实现电厂的上网电量接近零,为清洁能源就地消纳做出贡献。     

基于流数据聚类算法的电力大数据异常检测

针对电力大数据流的异常检测问题,该文将流数据聚类算法与电力大数据相结合,针对现有流数据聚类算法不易存储全部数据、断电数据易丢失等问题,以及流数据聚类算法对于离线阶段聚类算法实时应答的要求,从数据的完整性、安全性以及流数据聚类算法的低时间复杂度的角度出发,对CluStream流数据聚类算法进行改进,提出流式K-means聚类算法。对在线阶段,使用Redis集群进行流数据的缓冲,并设计节点时间衰减策略,增大心跳消息中有效消息所占比例;对离线阶段聚类算法进行优化,使用最佳距离法确定初始聚类中心,减少迭代次数;最后,使用所提出的流式K-means聚类算法进行用户用电异常行为检测,实验结果表明,该算法能够很好的发现用户用电异常行为。     

Potential of performance improvement of concentrated solar power plants by optimizing the parabolic trough receiver

This paper proposes a comprehensive thermodynamic and economic model to predict and compare the performance of concentrated solar power plants with traditional and novel receivers with different configurations involving operating temperatures and locations. The simulation results reveal that power plants with novel receivers exhibit a superior thermodynamic and economic performance compared with traditional receivers. The annual electricity productions of power plants with novel receivers in Phoenix, Sevilla, and Tuotuohe are 8.5%, 10.5%, and 14.4% higher than those with traditional receivers at the outlet temperature of 550°C. The levelized cost of electricity of power plants with double-selective-coated receivers can be decreased by 6.9%, 8.5%, and 11.6%. In Phoenix, the optimal operating temperature of the power plants is improved from 500°C to 560°C by employing a novel receiver. Furthermore, the sensitivity analysis of the receiver heat loss, solar absorption, and freeze protection temperature is also conducted to analyze the general rule of influence of the receiver performance on power plants performance. Solar absorption has a positive contribution to annual electricity productions, whereas heat loss and freeze protection temperature have a negative effect on electricity outputs. The results indicate that the novel receiver coupled with low melting temperature molten salt is the best configuration for improving the overall performance of the power plants.     

分散式风电多点接入协调优化控制策略

针对分散式风电机组并网导致的配电网网损增加、电压稳定性降低等问题,文章提出一种分散式风电并网多点协调双层控制策略。首先,分析了分散式风电多点接入特性,研究分散式风电多点接入后的网损、电压分布和功率因数的关系,并提出最小网损和电压偏差为目标的双层优化控制策略。最后,基于IEEE-33节点进行仿真计算,结果表明,所提多点协调控制策略能够有效降低配电网网损和提升母线电压水平,增加系统的稳定性。与超前功率因数相比,滞后的功率因数能够增大风能消纳能力,提高供电可靠性,减少电压偏移水平。     

基于降噪时序深度学习网络的风电功率短期预测方法

利用风电场历史功率数据预测未来一段时间内的风功率,对保障电网安全稳定运行具有重要的意义。本文提出一种基于奇异谱分析SSA(singular spectrum analysis)和长短时记忆LSTM(long-short term memory net⁃work)网络的时序特征预测框架用于短期风功率的预测。首先通过SSA对历史风功率原始数据进行降噪处理,然后经过数据转换之后,以LSTM网络为基础进行预测模型的训练,最后通过某风电场提供的两个风机的历史功率数据进行验证。实验结果表明,奇异谱分析对风电场的历史数据具有良好的降噪性,SSA+LSTM模型在测试数据上取得了较好的预测性能,能够有效进行短期风功率的预测。     

计及风险规避的电力零售商平衡市场交易模型

由于新能源出力以及终端负荷需求的不确定性,电力零售商在日前市场的竞标电量与实时市场的购买电量之间存在不平衡而产生惩罚成本风险。引入用户侧可控负荷作为平衡资源参与市场交易,提出了一种风险规避程度指标,以此来度量交易前后电量偏差程度,以信息熵度量残差序列离散程度计算风险规避程度指标。以电力零售商运行收益、用户需求响应满意度以及风险规避程度最大为目标建立多目标风险规避模型,采用自适应权重粒子群算法进行模型求解。通过算例表明,所提出的模型从电网-电力零售商-用户多个角度去考虑电力零售商参与平衡市场交易策略,能够有效提高电力零售商的运行效益以及用户满意度,同时可以提高电力市场管理的可靠性与安全性。     

Novel CPG algorithm for tracking fast sudden changes based on tangent rule

ABSTRACT

This paper proposes a novel tracking method to deal with fast changes of solar irradiation and power limit change in order to increase tracking efficiency. This goal is achieved by estimating (i) next operating mode and (ii) next step point with the use of tangent rule in triangle. After every fast response to sudden changes, accurate response phase starts in order to track desired power in each operating mode by adaptive step size. Drift problem in defining next operating mode is eliminated in proposed method by estimating next operating mode, and settling time is decreased to about 25 percent of settling time of other methods by estimating next step point. Simulation and experimental results show the performance of proposed method.     

Computer‐aided design methodology for linearity enhancement of multiwatt GaN HEMT amplifiers using multiple parallel devices

This article presents a design methodology for linearizing GaN HEMT amplifiers based on splitting a large FET into multiple parallel FETs with same total gate periphery and by biasing them individually. By varying the biases, the magnitude and the phase of the IMD3 components at the output of FET changes. A detailed simulation methodology using commercial microwave CAD software is presented. Simulation results show that by biasing one device in Class AB and other(s) in deep Class AB mode, IMD3 components of parallel FETs can be made out of phase to each other leading to cancellation and improvement in linearity. Three prototype circuits were simulated using (a) a single 5 mm FET (1 × 5 mm), (b) two parallel 2.5 mm FETs (2 × 2.5 mm), and (c) four parallel 1.25 mm FETs (4 × 1.25 mm), for a total gate periphery of 5 mm, over the frequency range of 0.8 to 1.0 GHz. IMD3 improvement up to 20 dBc was achieved with the 4 × 1.25 mm circuit when the FET biases were optimized. Measurement results show improvement in linearity up to 20 dBc for 4 × 1.25 mm circuit. The proposed method improves linearity without a substantial penalty on the power consumption and is straightforward to implement.     

因素空间理论下基点分类算法研究

目前，基于因素空间理论的背景基提取算法计算过程复杂，初始化必须依赖各因素极值，基点数量提取冗余等原因，未能在应用中取得很好效果。为此，结合内点判别法和知识可继承、可扩展的思想，提出一种计算简单、初始化独立、基点数量小的改进的背景基提取算法。然后，利用改进的背景基提取算法构造出一种全新的数据分类算法-基点分类算法，基点分类算法以提取每一类样本的背景基为预测模型，再通过新定义的λ-背景基，优化预测模型。数值实验表明:基点分类算法原理简单、构造难度小、分类模型泛化能力强，预测能力准确率高，同时严格的模型限定区域又能为识别新类别提供新方法。     

Inhibition of the FGF/FGFR System Induces Apoptosis in Lung Cancer Cells via c-Myc Downregulation and Oxidative Stress

Lung cancer represents an extremely diffused neoplastic disorder with different histological/molecular features. Among the different lung tumors, non-small-cell lung cancer (NSCLC) is the most represented histotype, characterized by various molecular markers, including the expression/overexpression of the fibroblast growth factor receptor-1 (FGFR1). Thus, FGF/FGFR blockade by tyrosine kinase inhibitors (TKi) or FGF-ligand inhibitors may represent a promising therapeutic approach in lung cancers. In this study we demonstrate the potential therapeutic benefit of targeting the FGF/FGFR system in FGF-dependent lung tumor cells using FGF trapping (NSC12) or TKi (erdafitinib) approaches. The results show that inhibition of FGF/FGFR by NSC12 or erdafitinib induces apoptosis in FGF-dependent human squamous cell carcinoma NCI-H1581 and NCI-H520 cells. Induction of oxidative stress is the main mechanism responsible for the therapeutic/pro-apoptotic effect exerted by both NSC12 and erdafitinib, with apoptosis being abolished by antioxidant treatments. Finally, reduction of c-Myc protein levels appears to strictly determine the onset of oxidative stress and the therapeutic response to FGF/FGFR inhibition, indicating c-Myc as a key downstream effector of FGF/FGFR signaling in FGF-dependent lung cancers.