光热电站容量效益评估及影响因素研究

光热发电作为一种清洁能源,配置储热后具有良好的调节性能,近年得到大力发展。依据自身经济性,光热电站往往配备较大的储热装置,能够平移所吸收的光热能,且具有跨日调节能力,使得光热机组有一定替代常规机组带负荷的能力,即容量效益。本文提出一种基于等可靠性的光热电站容量效益评估方法,考虑了调峰方式、储热时长、新能源规模、光热电站规模对光热电站容量效益发挥的影响,采用基于数学优化的生产模拟仿真程序,以周为尺度,计算全年8760 h的系统运行状态,计及了机组启停、水电跨日调节、抽蓄跨日调节、光热电站的跨日调节等因素。最后通过对西北地区实际电网的仿真,验证了所提方法的有效性。     

能源高质量发展下中国电力供需格局演变趋势

为应对气候变化,世界各国都在加快能源转型,习近平总书记提出了“四个革命、一个合作”能源安全新战略和“碳达峰、碳中和”愿景,要求全力推动能源高质量发展,这将对中国电力供需格局产生深远影响。首先,提炼能源高质量发展的内涵、特征;其次,从消费侧、供给侧、技术、体制等角度研判能源高质量发展下电力行业的转型发展方向;最后,通过构建多区域“能源-经济-电力”分析预测模型体系,从电力需求、电力供应、跨区电力流、电力系统形态、电力市场交易等方面研究中国中长期电力供需格局的演变特征。     

采用Prenflo气化技术的IGCC流程

Prenflo气化属于粉煤气化技术 ,与Shell的粉煤气化技术相似 ,同属气流床气化工艺 ;整体煤气化燃气 蒸汽联合循环(IGCC)是先进的洁净煤技术 ,具有广阔的应用前景。介绍了IGCC技术的起源、进展、特色 ,重点介绍采用Prenflo煤气化工艺的IGCC流程。     

Time series forecasting by neural networks: A knee point-based multiobjective evolutionary algorithm approach

In this paper, we investigate the problem of time series forecasting using single hidden layer feedforward neural networks (SLFNs), which is optimized via multiobjective evolutionary algorithms. By utilizing the adaptive differential evolution (JADE) and the knee point strategy, a nondominated sorting adaptive differential evolution (NSJADE) and its improved version knee point-based NSJADE (KP-NSJADE) are developed for optimizing SLFNs. JADE aiming at refining the search area is introduced in nondominated sorting genetic algorithm II (NSGA-II). The presented NSJADE shows superiority on multimodal problems when compared with NSGA-II. Then NSJADE is applied to train SLFNs for time series forecasting. It is revealed that individuals with better forecasting performance in the whole population gather around the knee point. Therefore, KP-NSJADE is proposed to explore the neighborhood of the knee point in the objective space. And the simulation results of eight popular time series databases illustrate the effectiveness of our proposed algorithm in comparison with several popular algorithms.     

用GRF PP—30制备汽车分电器盖

采用玻纤增强阻燃聚丙烯ＧＲＦＰＰ－３０制备汽车分电器盖，并与已往ＰＢＴＰ、酚醛塑料制备的分电器盖性能、价格等进行了比较。     

A RANDOM PARAMETER PROCESS FOR MODELING AND FORECASTING TIME SERIES

Abstract. A generalized autoregressive (GAR) process {Z ( t ) ; t = 0 , ±1, …} is defined to satisfy the recurrence relation Z(t) = A_θ (t)Z (t -l)+ u( t ), where {A_θ(t); t = 0,±1, …} is itself a stochastic process depending on a vector parameter θ and where {u( t ); t = 0, ±1, …} is white noise with Eu ² ( t ) = a ². This paper develops theory and methodology and implementing the class of GAR processes for time series modeling and forecasting. Conditions on the 'parameter process' { A _θ ( t ); t = 0, ±1, …} are obtained for the existence of a GAR process; necessary and sufficient conditions on { A_θ ( t ) ; t = 0, ±1, …} for existence of a stationary GAR process are also obtained. Procedures are developed for computing maximum likelihood estimates of the parameters 0 and u² and for computing the minimum mean squared error forecasts for GAR processes.     

用DCS顺控实现电除尘自动控制

介绍一种对电除尘工序进行远程自动控制的方法。使用DCS顺序控制图，通过模块组态和内部编程，实现多台设备的自动控制，优化工艺过程，提高该工序的自动化水平。     

模拟在财务预测、决策中的应用

阐述了模拟在财务预算、决策中的应用及其优越性，结合模拟软件进行了案例分析。     

嵌入式技术在电力系统中的应用

重点指出操作系统的突出优势和嵌入式实时数据库在电力系统应用中的重要作用,接着引出嵌入式技术在电力系统电力监控、抗EMC、电费计量、自动化系统和装置中的应用,最后展望嵌入式技术的发展前景.     

无先验地图条件下电力管廊无人机自主巡检方法研究

针对无先验地图条件下电力管廊无人机自主巡检能力不足的问题,本文提出了一种不依赖先验地图的无人机巡检方法。首先,无人机搭载激光雷达,通过SLAM（Simultaneous Localization and Mapping）算法进行实时场景构图,并基于RRT（Rapidly-exploring Random Tree）算法对构建的全局栅格地图进行边界搜索;其次,针对传统RRT算法难以判断环境地图完整性、保障巡检全面性的问题,提出了一种基于数字图像处理的边界检测方法。通过Canny算子对实时构建的地图进行边缘检测,并对地图进行完整性评估。最后,为验证本文提出方法的有效性,在江苏无锡处某220kV电力管廊的仿真模型中进行验证,分别采用RRT算法和本文改进算法进行自主巡检测试,结果表明本文提出的算法相比RRT算法可提升21.8%的巡检覆盖率。