微电网关键控制技术综述

为了提高微电网技术的发展,加强微电网控制技术的广泛应用。文中系统介绍了微电网的结构类型、综合监控系统、运行控制、分布式电源控制方法等关键技术和研究现状,重点对综合监控系统、运行控制、分布式电源控制方法技术特点进行了阐述。并展望了微电网的结构类型和能量管理系统的重要发展方向。     

基于抑制环流的自适应下垂控制改进策略

在孤岛模式下的微电网中由于线路阻抗存在差异,采用传统下垂控制的逆变器不仅无法精确分配负载功率,还会产生环流。为解决该问题,提出了一种基于抑制环流的自适应下垂控制改进策略。该策略采用旋转坐标的环流来构造虚拟阻抗,通过PI控制使线路等效阻抗不断相向趋近直至相等,从而均衡分配负载功率。所提出的改进策略无需实时检测线路阻抗,也无需借助通信网络。此外,构造的虚拟阻抗不仅能有效抑制环流,还不会引起输出电压大幅跌落。仿真结果验证了改进控制策略的有效性。     

蓬辣滩水电站船闸综合自动化系统的改造

介绍了蓬辣滩水电站原有船闸自动化系统的运行状况及存在问题,着重介绍了改造方案,解决了原有监控系统运行不正常、船只收费方式落后等问题,提高了现场的运行管理水平,也为其他船闸工程的自动化建设提供了有益的借鉴.     

智能配电网自愈控制技术

自愈是智能配电系统的重要特征。智能配电网自愈控制是解决中国配电网长期以来存在的设备利用率低、供电可靠性低、线损率高等关键问题的核心技术。首先介绍了智能配电网自愈控制的目标、技术方案与实施条件,在此基础上介绍了自愈控制研究与示范中的关键科学问题,包括智能配电网仿真、分析与试验,智能决策与网络重构,故障特性与保护,关键负荷保障等技术。最后,分析了智能配电网自愈控制技术研究与应用面临的问题与挑战。     

Optimising residential electric vehicle charging under renewable energy: Multi‐agent learning in software simulation and hardware‐in‐the‐loop evaluation

The integration of intermittent renewable energy sources coupled with the increasing demand of electric vehicles (EVs) poses new challenges to the electrical grid. To address this, many solutions based on demand response have been presented. These solutions are typically tested only in software‐based simulations. In this paper, we present the application in hardware‐in‐the‐loop (HIL) of a recently proposed algorithm for decentralised EV charging, prediction‐based multi‐agent reinforcement learning (P‐MARL), to the problem of optimal EV residential charging under intermittent wind power and variable household baseload demands. P‐MARL is an approach that can address EV charging objectives in a demand response aware manner, to avoid peak power usage while maximising the exploitation of renewable energy sources. We first train and test our algorithm in a residential neighbourhood scenario using GridLAB‐D, a software power network simulator. Once agents learn optimal behaviour for EV charging while avoiding peak power demand in the software simulator, we port our solution to HIL while emulating the same scenario, in order to decrease the effects of agent learning on power networks. Experimental results carried out in a laboratory microgrid show that our approach makes full use of the available wind power, and smooths grid demand while charging EVs for their next day's trip, achieving a peak‐to‐average ration of 1.67, down from 2.24 in the baseline case. We also provide an analysis of the additional demand response effects observed in HIL, such as voltage drops and transients, which can impact the grid and are not observable in the GridLAB‐D software simulation.     

Development of anion conducting zeolitic imidazolate framework bottle around ship incorporated with ionic liquids

Imidazolium based ionic liquids (denoted BMIM-ILs) with the altering anions (OH⁻, HCO₃⁻ and AcO⁻) as ionic carriers were synthesized and bottle around ship introduced into the cages of zeolite-type metal organic frameworks (ZIF-8) as porous host, resulting in a series of anion-containing composites (BMIM-ILs/ZIF-8) with anion conducting. Bottle around ship method could integrate with the superiorities of BMIM-ILs and ZIF-8 for more excelling conduction and quite eliminate IL leakage. Besides, the hybrid membranes combined BMIM-ILs/ZIF-8 as fillers with polymer blends consisting of polyvinylidene fluoride (PVDF) and polyvinylpyrrolidone (PVP) as matrix were assembled with varying weight percentages. The structures of the prepared composites and hybrid membranes were inspected. It should be noted that ZIF-8 encapsulating into BMIM-OH (6.8 × 10⁻⁴ S cm⁻¹) and BMIM-HCO₃ (1.08 × 10⁻³ S cm⁻¹) reveal two orders of magnitude increase in conductivity-values comparison to that of the parent framework (2.3× 10⁻⁵ S cm⁻¹) at 353 K and ∼98% relative humidity (RH). The hybrid membrane containing 30%BMIM-OH/ZIF-8 has the advantage in proton conductivity of 1.02 × 10⁻³ S cm⁻¹ at 353 K and ∼98% RH, which is 6.49 times higher than that of the ZIF-8/PVP/PVDF. The activation energies (E_a) of BMIM-OH/ZIF-8 and its hybrid membrane are calculated to be 0.15 eV and 0.23 eV, respectively. They could be regarded as a fast-ion conductor on the ground of high conduction and low activation energy, which make them bright outlooks and wonderful potential for electrochemical devices.     

融合多种相关性分析方法的行业电量需求预测

随着供给侧改革的深入推进,为满足电网发展的需要,需要对行业电量需求预测模型进行精细化改进。从行业电量增长因素入手,提出基于关联规则挖掘和主成分分析相结合的行业电量相关性分析方法,建立历史用电相关分析数据集,挖掘行业电量增长的主导因素;分别对传统ARIMA模型和多元回归模型进行改进,得到融合多种相关性分析方法的行业电量需求模型。最后利用某地区有色金属行业为例进行实证分析,结果表明改进后的模型较传统预测模型的预测精度有较大的提升。     

Comparative feasibility study of combined cycles for marine power system in a large container ship considering energy efficiency design index (EEDI)

This study investigates an appropriate combined cycle as the electric propulsion system in a large container ship. A gas turbine combined cycle and molten carbonate fuel cell-steam turbine cycle are considered; the gas turbine uses LNG or hythane fuels. Because it is difficult to choose an appropriate propulsion system from only one perspective, comprehensive and unbiased analyses refer to the system performance, eco-efficiency, and economic feasibility for three configurations. An LNG-fueled COGES (combined gas turbine and steam integrated electric drive system) seems to be a promising alternative with regards to economic feasibility as well as a greenhouse gas regulation. The following alternative is the molten carbonate fuel cell-steam turbine cycle. A hythane-fueled COGES has a relatively low economic feasibility but will be the sole propulsion system if the regulation of greenhouse gas emission from shipping is stringent. On the other hand, the carbon taxation and implementation of an incentive for hydrogen fuel may facilitate a greener shipping environment; the additional eco-friendly policy for the shipping industry needs to be provided, shortly soon.     

STUDY ON FUZZY SELF-LEARNING CONTROL SYSTEM FOR SHIP STEERING

Fuzzy control has shown success in some application areas and emerged as an alternative to some conventional control schemes. There are also some drawbacks in this approach, for example it is hard to justify the choice of fuzzy controller parameters and control rules, and control precision is low, and so on. Fuzzy control is developing towards selflearning and adaptive. The ship steering motion is a nonlinear, coupling, time-delay complicated system. How to control it effectively is the problem that many scholars are studying.In this paper, based on the repeated control of the robot, the self-learning arithmetic was worked out. The arithmetic was realized in fuzzy logic way and used in cargo steering. It is the first time for the arithmetic to be used in cargo steering. Our simulation results show that the arithmetic is effective and has several potential advantages over conventional fuzzy control.This work lays a foundation in modeling and analyzing the fuzzy learning control system.     

船舶在波浪中大幅度运动的工程算法

本文基于切片理论，计入船体运动时湿表面及其对船体流体动力性能的影响，提出了一种船舶在波浪中大幅度运动的工程估算方法，并通过对一系列６０船型计算，考虑了船舶在迎流中大幅度运动昱的运动特性、与波面的相对运动和船体瞬时受力。这一方法简单实用，对船舶方案设计有积极的意义。