楼宇型分布式能源系统设备容量和运行策略优化研究

设备容量优化和运行策略优化是分布式能源系统设计,运行的关键问题。为实现分布式能源系统的经济效益,能效水平和环境效益最大化,针对楼宇型分布式能源系统建立了相对普适化的物理模型和数学模型,以粒子群优化算法和线性规划相结合,采用两阶段优化方法计算系统的最优容量配置,并给出运行策略。以某写字楼的分布式能源系统为例,得到最优的系统设备容量和全年逐时运行策略,并采用遍历法验证计算结果的准确性。优化的分布式能源系统与传统供能系统相比,费用年值降低7.79%,年总能耗降低24.18%,污染物排放量减少了62.77 %。     

离网型混合发电系统的分布式预测控制

针对离网型风力发电和光伏发电构成的混合发电系统,研究其功率的优化分配问题,提出采用分布式预测控制的分层控制结构。应用迭代分布式MPC(model predictive control)优化算法,分别设计风力/光伏发电子系统的MPC优化问题,通过MPC之间的信息交换,得到保证全局性能优化的风力/光伏发电子系统的功率参考值,根据此功率参考值,本地控制器调节风力/光伏发电子系统的运行状态,达到混合发电系统的全局优化运行,可解决混合发电系统中集中式MPC优化模型复杂、难以满足实时控制要求的问题。仿真结果表明,采用迭代分布式MPC的离网型混合发电系统,能够很好地满足负荷的功率需求,并延长蓄电池的使用寿命。与集中式MPC相比,迭代分布式MPC能够在保证较小性能指标的前提下,减小优化问题的计算复杂度。     

基于改进蝙蝠算法的微电网优化研究

为了协调微电网中各微电源的优化调度,文中研究了涵盖光伏、风电、储能、燃气轮机和燃料电池的分布式电源,在微电网并网与孤岛运行条件下,建立了以发电费用和污染物处罚费用最低的目标函数,并采用了具有Lévy飞行特征的蝙蝠算法求得一个调度周期内各个分布式电源的最优出力及总运行成本,最后将仿真结果与基本蝙蝠算法的结果相比较,从而验证了该文所研究的优化模型及改进后算法的可行性。     

基于太阳能光伏热利用的光伏/热电(PV/TV)建筑一体化试验研究

将太阳能电池板、集热器、热电发电片结合起来,设计并制成了一套光伏/热电(PV/TV)系统,在利用太阳能电池发电的同时,收集热量并利用其发电。在北京地区进行了该系统的室外模拟试验,测试并讨论了该系统在不同结构和不同环境下的性能,探讨该系统在光伏建筑中的应用。试验结果表明,与单纯的光伏发电系统或太阳能热水系统相比,PV/TV系统具有占地面积小、综合效率高等优点。     

基于氢氧联合循环的分布式能源系统设计

风能、太阳能等新能源发电迅速发展,新能源发电系统联网对于缓解传统电网供电压力,改善能源结构具有重要作用.这些能源表现出波动性和间歇性,给电网运行带来前所未有挑战.通过分析以清洁能源发电为主的分布式电源大量联网的局限性,结合微网技术,提出了在氢氧联合循环发电系统基础上的分布式能源系统,系统采用联合最优功率控制模式,与清洁...     

含分布式发电系统的配电网无功优化研究

引入有功网损、电容器以及分布式发电的费用,并充分考虑了电压质量和无功补偿容量作为罚函数的综合目标函数,采用PSO算法时运用改变更新方式,并在后期引进变异因子,建立了含分布式发电系统的配电网无功优化模型.通过算例表明,验证了模型和算法是可行的,具有较强的收敛性,对分布式发电并入配电网的运行具有一定的参考价值.     

基于SOFC-GT-ST的双塔解吸CO2捕集工艺模拟研究

设计并验证了一种新型固体氧化物燃料电池、燃气轮机和蒸汽轮机(SOFC-GT-ST)联合循环动力系统,采用了阳极排气和后燃烧室排气两个再循环回路,研究了气体再循环对系统性能的影响,并对系统发电效率进行优化;针对烟气处理工段设计了闪蒸塔和再生塔结合的双塔解吸CO₂捕集工艺,并改进了MDEA溶液补充水的方式,优化了多处余热利用,使用Aspen Plus软件建立了系统模型,研究了贫液温度、烟气温度、贫液流量、吸收塔压力和解吸塔压力等对CO₂捕集率的影响。结果表明：阳极排气再循环比最优值为0.28,燃烧室排气再循环比最优值为0.36,CO₂的捕集率可达90.82%,碳捕集能耗为3.78 GJ/t。     

基于自适应遗传算法的分布式综合能源系统优化设计

针对分布式综合能源系统的非线性特征,构建了基于自适应遗传算法的系统优化模型,以系统最小成本为目标优化函数,同时考虑到系统的环保指标和运行可靠性等因素,运用MATLAB软件针对东南沿海一旅游岛屿进行了为期一年的动态运行仿真。研究结果表明：采用优化后的分布式综合能源系统发电成本仅0.8元/KW·h,而单一柴油发电机发电成本达到3.236元/KW·h。在提高系统供电可靠性的同时,大大降低了发电系统的运营成本。系统污染物排放量也得到了大幅降低,相较于单一柴油机发电形式,新的分布式综合能源发电系统的污染排放可以忽略不计,因此可很大程度改善岛上环境。     

上海市区域天然气分布式供能项目供电成本研究

结合目前上海市已建和拟建的部分区域式天然气分布式供能项目情况,根据其投资和运行费用,分析研究并合理界定发电工程部分的投资和运行费用,进而测算项目的供电成本,为相关政府部门确定区域天然气分布式供能项目上网电价提供参考。     

考虑DG与网架适应性的配网双层优化规划

为了适应高渗透率分布式发电并网及主动管理的配网发展趋势,在考虑分布式发电与网架适应性的情况下,建立了以年社会成本最小为目标的配网双层优化规划静态经济模型。上层模型是以系统年综合费用最小为目标的配网网架规划,下层模型是以年投资运行费用最小为目标的分布式电源选址定容规划。并根据各自的特点,分别采用二进制顺序编码的改进自适应单亲遗传算法和十进制顺序编码的改进粒子群算法求解。以某实际规划区域作为算例,验证所提模型的合理性和有效性     

Stabilization and control of tie-line power flow of microgrid including wind generation by distributed energy storage

High penetration of wind generation in electrical microgrids causes fluctuations of tie-line power flow and significantly affects the power system operation. This can lead to severe problems, such as system frequency oscillations, and/or violations of power lines capability. With proper control, a distribution static synchronous compensator (DSTATCOM) integrated with superconducting magnetic energy storage (SMES) is able to significantly enhance the dynamic security of the power system. This paper proposes the use of a SMES system in combination with a DSTATCOM as effective distributed energy storage (DES) for stabilization and control of the tie-line power flow of microgrids incorporating wind generation. A new detailed model of the integrated DSTATCOM-SMES device is derived and a novel three-level control scheme is designed. The dynamic performance of the proposed control schemes is fully validated using MATLAB/Simulink.     

Design of a robust and efficient power electronic interface for the grid integration of solar photovoltaic generation systems

Nowadays, the penetration of photovoltaic (PV) solar power generation in distributed generation (DG) systems is growing rapidly. This condition imposes new requirements to the operation and management of the distribution grid, especially when high integration levels are achieved. Under this scenario, the power electronics technology plays a vital role in ensuring an effective grid integration of the PV system, since it is subject to requirements related not only to the variable source itself but also to its effects on the stability and operation of the electric grid. This paper proposes an enhanced interface for the grid connection of solar PV generation systems. The topology employed consists of a three-level cascaded Z-source inverter that allows the flexible, efficient and reliable generation of high quality electric power from the PV plant. A full detailed model is described and its control scheme is designed. The dynamic performance of the designed architecture is verified by computer simulations.     

高温燃料电池/燃气轮机混合循环发电技术

高温燃料电池／燃气轮机混合循环系统以其效率高、排放低的特点,在未来分布式发电和集中式大规模发电中占有重要地位。本文首先简介了高温燃料电池和先进燃气轮机的结构特点及其分类,在此基础上阐述了高温燃料电池与先进燃气轮机混合系统的基本模式,然后对适用于分布式发电和集中式发电的几种典型混合循环系统的结构和相应的流程及特点进行了详细的描述,最后给出了高温燃料电池和燃气轮机混合循环发电系统中的一些主要代表性技术以及目前研究的进展、挑战和目标。     

Economic droop parameter selection for autonomous microgrids including wind turbines

Droop control is a key strategy for operating islanded microgrid systems. The droop settings of the different distributed generation (DG) units in an islanded microgrid determine the operational characteristics of the island. This paper presents an algorithm for choosing the optimal droop parameters for islanded microgrids with wind generation in order to minimize the overall island generation costs in the absence of a microgrid central controller (MGCC). A detailed microgrid model is adopted to reflect the special features and operational characteristics of droop controlled islanded microgrid systems. The proposed problem formulation considers the power flow constraints, voltage and frequency regulation constraints, line capacity constraints and unit capacity constraints. Numerical case studies have been carried out to show the effectiveness of the proposed algorithm as compared to conventional droop parameter selection criteria typically adopted in the literature.     

分布式电源并网系统的研究

随着目前电力短缺的加剧,分布式电源与区域电网并联运行的趋势越来越明显.在分布式发电装置与电网并联运行的模式下,通过分析逆变型分布式电源＂负荷＂特性,提出基于功率电流双环控制策略的逆变控制系统.通过合理选取功率控制环、电流控制环、软件锁相环的PI控制器参数,可以使得分布式发电并网逆变装置具有良好的稳态及动态性能.通过在MATLAB上实现的仿真模型证明该控制系统能较好地维持逆变型分布式电源恒功率电压源的拟负荷外特性,控制灵活,反应迅速.     

Short-term impact of green certificates and CO2 emissions trading in the Swedish district heating sector

Swedish district-heating (DH) systems use a wide range of energy sources and technologies for heat-and-power generation. This provides the DH utilities with major flexibility in changing their fuel and technology mix when the economic conditions for generation change. Two recently introduced policy instruments have changed the DH utilities’ costs for generation considerably; the tradable green-certificate (TGC) scheme introduced in 2003 in Sweden, and the tradable greenhouse-gas emission permit (TEP) scheme introduced in the EU on January 1, 2005. The objective of this study is to analyse how these two trading schemes impact on the operation of the Swedish DH sector in terms of changes in CHP generation, CO₂ emissions, and operating costs. The analysis was carried out by comparing the most cost-effective operation for the DH utilities, with and without, the two trading schemes applied, using a model that handles the Swedish DH-sector system-by-system. It was found that the volume of renewable power generated in CHP plants only increased slightly owing to the TGC scheme. The TGC and the TEP schemes in force together, however, nearly doubled the renewable power-generation. CO₂ emissions from the DH sector may either increase or decrease depending on the combination of TGC and TEP prices. The overall CO₂ emissions from the European power-generation sector would, however, be reduced for all price combinations assuming that increased Swedish CHP generation replaces coal-condensing power (coal-fired plants with power generation only) in other European countries. The trading schemes also lower the operational costs of the DH sector since the cost increase owing to the use of more expensive fuels and the purchase of TEPs is outweighed by the increased revenues from sales of electricity and TGCs.     

State coordinated voltage control in an active distribution network with on-load tap changers and photovoltaic systems

Decreasing costs and favorable policies have resulted in increased penetration of solar photovoltaic (PV) power generation in distribution networks. As the PV systems penetration is likely to increase in the future, utilizing the reactive power capability of PV inverters to mitigate voltage deviations is being promoted. In recent years, droop control of inverter- based distributed energy resources has emerged as an essential tool for use in this study. The participation of PV systems in voltage regulation and its coordination with existing controllers, such as on-load tap changers, is paramount for controlling the voltage within specified limits. In this work, control strategies are presented that can be coordinated with the existing controls in a distributed manner. The effectiveness of the proposed method was demonstrated through simulation results on a distribution system.     

Hybrid intelligent water drop bundled wavelet neural network to solve the islanding detection by inverter-based DG

In this paper, a passive neuro-wavelet based islanding detection technique for grid-connected inverter-based distributed generation was developed. The weight parameters of the neural network were optimized by intelligent water drop (IWD) to improve the capability of the proposed technique in the proposed problem. The proposed method utilizes and combines wavelet analysis and artificial neural network (ANN) to detect islanding. Connecting distributed generator to the distribution network has many benefits such as increasing the capacity of the grid and enhancing the power quality. However, it gives rise to many problems. This is mainly due to the fact that distribution networks are designed without any generation units at that level. Hence, integrating distributed generators into the existing distribution network is not problem-free. Unintentional islanding is one of the encountered problems. Discrete wavelet transform (DWT) is capable of decomposing the signals into different frequency bands. It can be utilized in extracting discriminative features from the acquired voltage signals. In passive schemes with a large non-detection zone (NDZ), concern has been raised on active method due to its degrading power quality effect. The main emphasis of the proposed scheme is to reduce the NDZ to as close as possible and to keep the output power quality unchanged. The simulation results from Matlab/Simulink shows that the proposed method has a small non-detection zone, and is capable of detecting islanding accurately within the minimum standard time.     

Dynamic modeling of a hybrid wind/solar/hydro microgrid in EMTP/ATP

Microgrids are LV or MV electric networks which utilize various distributed generators (DG) to serve local loads. In this paper, dynamic models of the main distributed generators including photovoltaic (PV) cell, wind turbine, hydro turbine as well as the equivalent power electronic interfaces, battery unit of PV and excitation system of hydro turbine have been made in ElectroMagnetic Transient Program/Alternative Transient Program (EMTP/ATP) software package. Control strategies based on active power/frequency and reactive power/voltage droops for the power control of the inverters have been also developed. Case studies have been carried out in a distribution network to investigate the dynamic behavior of the micro-sources in both steady state and fault scenarios. Simulation results verify the feasibility of the proposed models.     

Dynamic modeling of a SOFC/MGT hybrid power system based on modified OIF Elman neural network

Solid oxide fuel cell (SOFC) integrated into micro gas turbine (MGT) cycle is a promising power‐generation technology. This article proposes a modified output–input feedback (OIF) Elman neural network model to describe the nonlinear temperature and power dynamic properties of the SOFC/MGT hybrid system. A physics‐based mathematical model of a 220 kW SOFC/MGT hybrid power system is used to generate the data required for the training and prediction of the modified OIF Elman neural network identification model. Compared with the conventional Elman neural network, the simulation results show that the modified OIF Elman identification model can follow the temperature and power response of the SOFC/MGT hybrid system with higher prediction accuracy and faster convergent speed. Copyright © 2010 John Wiley & Sons, Ltd.