西藏4kW风/光互补发电系统优化设计

根据在西藏一个实际村庄的风、光资源和负载特性，利用美国可再生能源实验室开发的混合发电系统性能模拟软件“Ｈｙｂｒｉｄ２”，模拟并比较了在该村庄利用风／蓄、风／光／蓄、光／蓄系统解决其基本生活用电的技术经济可行性。模拟结果指出，风／光／蓄混合发电系统是该村庄最适合的发电系统。文中还对风／光／蓄发电系统进行了优化设计。通过改变风资源数据，利用“Ｈｙｂｒｉｄ２”模拟和优化设计不同风速时的发电系统，结果显示在西藏那曲地区利用风／光混合发电系统解决无电村庄居民的供电问题是可行的。     

光水混合发电系统优化策略研究

为了提高独立能源发电的可靠性与运行效率,结合光水发电系统的混合发电模式,搭建出光水混合发电系统的优化模型,并基于改进型粒子群优化算法(CPSO)对混合光水发电系统进行仿真计算,比较了混合发电与单一发电系统中传输功率及效益。结果表明,通过对光水混合发电系统中水电优化,解决了光伏发电不稳定问题,更好地利用了太阳能与水电资源优化互补的特性,实现了效益最大化。     

基于改进遗传算法的风/光互补发电系统恒压控制

针对带有约束条件的风/光互补发电系统恒压控制这个多极值非线性组合优化问题,采用一种改进遗传算法,以系统发电成本最低为目标,根据拧制规则对一风/光互补发电系统的电压进行了优化.仿真结果表明.该算法能显著地提高收敛速度和计算精度,有效地提高了风/光互补发电系统的电压稳定性.     

风一光互补发电系统的频率控制研究

针对风、光资源随机性强和负荷多变使风-光互补发电系统频率变化频繁、控制难度增大的问题,分析了混合系统的特点,建立了风-光互补发电系统频率控制的自动机模型,并对发电系统的频率控制进行了仿真实验.结果表明,该自动机模型既能确保风-光互补发电系统频率的稳定,又能使发电系统经济运行.     

风-光互补发电系统的频率控制研究

针对风、光资源随机性强和负荷多变使风-光互补发电系统频率变化频繁、控制难度增大的问题,分析了混合系统的特点,建立了风-光互补发电系统频率控制的自动机模型,并对发电系统的频率控制进行了仿真实验。结果表明,该自动机模型既能确保风-光互补发电系统频率的稳定,又能使发电系统经济运行。     

电力市场环境下的新能源有功自动控制

针对当前电力资源紧缺、控制力度不佳的问题,提出新型的风/光发电系统有功自动控制方案,该方案通过时域分析和计及交叉权重校正算法等方法,大大减少了整个自动控制系统的无功损耗。利用西门子PLC对分站进行控制,能够实时掌握系统运行状态,通过时域分析解决系统稳定性问题,利用计及交叉权重校正算法完成风/光发电有功控制。最后根据得出的灵敏度数据,通过Matlab仿真对两种有功控制系统进行对比,发现所提方法比传统方法有功输出高20%以上,增加了风/光发电系统在电力市场上的竞争力,证实了本设计的可行性。     

风/光互补发电系统的优化设计

在分析现有风/光互补发电系统研究的基础上,确定风机容量与PV组件容量在系统总容量中所占的比例;根据安装地点气候条件与地理条件、负载要求,估算出蓄电池的最低容量,并归纳设计各部件的数量和类型选择的约束关系;综合给出一种适合于风/光互补发电系统优化设计的模型。     

新能源发电工程储能系统容量/功率优化配置

新能源风、光发电工程中配置一定容量的储能系统,可以显著提高新能源发电的消纳水平。储能系统的容量/功率的优化配置可最大程度提高储能系统利用效率和经济性,同时将新能源风电、光伏的弃电率降低到设定的目标值。提出以全生命周期内储能系统净现值最大为目标,综合考虑储能系统全生命周期内投资、运维成本、购电成本、售电收入、充放电效率、荷电状态、储能电池寿命、弃电率等多种因素的储能系统容量/功率优化配置方法,并以青海某工程1 030 MW光伏阵列和250 MW风电场的运行数据为例,计算得到该新能源风电、光伏发电工程中净现值最大的储能系统容量/功率配置,使整个储能系统获得最优的经济性。     

基于双层优化模型的风-光-储互补发电系统优化配置

提出一种基于双层优化模型的风-光-储互补发电系统优化配置方法,外层优化以互补发电系统年净收益最大化为目标、通过量子粒子群算法优化风-光-储容量配置;内层优化以互补发电系统日出力波动率和日出力峰谷差最小化为目标、通过8760 h生产模拟优化储能充放电功率。实际算例仿真计算结果表明,所提算法能有效解决风-光-储互补发电系统在规划阶段的优化配置问题。     

风光互补发电系统的优化设计(I) CAD设计方法

给出了一整套利用CAD进行风光互补发电系统优化设计的方法。为了精确确定系统每小时的运行状态,采用了更精确地表征组件特性及评估实际获得的风光资源的数学模型。为了寻找出以最小设备投资成本满足用户用电要求的系统配置,首先在风力发电机容量固定不变的前提下,计算了与该容量风力发电机匹配的不同容量的PV方阵和蓄电池所组成的风/光/蓄组合的全年功率供给亏欠率LPSP,根据总的设备投资成本最小化的原则筛选出一组与该容量风力发电机对应的满足用户给定系统供电可靠性即LPSP值的风/光/蓄组合;然后通过改变风力发电机的容量,优选出多个与不同容量风力发电机对应的既能满足用户用电要求同时总的设备购置成本又是最低的风/光/蓄组合,比较它们的成本最终唯一确定出以最小投资成本满足用户用电要求的优化的系统配置。     

并网风光互补资源评价与系统容量优化配置

为降低风电并网后冲击电网,充分利用风能和太阳能等清洁能源,以并网风光互补发电系统年内出力最平稳为前提,对风光互补资源评价和容量优化配置方法进行了研究。基于平均距平百分率和变异系数等指标,提出了衡量年内发电量波动性的方法,以发电量年内波动性最小作为求解条件,建立了风光互补系统最优装机容量比例计算方法,并确定了进行风光互补性资源禀赋定量评价的指标。以湖北省内石首市桃花山和阳新县富池风光资源状况为计算实例,验证了该方法的正确性。     

Computer-aided design of PV/wind hybrid system

A complete set of match calculation methods for optimum sizing of PV/wind hybrid system is presented. In this method, the more accurate and practical mathematic models for characterizing PV module, wind generator and battery are adopted; combining with hourly measured meteorologic data and load data, the performance of a PV/wind hybrid system is determined on a hourly basis; by fixing the capacity of wind generators, the whole year’s LPSP (loss of power supply probability) values of PV/wind hybrid systems with different capacity of PV array and battery bank are calculated, then the trade-off curve between battery bank and PV array capacity is drawn for the given LPSP value; the optimum configuration which can meet the energy demand with the minimum cost can be found by drawing a tangent to the trade-off curve with the slope representing the relationship between cost of PV module and that of the battery. According to this match calculation method, a set of match calculation programs for optimum sizing of PV/wind hybrid systems have been developed. Applying these match calculation programs to an assumed PV/wind hybrid system to be installed at Waglan island of Hong Kong, the optimum configuration and its hourly, daily, monthly and yearly performances are given.     

风光互补技术及应用新进展

简要回顾国内外风电、光伏技术与应用发展态势,结合风光互补系统应用,分析、介绍了风光互补LED路灯照明系统、智能控制器设计、分布式供电电源、风光互补水泵系统．并着重分析生物质能、风能和太阳能互补分布式能源梯级系统原理,涉及的技术关键等。研究表明,风能、光伏发电应用需要实现低成本、规模化,风光互补技术应用前景广阔。     

Intelligent hybrid power generation system using new hybrid fuzzy-neural for photovoltaic system and RBFNSM for wind turbine in the grid connected mode

Photovoltaic (PV) generation is growing increasingly fast as a renewable energy source. Nevertheless, the drawback of the PV system is intermittent because of depending on weather conditions. Therefore, the wind power can be considered to assist for a stable and reliable output from the PV generation system for loads and improve the dynamic performance of the whole generation system in the grid connected mode. In this paper, a novel topology of an intelligent hybrid generation system with PV and wind turbine is presented. In order to capture the maximum power, a hybrid fuzzy-neural maximum power point tracking (MPPT) method is applied in the PV system. The average tracking efficiency of the hybrid fuzzy-neural is incremented by approximately two percentage points in comparison with the conventional methods. The pitch angle of the wind turbine is controlled by radial basis function network-sliding mode (RBFNSM). Different conditions are represented in simulation results that compare the real power values with those of the presented methods. The obtained results verify the effectiveness and superiority of the proposed method which has the advantages of robustness, fast response and good performance. Detailed mathematical model and a control approach of a three-phase grid-connected intelligent hybrid system have been proposed using Matlab/Simulink.     

Optimal sizing method for stand-alone hybrid solar–wind system with LPSP technology by using genetic algorithm

System power reliability under varying weather conditions and the corresponding system cost are the two main concerns for designing hybrid solar–wind power generation systems. This paper recommends an optimal sizing method to optimize the configurations of a hybrid solar–wind system employing battery banks. Based on a genetic algorithm (GA), which has the ability to attain the global optimum with relative computational simplicity, one optimal sizing method was developed to calculate the optimum system configuration that can achieve the customers required loss of power supply probability (LPSP) with a minimum annualized cost of system (ACS). The decision variables included in the optimization process are the PV module number, wind turbine number, battery number, PV module slope angle and wind turbine installation height. The proposed method has been applied to the analysis of a hybrid system which supplies power for a telecommunication relay station, and good optimization performance has been found. Furthermore, the relationships between system power reliability and system configurations were also given.     

一种并网型风光互补发电系统的建模与仿真

分析了风光互补发电系统的技术优势,设计了基于固态变压器结构的并网型风光互补发电系统。分别建立了光伏系统,风力发电系统,超级电容和蓄电池的模型,并分析各环节的控制策略,提出了基于平均功率的储能设备容量配置方法。仿真结果表明,该系统能模拟风光互补系统在不同模式下的运行特性,可以有效降低功率波动和维持电压稳定,并能在低光照强度、低风速等情况下为系统提供短时能量支撑。     

A comprehensive method for optimal power management and design of hybrid RES-based autonomous energy systems

The power management strategy (PMS) plays an important role in the optimum design and efficient utilization of hybrid energy systems. The power available from hybrid systems and the overall lifetime of system components are highly affected by PMS. This paper presents a novel method for the determination of the optimum PMS of hybrid energy systems including various generators and storage units. The PMS optimization is integrated with the sizing procedure of the hybrid system. The method is tested on a system with several widely used generators in off-grid systems, including wind turbines, PV panels, fuel cells, electrolyzers, hydrogen tanks, batteries, and diesel generators. The aim of the optimization problem is to simultaneously minimize the overall cost of the system, unmet load, and fuel emission considering the uncertainties associated with renewable energy sources (RES). These uncertainties are modeled by using various possible scenarios for wind speed and solar irradiation based on Weibull and Beta probability distribution functions (PDF), respectively. The differential evolution algorithm (DEA) accompanied with fuzzy technique is used to handle the mixed-integer nonlinear multi-objective optimization problem. The optimum solution, including design parameters of system components and the monthly PMS parameters adapting climatic changes during a year, are obtained. Considering operating limitations of system devices, the parameters characterize the priority and share of each storage component for serving the deficit energy or storing surplus energy both resulted from the mismatch of power between load and generation. In order to have efficient power exploitation from RES, the optimum monthly tilt angles of PV panels and the optimum tower height for wind turbines are calculated. Numerical results are compared with the results of optimal sizing assuming pre-defined PMS without using the proposed power management optimization method. The comparative results present the efficacy and capability of the proposed method for hybrid energy systems.     

Comparative study of artificial intelligence techniques for sizing of a hydrogen-based stand-alone photovoltaic/wind hybrid system

As non-polluting reliable energy sources, stand-alone photovoltaic/wind/fuel cell (PV/wind/FC) hybrid systems are being studied from various aspects in recent years. In such systems, optimum sizing is the main issue for having a cost-effective system. This paper evaluates the performance of different artificial intelligence (AI) techniques for optimum sizing of a PV/wind/FC hybrid system to continuously satisfy the load demand with the minimal total annual cost. For this aim, the sizing problem is formulated and four well-known heuristic algorithms, namely, particle swarm optimization (PSO), tabu search (TS), simulated annealing (SA), and harmony search (HS), are applied to the system and the results are compared in terms of the total annual cost. It can be seen that not only average results produced by PSO are more promising than those of the other algorithms but also PSO has the most robustness. As another investigation, the sizing is also performed for a PV/wind/battery hybrid system and the results are compared with those of the PV/wind/FC system.