提高风出力预测精度的储能系统模糊控制策略

风气象信息的精细化程度不够高会造成风电场风出力预测精度的降低,给电网调度增加了难度。在风电场中配置锌溴电池储能系统是提高风电场日前预报精度的有效措施,对储能装置控制是其关键问题。文章采用模糊控制方法,搭建了储能系统模糊控制规则库,根据电池储能系统荷电状态SOC的变化来控制储能充放电功率;并将所提出的控制策略在新疆达坂城风电场-储能联合发电系统中进行了仿真验证,与传统控制策略进行了对比分析。研究结果表明,采用模糊控制策略的储能系统能够更有效地提高风出力短期预测精度,85%的预测值达到了国家电网要求。     

提高双向调节能力的混合储能平滑风电控制策略

为有效平滑风电出力,避免电池频繁充放电,提出了基于模型预测控制-模糊控制的并网功率平滑控制策略。首先采用模型预测控制获取风电目标出力与混合储能总输出参考功率;然后,设计了基于超级电容荷电状态的模糊自适应时间常数的一阶低通滤波法,对超级电容与锂电池实现自适应功率分配;接着基于双储能系统的充放电不平衡指标设计了模糊荷电状态优化控制,同时设计了改进双储能工作模式及相应切换规则以避免荷电状态越限;最后在Matlab/Simulink平台上建模仿真,验证了该控制策略的有效性。结果表明,所提控制策略不仅可以有效平滑风电并网功率,减小储能容量与功率配置,还可以减小锂电池的充放电切换次数,提高系统的双向调节能力。     

提高风电功率短期预报精度的储能控制策略优化及效益评估

风电场功率短期预报精度不高严重制约大规模风电并网。文章以提高风电功率短期预报精度为目标,采用正态分布进行储能容量配置,提出了储能系统的运行控制策略。考虑储能装置自身限制问题,基于SOC控制策略对其进行优化,降低储能装置的SOC状态约束对其充放电行为的影响,最大限度地利用储能实现提高短期预报精度的目标,并进行效益评估,降低弃风量与备用量,提高经济效益。利用该运行控制策略对某大型风电场与储能联合系统的出力特性进行了仿真验证及效益评估,验证了控制策略的有效性和实用性。     

风氢-混合储能系统全寿命周期经济性研究

由于风力发电输出功率具有随机性和波动性,安装储能系统可以平滑风力发电输出功率,有效改善电能质量,提高风力发电点的经济效益。建立风氢-混合储能系统（WHMESS）全寿命周期经济性数学模型,考虑以平抑风电波动功率的经济效益和WHMESS的稳定运行为约束,对WHMESS系统投资回收周期和全寿命周期净利润进行求解。编写程序建立Qt界面,用算法求解WHMESS全寿命周期经济评估数学模型,得出全寿命周期内净利润和资金回收期,验证了WHMESS全寿命周期经济评估数学模型的合理性。     

数据分辨率影响风电功率预测精度分析

目前对风电功率短时预测的研究主要集中在预测方法上,而缺乏对数据本身特性的探讨。从实测数据出发,呈现3种典型分辨率5 min、10 min、15 min,并结合Elman神经网络算法对超短期（4 h）和短期（24 h）的风力发电机输出功率进行预测分析。结果表明：分辨率为10 min的原始数据对风电输出功率的超短期预测具有更好的结果,15 min分辨率的数据对风电功率的短期预测结果更佳。采用合理分辨率的数据后,能够有效地提高风电功率的预测精度。     

带混合储能的微网并网控制策略研究

新能源发电的不确定性严重影响了电力系统的稳定。采用蓄电池单一储能的方式很难具有高功率密度、高效率、无污染等优点。为了克服蓄电池储能的缺点,文章将蓄电池和超级电容组成混合储能单元,利用高通滤波器将微网系统功率波动分为高、低频两部分,高频部分由超级电容直接吸收或释放,而低频功率分量与蓄电池、超级电容的剩余容量一起作为模糊控制器的输入,通过模糊规则的建立,求解出超级电容对低频功率分量的分担系数,进而计算出蓄电池和超级电容对系统功率的分担量。搭建仿真与实验平台,结果表明该控制策略充分利用了超级电容的容量,且能使整个微网系统高效稳定地运行。     

有功分级平滑修正风电出力短期预测精度

为达到国家电网要求的风电场短期预测(日前)误差不超过25％的技术规定,文章以15 min时间间隔的风电实测和预测功率历史数据为基础,从横向误差和纵向误差的角度,提出了一种利用横向一次修正和储能系统二次修正的有功分级平滑来提高风电功率短期预测精度的方法.通过对误差时间序列进行统计分析,得出所需的横向时间向量将0～24 h预测功率前后平移,实现初级修正;运用储能系统装置,制定储能系统能量管理策略,有效地补偿风电功率的纵向误差,实现二级修正.以风电场的典型历史数据为例,经过两级有功分级修正,对风电功率预测进行较精确评估,同时做了简易的经济评价.     

基于风电场出力计划的储能系统容量优化

储能系统的引入为风电成为可调度电源提供了可能,但增加了投资成本。文章提出一种基于风电场出力计划的储能系统容量优化方法。首先,利用风电场功率预测误差的标准偏差对风电场出力计划进行优化;其次,以出力计划为风电场出力目标,在风电场实际出力跟踪出力计划允许的误差带宽内,以风电并网条件为约束,用遗传算法确定出储能系统在各时刻的最优出力值,进而考虑储能系统充/放电效率、荷电状态确定出储能系统容量;最后以新疆某风电场为例进行算例分析,结果表明该方法是合理、有效的。     

混合储能辅助风电场平滑出力的功率配比方法研究

随着风电渗透率的增大,风电并网时对电网产生的波动也逐渐增大,采用储能系统对风电场出力进行平滑处理,可以使风电满足规定的并网要求.针对风电场出力波动成分的频率范围较宽的问题,采用混合储能系统(飞轮+电化学储能)进行不同波动频率成分平滑,提出一种运行数据驱动的混合储能容量配置方法,利用抗脉冲平均滤波法对风电场出力数据序列进...     

基于储能电站提高风电消纳能力的电源规划研究

针对当前电网对大规模风电消纳难的问题,提出在风电开发之初,从规划层面考虑利用储能电站优化区域电力系统的电源结构,提高电网对风电的消纳能力。文章综合考虑环境效益、社会效益、市场竞争力后,以风电消纳能力最大和国民经济投入最小为目标函数,构建了包含火电、储能电站、大规模风电的电源规划模型,并采用允许风电在一定范围内波动这一策略来减少储能电站的投资和运行费用。最后采用改进遗传算法对该模型进行求解,并针对某区域电力系统电源规划进行了仿真计算,结果表明,文章所建的模型既提高了电网对风电的消纳能力,又兼顾了其经济性。     

Hydrogen energy storage systems to improve wind power plant efficiency considering electricity tariff dynamics

One of the limitations of the efficiency of renewable energy sources is the stochastic nature of generation; consequently, it is necessary to use high-capacity energy storage systems such as hydrogen storage for its integration into existing power networks. At the same time, electricity market tariffs for large enterprises change during the day. Therefore, it can be assumed that storing energy during cheaper hours and usage in more expensive hours allows increasing the efficiency of renewable energy sources. Evaluation of the economic efficiency of an energy storage system requires simulation with a step of at least 1 h for several years since the use of averaged production volume and averaged electricity tariffs will not allow obtaining an adequate to the task accuracy. A simulation model and software have been implemented to perform simulations and calculate the economic efficiency of a wind turbine with and without a hydrogen storage device. The methodology has been approved on three-year real data of wind speeds and electricity tariffs in the Novosibirsk region and Krasnodar Territory (Russian Federation).     

A control strategy for energy storage system based on wind power prediction error interval

由于风能的间歇性和随机性,风电功率预测的精度依然较低。随着大规模风电的集中接入,不确定性风电功率并网运行会加重电力系统的调控负担,同时会对日前调度计划安排带来不利影响。储能系统具有对功率和能量的时间迁移能力,被认为是平抑风电功率波动性、提高风电功率确定性的有效手段。本文从电力系统安全角度分析了制约风电上网规模的原因,使用基于时间序列的自回归模型预测风电功率,提出利用储能平抑风电功率预测误差区间的方法,对比考虑最大预测误差的传统调度方法,采用风电平均入网容量、风电发电量、电网空间利用率等评价指标评估所提出方法的有效性。     

Effect of energy storage on variations in wind power

Irregularities in power output are characteristic of intermittent energy, sources such as wind energy, affecting both the power quality and planning of the energy system. In this work the effects of energy storage to reduce wind power fluctuations are investigated. Integration of the energy storage with wind power is modelled using a filter approach in which a time constant corresponds to the energy storage capacity. The analyses show that already a relatively small energy storage capacity of 3 kWh (storage) per MW wind would reduce the short‐term power fluctuations of an individual wind turbine by 10%. Smoothing out the power fluctuation of the wind turbine on a yearly level would necessitate large storage, e.g. a 10% reduction requires 2–3 MWh per MW wind. Copyright © 2005 John Wiley & Sons, Ltd.     

Economic evaluation for wind power generation–hybrid energy storage system based on game theory

The installation of energy storage system to smooth the fluctuations of wind power output connected to the grid can effectively improve the electric quality and increase economic benefits of wind‐generated electricity. Aiming at the overall profit maximization of wind power generation and storage system (WPGSS), taking the smoothing effect of active power output, the cost of hybrid energy storage system, and the earnings of wind power connected to the grid into consideration, this paper brings forward a game theory‐based coordination and optimization control methodology for WPGSS adopting two low‐pass filters to smooth the fluctuation of wind power output. The smoothing control to the active power of wind power and the power distribution of the hybrid energy storage system is respectively achieved by regulating the time constants of the two filters. With the combinations of wind power–batteries and wind power–super‐capacitors as game's participants and the maximization of the WPGSS's overall profit as game's goal constraint conditions, game theory is introduced to realize the coordination and optimization between the time constants of the two filters. For comparative analysis, the model's optimal solution is respectively worked out by genetic algorithm and particle swarm optimization. The simulation results verify the effectiveness of the proposed method and provide a theoretical basis for the economic evaluation of the WPGSS. Copyright © 2016 John Wiley & Sons, Ltd.     

Evaluating energy storage technologies for wind power integration

In this paper we perform a cost analysis of different types of energy storage technologies. We evaluate eleven storage technologies, including lead-acid, sodium–sulfur, nickel–cadmium, and lithium-ion batteries, superconducting magnetic energy storage, electrochemical capacitors, flywheels, flow batteries, pumped hydro and compressed air energy storage systems. We perform economic analysis for key applications associated with a wind farm integrated into the electric grid, including load shifting, frequency support, and power quality. We identify the key characteristics that affect the economic viability for these technologies, perform sensitivity analyses based on key performance criteria and find improvement areas that could make them more competitive in the near future.     

The economics of wind power with energy storage

We develop a nonlinear mathematical optimization program for investigating the economic and environmental implications of wind penetration in electrical grids and evaluating how hydropower storage could be used to offset wind power intermittence. When wind power is added to an electrical grid consisting of thermal and hydropower plants, it increases system variability and results in a need for additional peak-load, gas-fired generators. Our empirical application using load data for Alberta's electrical grid shows that costs of wind-generated electricity vary from $37 per MWh to $68/MWh, and depend primarily on the wind profiles of installed turbines. Costs of reducing CO₂ emissions are estimated to be $41–$56 per t CO₂. When pumped hydro storage is introduced in the system or the capacity of the water reservoirs is enhanced, the hydropower facility could provide most of the peak load requirements obviating the need to build large peak-load gas generators.