计及充电负荷不确定性的充电站储能鲁棒优化配置方法

针对充电站充电负荷的波动性和不确定性特点,提出了计及充电负荷不确定性的充电站储能鲁棒优化配置方法.首先,建立了多面体不确定集描述电动汽车充电负荷的波动性与不确定性.随后,建立了储能系统容量优化配置模型,同时,在优化配置模型中利用储能电池可变寿命模型,实现多约束条件下的储能系统综合成本最小化,使得充电站可以在增加较少综合成本的情况下应对负荷的随机波动.最后,基于鲁棒优化理论实现不确定模型从随机参数到确定性参数模型的转换,结合网格自适应直接搜索算法得到储能系统最佳配置参数.算例通过与确定性算法的对比,验证了所提方法的可行性.     

Optimal thermal mix in electricity grids containing wind power

A numerical probabilistic model is used to calculate the optimal mix of thermal base and peak load plant in an electricity grid with zero storage and with differing amounts of wind power capacity. It is found that wind power capacity tends to displace conventional base load capacity with the same annual average energy production. The dollar value of the capital saving made by using wind power is often comparable with the dollar value of the fuel saving. The breakeven cost of wind power depends mainly on the capital cost of the base capacity, the fuel and other variable costs of the base plant, interest rates and on the penetration of wind power into the grid, but is relatively insensitive to other economic, grid, aerogenerator and load parameters.     

A load dispatch method using fractional programming and semidefinite programming

This paper describes a load dispatch method which minimizes power cost—[fuel cost]/[electric output]—for a power system with thermal plants and energy storage facilities. The proposed method employs fractional programming to convert a minimization problem with fractional objective function to a series of quadratic minimization problems, and semidefinite programming to solve converted problems. The method provides the optimum time‐dependent power output/input and storage level of energy storage facilities as well as time‐dependent power output of thermal plants. The method has been applied to a power system with five thermal plants, two energy storage facilities of various performances, and five load demands. The optimum load scheme of four time mesh points is obtained for the thermal plants and energy storage facilities. The fractional programming successfully converges the optimal scheme through a few iterations. The semidefinite programming deals with a variable matrix of 164 dimensions, and 185 inequality constraints. © 2001 Scripta Technica, Electr Eng Jpn, 138(2): 49–58, 2002     

满足电网调峰的化学储能最优容量敏感因素分析

近年来化学储能由于选址灵活、建设周期短、成本下降快的特点,逐渐在电网调峰中得到应用.然而化学储能用于电网调峰时的最优容量受哪些敏感因素影响以及如何影响,目前尚未得到充分研究.针对该内容,构建了用于调峰的化学储能最优容量配置模型,模型以系统总成本最小为目标,以目标规划年各类电源、负荷的规划或预测数据为边界,对各储能容量待...     

基于机会约束理论的微电网随机优化调度

随着风能、太阳能等可再生能源的开发利用,基于分布式电源的微电网安全经济调度日益引起人们关注。本文考虑了风能和太阳能的随机性和互补性,以及储能蓄电池中能量的不确定性,提出在满足系统功率平衡约束和运行约束的条件下,建立基于机会约束理论的微电网随机经济优化模型。该模型以微电网用电总费用最小为目标函数,利用抽样平均近似(SAA)法将机会约束条件转化为确定性条件,并采用粒子群算法进行寻优求解。最后,通过对随机优化模型和确定性模型进行了对比,并研究了置信度水平和抽样次数对调度的影响,算例结果表明了该随机优化模型的合理性和有效性。     

考虑源荷双重不确定性的电气互联综合能源系统分布鲁棒优化调度

针对电气互联综合能源系统中不确定因素对运行调度带来的风险问题,提出一种考虑新能源负荷双重不确定性的电气互联综合能源系统分布鲁棒优化调度模型。以系统运行总成本最小为目标函数,建立电气互联综合能源系统随机规划模型,采用矩不确定分布鲁棒优化方法(DRO-MU),构建风电出力和电力负荷的矩不确定集合,在源荷双重不确定集合下将随机规划模型转化为矩不确定分布鲁棒优化模型,通过拉格朗日对偶原理将鲁棒模型转化为确定性的半正定规划模型进行求解。仿真结果表明,与不考虑或仅考虑新能源、负荷不确定性相比,考虑源荷双重不确定性的DRO-MU模型运行成本有所增加,但方案降低了不确定性因素给系统运行带来的风险,且更加符合实际。与随机优化方法和传统鲁棒方法相比,DRO-MU方法既保证了调度策略的鲁棒性,又克服了其过于保守的问题;随着源荷矩不确定集范围的增大,系统运行成本增加,通过合理设置二者矩不确定集范围,实现系统经济性与鲁棒性的平衡。     

基于随机动态规划的多能联供系统冷热电经济分配模型

建立了风力发电机组与燃气轮机联合驱动下含压缩空气储能装置的多能联供系统冷热电经济分配模型。该模型考虑风电输出功率和冷、热、电负荷的波动特性,利用概率密度函数对系统的随机变量进行拟合。以投资成本和运行成本作为目标函数,以冷、热、电负荷平衡及各设备出力特性作为约束条件,采用随机动态规划对系统能源进行合理的调度和分配以达到最优经济效益,并通过控制系统的制冷比和风电输出功率平抑系数,实时调整系统各设备的容量及运行状态。实例的计算结果表明,压缩空气储能能够有效地平抑风电输出功率的波动,减少弃风经济损失;相比于固定能量分配,采用动态规划对系统的能量进行分配具有更多的价值和优势。     

考虑CCHP的工业大用户综合能源系统扩展规划

工业大用户是一个多能源综合供给系统,传统的工业大用户综合能源系统(integrated energy system,IES)规划忽略了多种能源的参与.计及冷热电联供系统(combined cooling,heating and power,CCHP),考虑多能梯级利用及其与可转移生产任务的耦合关系,文章建立了工业大用户...     

Stochastic multiobjective self-scheduling of a power producer in joint energy and reserves markets

This paper presents a stochastic multiobjective model for self-scheduling of a power producer which participates in the day-ahead joint energy and reserves markets. The objective of a power producer is to compromise the conflicting objectives of payoff maximization and gaseous emissions minimization when committing its generation of thermal units. The proposed schedule will be used by the power producers to decide on emission quota arbitrage opportunities and for strategic bidding to the energy and reserves market. The paper analyzes a scenario-based multiobjective model in which random distributions, such as price forecasting inaccuracies as well as forced outage of generating units are modeled as scenarios tree using a combined fuzzy c-mean/Monte-Carlo simulation (FCM/MCS) method. With the above procedure the stochastic multiobjective self-scheduling problem is converted into corresponding deterministic problems. Then a multiobjective mathematical programming (MMP) approach based on ?-constraint method is implemented for each deterministic scenario. Piecewise linearized fuel and emission cost functions are applied for computational efficiency and the model is formulated as a mixed-integer programming (MIP) problem. Numerical simulations for a power producer with 21 thermal units are discussed to demonstrate the performance of the proposed approach in increasing expected payoffs by adjusting the emission quota arbitrage opportunities.     

计及含氢储能与电价型需求响应的能量枢纽日前经济调度

为了解耦冷热电联供(combined cool,heat and power system,CCHP)机组“以热定电”的运行约束,提高风电消纳能力,降低社会碳排放,提出了计及含氢储能与电价型需求响应的能量枢纽日前经济调度模型。源侧利用冷、热、电、氢4种储能装置,打破CCHP机组热电耦合约束;荷侧引入电价型需求响应改变用户用电行为,通过优化各机组出力与电负荷曲线,增加风机出力。该模型以系统日运行成本最低为目标,引入弃风惩罚成本增加风电消纳,综合功率平衡等约束,调用Gurobi求解器进行优化求解。对不同场景下能量枢纽的优化结果进行分析,并计算燃油汽车的碳排放量以量化氢燃料电池汽车节约的社会碳排放。结果表明:在电价型需求响应策略下,考虑CCHP与含氢储能的能量枢纽系统在增加风电消纳能力的同时降低了系统的日运行总成本,减少了社会碳排放。     

不同电价下含储能系统的微电网经济调度

为了验证不同电价下储能技术的削峰填谷及其在电力系统经济调度中的作用,对含有储能的微电网进行建模分析。建立了含有风机、光伏电池、热电联产系统、燃料电池、燃气锅炉及储能系统的并网型微电网结构,在充分考虑电力市场分时/实时电价的条件下,优化了计及设备维护成本、售热收益和微电网与大电网之间的电能交互成本等的经济模型,并采用混合杂草蝙蝠算法对所提模型进行了优化。以2种电价下不含储能系统的微电网经济调度模型作为对照,通过具体的微电网实例优化了冬季典型日负荷下各微电源的最优机组出力和最佳运行成本。仿真结果验证了所提算法和模型的有效性：储能能够在电价引导下对网内电负荷削峰填谷并降低微电网运行成本;同时,不同电价政策对微电网总运行成本及储能作用的发挥影响不同。     

基于IGDT的含广义储能的独立直流微网日前优化调度

微电网的能量管理与优化调度作为构建新型电力系统的重要环节,提高其可再生能源的消纳水平、降低源荷不确定性风险以及优化系统运行成本具有重要意义。因此,文中提出一种基于信息间隙决策理论(information gap decision theory, IGDT)的含广义储能的独立直流微电网日前优化调度模型。首先,构建含超级电容的混合储能系统,以降低蓄电池运行成本,将具备虚拟储能特性的柔性负荷与混合储能相结合,形成广义储能,充分发挥微电网系统内灵活性资源特性;其次,考虑系统风光荷不确定性,引入IGDT模型,在确定性模型基础上建立风险规避策略下的鲁棒模型和风险投机策略下的机会模型,从2种决策角度追求降低风险与最大化收益;最后,基于算例仿真分析,证明该调度策略在降低微电网运行成本的基础上可量化不确定性因素对系统调度决策的影响,验证了模型的有效性和可参考性。     

基于可能度的冷热电联供微网区间优化调度模型

提出了含多种能量转换途径的冷热电联供微网非线性区间优化调度模型。首先,以充分利用光伏、风电等新能源为目标,确定了实现电冷、电热、热冷能量转化的灵活冷热电联供微网系统。然后以此系统为对象,针对光伏、风电、冷热电负荷随机性问题,考虑分时电价、环境效益等因素,建立以系统综合运行成本最低为目标的非线性区间优化模型。根据区间可能度模型,将不确定性模型转化为确定性模型,结合改进粒子群算法进行求解。最后通过算例验证了该模型的合理性、灵活性,并结合仿真结果分析了区间可能度和负荷波动对综合运行成本的影响。     

基于㶲经济学的综合能源系统动态冷热电成本

多能流耦合的综合能源系统(IES)成本分摊是综合能源服务研究的一个关键技术问题。现有IES产品成本计算未虑能量品位的影响,并且对含储能的IES成本变化缺乏深入研究。以热力学第二定律为基础,建立IES动态㶲经济学模型,并以某园区综合能源系统为例,研究动态负荷以及储能工况对系统冷热电成本的影响。结果表明：储热装置能够有效降低单位冷热电成本;相较无储热工况,在储热工况下系统单位冷、热、电成本分别降低6%、24%、1.2%;此外,储热工况下的IES冷热电平均成本与电负荷成正相关,与冷热负荷呈负相关。动态㶲经济学模型能够高效地分析含储热的IES在优化周期内的逐时冷热电成本,为冷热电实时定价提供依据,合理利用储能装置能够降低冷热电产品的成本,有助于内燃机消纳,提高系统运行的稳定性和经济性。     

基于㶲经济学的综合能源系统动态冷热电成本

多能流耦合的综合能源系统(IES)成本分摊是综合能源服务研究的一个关键技术问题。现有IES产品成本计算未虑能量品位的影响,并且对含储能的IES成本变化缺乏深入研究。以热力学第二定律为基础,建立IES动态㶲经济学模型,并以某园区综合能源系统为例,研究动态负荷以及储能工况对系统冷热电成本的影响。结果表明：储热装置能够有效降低单位冷热电成本;相较无储热工况,在储热工况下系统单位冷、热、电成本分别降低6%、24%、1.2%;此外,储热工况下的IES冷热电平均成本与电负荷成正相关,与冷热负荷呈负相关。动态㶲经济学模型能够高效地分析含储热的IES在优化周期内的逐时冷热电成本,为冷热电实时定价提供依据,合理利用储能装置能够降低冷热电产品的成本,有助于内燃机消纳,提高系统运行的稳定性和经济性。     

Estimating the variance of production cost using a stochastic loadmodel

The purpose of this paper is to provide a realistic load variation model to be used in short-term (one to three years) planning studies. A stochastic model is proposed, and this model is used to quantify the variation of the estimated production cost that is directly affected by the load uncertainty. The paper presents a method of estimating the variation of production cost. This is the first paper to use a Gauss-Markov stochastic model of load with a chronological production simulation model. This load model captures the stochastic load variation behavior and the correlation between weekly peak demand and weekly energy. A weekly Gauss-Markov sampling scheme is incorporated in the proposed approach to model load variation. This stochastic load model is used to generate sample chronological load profiles that represent the annual load variation in weekly detail. These load profiles are then used in annual Monte Carlo production simulation. Case studies illustrate the implementation of this stochastic load variation modeling. These case studies illustrate that load uncertainty has a significantly larger effect on cost uncertainty than does uncertainty in unit availability     

计及可靠性的电力市场分时定价方法

发电上网分时电价与当时的发电燃料边际成本及供电风险密切相关,随机生产模拟计算可以给出系统的最优发电方式、燃料费用、边际发电成本及系统可靠性指标。在随机生产模拟计算的基础上,提出了3种既考虑电能成本又考虑风险成本（可靠性成本）的分时电价制定方案,并以某实际系统为例计算出典型日运行方式下每种方案的分时电价,同时统计出该运行方式下的峰、腰、谷分时电价比,为电网实现分时电价提供了参考和依据。     

基于扩展序列运算的含不确定性需求响应电力系统优化调度

未来高比例可再生能源的随机性给电力系统运行带来了前所未有的挑战,灵活性资源的不足限制了可再生能源的发展,柔性负荷可作为一种灵活性资源参与电力系统的调峰和备用。文中根据响应机制的不同,将柔性负荷分为激励型负荷和价格型负荷两种。基于扩展概率性序列运算理论,分别建立表征激励型负荷和价格型负荷响应不确定性的概率模型,表征风电出力不确定性的概率模型也随之建立。在此基础上,以应对风电波动性和随机性为背景,基于风险约束和风险成本理论,构建了同时考虑风电出力和需求响应不确定性的电力系统日前优化调度模型。针对构建的随机优化问题,文中通过序列运算对机会约束条件进行转化,将其转化为一个约束条件为线性的确定性优化问题进行求解。最后,通过仿真算例验证了模型的有效性,并分析了序列运算应用于不确定性问题的实用价值。     

Stochastic models for power generation system production costs

Production costing models are widely used in the electric power industry for the purpose of generation capacity expansion planning, fuel management, and operational planning. These models account for the load variation over time and generator outages. A widely used model, due to Balériaux and Booth, yields a prediction of the expected production costs and is based on the load duration curve and forced outage rate of the generating units. This paper highlights the fact that, in order to obtain a more detailed characterization of the probability distribution costs beyond the expected value, a model involving the stochastic processes underlying the generator outages is necessary. A stochastic model is considered as an enhancement to the traditional Balériaux model. It is shown that Monte Carlo simulation can be routinely used on the enhanced model to provide answers concerning the distribution of production costs. Monte Carlo methods avoid the problems associated with the complexity of the analytical methods. Numerical examples are given using the enhanced model where load is considered to be either a deterministic or stochastic time-varying function. An example is given using decision analysis where a possible use of the more detailed information on the probability distribution of production costs in generation system planning is illustrated.     

基于改进人工蜂群算法的家庭储能容量优化配置*

家庭能源系统中的储能设备初始投资成本高,限制其实际应用。针对此问题,文章对混合储能的容量配置进行了研究。分别构建了刚性负荷、柔性负荷和储能类设备负荷模型;在此基础上搭建以用户每天用电费用最低为目标的家庭能源管理系统模型;提出一种改进的人工蜂群算法对模型求解。实验结果表明,通过和单储能的系统相比,在满足用户用电需求的同时,配置混合储能的家庭能源系统能有效减小用户每天用电费用。对文中算法与人工蜂群算法和粒子群算法优化结果进行比对,证实所提算法优化时长短、收敛速度快且不易于陷入局部最优。