Two-stage ADMM-based distributed optimal reactive power control method for wind farms considering wake effects

Since the connection of small-scale wind farms to distribution networks,power grid voltage stability has been reduced with increasing wind penetration in recent years,owing to the variable reactive power consumption of wind generators.In this study,a two-stage reactive power optimization method based on the alternating direction method of multipliers(ADMM)algorithm is proposed for achieving optimal reactive power dispatch in wind farm-integrated distribution systems.Unlike existing optimal reactive power control methods,the proposed method enables distributed reactive power flow optimization with a two-stage optimization structure.Furthermore,under the partition concept,the consensus protocol is not needed to solve the optimization problems.In this method,the influence of the wake effect of each wind turbine is also considered in the control design.Simulation results for a mid-voltage distribution system based on MATLAB verified the effectiveness of the proposed method.

Optimal Power Flow in Electrical Microgrids

This paper presents in the first place, the state of art relating to the methods to solve optimal power flows (OPF) and its application in electrical microgrids. Afterwards, a mathematical algorithm based on the gradient method is proposed for the application of OPF in a low power microgrid, in order to improve the voltages profiles and consequently reduce the active power losses. Finally, the proposed algorithm is implemented in a low power microgrid to demonstrate the effectiveness of the method.

Security Constrained Distributed Optimal Power Flow of Interconnected Power Systems

The security constrained distributed optimal power flow （DOPF） of interconnected power systems is presented. The centralized OPF problem of the multi-area power systems is decomposed into independent DOPF subproblems, one for each area. The dynamic security region （DSR） to guarantee the transient stability constraints and static voltage stability region （SVSR） constraints, and line current limits are included as constraints. The solutions to the DOPF subproblems of the different areas are coordinated through a pricing mechanism until they converge to the centralized OPF solution. The nonlinear DOPF subproblem is solved by predictor-corrector interior point method （PClPM）. The IEEE three-area RTS-96 system is worked out in order to demonstrate the effectiveness of the proposed method.

Solving Load Flow Problems of Power System by Explicit Pseudo-Transient Continuation (E-ψtc) Method

This paper is a further study of two papers [1] and [2], which were related to Ill-Conditioned Load Flow Problems and were published by IEEE Trans. PAS. The authors of this paper have some different opinions, for example, the 11-bus system is not an ill-conditioned system. In addition, a new approach to solve Load Flow Problems, E-ψtc, is introduced. It is an explicit method;solving linear equations is not needed. It can handle very tough and very large systems. The advantage of this method has been fully proved by two examples. The authors give this new method a detailed description of how to use it to solve Load Flow Problems and successfully apply it to the 43-bus and the 11-bus systems. The authors also propose a strategy to test the reliability, and by solving gradient equations, this new method can answer if the solution exists or not.

Three-Phase Optimal Power Flow for Study of PV Plant Distributed Impact on Distribution Systems

This paper presents a TOPF （three-phase optimal power flow） model that represents photovoltaic systems. The PV plant is modeled in the TOPF as active and reactive power source. Reactive power can be generated or absorbed using the available capacity and the adjustable power factor of the inverter. The reduction of unbalance voltage and losses in the distribution systems is obtained by actions of reactive power control of the inverter. The TOPF is formulated by current balance equations and the PV systems are modeled via an equivalent circuit. The primal-dual interior point method is used to obtain the optimal operating points for the systems for different scenarios of solar irradiance and temperature, thus providing a detailed view of the impact of photovoltaic distributed generation.

A Novel Location Method for Interline Power Flow Controllers Based on Entropy Theory

As one of the new generation flexible AC transmission systems(FACTS)devices,the interline power flow controller(IPFC)has the significant advantage of simultaneously regulating the power flow of multiple lines.Nevertheless,how to choose the appropriate location for the IPFC converters has not been discussed thoroughly.To solve this problem,this paper proposes a novel location method for IPFC using entropy theory.To clarify IPFC’s impact on system power flow,its operation mechanism and control strategies of different types of serial converters are discussed.Subsequently,to clarify the system power flow characteristic suitable for device location analysis,the entropy concept is introduced.In this process,the power flow distribution entropy index is used as an optimization index.Using this index as a foundation,the power flow transfer entropy index is also generated and proposed for the IPFC location determination study.Finally,electromechanical electromagnetic hybrid simulations based on ADPSS are implemented for validation.These are tested in a practical power grid with over 800 nodes.A modular multilevel converter(MMC)-based IPFC electromagnetic model is also established for precise verification.The results show that the proposed method can quickly and efficiently complete optimized IPFC location and support IPFC to determine an optimal adjustment in the N-1 fault cases.

Design and Power Flow Analysis of Electrical System Using Electrical Transient and Program Software

Power flow analysis is a numerical way of study of behavior of flow of electric power in an interconnected system. In order to meet the growing demands of electrical energy in an optimum way, there is a need to upgrade existing systems or to install new systems. Therefore, planning of new installations and determination of best operating conditions of existing systems need power flow analysis. In this way, cost/benefit ratio for both suppliers and customers is maintained. This research involves the design and power flow analysis of IEEE-14 bus system. Newton Raphson method is applied for better efficiency and reduced computational time. Simulation analysis is conducted in ETAP software because of its excessive used in real life systems.

New Variants of Newton’s Method for Nonlinear Unconstrained Optimization Problems

In this paper, we propose new variants of Newton’s method based on quadrature formula and power mean for solving nonlinear unconstrained optimization problems. It is proved that the order of convergence of the proposed family is three. Numerical comparisons are made to show the performance of the presented methods. Furthermore, numerical experiments demonstrate that the logarithmic mean Newton’s method outperform the classical Newton’s and other variants of Newton’s method. MSC: 65H05.

风电数据的不确定性建模及在电网规划的应用

在我国经济高速发展的同时,矿物资源的使用持续增长,对环境的污染也在不断加剧,发展风力发电是我国实现低碳转型的一项重要措施。然而,由于风力发电具有较强的不稳定性,这给电网的运行带来了较大的不确定性。因此,考虑风力发电过程中的不确定性因素,并对其进行建模,开展含风力发电的电网规划研究。首先对风电出力的不确定性进行建模,建立了风电机组出力的数学模型。其次,提出了以总成本、总网损最小为目标函数的考虑风电不确定性的最优潮流模型,并给出一种采用局部模型并引入动态惯性权重系数改进的粒子群优化求解算法。经采用实际的风电数据进行实验,结果表明与传统的粒子群优化算法相比,改进的粒子群优化算法在求解速度、收敛性以及稳健性方面均具有更优性能。

基于VPP碳流计算的多目标多时间尺度优化调度

为研究虚拟电厂低碳经济运行策略,以虚拟电厂能流和碳流模型为基础,执行了多目标多时间尺度优化调度。首先,基于碳流走向建立虚拟电厂低碳经济运行的非线性多目标规划模型,并采用归一化法向约束法进行求解。然后,建立了基于动态矩阵控制算法的有限时域优化模型,对日前结果进行跟踪优化和反馈校正,以降低不确定性因素的影响。最后,仿真对比实验验证了所提调度策略能在保证碳流计算精度超过95%的前提下实现虚拟电厂低碳经济运行。

计及不确定性的随机暂态稳定约束最优潮流

为应对电力系统中不确定性对系统安全稳定造成的显著影响,提出一种计及不确定性的随机暂态稳定约束最优潮流方法。首先,采用威布尔和正态分布分别描述风电和负荷两种不确定性变量。其次,设置相应的置信水平,基于机会约束理论建立相应的概率约束,以期望值形式表达目标函数,从而建立计及不确定性的随机暂态稳定约束最优潮流模型。然后,通过半不变量法和Gram-Charlier级数求取电力系统输出变量的累积分布函数,并利用改进量子粒子群算法进行求解。最后,算例分析验证了所提方法的优越性和有效性。

基于混沌与Pseudo-Newton法组合优化的直接衰减正弦原子库分解方法在低频振荡分析中的应用

传统原子库分解法在对信号进行分解时，往往先将信号分解为较易离散化的Gabor原子，再转化为衰减正弦原子，由于Gabor原子库并不符合振荡信号的本质特性，加之转化过程为近似转化，使分解存在双重误差。为克服以上不足，提出一种新的低频振荡分析方法，即基于混沌与Pseudo-Newton法组合优化的直接衰减正弦原子库分解方法。为了解决离散困难和六维空间寻优效率低的问题，采用混沌与Pseudo-Newton法组合优化方法，可以同时对6个参数进行寻优，极大的提高方法的速度。通过对自合成信号、仿真信号、华中电网能量管理单元实测信号等3个算例进行分析，并与其他2种辨识方法进行对比，表明该文算法在计算精度、辨识速度、抗噪能力方面都有较大优势。

基于PCE的系统参数化暂态稳定约束最优潮流

为更好地应对电力系统中存在的不确定参数给暂态稳定性带来的影响,提出了一种基于多项式混沌展开(polynomial chaos expansion,PCE)和随机伽辽金法(stochastic Galerkin method,SGM)的参数化暂态稳定约束最优潮流(parameterized transient stability constrained optimal power flow,PTSCOPF)问题的求解方案。针对电力系统不确定参数建立PTSCOPF模型;基于PCE和SGM近似拟合参数化暂态稳定轨迹,将原始的微分代数方程组(differential algebraic equations,DAE)形式的PTSCOPF模型转化为代数方程组形式的参数化非线性规划(non-linear programming,NLP)问题;采用原始-对偶内点法求解该NLP问题。利用改进的新英格兰10机39节点系统算例进行了各项测试,仿真结果表明,所提方法能够实现系统在预想故障下保持暂态稳定的优化效果。

二阶Newton法训练径向基函数神经网络的算法研究

提出了一种混合加权距离测量(weighted distance measure,weighted DM)参数的构建和训练RBF(radial basis function)神经网络的两步批处理算法.该算法在引进了DM系数参数的基础上,采用Newton法分别对径向基函数的覆盖参数、均值向量参数、加权距离测度系数以及输出权值进行了优化,并在优化过程中利用OLS(orthogonal least squares)法来求解Newton法的方程组.通过实验数据,不仅分析了Newton法优化的各个参数向量对RBF网络训练的影响,而且比较了混合优化加权DM与RLS-RBF(recursive least square RBF neural network)网络训练算法的收敛性和计算成本.所得到的结论表明整合了优化参数的加权DM-RBF网络训练算法收敛速度比RLS-RBF网络训练算法更快,而且具有比LM-RBF(Levenberg-Marquardt RBF)训练算法更小的计算成本,从而说明OLS求解的Newton法对优化RBF网络参数具有重要应用价值.

基于改进ADMM的含分布式光伏的配电网电压无功优化方法

由于所建立含分布式光伏(PV)的有源配电网电压无功优化模型是一个典型的非凸混合整数非线性优化模型,提出一种改进交替方向乘子法(ADMM)来求解含分布式光伏的配电网电压无功优化问题。首先以有载调压变压器和投切电容器组为例,建立一种新的广义可分解有源配电网电压无功优化模型,然后根据ADMM算法将有源配电网电压无功优化模型分解为2个子问题求解,并设计惩罚参数的自适应调节机制以加速收敛。在3个不同规模有源配电网算例上进行仿真测试,结果表明,所提出改进ADMM方法具有较好的收敛性和最优解。

基于分区选择的主动配电网分布式最优潮流分析

基于交替方向乘子法(ADMM)在分布式形式下解决主动配电系统最优潮流问题(OPF),针对分布式算法性能受到配电系统区域划分影响的问题,提出了一种基于量测数据驱动的电网分区方法,以加速优化算法的收敛速度。与传统的ADMM算法依赖于全局信息不同,本文引入了一致性方法来协调区域交界的平衡问题,从而实现最优潮流问题的完全分布式求解。此外,本文采用LinDistFlow(Linearized Distribution Flow)交流近似模型来应对配电网最优潮流问题的非凸性挑战。通过在不同规模的IEEE配电网案例上进行测试,验证了所提方法的有效性,且其在优化算法的迭代次数、计算时间和误差精度等性能上均优于其他分区方法。

基于概率最优潮流的电力系统灵活性量化评估方法

可再生能源发电具有波动性和随机性,高比例可再生能源的接入给电力系统的灵活性带来挑战。为此,提出一种基于概率最优潮流的电力系统灵活性量化评估方法。首先,构建电力系统灵活性资源模型。采用k-means聚类方法处理历史数据以生成场景,基于马尔可夫链模型和Copula函数构建考虑时间相关性的风电、光伏出力及负荷波动概率模型。其次,将经济成本与系统灵活性关联,在考虑系统灵活性裕度期望、缺额期望和不足概率的基础上,建立计及运行经济性的量化评估指标。第三,构建含灵活性资源的概率最优潮流模型,采用蒙特卡罗模拟方法和基于跟踪中心轨迹内点法估计系统状态和评估指标。以IEEE RTS-24系统为算例进行分析,结果表明合理配置可再生能源和储能装置有助于提升系统灵活性和运行经济性。

一种改进的Newton算法在电力系统潮流计算中的研究与应用

为了提高电力系统潮流计算的计算速度,适应不断发展的电力系统规模和多区域电网的互联运行,文章在分Newton-Raphson潮流算法存在的缺点的基础上,对离散Newton法和修正Newton法进行了比较,提出了一种基于二者的改进算法并将其用于电力系统潮流计算。该算法无需计算Jacobi矩阵,迭代次数更少,比Newton法具有更高的效率。利用IEEE57及IEEE300母线标准试验系统验证,结果表明在相同的收敛精度下,该算法具有更高的收敛速度,是一种可供实际运用的方法。

ILU预处理Newton-Krylov方法的潮流计算

由于电力系统修正方程组具有高维、稀疏的特点,本文提出将预处理Krylov子空间方法应用于潮流修正方程组的求解,形成预处理Newton-Krylov的潮流计算方法。结合ILU预处理方法,比较了最常用的3类Newton-Krylov方法求解潮流方程的计算效果。通过对IEEE30、IEEE118、IEEE300和3个Poland大规模电力系统进行潮流计算,结果表明:3类Newton-Krylov方法是电力系统潮流计算的有效方法,呈现出良好的收敛特性和计算效率。

基于配点法的参数化暂态稳定性约束的电力最优潮流分析

为实现针对暂态稳定约束最优潮流的精确描述,提出一套参数化TSCOPF模型。通过该模型来判定电力系统中可变参数与TSCOPF解之间的定量关系。借助可变参数的多项式表达式来逼近参数化TSCOPF的最优解。在此基础上,只需在参数化TSCOPF中代入电力系统的可变参数即可取得符合暂态稳定性的最优控制方案。