考虑直流固态断路器通态压降的低压直流配电网最优潮流

在直流固态断路器的实际应用中发现,其通态压降将对低压直流配电网的系统潮流产生不可忽略的影响。因此,文中对考虑直流固态断路器通态压降的低压直流配电网最优潮流(OPF)问题进行研究,建立了只包含连续变量的直流固态断路器稳态模型,从而可以方便地使用现有方法对该问题进行求解。通过RT-Lab仿真实验和对不同电压等级直流配电网的潮流分析可知,对于低压直流配电网而言,直流固态断路器的通态压降不可忽略,否则将导致较大的电压、功率计算误差,严重时将影响系统运行安全。此外,基于RT-Lab仿真平台,分别在考虑和不考虑断路器通态压降的情况下,对低压直流配电网OPF指令的控制效果给予验证。仿真结果表明,在低压直流配电网OPF中,考虑直流固态断路器的通态压降是必要的,并且所得到的指令可较为可靠地控制系统状态使其维持在可行域范围内。     

基于电压源换流器的多端柔性直流输电系统拟交流最优潮流

为便于求解含多端柔性直流输电系统的最优潮流,提出一种拟交流最优潮流计算方法。通过分析电压源换流器的工作原理,建立了计及换流站有功损耗的交流电源型等值电路。针对系统直流网络部分设定约束条件,将其等效为特殊的交流网络。为降低计算复杂度,对换流站的能量耦合方程进行了线性化处理。基于此,含多端柔性直流系统可视为纯交流系统并进行潮流计算。考虑到交流系统最优潮流问题具有非凸特性,将其最优潮流模型松弛为半定规划模型。实验结果表明,所述方法能够有效求解多端柔性直流系统最优潮流问题。     

互联电网的直流最优潮流分解算法研究

研究了大系统互联电网的最优潮流优化策略,基于部分对偶理论分析了电网分区的分解协调模型,提出了一种基于直流最优潮流模型的互联电网多区域分解最优潮流并行求解算法,将一个大的电网互联系统分解成多个区域子问题,每个区域子问题是个典型的二次规划问题,使用直流最优潮流模型来求解互联电网的最优潮流分布,讨论了分区优化收敛条件。通过交换输出电价和边界节点相位角,完成区域间的信息交换。使用上述分解算法对IEEERTS-96算例的多个互联区域进行了分析,结果表明本文算法是一种有效的求解算法,适合大区电网互联后在线分布式动态OPF计算。在电力系统有极大的应用前景。     

基于分布式多步回溯Q(λ)学习的复杂电网最优潮流算法

针对传统最优潮流算法对复杂多目标函数的不适应性以及常规算法难以满足大规模电网计算实时性的要求,本文中提出一种新颖的基于复杂电网分区的最优潮流分布式Q(λ)学习算法,该算法无须对最优潮流数学模型进行辅助处理,不依赖于对象模型,其内部各Agent使用标准的多步Q(λ)算法独立承担各分区子系统的学习任务,通过统一协作从而形成整体意义上的最优,并在IEEE 118节点等标准算例中进行了验证,取得了良好的效果,为解决复杂电网多目标最优潮流问题提供了一种新的可行、有效的方法。     

Optimal power flow solution of power system incorporating stochastic wind power using Gbest guided artificial bee colony algorithm

This paper focuses primarily on implementation of optimal power flow (OPF) problem considering wind power. The stochastic nature of wind speed is modeled using two parameter Weibull probability density function. The economic aspect is examined in view of the system wide social cost, which includes additional costs like expected penalty cost and expected reserves cost to account for wind power generation imbalance. The optimization problem is solved using Gbest guided artificial bee colony optimization algorithm (GABC) and tested on IEEE 30 bus system. The simulation results obtained using proposed method are compared with other methods available in the literature for a case of conventional OPF as well as OPF incorporating stochastic wind. Subsequently an extensive simulation study is conducted to investigate the effect of wind power and different cost components on optimal dispatch and emission. Numerical simulations indicate that the operation cost of system and emission depends upon the transmission system bottlenecks and the intermittency of wind power generation.     

基于半定规划法的含分布式潮流控制器最优潮流

分布式潮流控制器能够灵活地提升现有线路的输电能力,从而降低系统运行成本,但该设备的引入会增加电力系统最优潮流问题的复杂度与非凸程度。针对分布式潮流控制器的结构及原理进行了分析,提出一种简化的稳态功率模型,并考虑到装置运行时各串联单元自身容量限制,给出实际电网中分布式潮流控制器线路的潮流可行域。基于此,采用对初值选取不敏感的半定规划法建立含分布式潮流控制器的系统最优潮流模型,并选用原对偶内点法进行求解。算例测试结果表明,所提方法能有效解决含分布式潮流控制器的系统潮流优化问题。     

应用粒子群优化算法求解可用输电能力

在电力市场环境下,诸多问题(例如实时电价、网络阻塞等)都需要最优潮流作为理想的工具.本文以最优潮流为基础,应用一种简单有效、且收敛性很好的演化计算算法--粒子群优化算法(PSO)进行可用输电能力(ATC)问题的求解.根据约束条件的越限量大小,动态地调整罚函数,在保证全局搜索能力的基础上改进了收敛速度.应用此算法对IEEE-30节点系统进行了可用输电能力计算,并与传统的最优潮流算法进行了比较,结果表明该算法的有效性,具有实用意义.     

Optimal power flow by a fuzzy based hybrid particle swarm optimization approach

This paper presents a fuzzy based hybrid particle swarm optimization (PSO) approach for solving the optimal power flow (OPF) problem with uncertainties. Wind energy systems are being considered in the study power systems. OPF is an optimization problem which minimizes the total thermal unit fuel cost, total emission, and total real power loss while satisfying physical and technical constraints on the network. When performing the OPF problem in conventional methods, the load demand and wind speed must be forecasted to prevent errors. However, actually there are always errors in these forecasted values. A characteristic feature of the proposed fuzzy based hybrid PSO method is that the forecast load demand and wind speed errors can be taken into account using fuzzy sets. Fuzzy set notations in the load demand, wind speed, total fuel cost, total emission, and total real power loss are developed to obtain the optimal setting under an uncertain environment. To demonstrate the effectiveness of the proposed method, the OPF problem is performed on the IEEE 30- and 118-Bus test systems.     

A decentralized solution to the DC-OPF of interconnected power systems

This paper presents a new method for the decentralized solution of the DC optimal power flow (OPF) problem in large interconnected power systems. The method decomposes the overall OPF problem of a multiarea system into independent OPF subproblems, one for each area. The solutions of the OPF subproblems of the different areas are coordinated through a pricing mechanism until they converge to the global OPF solution. The prices used for the coordination of the subproblem solutions are the prices of electricity exchanges between adjacent areas. Test results from the application of the method to the three-area RTS-96 and the Balkan power system are reported.     

基于粒子群优化算法和动态调整罚函数的最优潮流计算

在电力市场环境下,诸多问题(例如实时电价,网络阻塞等)都需要最优潮流作为理想的工具.本文应用了一种简单有效、且收敛性很好的演化计算算法--粒子群优化算法(PSO)进行最优潮流问题的求解.在求解过程中,根据约束条件的越界量大小,动态的调节其罚函数,避免其收敛到局部最小点.应用此算法对IEEE 30 节点系统进行最优潮流计算,并且与线性规划和遗传算法进行了比较,结果表明该算法能够更好的获得全局最优解,具有实用意义.     

求解非光滑燃料费用函数的基于进化规划的机组最优潮流

提出求解具有非光滑燃料费用函数的存在爬坡率限制的最优潮流方法。针对两次、阶梯形、联合循环机组的非光滑燃料费用函数,介绍一个基于进化规划的算法。在该算法中,为避免早熟,交叉操作随后代的数目非线性变化。介绍了所提出的进化算法应用于有线路约束的IEEE30节点系统和印度62节点系统的情况。以MVA为单位的线路潮流直接采用牛顿-拉夫逊法计算。算例证明所提出的进化算法简单,对求解具有非光滑燃料费用函数的存在很多约束的最优潮流问题有效。     

Efficiency improvements in meta-heuristic algorithms to solve the optimal power flow problem

This paper presents three efficient approaches for solving the Optimal Power Flow (OPF) problem using the meta-heuristic algorithms. Mathematically, OPF is formulated as non-linear equality and inequality constrained optimization problem. The main drawback of meta-heuristic algorithm based OPF is the excessive execution time required due to the large number of load flows/power flows needed in the solution process. The proposed efficient approaches uses the concept of incremental power flow model based on sensitivities, and lower, upper bounds of objective function values. By using these approaches, the number of load flows/power flows to be performed are substantially, resulting in the solution speed up. The original advantages of meta-heuristic algorithms, such as ability to handle complex non-linearities, discontinuities in the objective function, discrete variables handling, and multi-objective optimization, are still available in the proposed efficient approaches. The proposed OPF formulation includes the active and reactive power generation limits, Valve Point Loading (VPL) effects and Prohibited Operating Zones (POZs) of generating units. The effectiveness of proposed approaches are examined on the IEEE 30, 118 and 300 bus test systems, and the simulation results confirm the efficiency and superiority of the proposed approaches over the other meta-heuristic algorithms. The proposed efficient approaches are generic enough to use with any type of meta-heuristic algorithm based OPF.     

Optimal power flow solution of two-terminal HVDC systems using genetic algorithm

The usage extensively of high voltage direct current (HVDC) transmission links in recent years makes it necessary further work in this area. Therefore, two-terminal HVDC transmission link is one of most important elements in electrical power systems. HVDC link representation is mostly ignored and simplified for optimal power flow (OPF) studies in power systems. OPF problem of purely alternating current (AC) power systems is defined as minimization of the fuel cost to subjected equality and inequality constraints. Hence, OPF software of purely AC power systems is extended by taking into consideration power transfer control characteristics of HVDC links. In this paper, OPF problem of integrated AC–DC power systems is first solved by genetic algorithm that is a heuristic algorithm based on evolutionary. The proposed method is tested on two test systems which are the modified 5-node test system and the modified WSCC 9-bus test system. In order to show effectiveness and efficiency of the proposed method, the obtained results are compared to that reported in the literature.     

考虑不确定性因素的模糊最优潮流的发展

近年来,模糊集理论应用于求解电力系统最优潮流中的不确定性问题已取得很大的进展,在某些方面已趋向实用化,但仍有许多问题有待进一步深入研究。本文综述了模糊集理论应用于求解考虑不确定性因素的最优潮流问题的研究现状,并对其发展趋势进行了预测。     

基于树木生长算法的含UPFC的最优潮流计算

最优潮流(OPF)计算是一个非凸优化问题,统一潮流控制器(UPFC)的引入增加了OPF问题的非凸程度,使得基于内点法的传统优化算法难以获取全局最优解。文中提出基于树木生长算法(TGA)的计及UPFC的最优潮流计算方法,将发电成本与有功网损、电压偏移加权作为目标函数,并考虑网络与UPFC设备的安全运行约束,优化了OPF模型。最后基于IEEE 30节点系统以及南京西环网116节点实际系统进行算例测试,对比TGA、粒子群与内点法的结果,并使用蒙特卡洛方法对不同的启发式算法分别进行50次计算,验证了TGA具有更好的求解精度与鲁棒性。     

基于特征降维与分块的输电网概率最优潮流深度学习方法

概率最优潮流需要对非线性最优潮流问题进行重复求解，计算量较大，从而限制了其应用。提出一种基于特征降维、分块和深度神经网络辅助预测的最优潮流两阶段求解方法。在第一阶段，提出基于深度神经网络的最优潮流部分关键决策变量的优先辨识策略，以解决深度学习中因特征维度过高而导致的数值湮没问题，进而以最优潮流的结果特征为导向，基于关联性分析和聚类分析挖掘最优潮流输入与输出特征的关联性匹配度，并构建样本数据的分块特征库，以降低学习难度。在第二阶段，利用深度神经网络完成部分关键决策变量的分块映射，基于潮流模型恢复剩余状态变量，并对计算结果不收敛、不满足约束的情况进行修正，以恢复可行性。根据最优潮流两阶段求解方法构建概率最优潮流求解方法。仿真结果表明所提方法在最优潮流、概率最优潮流的求解速度和求解精度上均有较好的表现。     

含UPFC的灵活交流输电系统最优潮流控制

潮流计算和无功优化计算是电力系统非常重要的计算,两者都包括在电力系统最优潮流（OPF）问题中,灵活交流输电系统（FACTS）的出现需要对传统的潮流计算进行修正,利用遗传算法探讨了含统一潮流控制器（UPFC）的灵活交流输电系统最优潮注控制问题,计算机仿真表明,该方法可有效解决含UPFC的灵活交流输电最优潮流控制。     

含VSC-HVDC交直流系统精确化离散最优潮流的研究

原对偶内点法在求解含电压源换流器的高压输电(Voltage source converter based high voltage direct current,VSC-HVDC)的交直流系统最优潮流(Optimal power flow,OPF)问题时,有较高的效率与准确性,但是无法很好地解决含离散变量的OPF(如无功优化),而智能算法在解决此类问题时易于陷入局部最优解,同时计算时间过长。因此提出一种含离散惩罚函数的混合内点法算法。算法的主要思想是以内点法为框架,对连续变量进行优化,在当对偶间隙小于一定值时,对离散量的计算中引入罚函数,同时随着迭代量差值的变化随时调整罚函数的罚因子的大小。通过算例表明,该算法稳定性高,寻优能力强,能够很好地解决含VSC-HVDC交直流系统的离散变量的优化问题。     

求解最优潮流问题的内点半定规划法

基于内点半定规划(semi-definite programming,SDP),提出一种求解最优潮流(optimal power flow,OPF)的新方法--SDP-OPF法。该方法将非凸OPF问题等价转换为半定规划问题,然后应用原始-对偶内点法求解。根据OPF半定规划模型的特点,采用基于半定规划的稀疏技术,使存储效率和计算性能得以大幅度提高。以4节点的简单电力系统为例,展示模型等价转换的过程及如何获取原OPF问题的解。IEEE-300节点等6个标准系统的仿真计算表明：所提算法具有超线性收敛性,其计算结果与内点非线性规划的结果一致,且能保证解的全局最优性,可在多项式时间内完成,是一种应用前景广阔的方法。     

基于线性最优潮流的电力系统新能源承载能力分析

随着能源结构的深化调整,可再生能源在电力系统中的渗透率逐步提高,而其出力的波动性和随机性对电力系统的稳定运行带来了新的挑战.科学地评估电力系统对新能源的承载能力,对于含高比例新能源电力系统的规划和运行具有重要意义.建立电力系统中新能源承载能力的线性最优潮流(optimal power flow,OPF)模型.针对电力系...