电力系统无功优化的内点非线性互补约束算法

建立了一种含离散变量的电力系统无功优化的非线性互补约束模型,并提出相应的现代内点非线性互补算法。该方法先将变压器抽头和电容器组数等离散变量按连续化处理,进行无功优化计算,快速寻求离散变量的两界;用所得结果作为初始解,以离散变量的两界构造其互补约束条件。该方法有效地解决了传统方法求解离散量存在的时间与精度之间的矛盾,可精确求解无功优化中可调变压器抽头和可调电容器组别。经多个测试系统的计算结果表明,算法具有收敛性好、计算迅速的特点,能有效地解决含离散变量的大规模电力系统无功优化问题,满足在线运行的需要。     

An on-line relay coordination algorithm for adaptive protectionusing linear programming technique

An adaptive system for protecting a distribution network should determine and implement relay settings that are most appropriate for the prevailing state of the power system. This paper presents a technique for determining coordinated relay settings. The technique uses the Simplex two-phase method; Phase I determines whether the constraints selected for illustrating the conditionality between primary and back up relays are feasible, and Phase II finds the optimal relay settings. A looped distribution system, protected by directional overcurrent relays, was used for testing the technique. The tests were conducted in a laboratory environment; some results from those tests are reported in the paper     

A homogeneous linear programming algorithm for the securityconstrained economic dispatch problem

This paper presents a study of the simplified homogeneous and self-dual (SHSD) linear programming (LP) interior point algorithm applied to the security constrained economic dispatch (SCED) problem. Unlike other interior point SCED applications that consider only the N security problem, this paper considers both (N-1) and (N-2) network security conditions. An important feature of the optimizing interior point LP algorithm is that it can detect infeasibility of the SCED problem reliably. This feature is particularly important in SCED applications since line overloading following a contingency often results in an infeasible schedule. The proposed method is demonstrated on the IEEE 24 bus test system and a practical 175 bus network. A comparison is carried out with the predictor-corrector interior point algorithm for the SCED problem presented previously (see ibid., vol. 12, no.2, p.803-10, 1997)     

A hybrid genetic algorithm for optimal reactive power planningbased upon successive linear programming

A hybrid methodology is presented for the solution of the problem of the optimal allocation of reactive power sources. The technique is based upon a modified genetic algorithm, which is applied at an upper level stage, and a successive linear program at a lower level stage. The objective is the minimization of the total cost associated to the installation of the new sources. The genetic algorithm is devoted to defining the location of the new reactive power sources, and therefore to handle the combinatorial nature of the fixed costs problem. At the lower level, the variable cost problem is solved by calculating the magnitude of the sources to be installed at the previously determined locations by means of a linear program iterated successively with a fast decoupled load flow. Results are presented for the application of the proposed methodology when applied to the Venezuelan electric network     

A reliable and efficient linear programming algorithm for two-level power system state estimation

Two linear programming (LP) algorithms for the integrated state estimation (ISE) for the whole system are formulated and tested. It was found that a direct application of an ISE on a large power system suffers certain limitations. This paper presents an efficient and reliable two-level state estimator (TLSE) based on LP techniques. Both the ISE and the proposed TLSE were tested under different conditions. The results are discussed and comparisons are given which show that the TLSE has many advantages over the ISE.     

基于整数线性规划的配电网故障定位容错算法

为了提高配电网馈线故障定位的速度和容错能力,提出一种基于整数线性规划模型的配电网故障区段定位容错算法。将各馈线终端单元(Feeder Terminal Unit, FTU)的漏报、误报状况和馈线状态作为决策变量,基于最小故障诊断集理论,建立计及FTU漏报、误报信息的故障定位模型。针对逻辑运算在求解大规模配电网故障区段时建模复杂、算法受限的问题,构建基于代数关系运算的开关函数,并提出一种逻辑关系线性化策略将约束条件线性化。所建模型采用具有良好数值稳定性的常规优化方法进行决策,以保证解的全局最优性。仿真算例表明,所提方法定位准确高效、容错性强,在正确定位故障馈线区段的同时能获取具体节点的漏报、误报状况,适用于多节点过流信息发生畸变的大型配电网络。     

基于线性规划灵敏度分析的发电机组市场力实时监控方法

衡量发电机组市场力的现有方法多不适用于实际系统的市场力实时定量计算,具有很大的局限性。基于线性规划LP(LinearProgramming)方法求解最优潮流OPF(OptimalPowerFlow),利用带上界变量的单纯形法推出反映机组投标变化对其收入影响的灵敏度矩阵,可以用来实时判定发电机组是否拥有市场力,并衡量其大小。相应矩阵元素为正值,采取抬高投标价格策略时收入增加会多,正值越大机组市场力越强;相应矩阵元素为负值,采取降低投标容量策略时其收入增加也多,负值绝对值越大机组市场力越强。该方法可作为系统操作员实时监控市场势力的依据,有较强的实用性。     

Optimal reactive power planning using evolutionary algorithms: acomparative study for evolutionary programming, evolutionary strategy,genetic algorithm, and linear programming

This paper presents a comparative study for three evolutionary algorithms (EAs) to the optimal reactive power planning (ORPP) problem: evolutionary programming, evolutionary strategy, and genetic algorithm. The ORPP problem is decomposed into P- and Q-optimization modules, and each module is optimized by the EAs in an iterative manner to obtain the global solution. The EA methods for the ORPP problem are evaluated against the IEEE 30-bus system as a common testbed, and the results are compared against each other and with those of linear programming     

Economic dispatch of active power by quadrativ programming using a sparse linear complementary algorithm

A new method for economic dispatch of active power is presented. Formulation of the problem as a quadratic program allows the inclusion of a linear network model and operational constraints together with an explicit representation of the cost incurred by transmission losses. The problem is solved by a linear complementary pivoting algorithm which takes full advantage of the sparse form of the objective function and constraints. Computational experience indicates that the method is highly efficient and is capable of solving realistic problems in elapsed times that are compatible with online applications using minicomputer hardware.     

Dual programming methods for large-scale thermal generationscheduling

The problem of thermal generation scheduling is considered in the framework of the short-term hydro-thermal coordination problem. Dual programming methods are applied to the large-scale problem deriving from a fine subdivision of the daily optimization horizon for networks with hundreds of thermal units. The starting point for the dual approach is obtained from the solution of a thermal scheduling problem with discarded generation ramp-rate constraints. The relaxed daily scheduling decouples into as many smaller dispatch problems as the number of subintervals. Two dual programming methods are implemented: the former is the dual active set algorithm by Goldfarb and Idnani while the latter is based on the application of continuation method techniques. These approaches are extensively tested with reference to both a small sample system and to the daily thermal generation scheduling of the Italian (ENEL) system (over 100 thermal units and 96 quarter hour subintervals). Incorporating the dual programming approach within the ENEL hydro-thermal coordination procedure is also considered     

A bad data identification method for linear programming stateestimation

The author presents a bad-data identification procedure for linear programming (LP) power system static state estimation. LP state estimators minimize the weighted sum of the absolute values of the measurement residuals. The proposed procedure first detects the bad data using the measurement residuals of those measurements rejected by the LP estimator. Then the bad measurement is identified and eliminated by estimating the measurement errors of the zero residual measurements. The residuals obtained from this second estimation step are made use of for this purpose. In order to minimize the computational burden during the elimination cycles, a fast way of eliminating measurements through weight changing is also presented. The performance of the proposed procedure is tested and the results are presented, using AEP's 14, 30, 57 and 118     

Neural network for non-linear programming with linear equality constraints

This paper presents a simplified approach to neural optimization in the presence of linear equality constraints. In contrast to the standard Lagrangian approach, the constraints simplify the final neural circuit instead of complicating it. the number of elements used is also significantly reduced. Instead of n + t integrators we need only n – t. There is also a similar saving in the number of preprocessing non-linear devices. Elimination of the constraints allows a large speed-up of the solution.     

含抽水蓄能电网安全约束机组组合问题的混合整数线性规划算法

抽水蓄能机组的投运对电网发电调度计划的制定具有很大影响,建立了含抽水蓄能机组电网的安全约束机组组合模型。以考虑了抽水蓄能机组启停费用的所有机组总运行费用为目标函数,根据抽水蓄能机组的不同运行工况给出旋转备用容量的解析表达式,同时在系统功率平衡约束中考虑了网络损耗的影响,并考虑了抽水蓄能机组的运行调度约束及网络安全约束。为了保证模型求解的可靠性和提高模型求解的计算效率,将目标函数进行分段线性化,并根据抽水蓄能机组的运行特点将其旋转备用容量约束等价转化为线性表达式。同时采用一种动态分段线性化方法近似逼近网络损耗,从而将机组组合模型转化为混合整数线性规划模型,并采用成熟的数学优化求解器CPLEX进行求解。对某实际23机306节点电网算例的计算结果表明,所提出的混合整数线性规划调度模型的网损逼近效果合理正确,算法求解速度快,具有较好的工程实用价值。     

A linear programming approach to online set membership parameter estimation for linear regression models

This paper presents a new technique for online set membership parameter estimation of linear regression models affected by unknown‐but‐bounded noise. An orthotopic approximation of the set of feasible parameters is updated at each time step. The proposed technique relies on the solution of a suitable linear program, whenever a new measurement leads to a reduction of the approximating orthotope. The key idea for preventing the size of the linear programs from steadily increasing is to propagate only the binding constraints of these optimization problems. Numerical studies show that the new approach outperforms existing recursive set approximation techniques, while keeping the required computational burden within the same order of magnitude. Copyright © 2016 John Wiley & Sons, Ltd.     

Interior-point methods and their applications to power systems: aclassification of publications and software codes

Since Karmarkar's first successful interior-point algorithm for linear programming in 1984, the interest and consequently the number of publications in the area have increased tremendously, leaving the newcomers to the field trapped in a jungle of papers and reports. In this paper,the authors review and classify major publications on interior-point methods theory, on the practical implementation of the most successful interior-point algorithms, and on their applications to power systems optimization problems. A listing of state-of-the-art interior-point software codes and major online research resources on the Internet are included     

Robustness of convergence in finite time for linear programming neural networks

A recent work has introduced a class of neural networks for solving linear programming problems, where all trajectories converge toward the global optimal solution in finite time. In this paper, it is shown that global convergence in finite time is robust with respect to tolerances in the electronic implementation, and an estimate of the allowed perturbations preserving convergence is obtained. Copyright © 2006 John Wiley & Sons, Ltd.     

基于动态规划算法的配电网孤岛划分策略

配电网发生故障后,失电区域内应该形成含分布式电源(DG)的电力孤岛保证负荷供电的连续性。在孤岛形成算法中充分考虑负荷等级及其可控性,建立孤岛划分问题的数学模型,并利用动态规划算法形成含单DG或多DG组合的初级孤岛划分方案;根据一定的规则修正初级孤岛,形成次级孤岛;校验岛内各负荷点的电压和潮流约束,确定最优孤岛。算例验证了所提模型的有效性和优越性。     

Design algorithm for gearless elevator winches based on discrete programming

A design algorithm for gearless elevator winches with a frequency-controlled electric drive is developed on the basis of discrete programming. The cost-optimal winch design is determined.     

A linear programming model for minimizing U.S. oil consumption

This paper describes applications of a new model which can be used to help minimize oil consumption by electric utilities in the U.S. The model can be employed to determine the theoretical upper bound on oil savings against which performance can be measured. It can also be used to identify oil conservation options on an hourly basis. In conjunction with other models it can be used to determine system additions and contractual changes necessary for exercising these options. Further, the results can be verified by inspection. Test results using actual hourly data for the Eastern Interconnected System indicate that significant oil savings, over and above those already achieved by electricity transfers, may be realizable.     

A successive linear programming model for real-time economic power dispatch with security

A successive linear programming model with penalty terms for solving real-time economic active power dispatch with security is presented in the paper. It maintains the advantages possessed by the linear programming model, that is, rapid calculation, reliable convergency and easy treatment of the N and N — 1 line-security constraints. At the same time, it settles quite accurately the problem of the non-linear cost characteristic by incorporating the differential loss coefficients into the successively linearized objective function. A fictitious generation variable is introduced at each load bus and penalized in the objective function. This, on the one hand, guarantees the solvability of the successive linearization from beginning to end. On the other hand, if there exists a non-zero fictitious generation by the end of the iteration, it indicates that load-shedding is indispensable, and thus we get the optimal position and the value of the load-shedding. The calculation results of the IEEE 30-bus system are given. These results demonstrate that the presented model has the same accuracy as the two non-linear models, while it needs much less computing time.