具有爬升约束机组组合的充分必要条件

在Lagrangian松弛框架下，很难确定机组组合问题的一个可行解是否可通过调整对偶机组组合而获得。对于具有爬升约束的机组组合调度问题来说，由于机组出力在连续的2个开机区间的耦合性，求解可行解就更困难。在Lagrangian松弛框架下，开发1个机组组合新方法的核心是如何获得1个可行的机组组合。文中采用Benders分解可行性条件严格证明了在给定时段，机组组合可行的充分必要条件：即在该时段一个相应于系统负载平衡约束和旋转各用约束的不等式组成立。该条件不需要求解经济分配问题，就可以判定机组组合的可行性。有了此条件，可在发电功率经济分配前知道机组组合是否可行，若不可行，则可通过调整机组组合状态而获得可行的组合。该条件对于构造一个求解机组组合问题的系统方法是重要且有效的。数值测试表明该条件是判定机组组合可行性的有效方法。     

基于优先级排序和内点法的机组优化组合

机组优化组合的目标是确定电力系统煤耗量和网损最小的发电调度方式.优化模型中考虑了机组爬坡率的限制、输电网络断面安全约束,针对寻优效率提出了一种优先级排序和内点法相结合的机组组合优化方法.按能耗指标形成机组优先级排序表,以获得尽可能好的开机方式初始值;用局部寻优法在初始值附近的可行域内寻求最优组合状态;对负荷分配的连续性子问题用内点法求解.通过对IEEE-39节点10机系统进行仿真计算,验证了所提方法收敛速度快、耗时少,对处理机组组合问题具有有效性和适用性.     

计及风电不确定性的多场景多时段安全约束机组组合解耦求解方法

为了加速求解计及风电不确定性的安全约束机组组合问题,提出计及风电不确定性的多场景多时段安全约束机组组合解耦求解方法。将原问题解耦为多个场景的安全约束机组组合问题;通过将各场景的调度时段分为多个子时段对各场景安全约束机组组合问题进行解耦,形成多个并行的子问题;为了确保多场景解耦和多时段解耦解的可行性,利用一致性约束耦合不同的子问题,并在目标函数中添加惩罚项。通过算例分析验证了所提方法的有效性。结果表明,在可接受的精度下,所提方法比传统集中式方法显著缩短了多场景安全约束机组组合问题的求解时间。     

基于优先级排序和内点法的机组优化组合

机组优化组合的目标是确定电力系统煤耗量和网损最小的发电调度方式。优化模型中考虑了机组爬坡率的限制、输电网络断面安全约束,针对寻优效率提出了一种优先级排序和内点法相结合的机组组合优化方法。按能耗指标形成机组优先级排序表,以获得尽可能好的开机方式初始值;用局部寻优法在初始值附近的可行域内寻求最优组合状态;对负荷分配的连续性子问题用内点法求解。通过对IEEE-39节点10机系统进行仿真计算,验证了所提方法收敛速度快、耗时少,对处理机组组合问题具有有效性和适用性。     

松弛约束发电计划优化模型和算法

安全约束机组组合和安全约束经济调度是发电计划优化的核心,算法鲁棒性是影响其工程应用的关键因素.在对通用安全约束机组组合优化模型分析基础上,提出安全约束发电计划的松弛约束模型.通过松弛机组发电量约束、环保约束、网络约束、机组速率约束和机组调节范围约束等,提高算法收敛性能.文中所提出的模型和算法已成功应用于某省级电网.     

基于改进近似动态规划的安全约束机组组合算法

针对电力系统的安全约束机组组合问题,提出了一种基于改进近似动态规划的求解算法。考虑到安全约束机组组合是一个多时段混合整数非线性规划问题,难以直接求解,所提算法将其建模成马尔可夫决策过程,并利用近似动态规划实现解耦求解。为了处理近似动态规划决策空间过大的问题,所提算法通过决策空间缩减技术提前获得大部分机组的开停机状态,有效提高求解效率。在IEEE 39节点系统和一个实际系统上进行了算例分析,验证了所提算法的有效性。     

面向节能发电调度的日前机组组合优化方法

节能发电调度是对电网优化调度机制的重大修改。机组组合是电网调度的重要环节,随着节能发电调度的逐步推广,需要结合中国国情研究新形势下机组组合模型与优化方法。提出一种求解电力系统机组组合的新方法,将机组组合问题分解为末状态和状态改变时间优化2个过程。基于节能发电调度通过多贪婪因子完善机组排序指标,利用贪婪算法确定机组组合初始解,进而结合深度优先算法遍历机组组合方案以保证问题优化的深度。10机24时段系统算例表明,该方法可有效处理机组组合各类约束条件及保证节能调度效果。     

月度安全约束机组组合建模及求解

月度发电计划的复杂性和求解规模,使得月度机组组合方案的制订变得十分困难.文中基于兼顾计算性能和月度计划关键需求的原则,通过时段简化和电力电量解耦,建立了以电量进度偏差最小为目标的月度安全约束机组组合(SCUC)模型,并采用混合整数规划(MIP)算法加以求解.实际系统算例测试验证了该模型的有效性.     

含风电场的电力系统机组组合问题随机模拟粒子群算法

由于风电具有随机性,含有风电场的机组组合问题不再是一个常规意义下的确定性问题。利用传统的方法也难获得既经济又有较高可靠性的解。本文建立了基于机会约束规划的含风电场的电力系统机组组合的数学模型,以概率的形式描述相关约束条件,并把组合问题分为内外两层优化子问题求解。外层为机组的启停状态优化,用离散粒子群算法求解,并引入启发式搜索策略,有效提高了机组状态优化效率;内层为负荷经济分配,考虑到风电的不可靠性,利用随机模拟的改进粒子群算法求解,防止种群过早收敛于局部最优解,并确保发电计划的可行性。通过10机系统的算例计算,并与其他文献方法比较,结果表明该算法对解决含有风电场的电力系统机组组合的问题是行之有效的。     

求解大规模机组组合问题的二阶锥规划方法

基于混合整数二阶锥规划(mixed integer second-order cone programming,MI-SOCP)提出一种求解电力系统计及爬坡约束机组组合问题(unit commitment,UC)的新方法。利用UC问题的混合整数二次规划(mixed integer quadratic programming,MI-QP)模型和一个简单混合整数集合的凸包表示,产生UC问题一个更紧的MI-SOCP模型。将最小覆盖不等式作为割平面,应用内点割平面法求解MI-SOCP以获得不计爬坡约束UC问题的机组启停状态。为满足爬坡约束,提出一种简单易行的机组启停状态修正方法。100机组96时段等多个系统的仿真结果表明,利用内点割平面法求解2种模型时,MI-SOCP能比MI-QP获得质量更好的次优解,所提方法能有效处理爬坡约束,适用于大规模的UC问题。     

Evolutionary programming based economic dispatch of generators with prohibited operating zones

This paper presents a new approach using evolutionary programming for solving the economic dispatch (ED) problem of generators when some/all of the units have prohibited operating zones. In this method, additional constraints such as spinning reserve requirements and ramp-rate limits are also considered besides taking into account network losses. The proposed method is implemented for solving a few example dispatch problems. The results obtained by this new approach are compared with those obtained using traditional methods. The study results have shown that the approach developed is feasible and efficient.     

Economic dispatch with prohibited operating zones using fast computation evolutionary programming algorithm

This paper presents an efficient and simple approach for solving the economic dispatch (ED) problem with units having prohibited operating zones. The operating region of the units having prohibited zones is broken into isolated feasible sub-regions which results in multiple decision spaces for the economic dispatch problem. The optimal solution will lie in one of the feasible decision spaces and can be found using the conventional λ–δ iterative method in each of the feasible decision spaces. But, this elaborate search procedure is time consuming and not acceptable for on-line application. In this paper, a simple and novel approach is proposed. In this approach, the optimal solution and the corresponding optimum system lambda are determined using an efficient fast computation evolutionary programming algorithm (FCEPA) without considering the prohibited operating zones. Then, a small set of advantageous decision spaces is formed by combining the feasible sub-regions of the fuel cost curve intervening the prohibited zones in the neighbourhood of the optimal system lambda. A penalty cost for each advantageous decision space is judiciously computed using participation factor. The most advantageous decision space is found out by comparing the penalty cost of the decision spaces. The optimal solution in the most advantageous decision space is obtained using the FCEPA. The proposed algorithm is tested on a number of sample systems with units possessing prohibited zones. The study results reveal that the proposed approach is computationally efficient and would be a competent method for solving economic dispatch problem with units having prohibited operating zones.     

Unit commitment by an enhanced simulated annealing algorithm

A new simulated annealing (SA) algorithm combined with a dynamic economic dispatch method has been developed for solving the short-term unit commitment (UC) problem. SA is used for the scheduling of the generating units, while a dynamic economic dispatch method is applied incorporating the ramp rate constraints in the solution of the UC problem. New rules concerning the tuning of the control parameters of the SA algorithm are proposed. Three alternative mechanisms for generating feasible trial solutions in the neighborhood of the current one, contributing to the reduction of the required CPU time, are also presented. The ramp rates are taken into account by performing either a backward or a forward sequence of conventional economic dispatches with modified limits on the generating units. The proposed algorithm is considerably fast and provides feasible near-optimal solutions. Numerical simulations have proved the effectiveness of the proposed algorithm in solving large UC problems within a reasonable execution time.     

Congestion management solution under secure bilateral transactions in hybrid electricity market for hydro-thermal combination

The deregulation of power system has created an environment of competitiveness among different market players and the transmission lines are forced to operate near to their thermal or stability limits. It is a challenge with System Operators (SO) to ensure a secure and reliable transmission of power under these conditions. This paper proposes a rescheduling based congestion management strategy in hybrid (pool + bilateral) electricity market structure for a combination of hydro and thermal units. The proposed congestion management problem has been formulated as mixed integer nonlinear programming (MINLP) problem with an objective to minimize the congestion management cost by suitably rescheduling the hydro and thermal units based on their up and down generation cost bids. The hydro units having lowest operational cost and fast startup time have been used to alleviate the congestion by considering non-concave piecewise linear performance curves for them. The secure bilateral transactions have been ensured while rescheduling of the generators for alleviating the congestion. The performance of the proposed model has been demonstrated by solving the congestion management problem on modified IEEE-24 bus system.     

地县级电网全局电压无功优化的研究和软件开发

针对地县级电网辐射状的网络结构,将网络划分为小的独立的优化单元,采用将电容器投切和变压器分接头档位的调节进行解耦处理的优化方法,简化了全局电压无功优化问题求解的复杂度;开发出适用于地县级电网的全局电压无功优化软件,该软件同时考虑现场操作的实际要求,对调节效果进行评估,提高了软件的实用性。     

逐次逼近动态规划法求解水电机组组合问题

水电站厂内机组间的发电流量分配是水电站经济运行中的一个重要混合非线性优化问题。文章设计了一种逐次逼近动态规划法,可用于求解水电机组的组合问题。该算法可有效地减少状态变量的个数,且能收敛到满意解。通过实例研究,验证了模型合理性和算法的可行性与有效性。     

基于纵横交叉算法的热电联产经济调度

为解决热电联产经济调度优化问题,提出了一种基于纵横交叉算法(Crisscross optimization algorithm,CSO)的新求解方法。CSO采用一种双交叉搜索机制,其中横向交叉引入扩展因子增强全局搜索能力,纵向交叉引入维交叉概念,从而避免维局部最优问题。CSO的全局并行搜索,避免了陷入局部最优,有效提高了收敛速度。以一个包含纯发电机组、热电联产机组、纯发热机组的48机组系统为例,建立了热电联产经济调度问题的模型。仿真结果表明,CSO解决热电联产经济调度问题具有可行性和有效性,为实际调度系统提供了一个较好的方法。     

Design and analysis of multi-source multi-area deregulated power system for automatic generation control using quasi-oppositional harmony search algorithm

The present article focuses on the study of automatic generation control (AGC) of a realistic power system having a distinct combination of multi-area multi-source generating units in each control area under deregulated framework. An attempt is made in this paper to integrate reheat thermal, hydro and gas generating unit in a single control area and, then, extended this combination to five control areas. In this work, six reheat thermal, six hydro and three gas generating units are taken into account for the modeling of five-area power system. Some important physical constraints like time delay, governor dead band and generation rate constraint are imposed in the power system dynamics to get an accurate perception of the deregulated AGC subject. The highlighting features of the present work are to model, simulate, optimize and co-relate their inter-related dynamic performances for the purpose of AGC study. For such a complex AGC model, the vital role of the proposed quasi-oppositional harmony search (QOHS) algorithm, as an optimizing tool, is signified while solving the AGC problem in deregulated regime. The simplicity of the structure and acceptability of the responses of the well-known proportional–integral–derivative controller, inherently, enforces to employ in this work. The three classes of extensive deregulated cases (in the presence of load following and physical constraints) are demonstrated by examining the closed loop performance of the studied model. The simulation results show that the designed power system model may be a feasible one and the proposed QOHS algorithm may be a promising optimization technique under these circumstances.     

Solving non-smooth economic dispatch by a new combination of continuous GRASP algorithm and differential evolution

The power economic dispatch is one of the most important problems in power system operation. Its objective is to minimize the total generation cost of the generating units while satisfying various constraints of the units and system. In past decades, modern metaheuristics have been applied in solving the economic dispatch problem due to their ability to find an almost global optimal solution. Recently, inspired in classical GRASP (Greedy Randomized Adaptive Search Procedure) algorithm, Hirsch et al. (2006) proposed a novel variant of the GRASP for continuous domain, called continuous GRASP (C-GRASP) algorithm. This paper proposes a combination of C-GRASP and differential evolution (DE) algorithm (C-GRASP–DE) in order to improve the global searching capability and prevent the convergence to local minima. The feasibility and performance of proposed C-GRASP and DE is demonstrated by power systems consisting of 13, 40 and 140 generators whose fuel cost function is calculated taking into account the effect of valve-point loading. Simulation results demonstrate the superiority of the proposed C-GRASP in combination with a self-adaptive DE approach (C-GRASP–SaDE) compared to the classical C-GRASP. Furthermore, some obtained optimization results for the three case studies by the proposed C-GRASP–SaDE are competitive with the best results presented in recent literature.     

数字编码神经网络模型及其在电力系统发展规划中的应用

本文以数字编码技术为基础，根据三种编码方式分别构筑了不同的Ｈｏｐｆｉｅｌｄ数字编码神经网络模型，这种模型可以用来求解各类输出为整数的优化问题。文中以Ｇａｒｖｅｒ６节点系统和某１８节点系统为算例，对电力系统发展规划问题进行计算分析，得到了满意的结果。