Different time-scale approaches to the real power dispatch ofthermal units

Different time-scale approaches to the dispatch problem are proposed for the centralized control of real power. In particular, the problem of optimally sharing a time-varying load among the committed thermal units of an electrical power system is addressed. It is shown that the real power dispatch of the thermal units is handled at different time scales as a dynamic problem where rate of change limits , environmental constraints, and the security constraints of the traditional static approach are taken into account. The adoption of the same general model guarantees the coherency of the results in the three phases of day-before scheduling, advance dispatch, and online dispatch. A modified gradient projection algorithm, which suitably exploits some good second-order information, has been adopted for the solution of the large-scale problem arising from the discretization of the dynamic model. The resulting procedure is capable of solving the very large day-before scheduling (more than 2000 variables and 4000 constraints for the Italian EHV system) in a few minutes, as well as providing the solution of the advanced dispatch problem in no more than 10 s even when a corrective rescheduling is required     

水火电力系统短期实用化调度模型及求解方法

以某电网的大型水火电力系统为研究对象,从节能降耗及与生产实际接轨的角度出发,基于水火电力系统的解耦机制,将水火联合调度问题建模为2个具有优化时序的子优化问题。在火电优化子问题中,在考虑常规约束的基础上,提出火电机组出力升降走向约束及相邻时段火电总负荷波动阈值约束,以保证火电机组出力平滑;在水电优化子问题中,考虑水电厂日平均出力约束及振动区约束,以保证水电的充分利用。采用改进的具有柔性更新策略的教与学优化算法依次求解2个子优化问题,并针对2个子优化问题中呈现强耦合性的复杂约束,设计不同的启发式约束处理方法。对含有15座火电厂和29座水电厂的某水火电力系统的日前调度进行仿真测试,验证了所提调度模型的可行性和实用性及求解方法的有效性。     

基于粒子群算法的火电厂机组负荷优化分配研究

负荷优化分配是火电厂运行优化的一个重要研究领域,在机组之间合理地优化分配负荷能够提高整个火电厂运行的经济性。针对火电厂实际的运行情况,考虑多个实际约束条件,建立了并行火电机组间连续多时段动态负荷优化分配的数学模型;提出运用新近发展起来的智能算法-粒子群算法来解决动态负荷优化分配问题,详细介绍和研究了该算法的基本原理以及在负荷优化分配问题上的实现过程,并针对原算法的不足,对算法进行了改进;根据负荷分配和算法的特性,对初始种群的生成方法进行了改进,同时对约束条件进行了有效处理。仿真实例表明,该方法收敛性好,收敛速度快,能够有效地达到或接近全局最优,从而为火电厂机组负荷优化分配的求解提供了新的有效算法。     

动态系统实现火电厂机组负荷优化分配

利用连续型Hopfield神经网络(CHNN)可以将负荷优化分配问题转化为求解多变量非线性动态系统的稳态值。文中直接将负荷上下限约束条件作为神经元激活函数，构造出了通用的网络拓扑结构，理论和仿真试验证明了该方法能够全局收敛。并通过动态仿真手段获取稳态负荷优化分配结果。通用软件包开发和仿真过程表明该方法简单、可靠且适用。     

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     

一种用于机组组合问题的改进双重粒子群算法

为了更经济快速地解决机组组合问题,提出一种改进双重粒子群优化(particle swarm optimization,PSO)算法,包含离散部分和连续部分。离散PSO分时段优化机组的启停状态,在种群更新时加入了临界算子,改进了可行解的判别条件,各机组出力最低值的和要在一定程度上低于负荷需求值,并考虑机组启停时间的向前继承和向后约束。连续PSO用于启停状态确定过程中和确定后的负荷分配,考虑功率平衡约束、热备用约束和机组的出力上下限约束。求解经济负荷分配时,利用罚函数的方法满足机组的爬坡速率约束,最后得到煤耗最小值。采用2个24时段的算例进行仿真,实验结果表明新算法减少了搜索量,提高了收敛速度,并为机组组合问题提出了新思路。     

Security constrained economic load dispatch using improved particle swarm optimization suitable for utility system

The objective of this paper is to evolve simple and effective methods for the economic load dispatch (ELD) problem with security constraints in thermal units, which are capable of obtaining economic scheduling for utility system. In the proposed improved particle swarm optimization (IPSO) method, a new velocity strategy equation is formulated suitable for a large scale system and the features of constriction factor approach (CFA) are also incorporated into the proposed approach. The CFA generates higher quality solutions than the conventional PSO approach. The proposed approach takes security constraints such as line flow constraints and bus voltage limits into account. In this paper, two different systems IEEE-14 bus and 66-bus Indian utility system have been considered for investigations and the results clearly show that the proposed IPSO method is very competent in solving ELD problem in comparison with other existing methods.     

Application of linear programming redispatch technique to dynamicgeneration allocation

Consideration is given to dispatch problems that involve the allocation of system generation optimally among generating units while tracking a load curve and observing the power rate limits of the units, system spinning reserve requirements, and other security constraints. Two methods are used in the solution of the problem. The first method is a quadratic programming technique combined with a linear programming redispatch technique. The latter utilizes a linear programming formulation of the dynamic dispatch problem about the base case static economic dispatch solution. The second method is based on the Dantzig-Wolfe decomposition technique. Tests and computer results of four systems of different combinations of units and intervals are given to show the advantages of the techniques proposed     

Optimal dynamic economic dispatch of generation: A review

This paper presents a review of the research of the optimal power dynamic dispatch problem. The dynamic dispatch problem differs from the static economic dispatch problem by incorporating generator ramp rate constraints. There are two different formulations of this problem in the literature. The first formulation is the optimal control dynamic dispatch (OCDD) where the power system generation has been modeled as a control system and optimization is done in the optimal control setting with respect to the ramp rates as input variables. The second one is a later formulation known as the dynamic economic dispatch (DED) where optimization is done with respect to the dispatchable powers of the committed generation units. In this paper we first outline the two formulations, then present an overview on the mathematical optimization methods, Artificial Intelligence (AI) techniques and hybrid methods used to solve the problem incorporating extended and complex objective functions or constraints. The DED problem in deregulated electricity markets is also reported.     

基于变量降维的大电网经济调度优化方法

随着电网规模扩大,经济调度问题因变量增多,维度巨大,造成求解困难。文中利用Benders分解法,将大电网安全约束经济调度问题分解为无安全约束的优化主问题和网络潮流安全约束子问题,将子问题安全约束返回主问题进行模型重构,通过主子问题协调最终实现问题求解。优化问题求解过程中,根据当前运行信息,对机组调整价值进行甄别,将其中对安全和经济贡献小的机组进行集中处理,同时根据重要断面潮流负荷变化的物理特征对研究时段进行检验,将非重点关注的相邻时段进行简化合并,实现压缩机组变量和时段数量、降低求解维度的目的。最后,算例验证表明基于变量降维的优化方法可以减少大电网优化时间,同时保持较高的求解精度,满足工程化计算要求。     

光伏光热联合发电基地并网优化调度模型

太阳能能源基地建设正在从单一光伏发电向光伏光热等多种太阳能能源利用形式方向发展。借助光热电站的大容量储热装置和具备快速爬坡速率的汽轮机组,光伏光热联合发电基地的并网运行的可调度性和可控性大大提升。从光伏光热联合发电基地的运行机理出发,建立了基于改进粒子群算法的光伏光热两阶段优化调度模型,第一阶段以削减等效负荷峰谷差、改善负荷曲线为优化目标,第二阶段以发电总成本最小为优化目标。该模型满足光伏光热电站的主要运行约束和传统机组组合安全约束,适用于光伏光热联合发电基地并网调度运行。对10机系统的仿真表明,在完全接纳太阳能发电的前提下,光伏光热发电基地在削减等效峰谷差、提高新能源消纳和降低发电总煤耗效益显著,同时对于光热电站的灵敏度分析表明,在规划建设光热电站时可根据单位峰谷差削减量以及建设成本来选择合适的装机容量和储热装置容量。     

应用近似动态规划算法求解安全约束随机动态经济调度问题

针对大电网安全约束随机动态经济调度(DED)问题的求解时间太长,提出了应用近似动态规划算法快速求解不含抽水蓄能电站电网的安全约束随机DED问题的方法。建立了随机DED问题的虚拟存储器模型,以系统的正旋转备用容量作为存储变量,构建系统相邻时段的状态转移方程,并考虑了各输电线路和断面的安全约束。以风电场日前功率预测曲线为基础,通过拉丁超立方抽样产生风电场出力的误差场景,并逐一场景递推求解每个时段的二次规划模型以对各个时段的值函数进行训练,形成收敛的值函数,再代入预测场景求解以获得最终的优化调度方案。该方法实现了对随机DED模型各个场景和各个时段的解耦求解,将一个大规模优化问题分解为一系列的小规模优化问题,有效提高了对大电网随机DED模型的求解速度。以某一实际省级电网为算例,通过与场景法和鲁棒优化调度方法的比较验证了所提出模型和求解方法的正确有效性。     

The solution of scheduling of thermal units by mathematical programming techniques

In this paper, the thermal units scheduling problem is considered from both its aspects: the selection of units to be placed in operation, and the load distribution among them. The solution of these problems can be found by considering two separate, but mutually dependent optimization problems, with a general objective of minimizing the system operating costs, subject to demand and operating constraints. Both optimization problems are formulated as mathematical programming problems. The first, usually called the unit commitment problem, is solved by a dynamic programming method. The second, which represents the economic dispatch problem, is solved by both dynamic and linear programming techniques. The solution methods are applied to a real power system, consisting of twelve generating units. The mathematical algorithms for the solution of specified problems are presented and the results of some computer studies on the selected sample system are given.     

发电动态经济调度的有效响应能力调整量算法

对基于前瞻技术和响应能力解耦的动态经济调度算法中的机组进行了精确分类,给出最大有效响应能力调整量的概念。分析了快速机组、临界机组和慢速机组补偿响应能力的作用特点,指出现有算法的不足。基于有效响应能力调整量提出一种新的动态经济调度算法,该算法以静态优化调度结果为基础,采用“在最大有效响应能力调整量范围内,快速机组向临界机组过渡、慢速机组向临界机组过渡”的调整原则进行二次经济调度。分析表明,该算法具有动态前瞻机制、可一次精确完成响应能力缺额补偿、迭代次数少、计算效率高等特点。算例证实了算法的可行性。     

Contingency constrained optimal reactive power flow procedures forvoltage control in planning and operation

The paper presents a preventive secure contingency constrained approach to power system voltage profile optimization suitable both for VAr planning and for short term reactive scheduling. The solution of the problems is based upon the implementation of two optimal reactive power flow (ORPF) programs: the first relevant to determining a workable state (security aspect); and the second relevant to attaining the optimal and secure point (global target). The first ORPF is solved by recursively employing a linear programming algorithm, whilst the second is based on the Han-Powell algorithm. In the paper, emphasis is given to the introduction of the contingency constraints in the ORPF models. The N-1 security constraints are explicitly introduced in the programs in order to obtain an operating point preventive-secure with respect to a selected contingency set. The performances of the procedures are shown by presenting the numerical results obtained from their applications to a small test network and to the large ENEL transmission system     

基于综合自适应滤波器的在线短期负荷预测

准确地实现小时负荷预测是实施优化控制和动态安全分析的前提。采用嵌入维最小二乘支持向量机（ELS-SVM）的方法进行建模和预测,对影响负荷的因素进行模糊化处理。采用了粒子群（PSO）优化算法解决ELS-SVM学习过程中多参数难以调整的问题。提出分段小批量学习和更新的在线学习方法,既降低了运算量又能有效地避免积累误差,从而提高预测精度。实验结果表明,该方法有效地将预测精度从2.1%提高到了1.29%。     

节能发电调度发电计划编制算法

在发电计划的编制过程中,如何实现机组发电序位表是体现节能发电要求的关键所在,为此,提出了发电计划编制核心算法。该算法基本原理为:根据全网负荷、分区负荷预测以及节能发电序位表,确定机组开机方式,然后采用等微增率法分配机组发电量;通过引入设备利用率系数分配机组发电曲线以满足系统安全运行和调峰要求,并修正机组发电曲线以满足运行约束条件,最终得到机组发电曲线。结合江苏电网以火电机组为主的特点,利用该算法进行节能调度发电试验日发电计划编制,验证了算法的合理性。     

基于模糊多目标优化的负荷优化分配研究

针对火电厂负荷优化分配,基于煤耗最小的单目标优化的局限性,提出了兼顾全厂煤耗最小和完成变负荷时间最短的双目标负荷优化分配模型,利用模糊理论将此双目标函数处理成相同约束条件下的单目标函数;然后用动态规划法求解,并将此结果同只考虑煤耗最小的单目标优化模型的结果相比较;最后对4台机组进行仿真。结果表明:采用多目标模糊优化设计对负荷优化分配效果良好。     

Co-ordinated economic and advance dispatch procedures

The paper deals with the problem of improving co-ordination between the online economic dispatch (ED) function and the very short-term advance dispatch (AD). Both procedures are formulated as optimal dispatching problems, but while a static model is used for the ED function, a dynamic model is employed in AD. The need to account for ramp-rate limits of thermal power generation even in the ED phase is satisfied by adding suitable penalty terms to the objective function of the classical ED problem. These penalties are proportional to the Lagrange multipliers associated with ramp-rate limits that are active at the AD solution. An efficient updating procedure is used to correct the penalization by taking the load forecast errors into account. The proposed co-ordination procedure can provide the snapshot ED with the long range perspective of AD without resorting to heuristic approaches. The procedure is validated by extensive testing carried out both on a small CIGRE test case and on a medium-large scale network representative of the Italian EHV system. Moreover, test results show that the CPU time requirements of the modified ED procedure are still suited to online applications     

基于一致性理论的独立微电网分布式动态经济调度

独立微电网是提高可再生能源利用率的有效途径,动态经济调度是微电网系统运行的重要环节。文中给出了独立微电网动态经济调度模型,提出了一套基于一致性理论的分布式实现方法,各参与者依靠本地计算以及邻居间的少量信息交互实现系统优化。计算分为两个阶段:在第一阶段,各单元通过平均一致性算法获得全网信息,并以最大化利用可再生能源为目标预设可控负荷的用电计划;在第二阶段,各单元通过更新发电机或储能系统时段间的出力上下限,将原问题解耦为一系列单时段经济调度问题,再采用一致性牵引算法根据等微增率准则逐个计算每个时段的最优出力。通过仿真算例验证了所提模型与算法的有效性。