电力市场环境下解决机组组合问题的研究

提出了一种解决电力市场环境下机组组合的新方法 ,考虑了包括网络安全约束在内的多种约束条件。这种方法首先将一个大系统按系统通常的运行方式分成一些小的子系统 ,满足联络线功率不过载的约束条件 ,并在这些小的子系统之间分配负荷 ;然后将各子系统的机组组合问题分为两层的规划问题 ,用动态规划法和分段线性规划算法分别解决这两个问题 ,并满足时间约束 ,机组出力上升、下降速度约束等各种约束条件。本算法经一个 8机系统的检验 ,说明本算法是非常有效的     

电力市场环境下解决机组组合问题的研究

提出了一种解决电力市场环境下机组组合的新方法,考虑了包括网络安全约束在内的多种约束条件。这种方法首先将一个大系统按系统通常的运行方式分成一些小的子系统,满足联络线功率不过载的约束条件,并在这些小的子系统之间分配负荷;然后将各子系统的机组组合问题分为两层的规划问题,用动态规划法和分段线性规划算法分别解决这两个问题,并满足时间约束,机组出力上升、下降速度约束等各种约束条件。本算法经一个8机系统的检验,说明本算法是非常有效的。     

光伏并网下考虑电网安全约束的机组组合

基于Benders算法提出了一种求解光伏并网下考虑安全约束机组组合方法,借鉴两层分解思想,将其分解为无安全约束机组组合和考虑安全约束机组组合的线路潮流检测问题,形成了适合于混合整数规划问题的主问题和子问题的计算方法。针对主问题的检测引入了发电机输出功率转移分布因子及惩罚变量,从安全性和经济性角度实现对该机组组合问题的优化。在MATLAB和CPLEX中以加入光伏的IEEE14系统为测试算例进行仿真,结果显示在满足安全约束的前提下机组组合的总运行成本较无光伏并网时有所下降,表明该方法可以合理协调机组组合中的安全性与经济性。     

利用CC-PN建立机组组合问题中时间约束辅助模型

在为机组组合问题编制算法的过程中，因需要满足错综复杂的约束条件，容易使程序结构混乱、逻辑判断出错，最终导致算法求解失败。文中提出一种用于解决水力机组组合中时间约束问题的受控着色Petri网（CC-PN）模型，以指导和辅助机组组合算法程序的编制。该模型能直观地表达水力机组的启/停状况，并输出计算流量费用的开关量，将机组组合算法中面临启/停新机组时的约束判定和流量损失计算单独处理，为解决考虑时间约束的机组组合问题提供了新的辅助方法。     

考虑安全约束的机组组合免疫算法模型

根据机组组合问题的特点,尤其是电力系统中安全约束的特性,提出了一种基于改进免疫算法的机组组合算法.免疫算法的优势是处理0-1变量,该算法对免疫算法有2个改进:一是以一个抗体片段表示一个机组在调度期间的状态,并以抗体片段记忆库形式保留优秀抗体的信息;二是扩展抗体,将起作用的安全约束信息也作为抗体信息的一部分,并形成安全约束记忆库,从而模拟了调度中"人工选择起作用的约束"过程,解决了以往基于启发式算法的机组组合模型一般难以处理大规模安全约束的问题.此外,算法中采用基于群搜索优化的最优逼近变异法,减少了抗体随机变异的盲目性.最后用IEEE 118节点系统算例对所提出的方法的有效性和合理性进行了验证.     

具有安全约束的发电机组组合可行的充分必要条件

在拉格朗日松弛框架下,具有安全约束的发电机组组合问题的求解可以分为 2 个步骤:一是通过求解问题的对偶,以获得原问题近似可行、甚至近优的机组状态,再通过启发式方法或者通过求解一个整数规划问题,调整某些机组的状态,从而获得一个可行的、近优的机组组合状态;二是求解各个调度时段上处于开机状态机组的发电功率,使发电成本最小化.因此,判断某时段机组组合状态是否可行显得尤为重要.为此,利用Benders分解可行性定理,给出并证明了安全约束机组组合可行的充分必要条件以及数值计算方法.结合某电力系统测试算例,验证了相关理论和算法的有效性.     

解决机组组合问题的改进动态规划方法

提出了一种确定机组组合的改进动态规划方法,用以解决多种约束条件下机组的组合问题。该算法可以考虑机组功率上升、下降速度约束,机组启停约束,并有效避免了常规动态规划方法的“维数灾”问题,计算方法简单,计算速度快。用MATALB语言编制了程序,对一个10机系统进行了计算,结果表明该算法实用性较强。     

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。     

一种计及静态安全约束机组组合的有效算法

以直流潮流模型为基础,将计及电网静态安全约束的机组组合问题分解为无安全约束的机 组组合问题和计及电网静态安全约束的优化潮流问题2个子优化问题。通过在后者中引入虚拟变 量来反映机组组合对输电元件传输限制的牵制及影响,并借用虚拟变量和发电转移因子,构建前者 与后者间关联的补充约束条件,从而形成前者随后者变化的影响机制及优化方向的修正手段,由此 提出了2个子优化问题间交替求解的算法。该算法充分兼容现有成型方法,符合电力系统实际,对 解决电网静态安全对机组组合制约现象,以及对机组组合方案评价,有良好的适应性。     

考虑频率安全约束及风电综合惯性控制的电力系统机组组合

随着风电渗透率上升,电力系统惯性响应和一次调频能力下降,频率安全问题凸显,有必要在机组日前发电计划安排中考虑频率安全约束。依据电力系统频率安全要求,提出了考虑频率跌落最低值的频率安全约束构造方法。同时引入风电综合惯性控制使风电机组参与一次调频,在此基础上建立了考虑频率安全约束及风电综合惯性控制的机组组合模型。运用M语言动态控制多机频率响应模型进行Simulink仿真,并将其嵌入到改进粒子群优化算法中迭代求解。含风电的IEEE39节点系统算例结果表明,所提模型和方法能有效提升系统频率响应能力,保证系统安全运行。     

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.     

Ramp rate constrained unit commitment by improved priority list and augmented Lagrange Hopfield network

This paper proposes an improved priority list (IPL) and augmented Hopfield Lagrange neural network (ALH) for solving ramp rate constrained unit commitment (RUC) problem. The proposed IPL-ALH minimizes the total production cost subject to the power balance, 15 min spinning reserve response time constraint, generation ramp limit constraints, and minimum up and down time constraints. The IPL is a priority list enhanced by a heuristic search algorithm based on the average production cost of units, and the ALH is a continuous Hopfield network whose energy function is based on augmented Lagrangian relaxation. The IPL is used to solve unit scheduling problem satisfying spinning reserve, minimum up and down time constraints, and the ALH is used to solve ramp rate constrained economic dispatch (RED) problem by minimizing the operation cost subject to the power balance and new generator operating frame limits. For hours with insufficient power due to ramp rate or 15 min spinning reserve response time constraints, repairing strategy based on heuristic search is used to satisfy the constraints. The proposed IPL-ALH is tested on the 26-unit IEEE reliability test system, 38-unit and 45-unit practical systems and compared to combined artificial neural network with heuristics and dynamic programming (ANN-DP), improved adaptive Lagrangian relaxation (ILR), constraint logic programming (CLP), fuzzy optimization (FO), matrix real coded genetic algorithm (MRCGA), absolutely stochastic simulated annealing (ASSA), and hybrid parallel repair genetic algorithm (HPRGA). The test results indicate that the IPL-ALH obtain less total costs and faster computational times than some other methods.     

Control area performance improvement by extended securityconstrained economic dispatch

An algorithm for solving the extended security constrained economic dispatch (ESCED) problem with real-time economic dispatch grade speed and reliability is presented. The ESCED problem is formulated by adding a regulating margin and ramp rate constraints to the network security constrained economic dispatch problem previously solved by the CEDC algorithm. Starting with Newton's method to optimize the Lagrangian, the ESCED is developed by superimposing on Newton's method eight major components called tracking start initialization, hessian pre-elimination, implicit dual variable calculations, regulating margin sensitivity coefficient calculations, traumatic event evaluation, constraint relaxation, implicit ramp rate constraint implementation, and relaxed incremental cost calculations. Test results are also presented     

Augmented Lagrange Hopfield network based Lagrangian relaxation for unit commitment

This paper proposes an augmented Lagrange Hopfield network based Lagrangian relaxation (ALHN-LR) for solving unit commitment (UC) problem with ramp rate constraints. ALHN-LR is a combination of improved Lagrangian relaxation (ILR) and augmented Lagrange Hopfield network (ALHN) enhanced by heuristic search. The proposed ALHN-LR method solves the UC problem in three stages. In the first stage, ILR is used to solve unit scheduling satisfying load demand and spinning reserve constraints neglecting minimum up and down time constraints. In the second stage, heuristic search is applied to refine the obtained unit schedule including primary unit de-commitment, unit substitution, minimum up and down time repairing, and de-commitment of excessive units. In the last stage, ALHN which is a continuous Hopfield network with its energy function based on augmented Lagrangian relaxation is applied to solve constrained economic dispatch (ED) problem and a repairing strategy for ramp rate constraint violations is used if a feasible solution is not found. The proposed ALHN-LR is tested on various systems ranging from 17 to 110 units and obtained results are compared to those from many other methods. Test results indicate that the total production costs obtained by the ALHN-LR method are much less than those from other methods in the literature with a faster manner. Therefore, the proposed ALHN-LR is favorable for large-scale UC implementation.     

The conditions for obtaining feasible solutions to security-constrained unit commitment problems

The core of solving security-constrained unit commitment (SCUC) problems within the Lagrangian relaxation framework is how to obtain feasible solutions. However, due to the existence of the transmission constraints, it is very difficult to determine if feasible solutions to SCUC problems can be obtained by adjusting generation levels with the commitment states obtained in the dual solution of Lagrangian relaxation. The analytical and computational necessary and sufficient conditions are presented in this paper to determine the feasible unit commitment states with grid security constraints. The analytical conditions are proved rigorously based on the feasibility theorem of the Benders decomposition. These conditions are very crucial for developing an efficient method for obtaining feasible solutions to SCUC problems. Numerical testing results show that these conditions are effective.     

A solution to the unit commitment problem considering LNG fuel constraints

In this paper, an algorithm is proposed for finding a quasi-optimal schedule for the short-term thermal unit commitment problem taking LNG fuel constraints into account. In recent years, LNG fuel has been used increasingly. As a result, LNG fuel constraints should be considered in making a unit commitment schedule. Generally, unit commitment is a nonlinear combinatorial problem including discrete variables. To solve the problem, a two-step algorithm is developed using mathematical programming methods. First a linear programming problem is solved to determine the amount of LNG fuel to be consumed by each LNG unit, then a Lagrangian relaxation approach is used to obtain a unit commitment schedule. This two-step algorithm simplifies the problem and thus has good convergence characteristics. To test the effectiveness of the proposed algorithm, a numerical simulation was carried out on a 46-unit thermal system over a 24-hour period. A result with a dual gap of 0.00546 was obtained. © 1998 Scripta Technica, Electr Eng Jpn, 125(3): 22–30, 1998     

A combination of the genetic algorithm and lagrangian relaxation decomposition techniques for the generation unit commitment problem

Unit commitment involves the scheduling of generators in a power system in order to meet the requirements of a given load profile. An analysis of the basis for combining the genetic algorithm (GA) and Lagrangian relaxation (LR) methods for the unit commitment problem is presented. It is shown that a robust unit commitment algorithm can be obtained by combining the global search property of the genetic algorithm with the ability of the Lagrangian decomposition technique to handle all kinds of constraints such as pollution, unit ramping and transmission security.     

电网安全节能发电日前调度优化模型及算法

华北电网安全节能发电调度辅助决策系统中的日前调度模块实现了机组组合和安全约束经济调度两大功能,制定日发电计划既符合各种安全约束又满足各类辅助服务需求。采用同一个优化模型,通过修改输入信息实现节能发电调度、电量进度发电调度、成本调度、市场竞争等多种调度模式。引入violation和violation penalty weights两类参数,确保优化模型始终有解,满足工程实际应用的要求。采用同时可行性测试与优化计算相迭代的方法缩短了计算时间。日前调度模型为混合整数规划模型,采用分支定界法进行求解。为了精确校核日前调度结果,该系统开发了研究态全网络多时段安全校核功能,选择多个时间节点对日前调度结果进行精确的交流潮流校核,确保日前调度结果满足安全运行要求。     

Benders decomposition applied to security constrained unit commitment: Initialization of the algorithm

Benders decomposition has been broadly used for security constrained unit commitment problems, despite the fact that it may present convergence difficulties due to instabilities and to the mixed integer nature of the unit commitment problem. The initialization of Benders decomposition has been recognized as a prominent feature for the algorithm enhancement. In this work, a new Benders decomposition initialization methodology is proposed. The objective of the initialization is to include inexpensive network signals that can be added during the initial unit commitment master problem. Numerical simulations using the IEEE-118 and RTS-96 systems are performed to illustrate the benefits of the proposed initialization methodology. Results suggest that the initialization of Benders decomposition applied to security constrained unit commitment problems improves the overall convergence of the algorithm.     

A method for unit commitment with transmission losses and flow constraint

Researches on the unit commitment with transmission network have been reported recently. However, most of these researches mainly discussed the security constrained unit commitment, while the relationship between unit commitment and transmission losses was not considered. However, from the standpoint of operating reserve for ensuring power supply reliability, a unit commitment considering transmission losses is required. Further, under the deregulation and liberalization of the electric power industry, not only the line's security but also transmission losses are expected to play an important role in calculating the network access charge, and unit commitment taking into account transmission losses is also desired from this viewpoint. In this paper, a unit commitment approach with both transmission losses and line flow constraint is presented. Based on a heuristic iterative optimization method, first, an initial schedule is created by using a successively decommitting unit approach that is proposed in this paper. Then, we determine constraints included in the unit commitment schedule by a heuristic iterative optimization approach, in which an algorithm able to get rid of line overload by DC optimal power flow is developed. Through numerical simulations on two test power systems, the effectiveness of the proposed method is shown. © 2003 Wiley Periodicals, Inc. Electr Eng Jpn, 142(4): 9–19, 2003; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10116