Power system operations scheduling using separable programming

The problem of electric power operations scheduling comprises maintenance scheduling, intermediate- and short-term hydro-thermal scheduling, unit commitment and production scheduling. Recognizing the inter-relationship among these subproblems, the effect on one another is analyzed. Computationally efficient formulations and algorithms for maintenance scheduling and intermediate- and short-term hydro-thermal scheduling are presented.A variation of the separable programming technique is presented. This results in a linear programming formulation of the nonlinear scheduling problem. This technique is applied to a hypothetical system containing nuclear, fossil, hydro-electric and pumped-storage units. The large problem of hydro-thermal scheduling due to the inclusion of a nuclear unit is decomposed into two stages. In the first stage, the relatively stable nuclear generation is optimized with respect to the generation from large fossil-steam units. Hourly generation levels for all units in the system are then determined in the second stage.     

考虑检修计划的中长期水火电联合优化调度方法

在中长期水火发电调度中考虑检修计划的影响是目前中长期水火发电调度面临的难题。利用现代整数代数建模技术,建立发电计划和检修计划协调优化的多场景调度模型。在该模型中,鉴于设备检修计划的连续性,在预测场景树的基础上,将场景节点划分成不同的场景,通过节点和场景关联矩阵,实现多场景下设备检修模型的构建。同时,鉴于中长期调度计划中发电计划和检修计划对时段间隔要求的不同,分别设置电量相关节点和电力相关节点,实现中长期发电计划和检修计划的协调。上述模型是一个大规模混合整数线性规划(mixed integer linear programming,MILP)问题,采用商用MILP求解器进行求解。大规模实际水火电系统的实例分析结果表明,所提模型和方法是可行、有效的。     

基于进化捕食策略法的风-水-火电短期负荷分配优化

考虑负荷与风电的不确定性,建立了基于机会约束规划的风-水-火电短期负荷分配优化模型。为了更好地权衡局部搜索与全局搜索性能,应用进化捕食策略法求解水-火电短期优化调度与风-水-火电短期负荷分配问题。算例结果表明,与其他算法相比,进化捕食策略法在水-火电短期优化调度中能够搜索到更优的解,同时基于机会约束规划的优化方法为系统旋转备用容量的合理设置提供了依据。     

Mixed integer programming of generalized hydro-thermal self-scheduling of generating units

This paper presents the application of mixed-integer programming (MIP) approach for solving the hydro-thermal self scheduling (HTSS) problem of generating units. In the deregulated environment, the generation companies schedule their generators to maximize their profit while satisfying loads is not an obligation. The HTSS is a high dimensional mixed-integer optimization problem. Therefore, in the large-scale power systems, solving the HTSS is very difficult. In this paper, MIP formulation is adopted for precise modeling of dynamic ramp rate limits, prohibited operating zones, operating services, valve loading effects, variable fuel cost, non-linear start-up cost functions of thermal units, fuel and emission limits of thermal units, multi head power-discharge characteristics of hydro plants and spillage of reservoir. The modified IEEE 118-bus system is used to demonstrate the performance of the proposed method.     

考虑负荷变化率的日发电计划

依据负荷曲线的变化趋势,提出了一种能够细致考虑负荷变化率的日发电计划安排方法。该方法运用融合思想对负荷曲线进行时间过程的划分,并提取相应时段的特征负荷。时间过程划分后,在负荷变化平稳时,少量时间过程较长子时段的负荷水平更接近系统的实际情况;而在负荷急剧变化时,数量较多的短子时段细致刻画了负荷曲线攀峰降谷过程,且提供了充足的缓冲时间渡越陡峭段落。基于瓶颈序列分析,运用段落全局优化方法进行求解。与传统方法相比,在不增加计算量的前提下,获得了更佳的优化效果,不仅提高了经济效益,而且发电机在各时段的有功输出更加平稳,有利于与自发电控制系统的协调,同时减轻了调度员的操作负担。IEEE 30节点算例证实了该方法的有效性。     

Power generation scheduling for multi-area hydro-thermal systemswith tie line constraints, cascaded reservoirs and uncertain data

The authors propose an approach to the short-term generation scheduling of hydro-thermal power systems (GSHT). The objective of GSHT is to minimize the total operation cost of thermal units over the scheduling time horizon. To solve the problem within a reasonable time, the problem is decomposed into thermal and hydro subproblems. The coordinator between these subproblems is the system Lagrange multiplier. For the thermal subproblem, in a multi-area power pool, it is necessary to coordinate the area generations for reducing the operation cost without violating tie limits. A probabilistic method is employed in considering load forecasting errors and forced outages of generating units to satisfy system reliability requirements. For the hydro subsystem, network flow concepts are adopted to coordinate water use over the entire study time span and the reduced gradient method is used to overcome the linear characteristic of the network flow method to obtain the optimal solution. Three case studies for the proposed method are presented     

Hydro-thermal unit commitment problem using simulated annealing embedded evolutionary programming approach

This paper presents a new approach to solve the hydro-thermal unit commitment problem using Simulated Annealing embedded Evolutionary Programming approach. The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. A utility power system with 11 generating units in India demonstrates the effectiveness of the proposed approach; extensive studies have also been performed for different IEEE test systems consist of 25, 44 and 65 units. Numerical results are shown comparing the cost solutions and computation time obtained by conventional methods.     

云南电网水火电机组AGC协调优化控制策略

云南电网属于水火电资源比较均衡的电网,为水火电协调控制提供了有利的条件.针对云南电网不同时段负荷变化的特点,将水火电机组自动发电控制(AGC)按调节特性划分为多个组,每组机组在不同时段下采取不同的控制模式,有效地实现了云南电网水火电AGC机组之间的协调优化控制.试运行结果表明,该控制策略能较好地适应云南电网的特点,提高了AGC性能.     

MINIMUM EMISSIONS HYDRO-THERMAL POWER FLOW

ABSTRACT

Minimum NO_x emission optimal power flow scheduling for a hydro-thermal power system is considered. Computational results using Newton's method and Powell's penalty function approach arc obtained for the 57 bus and 118 bus hypothesized IEEE hydro-thermal power systems. Based on a comparison with the minimum cost solution, it is concluded that regardless of which scheduling strategy is used, increasing the hydro generation results in decreasing both emissions and thermal fuel costs. The results obtained indicate that system N O _x emissions are influenced by bus voltage lower limits, reactive power generation and the hydro unit water conversion factor.     

Optimal Load Flow in Hydro-Thermal Systems: Computational Experience with Newton's Method

ABSTRACT

In this paper the problem of optimal load flow in a hydro-thermal electric power system is considered. It is assumed that the hydro generation resources are energy limited. As a result, a dynamic optimization problem involving the daily schedule of the system is encountered. The scheduling problem requires the solution of a large scale set of nonlinear simultaneous equations. In this paper Newton's method is used to solve the scheduling problem. The algorithm has been successfully tested with five test systems varying in size from a 5 bus system to a 57 bus system. Results of the computational experience are summarized in this paper.     

大型水火电力系统短期最优机组启停调度

给出了描述大型水火电力系统短期机组启停调度的数学模型,应用大系统分散控制理论将这一复杂问题分解为3个简单的子问题,分别用一维动态规划和网络规划法术解,最后,通过拉格朗日乘子协调控制得出最优可行解。该算法也可同时考虑火电的最优启停机计划和水电的优化调度。     

A genetic algorithm solution approach to the hydrothermal coordination problem

In this paper, a genetic algorithm solution to the hydrothermal coordination problem is presented. The generation scheduling of the hydro production system is formulated as a mixed-integer, nonlinear optimization problem and solved with an enhanced genetic algorithm featuring a set of problem-specific genetic operators. The thermal subproblem is solved by means of a priority list method, incorporating the majority of thermal unit constraints. The results of the application of the proposed solution approach to the operation scheduling of the Greek Power System, comprising 13 hydroplants and 28 thermal units, demonstrate the effectiveness of the proposed algorithm.     

基于随机规划的含风电场的电力系统节能优化调度策略

含风电场的多电源电力系统优化调度是一个新的具有重要经济和社会效益的复杂非线性问题.针对传统的水火经济调度模型以及新兴的火风互补经济调度模型,提出了基于随机规划的水、火、风混合系统短期优化调度模型,利用机会约束描述目标函数和约束条件,并给出不同置信水平下的调度方案.同时考虑水电站耗水量最小、火电煤耗量最小以及氮氧化物排放...     

Short-term resource scheduling with ramp constraints [powergeneration scheduling]

This paper describes a Lagrangian relaxation-based method to solve the short-term resource scheduling (STRS) problem with ramp constraints. Instead of discretizing the generation levels, the ramp rate constraints are relaxed with the system demand constraints using Lagrange multipliers. Three kinds of ramp constraints, startup, operating and shutdown ramp constraints are considered. The proposed method has been applied to solve the hydro-thermal generation scheduling problem at PG&E. An example alone with numerical results is also presented     

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.     

Generation scheduling with thermal stress constraints

This paper describes a scheduling method for representing the thermal stress of turbine shafts as ramp rate constraints in the thermal commitment and dispatch of generating units. The paper uses Lagrangian relaxation for optimal generation scheduling. In applying the unit commitment, thermal stress over the elastic limit is used for calculating the ramping cost. The thermal stress contribution to generation cost requires the calculation of a set that includes thermal stress at the end of each time step; this requirement presents a complicated problem which cannot be solved by an ordinary optimization method such as dynamic programming. The paper uses an improved simulated annealing method to determine the optimal trajectory of each generating unit. Furthermore, the paper uses linear programming for economic dispatch in which thermal stress limits are incorporated in place of fixed ramp rate limits. The paper illustrates the economics of frequently ramping up/down of low cost generating units versus the cost of replacement of their turbine rotors with a shorter life span. The experimental results for a practical system demonstrate the effectiveness of the proposed method in optimizing the power system generation scheduling.     

利用多目标模糊动态规划法进行抽水蓄能电站的运行优化

本文论述了利用多目标模糊动态规划的方法来解决具有抽水蓄能电站的水、火电系统的短基运行规划问题，建立了考虑经济性和可靠性等多个目标的抽水蓄能电站在整个水火电系统中的运行优化模型，并用多目标模糊动态规划法处理这些目标。     

节能发电调度实用化措施框架体系

节能发电调度方式改革是当前及将来很长一段时间内中国电力工业节能减排的指导思想。文章针对国内区域电网的实际情况,提出了当前环境下具备可操作性的调度机构节能发电调度措施的框架体系：优化火电机组发电调度,节能环保机组优先安排发电,不同能耗火电机组的等效利用小时数拉开差距;优化水火电联合经济调度,保证汛期富余水电吸纳;优化系统潮流分布,降低输电线损;加强地区调度火电机组的节能管理和节能发电调度信息管理;加强节能发电调度技术支持系统建设。最后给出了节能发电调度统计指标体系。     

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。     

A solution method using neural networks for the generator commitment problem

This paper studies the feasibility of applying the Hopfield-type neural network to unit commitment problems in a large power system. The unit commitment problem is to determine an optimal schedule of what thermal generation units must be started or shut off to meet the anticipated demand; it can be formulated as a complicated mixed integer programming problem with a number of equality and inequality constraints. In our approach, the neural network gives the on/off states of thermal units at each period and then the output power of each unit is adjusted to meet the total demand. Another feature of our approach is that an ad hoc neural network is installed to satisfy inequality constraints which take into account standby reserve constraints and minimum up/down time constraints. The proposed neural network approach has been applied to solve a generator scheduling problem involving 30 units and 24 time periods; results obtained were close to those obtained using the Lagrange relaxation method.