Short-Term Hydro Generation Scheduling of the Three Gorges Hydropower Station Using Improver Binary-coded Whale Optimization Algorithm

Water Resources Management - The short-term hydropower generation scheduling (STHGS) is a complicated problem in the utilization of hydropower and water resources. An improved binary-coded whale...     

梯级水电站优化调度的改进粒子群算法

针对粒子群算法易陷入局部最优的缺点,提出了一种双适应度方法、动态邻域算子和随机动态调整惯性权重机制有机结合的混合改进策略.算例计算表明,该改进策略能增强粒子的局部收敛能力,加快算法的收敛速度,便于处理复杂约束条件,为求解具有复杂约束条件的非线性规划问题提供了一种简单有效的方法.文中探讨了梯级水电站优化调度的相关问题,考虑了丰枯分时电价因素,建立了梯级水电站长期优化调度数学模型,并应用改进粒子群算法进行求解.实际梯级水电站计算表明,该模型使枯水期大部分时间出力均匀平稳,丰水期能兼顾防洪和蓄水的不同要求,有利于电力系统的稳定运行.改进粒子群算法计算速度快、收敛精度高,为梯级水电站长期优化调度提供了一种简单实用的求解方法.     

基于改进遗传算法的水电站优化调度模型与算法

基于整数的遗传算法编码规则,满足了染色体和解之间唯一映射的关系,极大的缩短了染色体的长度。引入退火罚因子设计动态罚函数处理约束条件和自适应的遗传算子的设计,建立了基于改进遗传算法的水电站优化调度的数学模型。算例研究表明,上述算法可以快速有效地得到水电站优化调度的全局优化方案,提高运算效率。     

Optimization of Sewer Networks Using an Adaptive Genetic Algorithm

This work aims at introducing an optimization model to design sewer networks. The approach specially focuses on handling the nonlinear and discrete constraints of the problem. For this purpose, an adaptive genetic algorithm is developed so that every chromosome, consisting of sewer diameters and slopes and pump indicators, is a feasible design. The binary chromosomes are freely generated and then decoded to feasible design alternatives following a sequential design-analysis algorithm. The adaptive decoding strategy is set up based on the open channel hydraulics and sewer design criteria. Through the proposed method, all the sewer system??s constraints are systematically satisfied. Consequently, there is neither need to discard or repair infeasible chromosomes nor to apply penalty factors to the cost function. A benchmark sewer network from the literature is considered to be designed using the proposed approach. The obtained results are then discussed and compared with the previous works. It is found that the adaptive constraint handling method computationally makes the optimization more efficient in terms of speed and reliability.     

The Short-Term Economical Operation Problem for Hydropower Station Using Chaotic Normal Cloud Model Based Discrete Shuffled Frog Leaping Algorithm

Water Resources Management - The short-term economical operation (STEO) in hydropower station is nonlinear mixed integer problem, satisfying complex hydrologic constraints simultaneously. In this...     

A Novel Adaptive Multi-Objective Particle Swarm Optimization Based on Decomposition and Dominance for Long-term Generation Scheduling of Cascade Hydropower System

Water Resources Management - Multi-objective long-term generation scheduling (MLGS) considering ecological flow demands is important for comprehensive utilization of water resources in cascade...     

改进粒子群优化算法在水库优化调度中的应用

为解决粒子群优化算法寻优过程中易出现种群趋同化而导致早熟收敛的问题,引入粒子群的进化速度和种群多样性适应度方差两个因素,构建了自适应的动态的惯性因子取值机制,并讨论了惯性因子的收敛性及参数的独立性,从而改进了传统粒子群优化算法的惯性因子线性取值机制。将改进的粒子群优化算法应用于某水库的优化调度中,验证了该算法能以较快的速度收敛得到全局极值,克服了易陷入局部最优的缺点,为水库优化调度问题提供了一条新途径。     

An Efficient Optimization Method for Long-term Power Generation Scheduling of Hydropower Station: Improved Dynamic Programming with a Relaxation Strategy

Integrating the characteristics of hydropower reservoir operations into optimization methods is an effective approach. Based on the concavity and monotonicity of hydropower reservoir operation with dynamic programming (DP), improved DP (IDP) with monotonicity in optimal decision-making can quickly search for an approximate optimal solution. However, IDP may not converge to the optimal solution of the long-term power generation scheduling (LPGS) problem of hydropower station due to the analysis conclusion of approximate monotonicity. Therefore, the relaxation strategy for expanding the search space based on the monotonicity of optimal decisions is introduced into IDP, which is named DP with a relaxation strategy (DPRS). The experimental results of Xiluodu, Xiangjiaba, and Three Gorges Reservoir (TGR) show that 1) the time complexity of DPRS and IDP decreases from the quadratic growth of DP with an increasing number of discrete states to linear growth; 2) DPRS and DP can obtain the optimal solution of the long-term power generation scheduling (LPGS) problem of hydropower station under the given discrete precision, whereas IDP searches for only an approximate optimal solution. Combined with the discussion with other relevant literature, all these results indicate that the DPRS has the strongest competitiveness in solving the LPGS problem of hydropower station, both in convergence accuracy and in calculation speed.

     

基于改进遗传算法的梯级橡胶坝调度优化

为解决城市河道中梯级橡胶坝的优化调度问题,求解出较为合理的塌坝泄流方案,保障河道行洪安全,根据橡胶坝塌坝泄流计算原理,以限定时间范围内最小泄流量为目标函数,建立梯级橡胶坝调度优化模型,并采用线性加速选择函数与改进的自适应交叉、变异函数,改进传统遗传算法(GA),进行模拟运算,求解最优塌坝方案。改进的遗传算法(IGA)收敛速度快、稳定性强、程序运算时间短,能高效精确地计算出符合客观实际要求的梯级橡胶坝优化调度方案,具有一定的工程应用价值。     

均匀设计方法在水电站发电调度优化中的应用研究

水电站工程的科学调度是实现水资源优化配置、发挥工程效益的重要方式和有效手段。文章以水丰水电站为例,进行了均匀设计方法在水电站发电优化调度中的应用研究,结果显示该方法与传统优化方法相比具有明显优势,可以用于水电站发电调度优化研究。     

基于文化粒子群算法的水库发电调度图绘制

为了解决使用常规方法绘制水库发电调度图时,典型水文年的样本容量有限、水文特征的代表性具有局限性的问题,引入了文化粒子群算法,采用信仰空间吸收种群的知识经验,形成规则引导种群进化,充分利用历史实测资料绘制调度图。通过实例研究,获得了较常规方法更优的结果,为优化方法在水电站中长期调度中的应用提供了一条新途径。     

Optimal Operation of Hydropower Reservoir Systems Using Weed Optimization Algorithm

The optimal hydropower operation of reservoir systems is known as a complex nonlinear nonconvex optimization problem. This paper presents the application of invasive weed optimization (IWO) algorithm, which is a novel evolutionary algorithm inspired from colonizing weeds, for optimal operation of hydropower reservoir systems. The IWO algorithm is used to optimally solve the hydropower operation problems for both cases of single reservoir and multi reservoir systems, over short, medium and long term operation periods, and the results are compared with the existing results obtained by the two most commonly used evolutionary algorithms, namely, particle swam optimization (PSO) and genetic algorithm (GA). The results show that the IWO is more efficient and effective than PSO and GA for both single reservoir and multi reservoir hydropower operation problems.     

基于改进鲶鱼效应粒子群算法的电站优化调度

为提高梯级电站的综合效益、获得较优的调度方案,建立了基于改进鲶鱼效应粒子群算法(CE-PSO)的梯级电站优化调度模型。针对鲶鱼效应粒子群算法在制作鲶鱼粒子时容易陷入局部加速的局限性,考虑到鲶鱼粒子的空间分布位置对改善粒子的多样性具有重要影响,尝试通过一定的途径将鲶鱼粒子均匀分布于整个搜索空间,提高种群的搜索效率,弥补CE-PSO算法容易陷入局部加速的局限性。将改进后的算法应用于某河流梯级电站的优化调度,结果表明,改进后的鲶鱼效应粒子群优化算法与标准PSO和CE-PSO相比,在全局搜索能力和收敛速度方面均有改善。     

Cooperation Search Algorithm for Power Generation Production Operation Optimization of Cascade Hydropower Reservoirs

Water Resources Management - Over the past decades, the reservoirs operation plays an increasingly important role in coping with the serious water, food and energy crisis. However, the curse of...     

基于改进粒子群算法梯级水电站短期优化调度研究

应用改进粒子群算法求解梯级水电站短期优化调度问题.考虑发电效益和存水效益结合峰谷电价建立综合效益最大模型,针对粒子群算法存在的后期收敛速度慢和易陷入局部最优等缺点,引入收缩因子和杂交算子对其进行改进.应用改进粒子群算法对"水布垭水电站一隔河岩水电站一高坝洲水电站"进行短期优化调度,分别采用传统优化模型和峰谷优化模型进行实例计算,结果表明实施峰谷电价,对于提高梯级水电站综合效益,同时缓解高峰期用电紧张局面有更高的应用价值;应用改进粒子群算法求解梯级水电站短期优化调度问题在求解时间、求解精度上都得到了较满意的效果.     

Short-Term Flood Control and Long-Term Energy Maximization in Multi-reservoir Systems Using Improved Particle Swarm Optimization

Water Resources Management - In this study, a model is developed for short-term flood control of a complex multi-reservoir system located on one of the largest basins in Turkey. The managing body...     

Optimization of Exclusive Release Policies for Hydropower Reservoir Operation by Using Genetic Algorithm

The efficient utilization of hydropower resources play an important role in the economic sector of power systems, where the hydroelectric plants constitute a significant portion of the installed capacity. Determination of daily optimal hydroelectric generation scheduling is a crucial task in water resource management. By utilizing the limited water resource, the purpose of hydroelectric generation scheduling is to specify the amount of water releases from a reservoir in order to produce maximum power, while the various physical and operational constraints are satisfied. Hence, new forms of release policies namely, BSOPHP, CSOPHP, and SHPHP are proposed and tested in this research. These policies could only use in hydropower reservoir systems. Meanwhile, to determine the optimal operation of each policy, real coded genetic algorithm is applied as an optimization technique and maximizing the total power generation over the operational periods is chosen as an objective function. The developed models have been applied to the Cameron Highland hydropower system, Malaysia. The results declared that by using optimal release policies, the output of power generation is increased, while these policies also increase the stability of reservoir system. In order to compare the efficiency of these policies, some reservoir performance indices such as reliability, resilience, vulnerability, and sustainability are used. The results demonstrated that SHPHP policy had the highest performance among the tested release policies.     

Multiobjective Pump Scheduling Optimization Using Harmony Search Algorithm (HSA) and Polyphonic HSA

Harmony Search Algorithm (HSA) is a metaheuristic method that has attracted the scientific interest since its first presentation in 2001. It is a music inspired method, imitating the music creation process in order to find optimal solutions in complicated problems. HSA’s successful application on single – objective optimization problems has resulted to an increasing interest in the implementation of HSA towards multiobjective optimization. The authors have adjusted HSA in order to deal successfully with multi-criteria water management problems. This adjustment has resulted to the creation of Multiobjective – HSA (MO-HSA). In addition, they have designed the multiobjective variant Polyphonic-HSA (Poly-HSA), which is inspired by the independent development of different voices in music and borrows elements from Swarm Intelligence and the single-objective variant Global-Best HSA. In the first part of this paper, both methods are presented in detail. Moreover, the performance of the proposed Algorithms is evaluated using standard multiobjective test – functions. ZDT and DTLZ multiobjective tests have been chosen and indicators such as Hypervolume, C – metric and diversity metric – Δ have been used to measure the convergence to the optimal front and the diversity of the solutions obtained by the proposed methods. In the second part, MO-HSA and Poly-HSA have been introduced towards the optimization of a pump scheduling problem. The objectives considered are water supply, pumping cost, electric power peak demand and pump maintenance cost. Both methods converged to non-dominated fronts and provided excellent results which are presented in 3d figures, indicating that these methods can be effectively used in multiobjective water management problems.     

改进粒子群优化算法在水电站群优化调度中的应用研究

针对常规粒子群优化算法易早熟，后期收敛慢且易陷入局部最优解的不足，提出一种新的惯性权重系数更新策略—自适应指数惯性权重系数（SEIWC）代替线性递减惯性权重系数（LDIWC），同时，将遗传算法中的染色体交叉、变异思想引入粒子的更新策略，提高粒子的多样性，增强算法的全局搜索能力。使用Rosenbrock函数和Schaffer函数验证了改进粒子群优化算法的有效性。以福建电网闽江流域水电站群优化调度为例，建立基于改进粒子群优化算法的库群长期优化调度模型，计算结果表明，该模型的调度结果显著优于常规粒子群优化算法，与逐步优化算法获得的结果达到相当水平。     

基于改进粒子群算法的重力坝断面优化设计

针对传统粒子群算法(PSO)存在局部收敛不稳定的缺陷,提出一种改进粒子群算法(D-PSO)。该算法通过提高平衡点的多样性,使其全局搜索能力得到明显增强,对求解多峰值优化问题具有较好的适应性。将D-PSO算法应用于重力坝断面优化设计中,优化结果表明,该算法具有易实现、鲁棒性强和精度高等优点,与其他算法相比更适合应用于重力坝断面的优化设计。