Research on joint flood control operation rule of parallel reservoir group based on aggregation–decomposition method

Pan, Zihao; Chen, Lihua; Teng, Xiang

doi:10.1016/j.jhydrol.2020.125479

Cited by 18 publications

(10 citation statements)

References 23 publications

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“…The final operation strategy obtained is the optimal one obtained by the DP algorithm, until the objective function cannot be further improved. DP can combine with other optimization algorithms in practical problems, such as progressive optimality algorithm (POA) [28]. In POA, it is not necessary for the state variables to be discrete, so more accurate solutions can be obtained.…”

Section: Optimization Methodsmentioning

confidence: 99%

Operation Rule Derivation of Hydropower Reservoirs by Support Vector Machine Based on Grey Relational Analysis

Zhu

Zhou

Qiu

et al. 2021

Water

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In practical applications, the rational operation rule derivation can lead to significant improvements in the middle and long-term joint operation of cascade hydropower stations. The key issue of actual optimal operation is to select effective attributions from the deterministic optimal operation results, however, there is still no general and mature method to solve this problem. Firstly, the joint optimal operation model of hydropower reservoirs considering backwater effects are established. Then, the dynamic programming and progressive optimality algorithm are applied to solve the joint optimal operation model and the deterministic optimization results are obtained. Finally, the grey relational analysis method is applied to select more effective factors from the obtained results as the input of a support vector machine for further operation rule derivation. The Xi Luo-du and Xiang Jia-ba cascade reservoirs in the upper Yangtze river of China are selected as a case study. The results show that the proposed method can obtain better input factors to improve the performance of SVM, and smallest value of root mean square error by the proposed method of Xi Luo-du and Xiang Jia-ba are 94.33 and 21.32, respectively. The absolute error of hydropower generation for Xi Luo-du and Xiang Jia-ba are 2.57 and 0.42, respectively. Generally, this study provides a well and promising alternative tool to guide the joint operation of hydropower reservoir systems.

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Section: Optimization Methodsmentioning

confidence: 99%

Operation Rule Derivation of Hydropower Reservoirs by Support Vector Machine Based on Grey Relational Analysis

Zhu

Zhou

Qiu

et al. 2021

Water

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“…In this paper, an aggregated SSDP is used to obtain the initial solution. Some aggregation-disaggregation approaches exist for reservoir operations [4][5][6][7], while the aggregated SSDP used in this paper need not accurately solve the optimal operation model, for the aim of the aggregated SSDP is only used to obtain an initial solution, and the final operation rule can be improved through simulation-optimization. To aggregate a large-scale hydropower system, the storage energy, as in Equation 1, is used as a state variable, and the power generation of the whole system is the decision variable.…”

Section: Derive Initial Operation Rule Using An Aggregated Ssdpmentioning

confidence: 99%

“…Considering system states, inflow uncertainty, power system demands [1], and other factors, hydropower systems adopt operating rules widely to determine the power generations of each reservoir in the current period. The methods based on dynamic programming (DP), including stochastic dynamic programming (SDP) [2], sampling stochastic dynamic programming (SSDP) [3], aggregation-disaggregation approach [4][5][6][7], and stochastic dual dynamic programming (SDDP) [8,9], are among the most popular reservoir operation methods. Yeh [10] and Labadie [11] presented the state-of-the-art views for the optimization method for reservoir operation.…”

Section: Introductionmentioning

confidence: 99%

Combined Aggregated Sampling Stochastic Dynamic Programming and Simulation-Optimization to Derive Operation Rules for Large-Scale Hydropower System

Guo

Cheng

et al. 2021

Energies

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Simulation-optimization methods are often used to derive operation rules for large-scale hydropower reservoir systems. The solution of the simulation-optimization models is complex and time-consuming, for many interconnected variables need to be optimized, and the objective functions need to be computed through simulation in many periods. Since global solutions are seldom obtained, the initial solutions are important to the solution quality. In this paper, a two-stage method is proposed to derive operation rules for large-scale hydropower systems. In the first stage, the optimal operation model is simplified and solved using sampling stochastic dynamic programming (SSDP). In the second stage, the optimal operation model is solved by using a genetic algorithm, taking the SSDP solution as an individual in the initial population. The proposed method is applied to a hydropower system in Southwest China, composed of cascaded reservoir systems of Hongshui River, Lancang River, and Wu River. The numerical result shows that the two-stage method can significantly improve the solution in an acceptable solution time.

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“…The optimization theories and methods can be divided into three categories: optimization methods based on mathematical theory, optimization methods based on evolutionary theory, and hybrid optimization methods [20]. The optimization methods based on mathematical theory include linear programming (LP) [21,22], nonlinear programming (NP) [23,24], dynamic programming (DP) [25][26][27], and large-scale system decomposition-coordination (LSSDC) [28]. The optimization methods based on evolutionary theory have developed rapidly in recent years, and include the non-dominated sorting genetic algorithm II (NSGA-II) [29][30][31], ant colony optimization (ACO) [32,33], the artificial bee colony algorithm (ABCA) [34], particle swarm optimization (PSO) [35][36][37], the artificial neural network (ANN) [38,39], and the simulated annealing algorithm (SAA) [40].…”

Section: Introductionmentioning

confidence: 99%

Multi-Stakeholder Coordinated Operation of Reservoir Considering Irrigation and Ecology

Wei

Lu³

et al. 2022

Water

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In traditional ecological operation, it is difficult to coordinate the balance among the interests of stakeholders, and stakeholders find it difficult to accept the operation scheme. To address these problems, this study proposed a method of multi-stakeholder coordinated operation of reservoir (MSCOR). By comprehensively considering the interest demands of stakeholders, the multi-stakeholder interval coordination mechanism (MSICM) for reservoir operation was established. The multi-stakeholder coordinated operation model (MSCOM) was constructed. The multi-stakeholder solution algorithm based on the MSICM, the non-dominated sorting genetic algorithm II, and the approach of successive elimination of alternative schemes based on the k-order and p-degree of efficiency (MSIC-NSGA-II-SEABODE) were applied to solve the MSCOR problem. The coordination mechanism, model construction, multi-stakeholder optimization, and multi-attribute decision making were coupled to establish a multi-stakeholder coordinated operation method, comprising the whole process of mechanism–modeling–optimization–decision making. Taking Baojixia Reservoir as an example, the performance of the coordinated operation method was compared with that of the traditional optimal operation method, and the relationship between the irrigation benefits and ecological benefits of the reservoir was explored. The results show that: (1) On the premise of the same satisfaction degree of basic irrigation interests, the ecological AAPFD value of coordinated operation decreased by 0.184, 0.469, and 0.886 in a normal year, dry year, and extraordinary dry year, respectively. The effect of coordinated operation on balancing various stakeholders was more obvious with the decrease in water inflow. (2) The MSICM ensures that the multi-stakeholder operation of the reservoir conforms to the principles of comprehensiveness, balance, and sustainability. (3) The coordination scheme obtained by the MSIC-NSGA-II-SEABODE algorithm is more reasonable and feasible. The research results provide a new idea and method to address the MSCOR problem.

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Research on joint flood control operation rule of parallel reservoir group based on aggregation–decomposition method

Cited by 18 publications

References 23 publications

Operation Rule Derivation of Hydropower Reservoirs by Support Vector Machine Based on Grey Relational Analysis

Operation Rule Derivation of Hydropower Reservoirs by Support Vector Machine Based on Grey Relational Analysis

Combined Aggregated Sampling Stochastic Dynamic Programming and Simulation-Optimization to Derive Operation Rules for Large-Scale Hydropower System

Multi-Stakeholder Coordinated Operation of Reservoir Considering Irrigation and Ecology

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