Optimization of Year-End Water Level of Multi-Year Regulating Reservoir in Cascade Hydropower System Considering the Inflow Frequency Difference

Jiang, Zhiqiang; Song, Peibing; Liao, Xiang

doi:10.3390/en13205345

Cited by 12 publications

(9 citation statements)

References 24 publications

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“…Hydropower production is an important function of many multireservoir systems [3,12,29]. The LTOS model of hydropower generation for a multireservoir system built by Liu et al [26] is employed in the study.…”

Section: Ltos Model and Cs Algorithmmentioning

confidence: 99%

“…According to the scheduling timescale, reservoir scheduling could be generally divided into short-term (hourly/daily) scheduling, mid-term (weekly/monthly) scheduling, and long-term (seasonal/annual) scheduling [11,12]. The LTOS of MRS reservoirs could offer water utilization objectives and constraints for the short-and mid-term scheduling of a multireservoir system, hence influencing the comprehensive water utilization benefits of the entire system [10,13].…”

Section: Introductionmentioning

confidence: 99%

“…The WL not only determines the WSV at the end of a wet season, but also affects the available water (storage and inflow) volume during the dry season of the same year [16,17]. As for the DL, it not only influences the discharge during the dry season of a year, but also affects the available water volume of the next year [5,7,12,18].…”

Section: Introductionmentioning

confidence: 99%

“…In order to alleviate the conflict between flood control and water utilization in wet season, Chou and Wu [19] investigated the stagewise flood moderating rules, and Peng et al [20] and Liu et al [21] studied the dynamic control of flood limit level of reservoirs, but they failed to specify how much water should be retained in MRS reservoirs at the end of the wet season. Some scholars are devoted to determining the DL by means of statistical regression analysis methods or machine learning techniques [11,12,15,19,22]. However, these studies focused on determining the DL for an individual MRS reservoir without considering its role in a multireservoir system, or they treated the DL of each year in isolation without considering the linkage of DL between adjacent years.…”

Section: Introductionmentioning

confidence: 99%

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Three-Parameter Regulation Rules for the Long-Term Optimal Scheduling of Multiyear Regulating Storage Reservoirs

Xie

Liu

Fang

et al. 2021

Water

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The perennial storage water level (PL), the water level at the end of wet season (WL), and the water level at the end of dry season (DL) are three critical water levels for multiyear regulating storage (MRS) reservoirs. Nevertheless, the three critical water levels have not been paid enough attention, and there is no general method that calculates them in light of developing regulating rules for MRS reservoirs. In order to address the issue, three-parameter regulation (TPR) rules based on the coordination between the intra- and interannual regulation effects of MRS reservoirs are presented. Specifically, a long-term optimal scheduling (LTOS) model is built for maximizing the multiyear average hydropower output (MAHO) of a multireservoir system. The TPR rules are a linear form of rule with three regulation parameters (annual, storage, and release regulation parameters), and use the cuckoo search (CS) algorithm to solve the LTOS model with three regulation parameters as the decision variables. The approach of utilizing the CS algorithm to solve the LTOS model with the WL and DL as the decision variables is abbreviated as the OPT approach. Moreover, the multiple linear regression (MLR) rules and the artificial neural network (ANN) rules are derived from the OPT approach-based water-level processes. The multireservoir system at the upstream of Yellow River (UYR) with two MRS reservoirs, Longyangxia (Long) and Liujiaxia (Liu) reservoirs, is taken as a case study, where the TPR rules are compared with the OPT approach, the MLR rules, and the ANN rules. The results show that for the UYR multireservoir system, (1) the TPR rules-based MAHO is about 0.3% (0.93 × 108 kW∙h) more than the OPT approach-based MAHO under the historical inflow condition, and the elapsed time of the TPR rules is only half of that of the OPT approach; (2) the TPR rules-based MAHO is about 0.79 × 108 kW∙h more than the MLR/ANN rules-based MAHO under the historical inflow condition, and the TPR rules can realize 0.1–0.4% MAHO more than the MLR and ANN rules when the reservoir inflow increases or reduces by 10%. According to the annual regulation parameter, the PLs of Long and Liu reservoirs are 2572.3 m and 1695.2 m, respectively. Therefore, the TPR rules are an easy-to-obtain and adaptable LTOS rule, which could reasonably and efficiently to determine the three critical water levels for MRS reservoirs.

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Section: Ltos Model and Cs Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Three-Parameter Regulation Rules for the Long-Term Optimal Scheduling of Multiyear Regulating Storage Reservoirs

Xie

Liu

Fang

et al. 2021

Water

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“…Grid search and cross-validation techniques are used to calibrate parameters of the SVR model to improve the performance of SVR. Jiang et al [16] used the least square principle to derive operation rules of the Lianghekou reservoir based on optimal computing results of multi-dimensional dynamic programming. The deterministic optimization may also encounter the curse of dimensionality, and the simulation result may be far from the deterministic optimization if the operation function or operation rule is not well derived.…”

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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Multi-objective optimization of a hydro-wind-photovoltaic power complementary plant with a vibration avoidance strategy

et al. 2021

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Optimization of Year-End Water Level of Multi-Year Regulating Reservoir in Cascade Hydropower System Considering the Inflow Frequency Difference

Cited by 12 publications

References 24 publications

Three-Parameter Regulation Rules for the Long-Term Optimal Scheduling of Multiyear Regulating Storage Reservoirs

Three-Parameter Regulation Rules for the Long-Term Optimal Scheduling of Multiyear Regulating Storage Reservoirs

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

Multi-objective optimization of a hydro-wind-photovoltaic power complementary plant with a vibration avoidance strategy

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