Optimization of Energy Storage Operation Chart of Cascade Reservoirs with Multi-Year Regulating Reservoir

Liu, Yi; Jiang, Zhiqiang; Feng, Zhong-kai; Chen, Yuyun; Zhang, Hairong; Chen, Ping

doi:10.3390/en12203814

Cited by 8 publications

(2 citation statements)

References 37 publications

(45 reference statements)

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“…The annual regulating reservoir can well regulate the water inequality within the year. The multi-year regulating reservoir can achieve the water distribution between years [91].…”

Section: Discussionmentioning

confidence: 99%

A New Clustering Method to Generate Training Samples for Supervised Monitoring of Long-Term Water Surface Dynamics Using Landsat Data through Google Earth Engine

et al. 2022

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Water resources are vital to the survival of living organisms and contribute substantially to the development of various sectors. Climatic diversity, topographic conditions, and uneven distribution of surface water flows have made reservoirs one of the primary water supply resources in Iran. This study used Landsat 5, 7, and 8 data in Google Earth Engine (GEE) for supervised monitoring of surface water dynamics in the reservoir of eight Iranian dams (Karkheh, Karun-1, Karun-3, Karun-4, Dez, UpperGotvand, Zayanderud, and Golpayegan). A novel automated method was proposed for providing training samples based on an iterative K-means refinement procedure. The proposed method used the Function of the Mask (Fmask) initial water map to generate final training samples. Then, Support Vector Machines (SVM) and Random Forest (RF) models were trained with the generated samples and used for water mapping. Results demonstrated the satisfactory performance of the trained RF model with the samples of the proposed refinement procedure (with overall accuracies of 95.13%) in comparison to the trained RF with direct samples of Fmask initial water map (with overall accuracies of 78.91%), indicating the proposed approach’s success in producing training samples. The performance of three feature sets was also evaluated. Tasseled-Cap (TC) achieved higher overall accuracies than Spectral Indices (SI) and Principal Component Transformation of Image Bands (PCA). However, simultaneous use of all features (TC, SI, and PCA) boosted classification overall accuracy. Moreover, long-term surface water changes showed a downward trend in five study sites. Comparing the latest year’s water surface area (2021) with the maximum long-term extent showed that all study sites experienced a significant reduction (16–62%). Analysis of climate factors’ impacts also revealed that precipitation (0.51 ≤ R2 ≤ 0.79) was more correlated than the temperature (0.22 ≤ R2 ≤ 0.39) with water surface area changes.

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“…The annual regulating reservoir can well regulate the water inequality within the year. The multi-year regulating reservoir can achieve the water distribution between years [91].…”

Section: Discussionmentioning

confidence: 99%

A New Clustering Method to Generate Training Samples for Supervised Monitoring of Long-Term Water Surface Dynamics Using Landsat Data through Google Earth Engine

et al. 2022

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“…There are a number of ESOC studies about the drawing, application, and optimization. Liu et al have studied the key issue of typical dry years selection and drawdown level optimization, then optimate the output coefficients of ESOC by the progressive optimality algorithm (POA) (Liu et al 2019). Cheng et al derive the ESOC from the single reservoir operation charts, and distribute the output of each reservoir according to the gap value of ESOC and single reservoir operation chart results (Cheng et al 2010).…”

Section: Introductionmentioning

confidence: 99%

Optimal Energy Storage Operation Chart and Output Distribution of Cascade Reservoirs Based on Operating Rules Derivation

Zhu

Zhou²,

Zhang³

et al. 2022

Water Resour Manage

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Energy storage operation chart (ESOC) has been one of the most popular method in cascade reservoirs conventional operation. However, the problem of distributing the total output obtained from the ESOC has not yet been solved reasonably. Discriminant coefficient method is a traditional method to guide the output distribution by determining the order of reservoir supply or storage, but cannot quantify the water used in operation. Thus, this study develops a new output distribution model using the polynomial fitting method and the artificial neural network (ANN) to express the functional relationship, which derive from deterministic optimization results of long-term runoff series with the goal of maximizing power generation.The cascade reservoirs of lower reaches of the Jinsha River in China are selected as a case study.By comparing with discriminant coefficient method and proposed method, the proposed method can rationally distribute the total output to avoid the problem of concentrated deserting water in downstream reservoirs, which usually happens in discriminant coefficient method.Generally, this study proposed an effective alternative method to guide the cascade reservoirs operation.

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Area Moment and Error Based Forecasting Difficulty and its Application in Inflow Forecasting Level Evaluation

Jiang

Tang

Liu

et al. 2019

Water Resour Manage

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Optimization of Energy Storage Operation Chart of Cascade Reservoirs with Multi-Year Regulating Reservoir

Cited by 8 publications

References 37 publications

A New Clustering Method to Generate Training Samples for Supervised Monitoring of Long-Term Water Surface Dynamics Using Landsat Data through Google Earth Engine

A New Clustering Method to Generate Training Samples for Supervised Monitoring of Long-Term Water Surface Dynamics Using Landsat Data through Google Earth Engine

Optimal Energy Storage Operation Chart and Output Distribution of Cascade Reservoirs Based on Operating Rules Derivation

Area Moment and Error Based Forecasting Difficulty and its Application in Inflow Forecasting Level Evaluation

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