Ecological operation of cascade hydropower reservoirs by elite-guide gravitational search algorithm with Lévy flight local search and mutation

Feng, Zhong-kai; Liu, Shuai; Niu, Wen-jing; Li, Shushan; Wu, Huijun; Wang, Jiayang

doi:10.1016/j.jhydrol.2019.124425

Cited by 53 publications

(22 citation statements)

References 71 publications

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“…is is very important in hydropower development, and ecological aspects should be well planned. is is to minimize the ecological damage by the hydropower stations [37][38][39][40][41]. erefore, the results of this research can be very useful in the protection of the ecology downstream of the minihydropower plant.…”

Section: Results For the Erathna Minihydropower Plantmentioning

confidence: 99%

Relationships between Hydropower Generation and Rainfall-Gauged and Ungauged Catchments from Sri Lanka

Perera

Rathnayake

2020

Mathematical Problems in Engineering

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The relationship between the rainfall and minihydropower generation in a catchment is highly nonlinear. Therefore, the prediction of minihydropower generation is complex. However, the prediction is important in optimizing the control of electricity generation under various environmental conditions. Ongoing climate variabilities have completely changed the minihydropower generation to some parts of the world, and it is significant. Therefore, this paper presents results from two soft-computing studies in searching the relationships between rainfall and the generated hydropower. The first study was carried out for a gauged catchment; however, the second was carried for an ungauged catchment. Results revealed that there is an acceptable correlation in between the rainfall and hydropower generation for the gauged catchment and a marginal contribution to the ungauged catchment.

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Section: Results For the Erathna Minihydropower Plantmentioning

confidence: 99%

Relationships between Hydropower Generation and Rainfall-Gauged and Ungauged Catchments from Sri Lanka

Perera

Rathnayake

2020

Mathematical Problems in Engineering

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“…QUATRE is an excellent algorithm which improved the drawback of DE that did not achieve equilibrium search in search space without prior knowledge and moveover, it generalized the crossover operation of DE from vector to matrix. In algorithms based on physical or mathematical models, Simulated Annealing (SA) [38], [39] originates from the principle of solid annealing; Gravitational Search Algorithm (GSA) [40], [41] mainly uses the law of gravitation between two objects to guide the motion optimization of each particle to search for the optimal solution; Sine Cosine Algorithm (SCA) [42], [43] is achieved by iteration of sine and cosine functions.…”

Section: Introductionmentioning

confidence: 99%

Optimal Design and Simulation for PID Controller Using Fractional-Order Fish Migration Optimization Algorithm

et al. 2021

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“…Long-term runoff forecasting is essential for the optimal management of hydroresources (Evsukoff et al 2012;Meng et al 2019), ecological restoration (Feng et al 2020a), flood mitigation (He et al 2020), power generation (Feng et al 2020b), irrigation scheduling (Poul et al 2019), etc. The problem has received extensive attention of researchers (Kisi and Sanikhani 2015;Wang et al 2009;Xiang et al 2020;Zamani Sabzi et al 2017).…”

Section: Introductionmentioning

confidence: 99%

An Ensemble Hybrid Forecasting Model for Annual Runoff Based on Sample Entropy, Secondary Decomposition, and Long Short-Term Memory Neural Network

Wang

Chau

et al. 2021

Water Resour Manage

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Accurate and consistent annual runoff prediction in regions is a hot topic in the management, optimization, and monitoring of water resources. A novel prediction model (ESMD-SE-WPD-LSTM) is presented in this study. Firstly, the extreme-point symmetric mode decomposition (ESMD) is used to produce several intrinsic mode functions (IMF) and a residual (Res) by decomposing the original runoff series.Secondly, the sample entropy (SE) method is employed to measure the complexity of each IMF. Thirdly, we adopt wavelet packet decomposition (WPD) to further decompose the IMF with the maximum SE into several appropriate components and detailed components. Then the LSTM model, a deep learning algorithm based recurrent approach, is employed to predict all components obtained in the previous step. Finally, the forecasting results of all components are aggregated to generate the final prediction.The proposed model, which is applied to five annual series from different areas in China, is evaluated based on four quantitative indexes (R, NSEC, MAPE and RMSE). The results indicate that the ESMD-SE-WPD-LSTM outperforms other benchmark models in terms of four quantitative indexes. Hence the proposed model can provide higher accuracy and consistency for annual runoff prediction, making it an efficient instrument for scientific management and planning of water resources.

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Ecological operation of cascade hydropower reservoirs by elite-guide gravitational search algorithm with Lévy flight local search and mutation

Cited by 53 publications

References 71 publications

Relationships between Hydropower Generation and Rainfall-Gauged and Ungauged Catchments from Sri Lanka

Relationships between Hydropower Generation and Rainfall-Gauged and Ungauged Catchments from Sri Lanka

Optimal Design and Simulation for PID Controller Using Fractional-Order Fish Migration Optimization Algorithm

An Ensemble Hybrid Forecasting Model for Annual Runoff Based on Sample Entropy, Secondary Decomposition, and Long Short-Term Memory Neural Network

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