The stochastic short-term hydropower generation scheduling considering uncertainty in load output forecasts

Yang, Zhe; Wang, Yufeng; Yang, Kun

doi:10.1016/j.energy.2021.122838

Cited by 6 publications

(2 citation statements)

References 40 publications

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“…Large numbers of papers (Alvarez et al, 1994;Asif & Muneer, 2007;Jiang et al, 2018;Marchand et al, 2019;Xu, J., Liu, Z., Jiang, 2021;Y. Yang et al, 2020;Z. Yang et al, 2022) are devoted to solving the generation plan problems.…”

Section: Introductionmentioning

confidence: 99%

Optimization tool for small hydropower plant resource planning and development: A case study

Çoban

Sauhats

2022

Journal of Advanced Research in Natural and Applied Sciences

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The dimensions and significance of the modern power systems prove the necessity to change the principles of energy generation and power supply planning and management. In order to decrease carbon dioxide emissions, fight climate change, not being attached to fuel resources, and increase energy security while decreasing dependence on foreign countries, governments of many countries are increasing the share of renewable energy in electricity production and have taken actions to exploit their domestic resources, which is why renewable energy is an essential and important issue in today‘s world and also in the future it may continue to play a globally essential role. The study addresses model applications, optimization techniques, and operational issues. The main goal was devoted to the problem of small-scale hydropower plant control regime optimization. The task of determining small hydropower plant operation conditions is solved by striving for maximum profit by looking at the cases of known variations of prices in the market environment. An optimization tool known as the Quasi-Newton method for nonlinear optimization tasks is used to plan energy generation under uncertainties. The opportunity to apply the Monte-Carlo method for the feasibility study is demonstrated

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Section: Introductionmentioning

confidence: 99%

Optimization tool for small hydropower plant resource planning and development: A case study

Çoban

Sauhats

2022

Journal of Advanced Research in Natural and Applied Sciences

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“…The runoff process during the process of hydropower plant operation is uncertain, which limits the traditional algorithms and determined dynamic programming, while the SDP algorithm fully takes the uncertain factors into consideration [20,21]. Little [22] applied the Markov theory to construct the SDP model of a hydropower plant.…”

Section: Introductionmentioning

confidence: 99%

Study on the Optimal Operation of a Hydropower Plant Group Based on the Stochastic Dynamic Programming with Consideration for Runoff Uncertainty

Zhang

Chang

et al. 2022

Water

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Hydropower plant operation reorganizes the temporal and spatial distribution of water resources to promote the comprehensive utilization of water resources in the basin. However, a lot of uncertainties were brought to light concerning cascade hydropower plant operation with the introduction of the stochastic process of incoming runoff. Therefore, it is of guiding significance for the practice operation to investigate the stochastic operation of cascade hydropower plants while considering runoff uncertainty. The runoff simulation model was constructed by taking the cascade hydropower plants in the lower reaches of the Lancang River as the research object, and combining their data with the copula joint function and Gibbs method, and a Markov chain was adopted to construct the transfer matrix of runoff between adjacent months. With consideration for the uncertainty of inflow runoff, the stochastic optimal operation model of cascade hydropower plants was constructed and solved by the SDP algorithm. The results showed that 71.12% of the simulated monthly inflow of 5000 groups in the Nuozhadu hydropower plant drop into the reasonable range. Due to the insufficiency of measured runoff, there were too many 0 values in the derived transfer probability, but after the simulated runoff series were introduced, the results significantly improved. Taking the transfer probability matrix of simulated runoff as the input of the stochastic optimal operation model of the cascade hydropower plants, the operation diagram containing the future-period incoming water information was obtained, which could directly provide a reference for the optimal operation of the Nuozhadu hydropower plant. In addition, taking the incoming runoff process in a normal year as the standard, the annual mean power generation based on stochastic dynamic programming was similar to that based on dynamic programming (respectively 305.97 × 108kW⋅h and 306.91 × 108kW⋅h), which proved that the operation diagram constructed in this study was reasonable.

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Stochastic optimization and scenario generation for peak load shaving in Smart District microgrid: sizing and operation

Bagheri

Dagdougui

Gendreau

2022

Energy and Buildings

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The stochastic short-term hydropower generation scheduling considering uncertainty in load output forecasts

Cited by 6 publications

References 40 publications

Optimization tool for small hydropower plant resource planning and development: A case study

Optimization tool for small hydropower plant resource planning and development: A case study

Study on the Optimal Operation of a Hydropower Plant Group Based on the Stochastic Dynamic Programming with Consideration for Runoff Uncertainty

Stochastic optimization and scenario generation for peak load shaving in Smart District microgrid: sizing and operation

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