Grid-Connection Control of Small Hydropower Stations Based on the Principle of Quasi-Contemporaneous Grid-Connected

Yan, Ling‐Qi; Wang, Jizhong; Yang, Kai

doi:10.1007/978-981-33-4572-0_208

Cited by 2 publications

(2 citation statements)

References 2 publications

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“…min ≤ P j ≤ P j max (3) Where P j max and P j min are the maximum and minimum allowable output of the power station unit, respectively.Downstream water level variation constraint: the downstream water level must not only meet the maximum and minimum water levels but also the value of water level variation per unit time.…”

Section: P Jmentioning

confidence: 99%

“…In the process of power system transformation, new energy power represented by water conservancy and hydropower is incorporated into the power grid system in a high-speed and large-scale manner 2 . Under the new operating environment, grid-connection hydropower stations must undertake comprehensive utilization tasks such as power generation, shipping, and flood control 3 . This is an important support for the construction of a new power system under the dual carbon goals and a reliable guarantee for the efficient use of water resources in the basin.At the same time, the management of water resources in the basin has become more refined and strict.…”

Section: Introductionmentioning

confidence: 99%

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Optimizing Hydropower Station Scheduling: A Multi-Objective Real-Time Approach

Liu¹,

Meng

et al. 2023

Preprint

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Efficiency improvement in power generation and navigation for grid-connected hydropower stations has emerged as a significant concern due to challenges such as discrepancies between declared and actual ship arrival times, as well as unstable power generation. To address these issues, this paper proposes a multi-objective real-time scheduling model. The proposed model incorporates an energy storage mechanism and prediction mechanism .Using XGBoost, the actual arrival time of the boat to the water station is predicted. Furthermore, an energy storage mechanism is introduced to stabilize power generation by charging the power storage equipment during surplus generation and discharging it during periods of insufficient generation at the hydropower station. We design a new scheduling objective metric. The proposed model employs the Non-Dominated Sorting Beluga Whale Optimization (NSBWO) algorithm, which combines the Elitist Non-Dominated Sorting Genetic Algorithm (NSGA-II) and Beluga Whale Optimization (BWO), to optimize and solve the real-time discharge flow scheduling in hydropower stations across different time periods.Experimental results demonstrate the superiority of the proposed model in ship expected arrival time prediction and downstream flow scheduling, exhibiting higher prediction accuracy and better solutions. This research contributes a theoretical basis and provides a practical reference solution for addressing hydropower generation scheduling problems.

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Section: P Jmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimizing Hydropower Station Scheduling: A Multi-Objective Real-Time Approach

Liu¹,

Meng

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

Hydropower station scheduling with ship arrival prediction and energy storage

Zhou,

Liu,

Meng

et al. 2023

Sci Rep

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Effectiveness improvement in power generation and navigation for grid-connected hydropower stations have emerged as a significant concern due to the challenges such as discrepancies between declared and actual ship arrival times, as well as unstable power generation. To address these issues, this paper proposes a multi-objective real-time scheduling model. The proposed model incorporates energy storage and ship arrival prediction. An energy storage mechanism is introduced to stabilize power generation by charging the power storage equipment during surplus generation and discharging it during periods of insufficient generation at the hydropower stations. To facilitate the scheduling with the eneragy storage mechanism, the arrival time of ships to the stations are predicted. We use the maximization of generation minus grid load demand and the maximization of navigability assurance rate as two objective functions in the scheduling process. The model uses the Non-Dominated Sorting Beluga Whale Optimization (NSBWO) algorithm to optimize and solve the real-time discharge flow scheduling of the hydropower stations in different time periods. The NSBWO algorithm combines the Elitist Non-Dominated Sorting Genetic Algorithm (NSGA-II) and the Beluga Whale Optimization (BWO). The experimental results show that the proposed method has advantages in predicting the expected arrival time of ships and scheduling the discharge flow. The prediction using XGBoost model reaches accuracy with more than 0.9, and the discharged flow obtained from scheduling meets the demand of hydropower stations grid load while also improves the navigation benefits. This study provides theoretical analysis with its practical applications in a real hyropower station as a case study for solving hydropower scheduling problems.

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Grid-Connection Control of Small Hydropower Stations Based on the Principle of Quasi-Contemporaneous Grid-Connected

Cited by 2 publications

References 2 publications

Optimizing Hydropower Station Scheduling: A Multi-Objective Real-Time Approach

Optimizing Hydropower Station Scheduling: A Multi-Objective Real-Time Approach

Hydropower station scheduling with ship arrival prediction and energy storage

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