Short-Term Peak-Shaving Operation of Single-Reservoir and Multicascade Hydropower Plants Serving Multiple Power Grids

Liao, Shengli; Zhang, Yan; Liu, Jie; Liu, Benxi; Liu, Zhanwei

doi:10.1007/s11269-020-02751-w

Cited by 7 publications

(1 citation statement)

References 26 publications

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“…Their model aims to minimize peak-to-valley differences in residual load while incorporating a contingency constraint on forecast errors to coordinate the operation of hydropower with wind and solar energy. In medium and long-term optimal dispatch [15], where there is a significant difference from the short-term, Liao Shengli et al [16] introduced an accurate optimization model for determining the mid-term peak shaving operation of a stepped hydropower plant while considering water delay times. They proposed a piecewise delay time method (PDTM) based on the water balance equation to accurately describe water delay times in cascade hydropower plants.…”

Section: Introductionmentioning

confidence: 99%

An Advanced Peaking Method for Improved Hydropower Plant Regulation and Power Grid Management

Chang

Zhang

2023

Preprint

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Hydropower, as a crucial component of power grid systems, plays an essential role in peak regulation due to its fast start-stop and high-speed climbing capabilities. Current hydropower peak regulation methods struggle to consider complex load demand and the highly coupled characteristics of runoff simultaneously. This study proposes the Adaptive Segmented Cutting Load Algorithm (ASCLA) to restructure the power station's load process and segment the scheduling period based on load characteristics, ensuring hydropower stations operate in peak regulation mode throughout the entire cycle. The method determines each sub-scheduling period's peak regulation depth based on runoff characteristics and considers factors impacting peak regulation capability. To minimize the residual load's rolling data window standard deviation, we apply ASCLA to the Three Gorges Reservoir (TGR) simulation. We introduce four evaluation indicators: Mean Squared Deviation of the Rolling Window (MSDRW), total time variation of residual load, peak residual load, and response time to assess peak regulation effectiveness. Our method can handle peak regulation demands under varying runoff conditions, providing feasible scheduling solutions. Simulations and analyses reveal ASCLA demonstrates stronger load tracking ability, a broader adjustment range of load peaks and valleys, and a more significant peak regulation effect compared to the conventional method. Finer segmentation of sub-scheduling periods and final water level determination under conditions of higher load variability and drier runoff optimizes the power station's regulation capacity and meets the power grid's operational needs. In conclusion, our research develops a comprehensive and adaptable peak regulation scheduling model for hydropower stations, offering more effective solutions to address challenges related to extreme weather events and renewable energy integration.

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Section: Introductionmentioning

confidence: 99%

An Advanced Peaking Method for Improved Hydropower Plant Regulation and Power Grid Management

Chang

Zhang

2023

Preprint

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Hydropower Reservoir Optimization with Solar Generation-Changed Energy Prices in California

Dogan,

Medellin-Azuara,

Lund

2024

Water Resour Manage

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Growing solar photovoltaic supply has significantly reshaped energy prices, lowering them during solar generating hours. Large-scale hydropower reservoir operations need to adapt to changes in energy prices to maximize hydropower revenue. This paper evaluates effects of solar generation-changed energy prices on hydropower generation for five multipurpose reservoirs in California using a hydroeconomic optimization model. In California, major solar generation began in 2013, so years 2010–2012 are a pre-solar period, and years 2013–2018 are post-solar. Reservoir operations, hydropower generation and revenue between these periods are compared. Operations in the wet season (January to June), and the dry season (July to December) are evaluated. Results show that releases are more profitable when hydropower is generated twice a day during on-peak hours in the morning and evening in the wet season. When water is scarce, energy is generated only during the higher-price evening peak. Hydropower generation is mostly curtailed between 10am and 6pm due to large solar supplies, and increase during morning and evening peaks when solar generation is unavailable. However, by optimizing hydropower scheduling hours, the new energy price pattern can be more profitable. With increased energy price variability and adaptation, overall daily revenue can increase by about 14% in the wet season and 30% in the dry season.

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Improved progressive optimality algorithm and its application to determination of optimal release trajectory of long-term power generation operation of cascade reservoirs

Chen¹,

Qi²,

Qiu

et al. 2022

Advances in Water Resources

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Short-Term Peak-Shaving Operation of Single-Reservoir and Multicascade Hydropower Plants Serving Multiple Power Grids

Cited by 7 publications

References 26 publications

An Advanced Peaking Method for Improved Hydropower Plant Regulation and Power Grid Management

An Advanced Peaking Method for Improved Hydropower Plant Regulation and Power Grid Management

Hydropower Reservoir Optimization with Solar Generation-Changed Energy Prices in California

Improved progressive optimality algorithm and its application to determination of optimal release trajectory of long-term power generation operation of cascade reservoirs

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