A Long-Term Operational Scheme for Hybrid Hydro-Photovoltaic (PV) Systems that Considers the Uncertainties in Reservoir Inflow and Solar Radiation Based on Scenario Trees

Han Cao, Jun Qiu, Hui-Min Zuo and Fang-Fang Li ()
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Han Cao: China Agricultural University
Jun Qiu: Qinghai University
Hui-Min Zuo: China Agricultural University
Fang-Fang Li: China Agricultural University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2023, vol. 37, issue 14, No 1, 5379-5398

Abstract: Abstract Most available long-term operation models for hydropower stations use deterministic historical data as inputs but cannot be employed to update the decision scheme in real time according to the actual solar radiation and inflow conditions, resulting in a disconnect between the given plan and actual decision-making process. In this study, a multistage rolling reservoir decision model considering the uncertainties in solar radiation and inflow is proposed to guide the formulation of long-term operational schemes for hydro-PV systems. We adopt the solar radiation and inflow series generated by the scenario tree (ST) method as inputs of the reservoir optimal operation model and use a genetic algorithm (GA) to solve the model. In the solution process, the scheme is adjusted according to the actual solar radiation and inflow conditions. Typical wet, normal, and dry years are analysed. The results illustrate that the model can better inform the design of long-term operational schemes for hydro-PV stations relative to the actual operational scheme and the traditional deterministic model.

Keywords: Uncertainty; Scenario tree (ST); Hydro-PV system; Long-term operational scheme (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11269-023-03609-7

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