Abstract

The large-scale development of renewable energy sources leads to high demand for energy storage. Pumped hydropower storage (PHS) is one of the most reliable and economic schemes, which uses a pair of lakes with different elevations. In this paper, we present a methodology for PHS potential evaluation optimization in the Qinghai-Tibet Plateau. We first evaluate the current PHS potential in the plateau. There are 6813 potential sites for the entire plateau, and its mean density is 3.0, i.e., an average of 3.0 potential sites surrounding each grid within 20 km. The non-zero region accounts for 25.4%, means that more than a quarter of the study area has access to PHS under the abovementioned assumptions. Then, we optimize the energy storage paths by a linear programming model. According to the proposed optimization method, the number of PHS potential sites is reduced to 1916, while the density of potential sites is reduced to 0.84. At the same time, the percentage of the non-zero region is kept at a certain level after optimization (21.5%), suggesting that the optimization can sharply reduce evaluation redundancy in lake-intensive area, without reducing the PHS availability in areas with fewer lakes. Moreover, the mean value of energy storage coefficient decreases to 2.5 h, which means energy storage potential of 2.5 kWh per kilowatt of potential wind and solar energy capacity, confirming the algorithm's ability to provide a more accurate potential estimate. Our study shows that the central and southern Qinghai-Tibet Plateau can provide more stable clean electricity, implying a great significance of power grid infrastructure development in these areas.

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