Effects of Valley Topography on Acoustic Communication in Birds: Why Do Birds Avoid Deep Valleys in Daqinggou Nature Reserve?

To investigate the effects of valley topography on the acoustic transmission of avian vocalisations, we carried out playback experiments in Daqinggou valley, Inner Mongolia, China. During the experiments, we recorded the vocalisations of five avian species, the large-billed crow (Corvus macrorhynchos Wagler, 1827), common cuckoo (Cuculus canorus Linnaeus, 1758), Eurasian magpie (Pica pica Linnaeus, 1758), Eurasian tree sparrow (Passer montanus Linnaeus, 1758), and meadow bunting (Emberiza cioides Brand, 1843), at transmission distances of 30 m and 50 m in the upper and lower parts of the valley and analysed the intensity, the fundamental frequency (F0), and the first three formant frequencies (F1/F2/F3) of the sounds. We also investigated bird species diversity in the upper and lower valley. We found that: (1) at the distance of 30 m, there were significant differences in F0/F1/F2/F3 in Eurasian magpies, significant differences in F1/F2/F3 in the meadow bunting and Eurasian tree sparrow, and partially significant differences in sound frequency between the upper and lower valley in the other two species; (2) at the distance of 50 m, there were significant differences in F0/F1/F2/F3 in two avian species (large-billed crow and common cuckoo) between the upper and lower valley and partially significant differences in sound frequency between the upper and lower valley in the other three species; (2) there were significant differences in the acoustic intensities of crow, cuckoo, magpie, and bunting calls between the upper and lower valley. (3) Species number and richness were significantly higher in the upper valley than in the lower valley. We suggested that the structure of valley habitats may lead to the breakdown of acoustic signals and communication in birds to varying degrees. The effect of valley topography on acoustic communication could be one reason for animal species avoiding deep valleys

Spatiotemporal Complementary Characteristics of Large-Scale Wind Power, Photovoltaic Power, and Hydropower

With the increasing proportion of renewable energy in power generation, the mixed utilization of multiple renewable energy sources has gradually become a new trend. Using the natural complementary characteristics of wind power, photovoltaic, and hydropower to evaluate the complementary potential of various energy sources has become a hot issue in the research of mixed utilization. Given that traditional complementarity research can only assess the complementarity between two energy sources, this paper proposes a method to simultaneously determine the complementarity between three large-scale renewable energy sources. Firstly, a three-dimensional vector represents the complementary characteristic combination of any two energy sources. The complementary characteristics of the three energy sources were obtained by finding the optimal solution for the three-dimensional vector. Finally, power stations were selected, located in different spatial areas on the world’s largest renewable energy base in Qinghai, China, as the research object to analyze and verify the complementary characteristics of wind-power–photovoltaic-power–hydropower at different spatiotemporal scales. The results show significant differences in the complementary characteristics of different time scales. The farther the spatial distance between different power stations, the stronger their complementarity. The best complementary index on the monthly and daily scales was improved by 8.49% and 6.51%. This study provides a new focus for the future evaluation of the complementary utilization potential of large-scale joint renewable energy in different world regions

Research on Capacity Allocation Optimization of Commercial Virtual Power Plant (CVPP)

Commercial virtual power plants (CVPP) connect the form of renewable energy resource portfolio to the power market and reduce the risk of the unstable operation of a single renewable energy. Combining different kinds of large-scale renewable energy in CVPP to provide capacity services like base load, peak shaving, and valley-filling, etc., for the system loads is an urgent problem to be solved. Therefore, it is valuable to analyze the capacity allocation ratio of the CVPP to maximize the utilization of all kinds of energy, especially for the large-scale multi-energy base. This paper proposed a multi-energy coordinated operation framework by considering various load demands, including base load and peak shaving for the capacity allocation of CVPP based on the world’s largest renewable energy resource base on the upstream area of the Yellow River. The main procedures of this framework are as follows: (1) A paratactic model satisfying base load and peak shaving is proposed to determine the ability of the CVPP operation model’s capacity services to meet the different demands of the power system load. (2) A hybrid dimension reduction algorithm with a better convergence rate and optimization effect solves the proposed paratactic model based on the ReliefF and the Adaptive Particle Swarm Optimization (APSO). The results show that the large-scale CVPP with different compositions can achieve both of the goals of a stable base load output and stable residual load under different weather conditions. Compared with the operation on sunny days, the base load fluctuation and residual load fluctuation of CVPP on rainy days are reduced by 14.5% and 21.9%, respectively, proving that CVPP can alleviate renewable energy’s dependence on weather and improve energy utilization