Search Results (2)

Hydropower stations play a crucial role in meeting the demand for peak shaving in the power grid. A method called the adaptive segmented cutting load algorithm (ASCLA) is proposed to address the problem of the uneven distribution of regulation effects when formulating long-term peak-shaving dispatching plans for hydropower stations. This method mainly consists of three components: full-period load segmentation, sub-period end water level treatment, and staged cutting load optimization. It can improve the average regulation ability of hydropower stations for the power grid’s long-term load by combining the inflow conditions. In order to compare the progressiveness of the proposed method, the Three Gorges hydropower station and the Central China Power Grid were used as research objects, and its long-term peak-shaving performance was analyzed by comparing it with that of the classical HCL solution method. The simulation dispatching results show that the proposed method resulted in significantly improved peak-shaving indicators, such as the mean squared deviation of the rolling window, load fluctuation index, and peak value compared to HCL. In years with abundant reservoir runoff, the comprehensive improvement can reach about 25%, indicating that the proposed ASCLA has more advantages in responding to the long-term load regulation needs of the power grid compared to existing methods. The research results of this paper can provide a reference and guidance for peak-shaving dispatching in hydropower stations during the dry season, effectively improving the long-term peak-shaving benefits of hydropower stations. Full article

With the increasing share of renewable energy in the grid and the enhanced flexibility of the future power system, it is imperative for thermal power companies to explore alternative strategies. The flexible transformation of thermal power units is an effective strategy to address the previously mentioned challenges; however, the factors influencing the diffusion of this technology merit further investigation, yet they have been seldom examined by scholars. To address this gap, this issue is examined using an evolutionary game model of multi-agent complex networks, and a more realistic group structure is established through heterogeneous group differentiation. With factors such as group relationships, diffusion paths, compensation electricity prices, and subsidy intensities as variables, several diffusion scenarios are developed for research purposes. The results indicate that when upper-level enterprises influence the decision-making of lower-level enterprises, technology diffusion is significantly accelerated, and enhanced communication among thermal power enterprises further promotes diffusion. Among thermal power enterprises, leveraging large and medium-sized enterprises to promote the flexibility transformation of units proves to be an effective strategy. With regard to factors like the compensation price for depth peak shaving, the initial application ratio of groups, and the intensity of government subsidies, the compensation price emerges as the key factor. Only with a high compensation price can the other two factors effectively contribute to promoting technology diffusion. Full article