With the continuous increase in global energy demand and growing environmental awareness, the utilization of renewable energy has become a worldwide consensus. In order to address the challenges posed by the intermittent and unpredictable nature of renewable energy in distributed power distribution networks, as well as to improve the economic and operational stability of distribution systems, this paper proposes the establishment of an active distribution network capable of accommodating renewable energy. The objective is to enhance the efficiency of new energy utilization. This study investigates optimal scheduling models for energy storage technologies and economic-operation dispatching techniques in distributed power distribution networks. Additionally, it develops a comprehensive demand response model, with real-time pricing and incentive policies aiming to minimize load peak–valley differentials. The control mechanism incorporates time-of-use pricing and integrates a chaos particle swarm algorithm for a holistic approach to solution finding. By coordinating and optimizing the control of distributed power sources, energy storage systems, and flexible loads, the active distribution network achieves minimal operational costs while meeting demand-side power requirements, striving to smooth out load curves as much as possible. Case studies demonstrate significant enhancements during off-peak periods, with an approximately 60% increase in the load power overall elevation of load factors during regular periods, as well as a reduction in grid loads during evening peak hours, with a maximum decrease of nearly 65 kW. This approach mitigates grid operational pressures and user expense, effectively enhancing the stability and economic efficiency in distribution network operations.

Utilizing panel data spanning from 2010 to 2021 across 30 Chinese provinces, this study examines the spatiotemporal dynamics of green finance and its correlation with high-quality economic development. Initially, the indicators for green finance and high-quality economic development were quantified by employing the entropy weight method. Secondly, we conducted a preliminary analysis of the spatiotemporal evolution patterns of green finance using the Mann-Kendall coefficient method and kernel density estimation, revealing an increasing trend in China’s green finance development level with regional disparities. Next, utilizing the Mann-Kendall coefficient method and spatial dynamic Markov model, we analyzed the spatiotemporal trends of green finance development and its coupling coordination with high-quality economic development across the 30 provinces in China. The research findings indicate a general upward trend in the degree of coordinated development between green finance and high-quality economic development from 2010 to 2021. Significant spatial differences in coupling coordination levels exist among different regions, with the highest level in the western regions, followed by the eastern regions, and the weakest in the central regions. This suggests an overall trend toward coordinated development between green finance and high-quality economic development in China, with green finance playing a significant role in promoting high-quality economic development. However, the growth rate of coupling coordination is relatively slow and exhibits regional heterogeneity. Lastly, drawing from these research findings, we put forward policy recommendations aimed at effectively advancing the development of green finance and high-quality economic growth in China.