Abstract：Under the “dual carbon” policy, the power system is undergoing a profound transformation. Evolutionary modeling provides a means of identifying future trends and optimizing resource allocation, thereby advancing the efficient deployment of renewable energy. Nonetheless, the complexity of the power system—encompassing multi-factor and multi-scale interactions—calls for an evolution model that incorporates random fluctuations, human decision-making, and optimization. In response, an open evolutionary framework for power systems based on multi-time scale hierarchical coordination was proposed, modeling coordinated evolution through simulations spanning long-term, medium-term, and short-term time scales. In the long-term phase, the proposed framework employs a strategic design model informed by national energy strategies, power demand forecasts, technological advancements, and regional resource endowments. The model aims to establish development targets for the coming decades, including generation-load hubs, dominant energy sources, and critical transmission corridors. In the medium-term phase, the framework integrates a generation-storage expansion model, a node growth model, and a coordinated planning model for generation, grid, and storage. The integration results in a comprehensive plan for generation, grid, load, and storage, culminating in a detailed construction blueprint. In the short-term phase, a sequential operation simulation model is employed to evaluate and validate specific construction plans. Through this process, the model identifies the optimal evolutionary pathway while ensuring that the planned power system delivers a safe, reliable, and cost-effective power supply. To validate the proposed framework, the evolution of a provincial-level power system was examined. The simulation results indicate that the system would deploy 213.35 GW of wind power, 614.99 GW of solar power, and 137.56 GW of storage to meet energy supply demands and carbon emission constraints. Over the course of the evolution, 40 nodes and 27 interconnection lines would be added, while the share of installed capacity and electricity generation from thermal power plants would decline sharply from 80% and 86% to 10% and 1%, respectively. The energy transformation process exhibits distinct stages: carbon peak, rapid carbon reduction, and carbon-neutral stability. These stages reflect the system's transition from peak carbon emissions to large-scale reductions, ultimately achieving carbon neutrality. The overall performance index, the levelized cost of electricity (LCOE), was further analyzed. The simulation results show that the system’s LCOE initially increases before decreasing. This trend suggests that in the early stages, integrating renewable energy is relatively straightforward, with low grid connection costs. However, in later stages, the need for additional supporting infrastructure and the increasing complexity of development drive costs higher. Additionally, a comparison was made between the coordinated evolution analysis and an analysis focused solely on generation and storage. Given the constraints that the maximum load-shedding rate must remain below 5% and the curtailment rate below 15%, the results from the coordinated evolution analysis indicate that wind and solar capacity would need to increase by 3% to 36%, and storage capacity by 5% to 50%, compared to the analysis that considered only generation and storage. This highlights that focusing exclusively on the evolution of generation and storage overlooks network constraints, potentially leading to overly optimistic projections and an underestimation of actual costs.
孔宇, 张恒旭, 施啸寒, 肖晋宇, 侯金鸣. 基于多时间尺度分层协同的电力系统开放式推演框架[J]. 电工技术学报, 2025, 40(7): 2063-2077.
Kong Yu, Zhang Hengxu, Shi Xiaohan, Xiao Jinyu, Hou Jinming. Open Evolution Simulation Framework for Power System Based on Multi-Time Scale Hierarchical Coordination. Transactions of China Electrotechnical Society, 2025, 40(7): 2063-2077.
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