Research on Optimization of Flexibility Resources for Urban Power Grids Considering Energy Storage Devices and Industrial Load Power Regulation
DOI:
https://doi.org/10.4108/ew.12142Keywords:
Converter transformer, Multiphysics coupling, Harmonic currents, DC bias, Hotspot temperature riseAbstract
Faced with the challenges of uncertainty and volatility in power output brought by high-penetration new energy integration, traditional regulation resources struggle to independently support the stable operation of urban power grids, making it urgent to establish an effective optimization mechanism for flexible resource allocation. To this end, this paper aims to investigate the synergistic planning of energy storage systems and industrially adjustable loads to enhance the resilience, security, and economic efficiency of urban power grids. To achieve this objective, a bi-level optimization model based on long- and short-term time scale coupling is constructed: the outer-level model focuses on ensuring secure grid operation under extreme scenarios such as N-1 contingencies, determining the minimum required capacity of energy storage and adjustable loads at each node through multi-contingency power flow analysis, thereby establishing a rigid safety boundary for the system. Building upon this, the inner-level model aims for optimal economic performance in typical daily operation, comprehensively considering new energy fluctuations, load characteristics, and regulation costs. It dynamically optimizes energy storage charging/discharging strategies, industrial load regulation pathways, and necessary resource expansion plans, while incorporating wind and solar curtailment variables to enhance model adaptability. Through iterative solving between the two levels, the model achieves an organic integration of safety boundaries from the planning phase with economic dispatch in the operational phase.Case study results based on a six-node system demonstrate that the proposed model can provide differentiated energy storage configurations and load retrofit schemes for various scenarios such as real-time control, peak shaving, and valley filling, effectively leveraging the differences in load characteristics among nodes. A comparative study shows that, under the premise of meeting the same flexibility requirements, the synergistic "storage-load" configuration scheme can effectively reduce both the scale of energy storage investment and the total system cost (by approximately 7.3%) compared to a single-mode approach relying solely on storage, and also helps reduce new energy curtailment losses. This research confirms the effectiveness of the constructed bi-level optimization model in coordinating safety and economic objectives and promoting complementary synergy among diverse resources. It provides a theoretically sound and practically guiding methodology and decision-making support for flexible resource planning in urban power grids under high-penetration new energy integration.
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