2025 Vol.8 Dec.N06

• Title: Multi-Level Optimization for Local Consumption of Distributed Renewable Energy Considering Short-Term Output Uncertainty
• Name: Hui Lv，jun Xie
• Company: Nanjing NARI Information & Commumication Technology Co., Ltd., Naniing 210000, China
• Abstract:

  Conventional optimization algorithms for local consumption of distributed renewable energy primarily rely on deterministic output models. These approaches construct optimization models targeting either minimum system operating costs or maximum renewable energy consumption rates, performing static solutions based on historical output data and load demand. However, neglecting the random characteristics of short-term output from distributed renewable energy sources leads to suboptimal optimization equilibrium. To address this, this paper proposes a multi-level optimization approach for local consumption of distributed renewable energy that accounts for short-term output uncertainty.By constructing a multivariate distribution function and generating random numbers to simulate output scenarios, the approach quantifies output fluctuation ranges at different confidence levels, providing dynamic constraint boundaries for the optimization model. Based on uncertainty analysis of typical scenarios, it formulates energy storage configuration and baseline dispatch plans targeting objectives such as cost and curtailed electricity. Utilizing updated forecast information, it recalculates energy storage and grid interaction power within rolling optimization windows to refine day-ahead plans.Based on real-time monitoring data, dynamically adjust energy storage charging/discharging power and grid interaction power according to real-time power balance equations. Simultaneously optimize through prediction error compensation, adjusting power interaction based on the magnitude and direction of prediction errors. Experimental tests verified the proposed method's optimization equilibrium. Comparative test results clearly demonstrate that when applying this method for renewable energy integration optimization, the average integration rate reaches approximately 81.5%, achieving relatively ideal optimization outcomes.

  
  

• Keyword: Short-term output; Uncertainty; Renewable energy integration; Multi-level optimization;
• DOI: 10.12250/jpciams2025091114
• Citation form: Hui Lv，jun Xie.Multi-Level Optimization for Local Consumption of Distributed Renewable Energy Considering Short-Term Output Uncertainty[J]. Computer Informatization and Mechanical System,2025,Vol.8,pp.

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