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The source-load-storage coordinated optimization model considering the cointegration degree constraint
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DOI：10.1016/j.segan.2025.101779.png)
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Abstract
En 中文
The frequent occurrence of wind/solar curtailment and load shedding in optimal dispatch of power systems with high renewable energy penetration is primarily due to the difficulty in achieving real-time power balance. This study found that the power curves of source-load-storage are non-stationary sequences, but their sum is a stationary time series, indicating that the power balance is actually a special cointegration relationship in the time series. Therefore, a cointegration operation approach is proposed to realize source-load-storage coordination using time series cointegration theory. The cointegration characteristics between power curves are first analyzed. The mathematical cointegration relationship called the source-load-storage cointegration relationship is built. Furthermore, the cointegration degree, calculated by measuring the dispersion of residual sequences through information entropy, is proposed to quantify the equilibrium between renewable energy fluctuations and load with schedulable resources. This metric ensures that traditional unit outputs remain stable while minimizing operational costs. Then, a cointegration degree constraint is integrated into the optimization model, where is derived from the entropy of residual sequences in the cointegration relationship. The simulation results show that the system operation costs are effectively reduced and the renewable energy utilization is improved. The model is scalable to large-scale grids and provides grid operators with a quantifiable metric (cointegration degree) to balance economic costs and power curves stability.
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