Therefore, minimizing the load peak-to-valley difference after energy storage, peak-shaving, and valley-filling can utilize the role of energy storage in load smoothing and obtain an optimal configuration under a high-quality power supply that is in line with real-world scenarios.
The model aims to minimize the load peak-to-valley difference after peak-shaving and valley-filling. We consider six existing mainstream energy storage technologies: pumped hydro storage (PHS), compressed air energy storage (CAES), super-capacitors (SC), lithium-ion batteries, lead-acid batteries, and vanadium redox flow batteries (VRB).
A simulation based on a real power network verified that the proposed strategy could effectively reduce the load difference between the valley and peak. These studies aimed to minimize load fluctuations to achieve the maximum energy storage utility.
Tan et al. proposed an energy storage peak-peak scheduling strategy to improve the peak–valley difference . A simulation based on a real power network verified that the proposed strategy could effectively reduce the load difference between the valley and peak.
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The combined control of energy storage and unit load can achieve a good peak-shaving and valley-filling effect, and has a good inhibitory effect on large load peak-valley …
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