(PDF) Research on the Optimal Scheduling Strategy of Energy Storage
Based on long short-term memory (LSTM) artificial neural network for predictive analysis of customer load, we evaluate the economics of adding energy storage to customers.
Abstract: In order to make the energy storage system achieve the expected peak-shaving and valley-filling effect, an energy-storage peak-shaving scheduling strategy considering the improvement goal of peak-valley difference is proposed.
Finally, taking the actual load data of a certain area as an example, the advantages and disadvantages of this strategy and the constant power control strategy are compared through simulation, and it is verified that this strategy has a better effect of peak shaving and valley filling. Conferences > 2021 11th International Confe...
(1) A power grid-flexible load bilevel model based on dynamic price is constructed in this study while considering the influence of peaking shaving and valley filling on the load-side comfort level. The optimal dispatch is achieved considering load-side peak shaving and valley filling incentive subsidy-comfort level economic penalties.
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