CHARGING STRATEGY FOR ELECTRIC VEHICLES UNDER HYBRID DEMAND RESPONSE BASED ON MC-BiLSTM-BDA PREDICTION

Zhong Ting; Wang Aijuan; Ding Xue

doi:10.19912/j.0254-0096.tynxb.2024-1472

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Acta Energiae Solaris Sinica ›› 2026, Vol. 47 ›› Issue (1) : 747-755. DOI: 10.19912/j.0254-0096.tynxb.2024-1472

CHARGING STRATEGY FOR ELECTRIC VEHICLES UNDER HYBRID DEMAND RESPONSE BASED ON MC-BiLSTM-BDA PREDICTION

Zhong Ting, Wang Aijuan, Ding Xue

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Abstract

A hybrid demand response orderly charging optimization strategy based on MC-BiLSTM-BDA prediction is proposed. Firstly, a charging load prediction model, named MC-BDA-BiLSTM, is constructed by integrating Markov chains （MC）, Bi-directional long short-term memory （BiLSTM） network, and Bi-directional Attention （BDA）. Secondly, according to the peak, flat, and valley charging periods classified by the K-means fuzzy clustering algorithm, a price-incentive hybrid demand response （PrIncHDR） strategy is presented, which introduces price compensation incentive mechanism on the basis of price based demand response to avoid peak-valley inversion and promote supply and demand balance. Based on this strategy, an EV orderly charging optimization model is constructes, which includes renewable energy utilization rate, user benefits and photovoltaic charging station （PVCS） benefits, and is solved by the NSGA-II algorithm. The experimental results show that compared with BiLSTM model, the MC-BiLSTM-BDA model increases the determination coefficient of the charging load prediction by 11.93%, and reduces the root-mean-square error by 35.06% and the mean absolute error by 37.41%, respectively. The proposed charging optimization strategy based on price-incentive hybrid demand response effectively reduces peak-valley differences, enhances renewable energy consumption, and achieves a win-win for users and photovoltaic charging stations.

Key words

electric vehicle / prediction / Markov chains / bi-directional long-short-term memory network / Bi-directional Attention / hybrid demand response / orderly charging optimization strategy

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Zhong Ting, Wang Aijuan, Ding Xue. CHARGING STRATEGY FOR ELECTRIC VEHICLES UNDER HYBRID DEMAND RESPONSE BASED ON MC-BiLSTM-BDA PREDICTION[J]. Acta Energiae Solaris Sinica. 2026, 47(1): 747-755 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1472

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