Abstract

The electricity grid is facing the dual pressure of a high percentage of renewable energy generation and increasing load-side spike load. The participation of demand-side resources in grid interaction is an effective solution to this problem. To address this issue, a demand-side guidance method based on time-of-use pricing and coupon is proposed to increase the revenue of power retailers and reduce peak-valley difference. First, a guidance mechanism combining time-of-use pricing and coupon is proposed, and an adjustment load prediction model based on Attention-LSTM network is constructed to predict the adjustment load of electricity customers under different coupon coefficients. Based on this, a power purchase-sale optimization decision model in multi-level electricity market with the goal of maximizing the revenue of power retailers is established to set a suitable coupon strategy to guide electricity customers to participate in the interaction more precisely. Finally, the effectiveness of the proposed method is demonstrated by arithmetic examples.

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