Based Eq. , to reduce the charging cost for users and charging piles, an effective charging and discharging load scheduling strategy is implemented by setting the charging and discharging power range for energy storage charging piles during different time periods based on peak and off-peak electricity prices in a certain region.
The energy storage charging pile achieved energy storage benefits through charging during off-peak periods and discharging during peak periods, with benefits ranging from 699.94 to 2284.23 yuan (see Table 6), which verifies the effectiveness of the method described in this paper.
The capacity planning of charging piles is restricted by many factors. It not only needs to consider the construction investment cost, but also takes into account the charging demand, vehicle flow, charging price and the impact on the safe operation of the power grid (Bai & Feng, 2022; Campaa et al., 2021).
According to the taxi trajectory and the photovoltaic output characteristics in the power grid, Reference Shan et al. (2019) realized the matching of charging load and photovoltaic power output by planning fast charging piles, which promoted the consumption of new energy while satisfying the charging demand of EVs.
Fig. 11 Before and after optimization of charging pile discharge load. The MHIHHO algorithm optimizes the charging pile's discharge power and discharge time, as well as the energy storage's charging and discharging rates and times, to maximize the charging pile's revenue and minimize the user's charging costs.
The proposed method reduces the peak-to-valley ratio of typical loads by 52.8 % compared to the original algorithm, effectively allocates charging piles to store electric power resources during off-peak periods, reduces user charging costs by 16.83 %–26.3 %, and increases Charging pile revenue.
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