As a kind of clean heating and cooling equipment with high energy efficiency ratio, ground source heat pump (GSHP) has been widely used in the integrated energy system (IES). However, the output of different types of power by GSHP in different seasons will cause seasonal scheduling problems. Therefore, this study constructs a seasonal differential scheduling model of IES with surface-water GSHP and ground-water GSHP. In addition, the bald eagle search algorithm (BES) is improved to solve the daily scheduling optimization problem of IES on typical days in summer, transition season and winter, for the IES to formulate different energy supply scheduling strategies in different seasons. Firstly, the power supply, heating and cooling equipment are modeled, considering the capacity characteristics of GSHPs. Meanwhile, the energy scheduling strategies of IES in summer, transition season and winter are constructed. Secondly, this study uses Hammersley low-disparity sequence to improve the initial population, adds the comparative analysis stage of search space and hunting position, and introduces the differential mutation population to jump out of the local solution to improve the BES algorithm. Thirdly, the improved bald eagle search algorithm (IBES) is used to solve the typical daily energy scheduling problem of IES with surface-water GSHP and ground-water GSHP in different seasons, taking into account the equality constraints of energy balance and the inequality constraints of normal operation of equipment. Finally, the effectiveness of IBES algorithm in solving seasonal differential scheduling model is verified by the measured data of IES. The optimization results show that the comprehensive economic cost of the IES solved by IBES algorithm is 0.01%, 0.06% and 0.03% lower than that of BES algorithm in summer, transition season and winter, and the comprehensive economic cost of the IES with surface-water GSHP and ground-water GSHP is 7.23% lower than that of the IES without GSHPs. The results of this study are helpful to improve the utilization efficiency of GSHPs in IES and the economy of the IES.

地源热泵（GSHP）作为一种高能效比的清洁供暖制冷设备，已广泛应用于综合能源系统（IES）。但是，地源热泵在不同季节输出不同类型的电力会造成季节性调度问题。因此，本研究构建了具有地表水地源热泵和地下水地源热泵的 IES 季节差异调度模型。此外，对白头鹰搜索算法（BES）进行了改进，解决了IES在夏季、过渡季节和冬季典型日的日常调度优化问题，供IES在不同季节制定不同的能源供应调度策略。首先，考虑地源热泵的容量特性，对供电、加热和冷却设备进行建模。同时，构建了IES在夏季、过渡季节和冬季的能源调度策略。第二，本研究采用Hammersley低视差序列对初始种群进行改进，增加搜索空间和狩猎位置的比较分析阶段，并引入差分变异种群跳出局部解来改进BES算法。第三，考虑到能量平衡的等式约束和能量平衡的等式约束，利用改进的秃鹰搜索算法（IBES）解决了不同季节地表水地源热泵和地下水地源热泵的IES典型日常能量调度问题。设备正常运行的不等式约束。最后通过IES的实测数据验证了IBES算法在求解季节差分调度模型中的有效性。优化结果表明，IBES算法求解的IES在夏季、过渡季节和冬季的综合经济成本分别比BES算法低0.01%、0.06%和0.03%，采用地表-水地源热泵和地下水地源热泵比没有地源热泵的 IES 低 7.23%。本研究结果有助于提高 IES 地源热泵的利用效率和 IES 的经济性。