栗然, 吕慧敏, 彭湘泽, 王炳乾, 祝晋尧. 阶梯成本下考虑混合租建模式的云储能优化配置[J]. 太阳能学报, 2024, 45(2): 263-273. DOI: 10.19912/j.0254-0096.tynxb.2022-1612
引用本文: 栗然, 吕慧敏, 彭湘泽, 王炳乾, 祝晋尧. 阶梯成本下考虑混合租建模式的云储能优化配置[J]. 太阳能学报, 2024, 45(2): 263-273. DOI: 10.19912/j.0254-0096.tynxb.2022-1612
Li Ran, Lyu Huimin, Peng Xiangze, Wang Bingqian, Zhu Jinyao. OPTIMAL CONFIGURATION OF CLOUD ENERGY STORAGE CONSIDEING HYBRID SELF-BUILT AND LEASE MODE UNDER TIERED COST[J]. Acta Energiae Solaris Sinica, 2024, 45(2): 263-273. DOI: 10.19912/j.0254-0096.tynxb.2022-1612
Citation: Li Ran, Lyu Huimin, Peng Xiangze, Wang Bingqian, Zhu Jinyao. OPTIMAL CONFIGURATION OF CLOUD ENERGY STORAGE CONSIDEING HYBRID SELF-BUILT AND LEASE MODE UNDER TIERED COST[J]. Acta Energiae Solaris Sinica, 2024, 45(2): 263-273. DOI: 10.19912/j.0254-0096.tynxb.2022-1612

阶梯成本下考虑混合租建模式的云储能优化配置

OPTIMAL CONFIGURATION OF CLOUD ENERGY STORAGE CONSIDEING HYBRID SELF-BUILT AND LEASE MODE UNDER TIERED COST

  • 摘要: 为解决盲目投建云储能造成资源浪费、成本增加的问题,提出阶梯成本下“自建+租赁”混合模式的园区云储能优化配置方法。首先,分析云储能的特点,构建园区内有大量光伏用户参与的云储能服务模式。其次,建立不同时间尺度、双主体的双层优化模型,上层求解长时间尺度下云储能的规划问题,下层求解短时间尺度下用户群的运行问题。然后,通过KarushKuhn-Tucker(KKT)条件将双层模型转化为单层模型,再利用Big-M法对所得单层模型进行线性化处理。最后,在3个不同场景下进行算例分析,结果验证了所提云储能配置模型的有效性,在降低储能投资成本、提高储能资源利用率的同时可节省用户用电成本。

     

    Abstract: In order to solve the problem of resource waste and cost increase caused by blind investment,the hybrid model of self-built and lease under tiered cost is applied to the cloud energy storage configuration in park. Firstly,the characteristics of cloud energy storage are analyzed,and service mode of cloud energy storage with a large number of photovoltaic users participating in the park is constructed. Secondly,a bi-level optimization model considering different time scales and two subjects is established,the upper layer solves the planning problem of cloud energy storage in long time scale,and the lower layer solves the operation problem of user group in a short time scale. Thirdly,the two-layer model is transformed into a single-layer model by Karush-Kuhn-Tucker(KKT)condition,and the resulting single-layer model is linearized by Big-M. Finally,with the analysis of three different scenarios,the results demonstrate the effectiveness of proposed cloud energy storage allocation model,it can reduce the investment costs of energy storage,improve the utilization rate of energy storage resources and save electricity cost of users.

     

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