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基于共享储能站的多能互补微能源网外衍响应双层优化

Double-Layer Optimization of External Derivative Response for Multi-Energy Microgrid with Shared Energy Storage Stations

  • 摘要: 高比例新能源接入能源系统带来的强不确定性使系统内部优化运行变得困难,同时可能导致不确定性风险外溢,从而影响到上级电网稳定运行。为此,提出了一种基于共享储能站的多能互补微能源网系统外衍响应双层协调优化策略。首先,构建了微能源网系统能源设备运行模型,并提出了共享储能站运行方式和盈利机制。其次,以微能源网系统运营商为上层,共享储能站运营商为下层,建立考虑2个不同利益体的双层协调优化模型。然后,通过Hong的(2m+1)点估计法量化风光不确定性,并利用基于KKT条件和Big-M将双层非线性优化模型转化为单层混合整数优化模型。最后,仿真结果表明该策略能有效防止风光不确定性风险外溢,减少了微能源网运营商6.3%的运行成本。

     

    Abstract: The strong uncertainty introduced by a high proportion of renewable energy sources integrated into the energy system complicates the internal optimization of system operation and may lead to the spillover of uncertainty risks, affecting the stable operation of the higher-level power grid. To address this issue, a two-layer coordinated optimization strategy for the external response of a multi-energy complementary micro-energy grid system based on a shared energy storage station is proposed. Firstly, operational models for energy equipment within the micro-energy grid system are constructed, and operational modes and profit mechanisms for the shared energy storage station are proposed. Secondly, a two-layer coordinated optimization model considering two different stakeholders is established, with the micro-energy grid system operator as the upper layer and the shared energy storage station operator as the lower layer. Subsequently, the Hong's (2m+1) point estimation method is used to quantify the uncertainty of wind and solar power, and the two-layer nonlinear optimization model is transformed into a single-layer mixed-integer optimization model using the KKT conditions and Big-M method. Finally, simulation results demonstrate that the proposed strategy can effectively prevent the spillover of uncertainty risks associated with wind and solar power, reducing the operational costs of the micro-energy grid operator by 6.3%.

     

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