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    考虑电网碳排放因子的新型电力系统储能双层容量配置优化

    Optimization of dual layer capacity configuration for energy storage in a new power system considering carbon emission factors of the power grid

    • 摘要: 在科技发展与可持续能源需求的背景下,我国新能源领域成果显著,但新能源特性给电力系统运行带来挑战。新型电力系统借助智能灵活技术应对,储能虽应用广泛,却面临诸多问题,需探索价值提升与优化配置策略。同时,储能系统投资成本高、回报各异,电网碳排放因子研究不断深入,但现有研究未能有效协同新能源消纳与电网低碳性。为此,提出储能分层容量配置方案,上层考虑储能配置成本和电网碳排放因子,下层考虑新能源消纳率和火电机组处理成本,基于分解协调思想求解储能最佳容量配置与运行优化结果。以西北某地区为研究对象,结果显示:配置储能后,新能源消纳率提升近10%,电网碳排放因子降低3%以上,成本达到最优效果,同时对未来5 a的最优化储能容量配置进行趋势预测。

       

      Abstract: Against the backdrop of technological development and sustainable energy demand, China has made significant achievements in the field of new energy, but the characteristics of new energy pose challenges to the operation of the power system. The new power system relies on intelligent and flexible technology to respond. Although energy storage is widely used, it faces many problems and needs to explore value enhancement and optimization configuration strategies. At the same time, energy storage systems have high investment costs and varying returns, and research on carbon emission factors in the power grid continues to deepen. However, existing research has failed to effectively coordinate the consumption of new energy with the low-carbon nature of the power grid. To this end, a layered capacity configuration scheme for energy storage is proposed. The upper layer considers the cost of energy storage configuration and the carbon emission factor of the power grid, while the lower layer considers the consumption rate of new energy and the processing cost of thermal power units. Based on the decomposition and coordination idea, the optimal capacity configuration and operation optimization results of energy storage are solved. Taking a certain region in northwest China as the research object, the results show that after configuring energy storage, the consumption rate of new energy increases by nearly 10%, the carbon emission factor of the power grid decreases by more than 3%, and the cost reaches the optimal effect. At the same time, trend prediction is made for the optimal energy storage capacity configuration in the next five years.

       

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