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Optimal allocation of HVDC interconnections for exchange of energy and reserve capacity services

机译:HVDC互连的最佳分配,以进行能量交换和备用容量服务

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摘要

The increasing shares of stochastic renewables bring higher uncertainty in power system operation and underline the need for optimal utilization of flexibility. However, the European market structure that separates energy and reserve capacity trading is prone to inefficient utilization of flexible assets, such as the HVDC interconnections, since their capacity has to be ex-ante allocated between these services. Stochastic programming models that co-optimize day-ahead energy schedules with reserve procurement and dispatch, provide endogenously the optimal transmission allocation in terms of minimum expected system cost. However, this perfect temporal coordination of trading floors cannot be attained in practice under the existing market design. To this end, we propose a decision-support tool that enables an implicit temporal coupling of the different trading floors using as control parameters the inter-regional transmission capacity allocation between energy and reserves and the area reserve requirements. The proposed method is formulated as a stochastic bilevel program and cast as mixed-integer linear programming problem, which can be efficiently solved using a Benders decomposition approach that improves computational tractability. This model bears the anticipativity features of a transmission allocation model based on a pure stochastic programming formulation, while being compatible with the current market structure. Our analysis shows that the proposed mechanism reduces theexpected system cost and thus can facilitate the large-scale integration of intermittent renewables.
机译:随机可再生能源份额的增加带来了电力系统运行中更高的不确定性,并强调了对灵活性的最佳利用的需求。但是,将能源和储备容量交易区分开的欧洲市场结构易于利用诸如HVDC互连之类的灵活资产,因为它们的容量必须在这些服务之间事先分配。随机规划模型与储备采购和调度共同优化日前能源计划,从而以最小的预期系统成本内生地提供了最佳的传输分配。但是,在现有的市场设计下,实践中无法实现交易大厅的这种完美的时间协调。为此,我们提出了一种决策支持工具,该工具可以使用能量和储备之间的区域间传输容量分配以及区域储备需求作为控制参数,实现不同交易大厅的隐式时间耦合。所提出的方法被公式化为一个随机的双层程序,并被转换为混合整数线性规划问题,可以使用提高计算可处理性的Benders分解方法有效地解决该问题。该模型具有基于纯随机规划公式的传输分配模型的预期功能,同时与当前市场结构兼容。我们的分析表明,提出的机制降低了预期的系统成本,从而可以促进间歇性可再生能源的大规模整合。

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