Co-Optimization of Energy and Ancillary Services for Hydrothermal Operation Planning Under a General Security Criterion
Co-Optimization of Energy and Ancillary Services for Hydrothermal Operation Planning Under a General Security Criterion
复制标题
通用安全准则下热液运行规划能源与辅助服务协同优化
DOI：
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发表时间：
2017
影响因子：
6.6
通讯作者：
D. Valladão
中科院分区：
文献类型：
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作者：
A. Street;Arthur Brigatto;D. Valladão
长期热液运行规划最常用的方法之一是随机对偶动态规划（SDDP）。使用这种方法，可以平衡当前和未来的水机会成本，并可以在流入不确定性的情况下为多个水库定义经济调度政策。在这个框架中，设备中断和储备交付能力通常被忽略，尽管它们对运营计划有很大影响。然而，鲁棒优化的最新进展表明如何在减少计算负担的情况下内生地考虑调度模型中的安全标准。在此框架内，通过能源和储备（辅助服务）的共同优化，确保整个网络的储备交付能力。在本文中，我们提出了一种新的多阶段热液协调规划模型，该模型共同优化名义能源调度和单独的上下储备分配。本文的主要目标是解决通用的 $n-K$ 安全标准，以便对于每个流入场景，系统能够承受高达 $K$ 组件（即发电或传输资产）的损失。所提出的方法使用列和约束生成算法来有效地将一组意外事件复合到 SDDP 算法中。巴西电力系统数据的结果证实了所提出模型的有效性。
One of the most used methods for long-term hydrothermal operation planning is the stochastic dual dynamic programming (SDDP). Using this method, the immediate and future water opportunity cost can be balanced and an economic-dispatch policy can be defined for multiple reservoirs under inflow uncertainty. In this framework, equipment outages and reserve deliverability are generally disregarded, despite their strong impact on the operative plan. However, recent advances in robust optimization have shown how to endogenously account for security criteria in scheduling models with reduced computational burden. Within this framework, reserve deliverability is ensured across the network via the co-optimization of energy and reserves (ancillary services). In this paper, we propose a new multistage model for planning hydrothermal coordination that co-optimizes the nominal energy dispatch and individual up and down reserve allocations. The main goal of this paper is to address a general $n-K$ security criterion, such that, for each inflow scenario, the system is capable of withstanding the loss of up to $K$ components, i.e., generation or transmission assets. The proposed methodology uses the column-and-constraint generation algorithm to efficiently incorporate a compound umbrella set of contingencies in the SDDP algorithm. Results for the Brazilian power system data corroborate the effectiveness of the proposed model.