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Implicit Stochastic Optimization for deriving reservoir operating rules in semiarid Brazil

机译:巴西半干旱地区油藏运行规则的隐式随机优化

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This paper deals with the application of Implicit Stochastic Optimization (ISO) to determine monthly operating rules for a reservoir system located in the semiarid Northeast of Brazil. ISO employs a deterministic optimization model to find optimal reservoir allocations under several possible inflow scenarios and later constructs the rules by analyzing the ensemble of these optimal releases. The operating policies provide the monthly reservoir release conditioned on the storage at the beginning of the month and the inflow predicted for the month. In addition to the classical regression analysis, this study establishes the rules by a two-dimensional interpolation strategy. After the rules are identified, they are applied to operate the system under new inflow realizations and show ability to produce policies similar to those obtained by deterministic optimization taking the same inflows as perfect forecasts.
机译:本文涉及隐式随机优化(ISO)的应用,以确定位于巴西东北半干旱的储层系统的每月运行规则。 ISO使用确定性优化模型来找到几种可能的流入情景下的最优油藏分配,然后通过分析这些最优释放的整体来构造规则。操作策略提供了以每月初的存储量为条件的每月水库释放量以及该月预测的流入量。除经典回归分析外,本研究还通过二维插值策略建立了规则。确定规则后,将它们应用于在新的流量实现下运行系统,并显示出产生与确定性优化所获得的策略相似的策略的能力,并采用与理想预测相同的流量。

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