Due to the continuous development of renewable energy as well as the emerging high-efficiency energy conversion techniques, the interdependencies among the heterogenous energy systems, such as power, natural gas, and district heating, are strengthening, which gradually forms the concept of integrated energy systems (IESs) and has drawn much attention from academia and industry. However, few research efforts have been spent on analyzing the interdependencies between IESs and the water distribution system (WDS), especially in the operation time scale, though water is one of the most necessary materials during energy production and conversion. In this article, a robust operation model for the water-energy nexus against the uncertainties of wind generation outputs is proposed to explore the interdependency between the IES and the WDS. The overall model is a two-stage program with a nonlinear program (NLP) in each decision stages, owing to the ubiquitous pressure-flow equations as well as the on/off switching of device operation status. Further, a two-step solution procedure is devised to obtain a solution with good quality, including the mixed integer second-order program based approximation for the original NLPs and the convex optimization based feasibility recovery, which is further embedded into the traditional column-and-constraint generation algorithm to generate a robust solution. Simulation results validate the necessity and the effectiveness of the proposed model and methods.

中文翻译：

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水能连结的稳健运行：多能量视角

由于可再生能源的不断发展以及新兴的高效能源转换技术的发展，电力，天然气和区域供热等异构能源系统之间的相互依存关系不断加强，逐渐形成了综合能源的概念。系统（IESs），并引起了学术界和工业界的广泛关注。但是，尽管水是能源生产和转换过程中最必要的材料之一，但很少有研究工作用于分析IES与水分配系统（WDS）之间的相互依赖性，特别是在运行时间范围内。在本文中，提出了针对风力发电输出不确定性的水能关系的鲁棒运行模型，以探索IES与WDS之间的相互依赖性。整个模型是一个两阶段程序，每个决策阶段都有一个非线性程序（NLP），这归因于无处不在的压力-流量方程以及设备运行状态的开/关切换。此外，设计了两步求解程序来获得高质量的解决方案，包括对原始NLP的基于混合整数二阶程序的逼近和基于凸优化的可行性恢复，并将其进一步嵌入到传统的列算法中。 -约束生成算法以生成可靠的解决方案。仿真结果验证了所提模型和方法的必要性和有效性。设计了两步求解程序来获得高质量的解决方案，包括对原始NLP的基于混合整数二阶程序的逼近和基于凸优化的可行性恢复，并将其进一步嵌入到传统的列约束中生成算法以生成可靠的解决方案。仿真结果验证了所提模型和方法的必要性和有效性。设计了两步求解程序来获得高质量的解决方案，包括对原始NLP的基于混合整数二阶程序的逼近和基于凸优化的可行性恢复，并将其进一步嵌入到传统的列约束中生成算法以生成可靠的解决方案。仿真结果验证了所提模型和方法的必要性和有效性。