Multienergy systems (MES) can optimally deploy their internal operational flexibility to use combinations of different energy vectors to meet the needs of end-users and potentially support the wider system. Key relevant applications of MES are multienergy districts (MEDs) with, for example, integrated electricity and gas distribution and district heating networks. Simulation and optimization of MEDs is a grand challenge requiring sophisticated techno–economic tools that are capable of modeling buildings and distributed energy resources (DERs) across multienergy networks. This article provides a tutorial-like overview of the state-of-the-art concepts for techno–economic modeling and optimization of integrated electricity–heat–gas systems in flexible MEDs, also considering operational uncertainty and multiple grid support services. Relevant mixed integer linear programming (MILP) formulations for two-stage stochastic scheduling of buildings and DER, iteratively soft-coupled to nonlinear network models, are then presented as the basis of a practical network-constrained MED energy management tool developed in several projects. The concepts presented are demonstrated through real-world applications based on The University of Manchester MED case study, the details of which are also provided as a testbed for future research.

中文翻译：

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集成的电-热-气系统：技术经济建模、优化和在多能源区的应用

多能源系统 (MES) 可以优化部署其内部操作灵活性，以使用不同能源矢量的组合来满足最终用户的需求并可能支持更广泛的系统。MES 的关键相关应用是多能源区域 (MED)，例如，集成的电力和天然气分配以及区域供热网络。MED 的模拟和优化是一项巨大的挑战，需要能够对跨多能源网络的建筑物和分布式能源 (DER) 进行建模的复杂技术经济工具。本文提供了关于灵活 MED 中集成电-热-气系统的技术经济建模和优化的最新概念的教程式概述，还考虑了操作不确定性和多电网支持服务。用于建筑物和 DER 两阶段随机调度的相关混合整数线性规划 (MILP) 公式，迭代软耦合到非线性网络模型，然后作为在几个项目中开发的实用网络约束 MED 能源管理工具的基础。所提出的概念通过基于曼彻斯特大学 MED 案例研究的实际应用进行了演示，其中的详细信息也可作为未来研究的测试平台。