论文标题

在分布式能源系统和微电网的优化模型中平衡准确性和复杂性,并具有最佳的功率流量:审查

Balancing Accuracy and Complexity in Optimisation Models of Distributed Energy Systems and Microgrids with Optimal Power Flow: A Review

论文作者

De Mel, Ishanki A., Klymenko, Oleksiy V., Short, Michael

论文摘要

与网格连接的分布式能源系统(DES)的设计和操作的优化和仿真模型通常排除与功率流以及生成和存储单元相关的固有非线性,以保持准确的复杂性平衡。这样的模型可以提供次优甚至不可行的设计和调度时间表。在DES中,最佳功率流(OPF)通常被歪曲,并将其视为独立问题。 OPF由与基础交替的电流(AC)分布网络相关的高度非线性和非凸约限制组成。在过程系统和优化领域的研究人员经常忽略了优化问题的这一方面。在这篇综述中,我们解决了OPF和DES模型之间的差异,强调了将OPF元素纳入DES设计和操作模型的重要性,以确保微电网的设计和操作满足电网的要求。通过分析DES和OPF的基础模型,我们确定了通常使用DES模型中使用过度的线性近似值表示的详细技术功率流约束。我们还确定了标有DES-OPF的模型子集,其中包括这些详细的约束,并使用创新的优化方法来解决它们。这些研究的结果表明,使用较低的DES模型实现全球最佳解决方案,实现可行的解决方案更为重要。未来工作的建议包括需要在高保真模型和具有线性近似的模型之间进行更多比较,以及使用模拟工具来验证DES-OPF模型。该评论针对的是有兴趣建模的研究人员和利益相关者的跨学科受众,他们希望为未来的更强大和准确的优化模型提供开发。

Optimisation and simulation models for the design and operation of grid-connected distributed energy systems (DES) often exclude the inherent nonlinearities related to power flow and generation and storage units, to maintain an accuracy-complexity balance. Such models may provide sub-optimal or even infeasible designs and dispatch schedules. In DES, optimal power flow (OPF) is often misrepresented and treated as a standalone problem. OPF consists of highly nonlinear and nonconvex constraints related to the underlying alternating current (AC) distribution network. This aspect of the optimisation problem has often been overlooked by researchers in the process systems and optimisation area. In this review we address the disparity between OPF and DES models, highlighting the importance of including elements of OPF in DES design and operational models to ensure that the design and operation of microgrids meet the requirements of the electrical grid. By analysing foundational models for both DES and OPF, we identify detailed technical power flow constraints that have been typically represented using oversimplified linear approximations in DES models. We also identify a subset of models, labelled DES-OPF, which include these detailed constraints and use innovative optimisation approaches to solve them. Results of these studies suggest that achieving feasible solutions with high-fidelity models is more important than achieving globally optimal solutions using less-detailed DES models. Recommendations for future work include the need for more comparisons between high-fidelity models and models with linear approximations, and the use of simulation tools to validate DES-OPF models. The review is aimed at a multidisciplinary audience of researchers and stakeholders who are interested in modelling DES to support the development of more robust and accurate optimisation models for the future.

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