基于 Stackelberg 博弈的海上风电场集群输电系统拓扑优化

IF 4.8 2区工程技术 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks Pub Date : 2024-10-11 DOI:10.1016/j.segan.2024.101542

Siyu Tao, Fuqing Jiang

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引用次数: 0

摘要

海上风能在全球能源转型中举足轻重，到 2022 年，全球装机容量将达到 64.3 千兆瓦，预计未来十年每年将增加 60.2 千兆瓦。本研究旨在利用斯塔克伯格博弈论优化海上风电场（OWF）集群的输电系统（TS）拓扑结构。海上风电场投资者（OWFI）作为领导者，在考虑尾流效应的同时优化投资回报，而海上风电场运营商（OTSO）则通过调整输电策略来降低成本。分析包括 OWF 集群内的唤醒效应及其对发电效率的影响。模拟结果表明，所提出的模型可以平衡利益相关者的利益，提高 OWF 集群的经济可行性，净现值 (NPV) 有可能增加 30%。这项研究验证了斯塔克尔伯格博弈模型在优化 OWF 簇 TS 拓扑中的实际应用，有助于提高可再生能源整合的效率和成本效益。

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Optimization of offshore wind farm cluster transmission system topology based on Stackelberg game

Offshore wind energy is pivotal in the global energy transition, with a global installed capacity reaching 64.3 GW by 2022 and an expected annual increase of 60.2 GW over the next decade. This study aims to optimize the topology of transmission systems (TS) for offshore wind farm (OWF) clusters using Stackelberg game theory. The OWF investor (OWFI) acts as the leader, optimizing investment returns while considering wake effects, and the offshore TS operator (OTSO) follows by adjusting transmission strategies to reduce costs. The analysis includes the wake effects within OWF clusters and their impact on power generation efficiency. Simulation results demonstrate that the proposed model can balance stakeholder interests and enhance the economic viability of OWF clusters, showing a potential increase in net present value (NPV) by up to 30 %. This study validates the practical application of the Stackelberg game model in optimizing OWF cluster TS topology, contributing to more efficient and cost-effective renewable energy integration.

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来源期刊

Sustainable Energy Grids & Networks Energy-Energy Engineering and Power Technology

CiteScore

7.90

自引率

13.00%

发文量

206

审稿时长

49 days

期刊介绍： Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.