【Advances in Applied Energy】以电动汽车智能充电概念为投资选择的战略网络扩展规划

学术   科学   2025-01-21 18:30   美国  

原文信息:

Strategic network expansion planning with electric vehicle smart charging concepts as investment options

原文链接:

https://www.sciencedirect.com/science/article/pii/S266679242100069X

Highlights

  • EV smart charging models integrated in state-of-the-art network expansion planning.

  • G2V, V2G and V2B are viable non-network investment alternatives.

  • Investment in smart chargers acts as a hedging tool against long-term uncertainty.

  • G2V, V2G and V2B yield significant long-term economic savings in the GB power system.

  • V2B is comparable to V2G at transmission level in the context of expansion planning.

摘要

作为全球脱碳努力的一部分,交通电气化似乎是不可避免的,但电动汽车的电力系统集成面临着诸多挑战,包括需求峰值过高,需要昂贵的基础设施投资。此外,电力部门的长期发展具有很大的不确定性,这增加了做出错误投资决策导致资产搁浅的风险。因此,如果不推进智能充电概念,并结合考虑不确定因素影响的战略网络扩展规划,就不可能实现具有成本效益的电气化交通系统集成。针对多维不确定条件下的大规模、长期电网扩建规划问题,本文提出了电网对车辆(G2V)、车辆对电网(V2G)和车辆对建筑物(V2B)的投资运营模型。此外,本文还提出了一个多阶段随机规划框架,该框架可以确定最优的投资策略,从而使期望系统成本最小化,并降低搁浅投资的风险。该模型在IEEE24节点测试系统上得到了验证,并在英国电力系统中得到了应用。结果表明,G2V、V2G和V2B是传统强化的有效非网络替代方案,经济性较好,并能够应对不确定性。就英国而言,在40年内,G2V、V2G和V2B的期权价值可能分别达到12亿英镑, 108亿英镑, 和101亿英镑。虽然量化值是系统特定的,但本文对智能充电概念作为投资选项的作用进行了关键研究,可以推广到任何低碳电力系统。

更多关于"Electric vehicles"的研究请见:

https://www.sciencedirect.com/search?qs=Electric%20vehicles&pub=Advances%20in%20Applied%20Energy&cid=777797

Abstract

The electrification of transport seems inevitable as part of global decarbonization efforts, but power system integration of electric vehicles faces numerous challenges, including a disproportionately high demand peak necessitating expensive infrastructure investments. Moreover, long-term developments in the power sector are characterized by great uncertainty, which increases the risk of making incorrect investment decisions leading to stranded assets. A cost-effective system integration of electrified transport would therefore not be possible without the implementation of smart charging concepts in combination with strategic network expansion planning that considers the impact of uncertainties. This paper proposes investment and operation models of Grid-to-Vehicle (G2V), Vehicle-to-Grid (V2G), and Vehicle-to-Building (V2B) for the large-scale and long-term network expansion planning problem under multi-dimensional uncertainty. Additionally, it presents a multi-stage stochastic planning framework that can identify optimal investment strategies such that the expected system cost is minimized and the risk of stranded investments is reduced. The models are demonstrated on the IEEE 24-bus test system and applied in a case study of the power system of Great Britain. The results highlight G2V, V2G and V2B as effective non-network alternatives to conventional reinforcement that could generate substantial economic savings and act as hedging instruments against uncertainty. For the case of Great Britain, the Option Values of G2V, V2G, and V2B could amount to £1.2bn, £10.8bn, and £10.1bn, respectively, over a 40-year horizon. Although the quantified values are system-specific, the paper presents key observations on the role of smart charging concepts as investment options that can be generalized for any low-carbon power system.

Keywords

Electric vehicles

Grid-to-vehicle

Option Value

Smart charging

Stochastic optimization

Transmission planning

Uncertainty

Vehicle-to-building

Vehicle-to-grid

Graphics

Fig. 1. An illustration highlighting the relationship between the studied topic and the energy transition, and the benefits of the proposed solution (green) compared to the conventional approach (grey).

Fig. 3. Stochastic network expansion planning framework.

Fig. 7. Scenario trees showing the optimal investment decisions for the demonstrative case study.

Fig. 15. Scenario trees showing the strategic investment decisions for the GB network expansion with only conventional reinforcements (top left), conventional and G2V investments (top right), conventional and V2G investments (bottom left), and conventional and V2B investments (bottom right).


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