地方能源和储备市场中虚拟电厂的动态容量预扣评估

IF 4.8 2区 工程技术 Q2 ENERGY & FUELS
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引用次数: 0

摘要

分布式发电资源利用率的提高导致了主动配电网和虚拟发电厂(VPP)的形成,改变了当地能源市场的电能交易模式。虚拟发电厂可以组成容量扣留集团并施加市场支配力以获取更多利润,这可能会增加消费者的能源采购成本。本文提出了一种算法,供配电网中的地方电力市场运营商评估地方能源和储备市场中的虚拟电力生产商的动态容量扣留情况。本文的主要贡献在于提出了在能源和储备市场中评估虚拟发电厂动态扣留容量的指数。本文的另一个贡献是定量分析了扣留过程对配电网灵活性的影响。本文采用了一种优化流程来估算能源市场中虚拟电力生产商的协调出价,以防止形成预扣集团。针对 123 总线 IEEE 测试系统评估了所提出的算法,并确定了不同运行条件下的能源和储备动态容量扣留指数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic capacity withholding assessment of virtual power plants in local energy and reserve market

The increasing utilization of distributed generation resources led to the formation of active distribution networks and virtual power plants (VPPs), which have changed the paradigms of electrical energy transactions in local energy markets. The VPPs can form capacity-withholding groups and impose market power to gain more profits, which may increase the costs of energy procurements for consumers. This paper presents an algorithm for the local electricity market operator in distribution networks to assess the dynamic capacity withholding of VPPs in the local energy and reserve markets. The main contribution of this paper is proposing indices to evaluate the dynamic capacity withholding of VPPs in energy and reserve markets. The other contribution of this paper is that it also quantitatively analyzes the impact of withholding processes on the flexibility of the distribution network. An optimization process is used to estimate coordinated offers of VPPs in the energy market in order to prevent the formation of withholding groups. The proposed algorithm was assessed for the 123-bus IEEE test system and the energy and reserve dynamic capacity-withholding indices were determined for different operating conditions.

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来源期刊
Sustainable Energy Grids & Networks
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.
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