太阳能光伏系统与直流配电网的协调优化模型

Eleonora Achiluzzi, B. Venkatesh
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引用次数: 0

摘要

太阳能光伏(PV)系统将推动能源系统的深度电气化,从而实现2050年的清洁能源。然而,将大量太阳能光伏系统连接到直流电(DC)网络上,如太阳能发电场和潜在的未来直流配电系统,将导致电压问题导致过电压和太阳能光伏发电输出的损失。此外,目前配电网内的光伏集成仅使用最大功率点跟踪算法来最大化输出,而没有网络协调,这可能导致由于电压问题而导致太阳能输出减少。本文提出了太阳能光伏系统与配电网调压器的协调优化模型。所提出的模型对电压控制器(DC - DC转换器)的设置进行了最佳控制,该控制器放置在太阳能光伏发电单元和选定的配电线路的输出端,同时最大化太阳能输出并最小化变电站功率(即系统损耗)。太阳能光伏系统使用训练好的神经网络建模。对各种系统在不协调情况下的测试表明,在28总线的情况下,所提出的模型产生了高达60.06%的太阳能增加。所提出的方法将是利用太阳能光伏系统实现深度电气化的一个很好的工具,它克服了目前实践中使用的不协调系统的局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Coordinated optimization model for solar PV systems integrated into DC distribution networks
Solar photovoltaic (PV) systems will drive deep electrification of energy systems leading to clean energy 2050. However, connecting large amounts of solar PV systems on direct current (DC) networks, like solar farms and potential future DC distribution systems, would lead to over voltages and loss of solar PV power output due to voltage issues. Further, current PV integration within distribution networks operate exclusively to maximize output using maximum power point tracking algorithms, without network coordination, which may lead to reduced solar output due to voltage issues. Here, a coordinated optimization model for solar PV systems and distribution network voltage regulators is presented. The proposed model optimally controls the settings of voltage controllers (DC‐DC converters), placed at the outputs of solar PV units and selected distribution lines, while maximizing solar power output and minimizing substation power (i.e. system losses). The solar PV systems are modelled using a trained neural network. Testing various systems against uncoordinated situations revealed that the proposed model yielded an increase in solar power of up to 60.06%, in the 28‐bus case. The proposed method will be an excellent tool enabling deep electrification using solar PV system and it overcomes limitations of uncoordinated systems used in practice today.
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