Styliani A. Vomva , Georgios C. Kryonidis , Angelos I. Nousdilis , Georgios C. Christoforidis , Grigoris K. Papagiannis
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引用次数: 0
Abstract
Considering the residential sector, greenhouse gas emissions can be effectively reduced by the widespread deployment of distributed renewable energy sources (DRESs) in low-voltage (LV) electrical networks (ENs). Through the electrification and the integration of different energy systems, the exploitation of the locally generated renewable energy can be further increased, acting also as an efficient countermeasure to the technical challenges in ENs posed by the intermittent nature of DRESs. This work deals with the modeling of multi-energy systems (MESs) consisting of unbalanced ENs and district heating networks (DHNs), formulated based on existing EN and DHN models. The developed model is enhanced by the incorporation of a thermal droop control scheme into the controllable sources of DHN, i.e., heat pumps (HPs). The validity of the proposed model is assessed via time-series simulations on a MES composed of a benchmark unbalanced LV EN and a real DHN. It is shown that the integrated droop control scheme can act as a means towards overvoltage mitigation, temperature control and reduced MES losses, improving the operational reliability and exploitation of the DRES potential. Therefore, the proposed model could be useful for system operators and decision makers for the efficient planning and operation of MESs.
考虑到住宅部门,在低压电网(ENs)中广泛部署分布式可再生能源(DRESs)可有效减少温室气体排放。通过电气化和不同能源系统的整合,可以进一步提高本地产生的可再生能源的利用率,同时也是应对低压电网中分布式可再生能源的间歇性所带来的技术挑战的有效措施。这项工作涉及多能源系统(MES)的建模,该系统由不平衡的能源网(EN)和区域供热网(DHN)组成,以现有的能源网(EN)和区域供热网(DHN)模型为基础。通过在 DHN 的可控源(即热泵 (HP))中加入热垂控制方案,对所开发的模型进行了改进。通过对由基准不平衡低压 EN 和真实 DHN 组成的 MES 进行时间序列模拟,评估了所建模型的有效性。结果表明,集成的降压控制方案可作为过电压缓解、温度控制和降低 MES 损耗的一种手段,从而提高运行可靠性并挖掘 DRES 的潜力。因此,所提出的模型可为系统运营商和决策者有效规划和运行 MES 提供帮助。
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.