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Stochastic optimal operation of a microgrid based on energy hub including a solar-powered compressed air energy storage system and an ice storage conditioner

机译:基于能量轮毂的微电网的随机最佳运行,包括太阳能压缩空气能量存储系统和冰储物调节器

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Energy Hub (EH) is known as a complex system capable of transferring, conversion, and saving various energies in a Microgrid (MG). An important issue for investors is taking advantage of EH for optimal management of all energy carriers, particularly in anticipating energy price. In this paper, a model for EH was considered for the purpose of the optimal operation of the MG with multiple energy carrier infrastructures for day-ahead. The goal of optimization was to minimize operation and environmental costs subjected to numerous technical constraints. The proposed EH manages dispatchable generation, i.e. Combined Cooling, Heat and Power (CCHP) and nondispatchable generations, i.e., Wind Turbine (WT) and Photovoltaic (PV). It considers an Ice Storage Conditioner (ISC) as well as a Thermal Energy Storage System (TESS) as the Energy Storage System (ESS). In particular, the effects of Solar-Powered Compressed Air Energy Storage (SPCAES) as a novel ESS were studied on the performance and efficiency of the EH operation and environmental costs. The suggested model considers the stochastic behavior of WT and PV generations as well as the electrical, thermal, and cooling demands in various scenarios. The scenario generation was performed while the K-means clustering algorithm was applied for reducing the number of scenarios. The proposed model was a Mix Integer Linear Problem (MILP), which was solved using CPLEX solver in GAMS software. Implementation of the proposed framework on the typical EH showed the efficacy of the ESSs to reduce the operation costs and emissions in the day-ahead energy management.
机译:能量毂(EH)被称为能够在微电网(MG)中传递,转换和节省各种能量的复杂系统。投资者的一个重要问题是利用EH以获得所有能源载体的最佳管理,特别是在预期能源价格上。在本文中,考虑了EH的模型,以实现MG的最佳运行,具有多个能量载体基础设施进行日期。优化的目标是最大限度地减少经受许多技术限制的操作和环境成本。所提出的EH管理调度发电,即组合冷却,热量和功率(CCHP)和非可匹配的代,即风力涡轮机(WT)和光伏(PV)。它考虑了冰储物调节器(ISC)以及作为能量存储系统(ESS)的热能存储系统(TESS)。特别地,研究了太阳能压缩空气能量存储(SPCAE)作为新型ESS的影响,对EH运行和环境成本的性能和效率进行了研究。建议的模型考虑了WT和PV世代的随机行为以及各种场景中的电气,热和冷却需求。在应用K-Means聚类算法以减少方案数量的情况下,执行方案生成。所提出的模型是混合整数线性问题(MILP),其在GAMS软件中使用CPLEX Solver解决。典型EH上提出的框架的实施表明,ESSS在提前的能源管理中降低运营成本和排放的功效。

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