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Quantifying network flexibility requirements in terms of energy storage

机译:在能量存储方面量化网络灵活性要求

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The energy storage requirement modelling tool outlined here uses an extension of the pinch methodology to quantify the network flexibility required due to greater variable renewable energy (VRE) integration. Quantifying this as the magnitude of energy storage required as a function of storage duration provides improved understanding of the fundamental balancing problem. Identification of the impact that key decision variables, such as location, VRE penetration and VRE that is supplied through wind have on these requirements has been enabled by condensing this dependence within two non-dimensional indices: the storage magnitude index and the storage duration index. These indices, in addition to the size of storage required, have enabled the tipping-points and VRE penetration levels beyond which short term storage is not sufficient to be identified for the UK and Australian locations considered. In addition to how effective the provision of excess VRE is in the mitigation of the balancing requirements. This analysis shows that seasonal balancing is required at high levels of VRE penetration for all combinations of wind and solar sources, but can be needed with as low as 50% penetration at certain combinations and locations. The tipping-point is highly specific to location and VRE that is supplied through wind, varying between 30% and 50% of VRE penetration. (c) 2020 Elsevier Ltd. All rights reserved.
机译:这里概述的能量存储需求建模工具使用捏切种方法的扩展来量化由于更大的可变可再生能源(VRE)集成所需的网络灵活性。量化这一点作为作为存储持续时间的函数所需的能量存储的幅度提供了改进对基本平衡问题的理解。通过在两个非维指数内缩小这一依赖性,通过缩小这些要求,识别关键决策变量的影响,例如通过风的位置,VRE渗透和VRE。通过在两个非维指数内缩小这一依赖性:存储幅度指数和存储持续时间索引。这些指数除了所需的存储尺寸外,还使得倾翻点和vRe渗透水平,超出了英国和澳大利亚地区的短期储存不足以被识别。除了提供多余的VE有效程度,还在缓解平衡要求。该分析表明,对于风力和太阳能源的所有组合,季节性平衡是在高水平的VRE渗透下,但在某些组合和位置的渗透率下可能需要低至50%。倾翻点是高度特异性的位置,通过风提供的VRE,距离普及的30%至50%之间。 (c)2020 elestvier有限公司保留所有权利。

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