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Facilitating high levels of wind penetration in a smart grid through the optimal utilization of battery storage in microgrids: An analysis of the tradeoffs between economic performance and wind generation facilitation

机译:通过微电网中电池存储的最佳利用促进智能电网中的高风速渗透:经济绩效与风力发电便利化之间的权衡分析

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The aim of this paper was to investigate the trade-offs that can be achieved between optimizing the electricity costs of a building integrated microgrid, while simultaneously facilitating high levels of wind penetration in a smart grid. This study applied multi-objective optimization to obtain a daily charge and discharge schedule of a battery bank, which was used to both store electricity from the microgrid and smart grid and could also provide electricity to the building and the smart grid. Multi-objective optimization was employed due to the independent objectives of minimizing building operating cost and maximizing the facilitation of wind energy from the smart grid. The trade-offs between the two objectives were simulated, evaluated and analyzed. A priority weighting factor (a) was applied to each objective. The purpose of a was to vary the importance of each objective relative to the other in an inversely proportional manner. This enabled the algorithm to optimize the battery operating schedule for the economic performance of the microgrid, the facilitation of wind generation on the smart grid or for trade-offs in between. The results present a comprehensive evaluation of 96 scenarios with varying daily weather conditions, building electricity demand, electricity pricing, microgrid output and wind penetration from the smart grid. A multi-objective optimization approach was then applied for each of the 96 scenarios with 11 a values to determine optimal trade-offs in these scenarios. Generally for the 96 scenarios analyzed, when the a value was 20% or higher, the amount of extra wind generation facilitation obtained was negligible while microgrid operating costs continued to increase. The results showed that when changing from an a value of 0% to an a value of 20%, there was a large increase in wind generation facilitation compared to the corresponding increase in cost, with wind generation facilitation increasing from its minimum value to within 89% of its maximum value (10.7% to 14.3% of facilitated wind generation). The corresponding building cost increased from its minimum value to within 13% of its maximum value ((sic)1.14/day to (sic)1.37/day). This produced a cost of approximately (sic)0.06 for every 1% increase in wind generation facilitation. In comparison to this, changing from an a value of 20% to an a value of 100% implied a cost of approximately (sic)3.64 for every 1% increase in wind generation facilitation. These results indicated that smart grids with large percentages of wind penetration may be substantially aided by utilizing the storage capacity of building integrated microgrids for a relatively low monetary cost.
机译:本文的目的是研究在优化建筑物集成微电网的电力成本与同时促进智能电网中高水平的风能渗透之间可以实现的取舍。这项研究应用了多目标优化来获取电池组的每日充电和放电计划,该电池组既用于存储微电网和智能电网的电能,也可以为建筑物和智能电网供电。由于实现了将建筑物运营成本最小化和将智能电网对风能的便利化最大化的独立目标,因此采用了多目标优化。模拟,评估和分析了两个目标之间的权衡。将优先权重因子(a)应用于每个目标。 a的目的是以反比例的方式改变每个目标相对于另一个目标的重要性。这使算法能够优化电池运行时间表,以实现微电网的经济性能,促进智能电网上的风力发电或在两者之间进行权衡。结果提供了对96种情景的综合评估,这些情景具有不同的每日天气条件,建筑用电需求,电价,微电网输出和智能电网的风速渗透。然后将多目标优化方法应用于96个方案中的每个方案,并使用11个a值来确定这些方案中的最佳折衷方案。通常,对于分析的96种情况,当a值为20%或更高时,获得的额外风力发电促进程度可忽略不计,而微电网的运营成本则继续增加。结果表明,当从0%的值更改为20%的值时,与相应的成本增加相比,风力发电便利性大幅增加,风力发电便利性从其最小值增加到89%以内最大值的百分比(占便利风力发电的10.7%至14.3%)。相应的建筑成本从最小值增加到最大值的13%以内((sic)1.14 / day到(sic)1.37 / day)。每增加1%的风力发电成本,就会产生大约(sic)0.06的成本。与此相比,从20%的值更改为100%的值意味着风力发电便利性每增加1%,成本大约为(sic)3.64。这些结果表明,通过以相对较低的货币成本利用构建集成微电网的存储容量,可以大大帮助风渗透率高的智能电网。

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