Robust Optimization Methodology for Generation Sizing of a Microgrid

Pandey, Shikhar; Han, Jiayu; Chen, Heng; Pabst, Paul; Gurung, Niroj; Li, Zuyi; Zhang, Liuxi; Khodaei, Amin

doi:10.1109/pesgm46819.2021.9637851

Cited by 2 publications

(1 citation statement)

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“…The microgrid islanding requirements limit RER deployment, as it enforces that the dispatchable generation capacity exceeds the load. This generation capacity is underutilized most of the time, since the main grid's electricity benefits from economy of scale, and thus the cost of energy purchase is less than local generation unless the grid is congested or not available [20]. On the other hand, the high investment cost of renewables discourages microgrid developers from investing in these sources.…”

Section: Introductionmentioning

confidence: 99%

Hybrid AC/DC Provisional Microgrid Planning Model Considering Converter Aging

et al. 2022

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Renewable energy deployment through distributed energy resources is among the central goals of future power systems. Microgrids have proven to be an economically viable solution for distributed energy resources’ integration into the power system and benefits customers with uninterrupted power supply. In this context, provisional microgrids have been introduced with the main goal of rapid renewable energy resource deployment. Since a considerable portion of renewable energy resources, as well as residential loads, are DC, and this portion is expected to grow even further, hybrid AC/DC design of provisional microgrids can improve both efficiency and economic benefit through an optimal arrangement of AC/DC feeders and converters. This paper presents a planning model for hybrid provisional microgrids considering the long-term influence of energy storage and the aging process of converters on economic revenues. Due to several intrinsic uncertainties involved in provisional microgrid operation, robust optimization is applied to the problem to ensure optimality under worst-case conditions. Results show the economic benefits of a hybrid provisional microgrid compared to a provisional microgrid and independent microgrid. Several sensitivity analyses are carried out to identify critical factors in planning.

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Section: Introductionmentioning

confidence: 99%