Abstract
This paper proposes a new probabilistic power flow method for the hybrid AC/VSC-MTDC (Voltage Source Control-Multiple Terminal Direct Current) grids, which is based on the combination of ninth-order polynomial normal transformation (NPNT) and inherited Latin hypercube sampling (ILHS) techniques. NPNT is utilized to directly handle historical records of uncertain sources to build the accurate probability model of random inputs, and ILHS is adopted to propagate the randomness from inputs to target outputs. Regardless of whether the underlying probability distribution is known or unknown, the proposed method has the ability to adaptively evaluate the sample size according to a specific operational scenario of the power systems, thus achieving a good balance between computational accuracy and speed. Meanwhile, the frequency histograms, probability distributions, and some more statistics of the results can be accurately and efficiently estimated as well. The modified IEEE 118-bus system, together with the realistic data of wind speeds and diverse consumer behaviors following irregular distributions, is used to demonstrate the effectiveness and superiority of the proposed method.
Highlights
The Voltage Source Converter based Multiple Terminal Direct Current (VSC-MTDC) technique has become the most feasible solution to the integration of remotely located large wind farms (WFs), as it can effectively support the AC grid, facilitate the integration of fluctuant wind power, and improve the transfer efficiency [1]
With more and more WFs integrated into AC grids by using VSC-MTDC, the fluctuant wind power will significantly increase the stochastic nature of the power system, further exacerbating the operational condition of the hybrid AC/VSC-MTDC grids [2]
probability density function (PDF) of probabilistic power flow (PPF) results are required in an operational scenario, a more strict convergence target can be set for the proposed method ninth-order polynomial normal transformation (NPNT)-inherited Latin hypercube sampling (ILHS) (like NPNT-ILHS(a)) to achieve the satisfactory accuracy while keeping the relatively low computational cost
Summary
The Voltage Source Converter based Multiple Terminal Direct Current (VSC-MTDC) technique has become the most feasible solution to the integration of remotely located large wind farms (WFs), as it can effectively support the AC grid, facilitate the integration of fluctuant wind power, and improve the transfer efficiency [1]. The probability model of input variables needs to be accurately built based on the historical records, regardless of whether the underlying distribution is known or unknown; the probabilistic method holds a good balance between computation accuracy and speed; the mean, standard deviation, frequency histogram, and even the PDF of output results obtained from PPF calculation can be comprehensively available. Unlike conventional MCS, the size of CLHS cannot be increased by generating additional samples, since the new sample set (including the original and the additional sample set) cannot preserve the stratification properties that make CLHS so effective [22] This naturally results in a problem regarding how many samples are required for PPF of the complex hybrid AC/DC grids with diverse operational scenarios.
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