IEEE Access (Jan 2020)

Interval Probabilistic Energy Flow Calculation of CCHP Campus Microgrid Considering Interval Uncertainties of Distribution Parameters

  • Yuquan Xie,
  • Shunjiang Lin,
  • Weikun Liang,
  • Yuerong Yang,
  • Zhiqiang Tang,
  • Yunong Song,
  • Mingbo Liu

DOI
https://doi.org/10.1109/ACCESS.2020.3013151
Journal volume & issue
Vol. 8
pp. 141358 – 141372

Abstract

Read online

Due to the absence of historical data and the errors of measurement instruments, there may be uncertainties in the distribution parameters of the random variables describing the uncertain fluctuations of node power including renewable energy station output and load power in the combined cooling heating and power (CCHP) campus microgrid. In this paper, intervals are used to describe the uncertainties of distribution parameters of the random variables, and an interval probabilistic energy flow (IPEF) calculation model of the CCHP campus microgrid is established. Introducing the interval arithmetic (IA) into the cumulant method, an IA-based IPEF algorithm is proposed to obtain the analytical expressions of probability density function or cumulative distribution function intervals of the state variables. Moreover, affine arithmetic (AA) is introduced to address the interval extension problem in the calculation, and an AA&IA-based IPEF algorithm is proposed. By constructing the correlation transformation matrixes, the correlation among different node power is considered in the IPEF calculation. A case study on a CCHP campus microgrid demonstrates that the results of the AA&IA-based IPEF algorithm are more accurate than those of the IA-based IPEF algorithm by using the results of the double-layer Monte Carlo method as a reference. Moreover, the proposed algorithms are more efficient than the double-layer Monte Carlo method.

Keywords