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Multi-Dimensional Holomorphic Embedding Method for Probabilistic Energy Flow Calculation in Integrated Distribution Power and Heating System

  • Yuge Sun
  • , Tao Ding
  • , Yixun Xue
  • , Wenhao Jia
  • , Xinyue Chang
  • , Mohammad Shahidehpour
  • Xi'an Jiaotong University
  • Shanxi Energy Internet Research Institute
  • Taiyuan University of Technology
  • Illinois Institute of Technology

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

A fast probabilistic energy flow (PEF) analysis method is proposed for integrated distribution power and heating system (IPHS) operations. The proposed solution will overcome the low efficiency of the Monte Carlo Simulation (MCS) method for calculating the probabilistic energy flows (PEFs) iteratively, which will require an exhaustive set of energy flow calculations for a large number of samples. First, we use the multi-dimensional holomorphic embedding method (MDHEM) to derive the analytical energy flow expressions, so that the solutions for massive scenarios can be obtained by merely substituting the boundary conditions into expressions. Second, a PEF analysis model is established based on the analytical method for evaluating the impact of uncertainties on IPHSs, and accelerating the efficiency of traditional MCS methods significantly. Case studies presented in the paper show the effectiveness of the proposed method for calculating the PEFs in IPHS operations.

Original languageEnglish
Pages (from-to)1677-1689
Number of pages13
JournalIEEE Transactions on Sustainable Energy
Volume15
Issue number3
DOIs
StatePublished - 1 Jul 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Integrated distribution power and heating systems
  • multi-dimensional holomorphic embedding method
  • probabilistic energy flow

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