Open AccessContingencies-Based Distributionally Robust Co-Risk Operation for Combined Electricity and Heat System
Author(s) -
Tongchui Liu,
Wenxia Pan,
Mingyang Liu,
Zhu Zhu
Publication year - 2021
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2021.3128419
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Sustainable development of combined electricity and heat system (CEHS) can effectively facilitate the energy transition from fossil energy consumption to comprehensive utilization of multiple energy. The coupled energy system, featured with the risk of components failure and the integrated uncertain renewable energy sources (RESs), can face a safety and reliability operation challenge. Therefore, achieving the tradeoff between the economy and risk aversion for the CEHS operation is an urgent issue to be settled. This paper proposes a contingencies-based distributionally robust co-risk operation model (DRCROM) for the CEHS, which provides the failure risk sample of components applied by the non-sequenced Monte Carlo simulation (MCS) method and the penalty of energy spillage (including wind spilling and load shedding) under contingencies. Moreover, the uncertain power output risk of RESs can be addressed by using the distributionally robust individual chance-constrained (DRICC) methodology with Wasserstein metric ambiguity set. As a result, incorporating the uncertain component state and power output of RESs into the risk operation can be considered in this paper. Case studies can be conducted to give risk analyses that the average violation probability $V_{p}$ and the total co-risk dispatch cost $C^{\text {Obj}}$ are mainly affected by $\varepsilon $ . Contingencies can also increase risk indices and influence the dispatch energy and energy spillage.