Minglei Bao, Xiaocong Sun, Yi Ding, et al. Multifactor-Influenced Reliability-Constrained Reserve Expansion of Integrated Electricity-Gas Systems Considering Failure Propagation[J]. CSEE Journal of Power and Energy Systems, 2023, 9(6): 2236-2250.
DOI:
Minglei Bao, Xiaocong Sun, Yi Ding, et al. Multifactor-Influenced Reliability-Constrained Reserve Expansion of Integrated Electricity-Gas Systems Considering Failure Propagation[J]. CSEE Journal of Power and Energy Systems, 2023, 9(6): 2236-2250.DOI: 10.17775/CSEEJPES.2021.06630.
Multifactor-Influenced Reliability-Constrained Reserve Expansion of Integrated Electricity-Gas Systems Considering Failure Propagation
With the increasing interactions between natural gas systems (NGS) and power systems
component failures in one system may propagate to the other one
threatening reliable operation of the whole system. Due to neglect of such cross-sectorial failure propagation in integrated electricity-gas systems (IEGSs)
traditional economy-oriented reserve expansion models may lead to unreasonable planning results. In order to address this
an innovative reserve expansion model is proposed to determine the allocation of energy production components through the harmonization between costs and reliability. First
novel multifactor-influenced reliability indices are defined considering synthetic effects of multiple uncertainties
including failure propagation
load uncertainties and generation failures. In reliability index formulation
contribution of failure propagation on system reliability is analytically expressed. To avoid high computational complexity
the fuzzy set theory is combined with conventional methods
e.g.
Monte-Carlo simulation technique to reduce numerous contingency states. Sampled contingency states are aggregated into several clusters represented by a fuzzy number. To effectively solve the planning model
a decomposition approach is introduced and applied to decompose the original problem into a master problem and two correlated reliability sub-problems. Numerical studies show the proposed model can plan reasonable reserves to guarantee reliability levels of IEGSs considering failure propagation.