An efficient analytical approach for operational reliability evaluation of integrated electricity‐heat energy systems with variable wind power

Abstract

Abstract The increase in wind power penetration leads to the risk of energy supply interruption in integrated electricity‐heat energy systems (IHES). This paper presents an analytical‐based approach for the efficient operational reliability evaluation of the IHES. The wind power distribution characteristic model considering correlation is constructed based on Hidden Markov Model (HMM). To reduce computational complexity, a critical system state identification (CSSI) method is proposed that characterises both random device failures and wind power uncertainty. Under each critical system state, the analytical function relationship between the reliability index and the uncertainty factors is established based on the virtual stochastic response surface (VSRS) method. The analytical function can directly calculate the reliability index when the wind power output varies, avoiding a large number of repeated calculations of the optimal load‐shedding model of the system and reducing the time required for reliability assessment. This allows the operator to evaluate the operational reliability of the integrated energy system in real‐time. The numerical simulation of the test system combining the IEEE 33‐node distribution system and the existing 28‐node heating system proves the effectiveness of the proposed method.

Keywords

• hidden Markov models
• polynomial approximation
• reliability theory
• renewable energy sources