Optimization of compressor standby schemes for gas transmission pipeline systems based on gas delivery reliability.

• The operating process of a gas pipeline system under each scenario is rigorously considered. • More than 160 scenarios are considered in compressor standby scheme optimization. • The large-scale NLP model is established for the power standby scheme optimization. • The constraints between the unit standby scheme and the probability of scenarios are established. • The original large-scale MINLP model for the unit standby scheme optimization is equivalently decomposed into two sub-problems. To guarantee the gas delivery reliability of a gas pipeline system, some standby compressor units or standby powers are typically installed in a compressor station. A reasonable compressor standby scheme plays a vital role in the efficient operation of compressor stations. This paper presents two standby scheme optimization models considering various normal and failure scenarios for two standby modes: unit standby and power standby, respectively. The proposed models aim to maximize the gas delivery reliability subjected to rigorous operating constraints of a gas pipeline system and budget constraints (e.g., the total amount of standby power/ units). The resultant optimization models for power standby and unit standby schemes are large-scale nonlinear programming (NLP) and mixed-integer nonlinear programming (MINLP), respectively. In order to solve the unit standby optimization scheme efficiently, we decompose the original large-scale model into two sub-problems equivalently. The first sub-problem is to maximize the gas delivery flow rate under various scenarios based on determined compressor configurations. Based on the solutions from the first sub-problem, the second one is to optimize the standby scheme. Numerical results are provided to verify the effectiveness of the proposed approaches. It is demonstrated that the results of compressor standby optimization models can provide valuable information for the design and planning of gas pipeline systems. [ABSTRACT FROM AUTHOR]