Optimizing gas entry-exit capacity utilization under uncertainty

Area of Science:

• Energy Systems Analysis
• Operations Research
• Econometrics

Background:

• Natural gas is crucial for Europe's energy supply, with Norway as a major provider.
• Managing entry-exit capacity in Norway's gas network is complex due to demand and price uncertainties.
• Network stability concerns often lead to risk-averse capacity allocation strategies.

Purpose of the Study:

• To develop a scalable stochastic programming model for optimal natural gas capacity allocation under uncertainty.
• To analyze the impact of risk aversion on capacity allocation and system welfare in Norway's gas network.
• To provide insights into system bottlenecks and the value of flexibility for policymakers and stakeholders.

Main Methods:

• Development of a scalable stochastic programming model for capacity allocation.
• Case study application to Norway's gas pipeline network.
• Analysis of risk aversion's influence on optimal capacity decisions and system outcomes.

Main Results:

• The model successfully determines optimal capacity allocation under uncertainty.
• Moderating risk aversion in capacity allocation leads to substantial system welfare gains.
• Identification of critical system bottlenecks and quantification of flexibility's value.

Conclusions:

• Stochastic programming offers an effective approach to optimize natural gas capacity allocation.
• Reducing excessive risk aversion in capacity management can unlock significant economic benefits for the European gas market.
• The study provides valuable data and insights for enhancing energy security and market efficiency.