Expansion co-planning with uncertainties in a coupled energy market

Natural gas is an important fuel source in the power industry. Electricity and natural gas are both energy that can be directly consumed. It is imperative that gas power plants, electricity transmission lines and gas pipelines are co-planned in future energy transmission expansion. The co-planning process is modeled as a mixed integer nonlinear programming problem to handle the multi-stage and conflicting objectives simultaneously. We propose a novel optimization algorithm called Historical Driven Differential Evolution (HDDE) to identify the optimal co-expansion plan in terms of the social welfare. Planning risks due to uncertainties of energy load, load percentages that can be mutually transferred between gas and electricity, and market price are effectively evaluated by the flexibility criterion in stochastic programming. Meanwhile, we use the sequential importance sampling (SIS) to deploy scenario reduction for a higher computational efficiency. After a test in the IEEE 14-bus system, promising results are obtained to validate our approach.