A Risk-Averse Stochastic Dynamic Programming Approach to Energy Hub Optimal Dispatch

This paper studies the optimal operation problem of an energy hub with multiple energy sources to serve stochastic electricity and heat loads in the presence of uncertain prices as well as operational constraints, such as minimum uptime and downtime requirements. Price and demand uncertainties are modeled by stochastic processes. The goal is to minimize some risk functional of the energy hub operational cost. A stochastic dynamic optimization formulation is introduced for the problem. An approximate dynamic programming framework, based on cost function approximation, is proposed to obtain dynamic dispatch policies. The approach enables a risk-sensitive energy hub operator to consider a non-differentiable risk measure and various constraints. The performance of the approach for the energy hub dispatch problem and characteristics of the storage levels are numerically investigated.