The Effect of Disruptive Events on Optimal Design and Operation of an Energy Community

The price of energy carriers follows very complex dynamics that are not only closely related to markets but can be significantly influenced by socio-political or environmental events. This paper examines how disruptive events of these types affect the total energy supply costs of multi-energy systems and explore potential actions to mitigate their effects. A stochastic model based on a CIR (Cox-Ingersoll-Ross) process with jumps is first developed to represent energy price trends featuring sudden peaks. The CIR process is chosen for its mean-reverting behavior, which drives prices back toward a long-term average, and for its ability to ensure price positivity, as observed in electricity markets like the Italian one. The models are used to generate stochastic scenarios of natural gas and electricity prices considering different jump frequencies. The multi-energy system of a renewable energy community is then considered as a case study. A stochastic optimization problem for the design and operation of this system is formulated and solved, using the generated stochastic scenarios as input, along with the other required input data (treated as deterministic). Results show that accounting for a single energy price peak during the design phase reduces total costs by 2.3%, primarily by increasing PV capacity. This strategic increase in installation costs enables a substantial reduction in net operating costs associated with electricity exchange with the grid when a price peak is expected to occur.