enhancing uncertainty management in energy hubs: incorporating heating and cooling assets and leveraging demand response programs

The energy hub (eh) concept is a key component in modern energy systems that integrates multiple energy resources and carriers to meet different energy demands. this paper investigates an eh composed of conventional generation units, renewable energy resources (rers), energy storage systems (esss), and heating and cooling assets. it tries to optimize eh owner profits while minimizing various costs through mathematical programming. additionally, it addresses uncertainty management in eh arising from rers outputs, utilizing a chance constraint - information gap decision theory - robust optimization (cc-igdt-ro) approach derived from optimization with uncertain data and feasibility robustness theorems. furthermore, it introduces flexibility services as an alternative means to effectively address this uncertain energy management component. a comparative analysis with existing literature demonstrates the robustness and applicability of the proposed framework, which is 42% lower in the costs within conventional ehs, and providing 10% more flexibility in comparison with cases in review.