Congestion management for coordinated electricity and gas grids in the presence of multi-energy hubs: A risk-based optimal scheduling

Abstract

Due to the development of cost-effective and high-efficient infrastructures in electricity and natural gas carriers, the need for optimal operation of multi-carrier energy systems is essential. On the other side, with the increasing penetration of renewable energy resources (RERs), and power demand, the congestion management (CM) of power systems is turning out to be a significant challenge for system operators. Motivated by these, this paper focuses on the congestion management problem for a multi-energy hub (MEH) system incorporated by RERs, flexible energy resources (FERs), and different energy conversion technologies to supply electrical, heat, and cooling demands, aiming to minimize the total operating costs. In current practice, the steady-state Weymouth equation and AC-power flow method for natural gas and electricity networks are implemented to investigate the interdependency of power and gas networks. The renewable energy generation variations are mitigated by the scenario-based stochastic framework. Also, to manage the risk associated with random variables, the downside risk constraint (DRC) model is employed to analyze the changes in the expected cost per several values of the risk parameters. The numerical results demonstrate that the proposed model can significantly utilize the energy hub’s flexibility to alleviate gas and power congestion while decreasing the total operation cost.