An estimation-Based optimal scheduling model for settable renewable penetration level in energy hubs

Several recent studies suggest that power-to-gas (PtG) facilities can be operated to absorb and convert surplus renewable energy into hydrogen or synthetic natural gas, which is then supplied to the natural gas grid, forming an energy hub (EH). This paper argues and demonstrates that there is a trade off between maximizing the renewable penetration level (PRL) into the EH and minimizing the cost associated with it. The paper presents a new optimal scheduling model allowing variable and settable PRLs into the EH to minimize the system operating cost. The RPL, as determined by the grid operator, is taken in as a setting to the scheduling model. A new al-gorithm is presented by which the relationship between the RPL and scheduling setpoints of PtG and gas-fired generation (GfG) facilities are estimated. Accordingly, the optimal scheduling setpoints of PtG and GfG facilities are decided by the model, so that the required RPL can be met. The problem is formulated using the mixed integer nonlinear optimization method where the estimation algorithm is developed using the least error square technique. The developed problem is then solved using the combined interior point nonlinear programming and Newton trust region techniques. Numerical studies are conducted on a test system using historical operating data to validate the efficacy of the model. The system operating parameters are analyzed, and it is demonstrated that it is imperative to optimally manage the desired RPL taking into consideration the arbitrage revenue shortfall resulted from RPL enhancement in an EH.

Automated summary

By optimizing the operational costs and setting the optimal level of renewable energy penetration, the efficiency of the energy hub can be improved effectively while minimizing associated costs.