Risk-based optimal decision-making strategy of a Power-to-Gas integrated energy-hub for exploitation arbitrage in day-ahead electricity and Natural Gas markets

Abstract

Utilizing multi-carrier energy systems is a significant step toward a lower-carbon economy and affordable energy production. Hence, this paper proposes a novel and comprehensive stochastic-based decision-making strategy for the optimal short-term management of a power-to-gas included energy hub considering the possibility of simultaneous participation as a prosumer in isolated day-ahead natural gas and electricity markets. The proposed model uses cross-product arbitrage between natural gas and electricity markets to submit the optimal bids, including electricity and natural gas buying/selling bids and offers. Furthermore, the uncertainties for day-ahead electricity and natural gas prices have also been taken into account using a scenario generation method. Appropriate risk measurement as conditional value at risk (CVaR) is also integrated into the model to mitigate the risk of expected cost due to market price volatilities. The risk-averse condition has also been considered. The proposed problem is finally formulated as mixed-integer linear programming and solved by executing CPLEX solver in GAMS optimization software. The simulation results demonstrate that implementing power-to-gas equipment and exploiting cross-product arbitrage in the day-ahead Natural gas and electricity markets increase decision-making capability and save up to 16% in the energy procurement cost of an energy hub.