Mixed neurodynamic optimization for the operation of multiple energy systems considering economic and environmental aspects

Highlights: • An multiple energy system (MES) bi-level optimization model is proposed. • The model coordinates the MES optimization considering carbon emissions. • A mixed neuraldynamic optimization method for global optimization is used. • The method can clearly observe its convergence process in continuous time. In addition to economic goals, environmental constraints play an increasingly important role in the operation of multiple energy systems. A optimization model combining the minimization of energy cost and the carbon emissions is established to evaluate environmental impact, which is significant in the policy making policy making of the energy saving and emission reduction. In this paper, a bi-level model of multiple energy systems is proposed, which considers the constraints of operation and emission. The upper-level model studies the optimal allocation of electric power and natural gas in multiple energy systems. Based on the energy hub modeling method, the low-level model investigates the optimal energy supply allocation of multiple energy carriers. The mixed neurodynamic algorithm combining neurodynamic algorithm and intelligent algorithm is used to get the optimization results. Simulation results verify the effectiveness of the model and algorithm.