Power-to-gas technology provides an emerging pathway for promoting green and low-carbon transformation of energy systems. Through the processes of electrolyzing water and the methanation reaction, it converts surplus renewable energy into hydrogen and natural gas, offering an effective approach for large-scale integration of renewable energy sources. However, the optimization of existing integrated energy systems has yet to finely model the operational characteristics of power-to-gas technology, severely limiting the energy conversion efficiency of systems. To address this issue, this paper proposes an integrated energy system operation strategy considering the slow dynamic response characteristics of power-to-gas. Firstly, based on the technical features of power-to-gas, an operational model for electrolyzing water to produce hydrogen is constructed, considering the transition relationships among cold start-up, hot start-up, and production states of a methanation reaction, thereby building a power-to-gas operation model considering slow dynamic response characteristics. This model finely reflects the impact of power-to-gas operational states on methanation, facilitating accurate representation of the operational states of methanation. Then, considering the energy conversion constraints and power balance of various coupled devices within integrated energy systems, an optimization model for the operation of the integrated energy system is constructed with the total daily operation cost of the system as the optimization objective. Finally, simulation comparisons are conducted to demonstrate the necessity of considering the slow dynamic response characteristics of power-to-gas technology for integrated energy system operation. The case study results indicate that the proposed power-to-gas operation model can accurately simulate the methanation process, facilitating the rational conversion of surplus renewable energy into natural gas energy and avoiding misjudgments in system operation costs and energy utilization efficiency.

The generation output of distributed power sources and the load possess periodic changes, which cause stability problems in the operation of the power grid. To ensure stability, energy storage devices are generally installed in the power grid, but their effectiveness is also limited by their fixed installation location and capacity. In this paper, to overcome the drawback of stationary energy storage devices, mobile energy storage devices are introduced to reduce power losses and enhance voltage stability. The installation location and capacity of these mobile energy storage devices can be changed with the generation output and load demands. Firstly, the influence of the mobile energy storage devices on power losses and voltage stability is analyzed. Next, a multi-objective optimization model is established to select the optimal installation location and the ideal capacity, which has optimization objectives including the improvement of voltage stability, the minimization of power losses, and the enhancement of utilization of energy storage devices. Finally, the particle swarm optimization algorithm is applied to solve the multi-objective optimization problem. The simulation results prove that the novel method of this paper enhances the dynamics of the power grid, i.e., the voltage vulnerability and power losses are reduced by 29% and 36%, respectively. In addition, it also increases the utilization rate of energy storage devices by 33.5% in different operating scenarios.

This study focuses on the stability of time-delay load frequency control (LFC) systems. Based on the Lyapunov–Krasovskii (L–K) functional method, a stability criterion with less conservatism and lower computational complexity is proposed. Unlike recent methods that decrease conservatism through enhancing the complexity of L–K functional, only the double integral is augmented in this paper. To estimate the L–K functional derivatives more precisely, an improved matrix-separation-based inequality is proposed, which introduces some delay-derivative-dependent matrices rather than the high-dimensional free matrices. By applying the augmented L–K functional and the improved matrix-separation-based inequality, the stability criterion is established. Case analysis demonstrates that the new stability criterion has less conservatism and lower computational complexity, thereby validating the correctness of the method presented.