The widely adoption of distributed renewable energy sources (DREs) effectively reduces carbon emission and beat atmospheric haze in developing countries. However, random disturbance issues emerge in power grids with DREs when applying traditional centralized automatic generation control (AGC) strategies. Therefore, a multi-agent distributed control strategy is proposed for AGC in this work, which is mainly based on the concept of deep reinforcement learning, and developed by the strategy of action discovery. Moreover, area control error and the amount of carbon emission are employed in reward functions to obtain optimal solutions in the implementing process of the proposed strategy. Simulations are provided in the work to show the effectiveness of the strategy, while comparisons are also offered, where the simulating results obtained by two other intelligent AGC algorithms are used as references, according to which, the superiority of the proposed strategy is confirmed.

This paper proposes a modeling and analysis method for fractional-order dc-dc converters operating in continuous conduction mode (CCM). As an example, a fractional-order boost converter is studied in detail. Instead of using fractional calculus, the method presented here uses a general state vector differential equation to describe the converter. By combining the principle of harmonic balance and equivalent small parameter method, an approximate analytical steady-state solution of the state variables could be obtained. Subsequently, the CCM-operating criterion of the converter is discussed based on the proposed method, and the appropriate parameters are provided to make sure that the fractional-order converter operates in CCM. In addition, a statistical analysis of harmonics is performed, from which the effects of fractional orders on harmonics can be observed. Moreover, numerical simulations are performed using the Adams-Bashforth-Moulton-typed predictor-corrector method and the Oustaloup's-filter-based approximation method. Both the dc components and ripples of the state variables obtained from these two methods are combined with those obtained by the proposed method, and they are in good agreement. Finally, the fractional-order capacitor and inductor are designed and verified by simulations, and on the basis of which experiments of the fractional-order boost converter are carried out to further verify the proposed method.

As the penetration rate of new energies, energy storage devices and electric vehicles increases continuously in power grid, power grid faces strong random disturbances, as well as the issues of downfall in frequency control ability induced by the factors such as system inertia reduction and frequency control under-capacity in traditional power units. Therefore, an algorithm of automatic generation control with DQ(σ, δ) is proposed for the multi-area interconnected power grid. By integrating the eligibility trace, DQ(σ, δ) adopts the principle of double Q learning to unify double Q(δ) and double Expected-Sarsa(δ), thereby the over-estimation of Q in the algorithm and the phenomenon of over-fitting can be avoided. The simulations are provided to demonstrate the effectiveness of the proposed algorithm, where the improved IEEE standard two-area load-frequency control model and the model of the multi-area interconnected power grid based on Central China Power Grid are adopted. The results show that the phenomena of random disturbances and frequency instability can be eliminated in multi-area interconnected power grid. The convergence is faster and the dynamic performance is better in the proposed algorithm compared with the traditional algorithms.

An optimal attack strategy combining denial-of-service (DoS) attacks and false data injection (FDI) attacks against the economic dispatch of integrated energy system (IES) is proposed in this brief. Firstly, the operation process of the distributed double consensus algorithm (DDCA) under DoS attacks is given, and the impact of DoS attacks on the economic dispatch of IES is qualitatively analyzed. Subsequently, an optimal stealthy DoS attack scheme consisting of the optimal attack sequence and the optimal attacked nodes is proposed. Furthermore, in order to enhance the economic destruction ability of DoS attacks, FDI attacks against measurement devices and communication links, respectively, are employed. The additional FDI attacks can minimize the power valley value in the optimal DoS attack scheme, and the explicit form of the vector to inject initial values is deduced. Finally, the proposed combining attack strategy that can maximize the operating cost is demonstrated by simulation cases on a 39-32 power-heat integrated energy system.

An quasi-online equivalent series resistance (ESR) identification method that considers the impact of capacitance based on variational mode decomposition (VMD) of forward converters is proposed in this letter. First, the capacitance impact is included in ESR derivation. Subsequently, VMD is adopted to process characteristic signals for harmonic analysis, filter out noise, and simplify circuits design. The experiments and simulation are employed to verify the proposed method. In addition, in order to overcome the disadvantages of using ideal capacitors in the traditional simulation, fractional-order capacitors are constructed to describe the nonideal characteristics of the capacitor. Meanwhile, the identification result is compared with the LCR meter measurement. Thus, the superiority of the proposed ESR quasi-online identification method and the construction method of fractional-order capacitors are confirmed through comparative analysis.