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.

Modern power systems are confronted with widespread concern on the frequency stability issue due to the widespread integration of randomly fluctuating renewable resources. To address the above concern, this work introduces a load-frequency-control (LFC) scheme based on a parameter tuning strategy for fractional-order proportional–integral–derivative (FOPID) controller. Firstly, a two-area interconnected power system (IPS) model, including thermal, hydro, solar, wind, and gas power generator and a hydrogen-based energy-storage unit, is established. Then, a FOPID controller is designed for this IPS model, and an improved gradient-based optimizer (IGBO) is developed to adaptively regulate the parameters of the FOPID controllers. Finally, the effectiveness of the offered LFC scheme is tested through load disturbance and renewable energy fluctuations test scenarios and provides a comparison and robustness analysis among different schemes. The test results validated that the offered LFC scheme can effectively suppress the frequency fluctuations of the IPS and has excellent robustness.

Aluminum electrolytic capacitors are the most commonly used components in circuit systems but are the weakest part of the systems. To make better use of this kind of components, it is crucial to monitor their status and parameter variations more accurately. This brief puts forward a prototype to test the frequency-dependent characteristics of the capacitors, both the capacitor voltage and current are acquired by using the prototype, while a variable forgetting factor recursive least square (VFF-RLS) method based scheme is applied to identify the capacitance (C) and the equivalent series resistance (ESR). Experiments are present by using the proposed scheme and the results of which are compared with the LCR meter measurement results. The extensive comparison results show that the relative error between experimental results and measurements are less than 5.03% which are acceptable compared with some other existing schemes and indicate that the proposed scheme is effective for the online parameter identification of Aluminum electrolytic capacitors.