Tao Jiang

Traditionally, it is assumed that microgrids transition seamlessly from grid‐connected operation to islanded mode in the event of sudden main grid outages. In reality, the islanding process, especially unintentional islanding, is rarely seamless. Instead, it is subject to voltage and frequency fluctuations caused by the instantaneous disconnection of the point of common coupling (PCC) switch, variations in loads and renewable generation output and even the protection tripping of distributed energy resources (DERs). To mitigate these fluctuations and facilitate a smooth islanding process, we propose a stochastic microgrid scheduling model that incorporates chance‐constrained resilience measures. Specifically, the resilience measure is defined as the probability of successful islanding (PSI), that is, the probability that a microgrid can mitigate the generation‐demand imbalance caused by the disconnection of the PCC switch, variations in load and renewable generation and DER tripping. This measure is modelled using chance constraints. Unlike existing reliability and resilience indices, which typically neglect the possibility of microgrid/DER failure under extreme events and assume their survival while primarily focussing on reducing impact duration or magnitude, the proposed PSI‐based framework explicitly addresses microgrid and DER survival during the islanding transition. The formulated nonlinear chance constraints are approximated using a multiinterval approach and equivalently represented as a mixed‐integer linear programming (MILP) formulation. Case study results validate the proposed method, showing that the PSI estimation error is reduced to less than 8%, compared to approximately 28% with existing methods. Various sensitivity analyses on the DER tripping rate and PSI settings were performed to validate the robustness of the proposed method. In particular, the necessity of accounting for DER tripping in the PSI calculation was demonstrated.

With the integration of high-proportion renewable energies, the independent operation of the transmission and distribution systems (T&DSs) makes it difficult to achieve optimal scheduling and ensure frequency security. Therefore, this paper proposes a two-stage robust frequency-constrained unit commitment (TRO-FCUC) model of T&DS. Firstly, the impacts of distributed energy resources (DERs) frequency regulation capabilities on inertial response and primary frequency response (PFR) are considered, and dynamic frequency constraints considering the cooperation of thermal units, wind farms, and DERs with their inertia-based frequency reserve are constructed. Then, the TRO-FCUC model is formulated to address uncertainties of wind farms (WFs) and distributed photovoltaics (DPVs) based on uncertainty sets. Further, the column and constraint generation (C&CG) algorithm and strong duality theory are utilized to transform the TRO-FCUC model into a mixed-integer second-order cone programming (MISOCP) model and then solve it iteratively. Finally, case analyses proposed demonstrate that the coordinated operation of T&DS can fully mobilize the frequency regulation potential of DERs and improve the operation’s economy while ensuring the frequency security of the system.

Forced oscillations (FO) in power systems are caused by sustained periodic disturbances, threatening the power system stability. Developing a fast and accurate FO detection and location approach is of great significance for mitigating FO. This manuscript proposes a novel FO detection and location method using synchrophasor measurements in bulk power systems. Firstly, based on the short-time Fourier transform (STFT) of measurements, an FO detection method is proposed using the energy ratio function in time-frequency domain. Then, the equivalence of dissipating energy flow and dissipating energy spectrum is demonstrated. On this basis, the cross power spectral density (CPSD) of governor and excitation system are defined. The amplitude and phase spectra of the governor and excitation system at FO frequency are then derived, and the criteria for control device collaborative location are presented. Furthermore, an index for evaluating the oscillation contribution of the disturbance device based on frequency band energy is proposed to identify the dominant FO disturbance control device. Finally, the proposed method is validated using the simulation data of WECC 179-bus test system and 2021 IEEE-NASPI oscillation source location contest, as well as the field data from ISO-New England. The results validate the effectiveness and feasibility of the proposed method.

With the proliferation of distributed generators (DGs), multimicrogrid distribution systems (MMDSs) have emerged, where cooperative optimal operation plays a crucial role in improving operational flexibility and economy. On the other hand, when considering distribution network reconfiguration (DNR), traditional iterative distributed algorithms can protect privacy but face challenges, such as high computational complexity and poor convergence. To address these issues, this article proposes a cooperative operation method for MMDSs based on an equivalent projection (EP) theory. Specifically, a bi-level cooperative method for MMDSs is first proposed. Therein, the flexible resources within the MMDS are identified, while DNR and soft open point (SOP) technologies are considered. Second, to protect privacy of the lower-level microgrids (MGs), the improved Fourier–Motzkin elimination (IFME) and Gaussian elimination methods are used to derive the low-dimensional projection feasible region (PFR) of the lower-level MGs. Third, a noniterative solution method based on the EP theory is developed to efficiently solve the bilevel cooperation model, while addressing the privacy concerns from participants. Numerical results show that the third-order approximate PFR model can achieve a lossless transformation of the bilevel model, effectively balancing computational efficiency and accuracy. Compared to traditional distributed algorithms, the developed noniterative solution method exhibits superior performance in solving mixed-integer programming (MIP) problems. Moreover, the proposed cooperative approach improves the operational performance of the MMDS, achieving a 7.22% reduction in operating costs.

Accurately and promptly extracting subsynchronous oscillation (SSO) components from measurements and locating SSO sources are crucial for SSO suppression. Existing transient energy flow (TEF) based SSO location methods suffer from low location accuracy and poor robustness. To cope with the shortcoming of the traditional TEF in SSO source location, this paper proposes a multivariate variational mode decomposition (MVMD) based SSO source location method to locate the SSO source from the measurements. Firstly, the multi-channel measurement matrix of each generator, including voltage and current measurements, is formed. Then, the multi-channel intrinsic mode functions (IMFs) are simultaneously decomposed from the formed multi-channel measurement matrix by using the MVMD approach, enabling the simultaneous decomposition of SSO components from measurements. Furthermore, the IMFs associated with the SSO mode are identified according to the Hilbert transform (HT). Using the identified IMFs, the MVMD-based TEF is calculated and the SSO source is located. Finally, the performance of the proposed method is evaluated using the simulation data of the modified 4-machine 11-bus test system and the field measurements from the Guyuan SSO event in the North China region. The results validate the accuracy and effectiveness of the proposed method in the SSO source location.

Fast and accurate forced oscillation source location (FOSL) is critical for mitigating forced oscillations in power systems. To overcome the shortcomings of traditional dissipating energy flow (DEF) in decomposing the forced oscillation components from the measurement responses, a multivariate variational mode decomposition (MVMD)-assisted FOSL is proposed in this paper to locate the forced oscillation sources from measurements in time-frequency (TF) plane. The multi-channel measurement matrix of each generator is formed, then the multi-channel modes are decomposed from the formed multi-channel measurement matrix using the MVMD. Further, the intrinsic mode functions (IMFs) associated with the forced oscillation mode are distinguished from the decomposed modes according to the relative energy weights. With the distinguished IMFs, the MVMD-assisted DEF calculation method is developed to locate the forced oscillation source. Finally, the performance of the proposed method is evaluated using the simulation data of the WECC 179-bus test system and IEEE-NASPI Oscillation Source Location Contest as well as the actual PMU data of ISO New England. The results validated the effectiveness and accuracy of the proposed method in the FOSL.

Forced oscillation source location (FOSL) plays a significant role in mitigating forced oscillations (FOs), which threaten the power system stability. This paper proposes a data-driven approach for FOSL in power systems using synchrosqueezing wavelet transform (SWT). The proposed approach conducts SWT on the measured system responses to obtain the SWT matrix. Then, the SWT-based dissipating energy flow (DEF) model in time-frequency domain and dissipating energy spectrum (DES) model in frequency domain are derived from the traditional DEF model. Further, the characteristics of SWT-based DEF and DES are revealed by referring to the traditional DEF, and the FOSL criteria of the SWT-based DEF and DES can be hereby obtained. Using the obtained FOSL criteria, the FO source can be located from the measured responses. The performance of the proposed FOSL method is evaluated by simulation data of the WECC 179-bus test system and field-measurement PMU data of the ISO New England. The results confirm the accuracy and efficiency of the proposed method in the FOSL.