Xubin Liu

Power flow calculation and static voltage stability (SVS) analysis of active distribution networks (ADNs) are facing convergence and applicability issues caused by extreme conditions and control strategies of grid-forming (GFM) and grid-following (GFL) distributed generations (DGs). To solve these challenges, an SVS and DG integration capacity quantification method based on extended holomorphic embedding power flow (EHEPF) is proposed which includes four aspects: 1) an EHEPF algorithm is developed that accommodates both convergence and converter’s internal primary and secondary control characteristics of DGs; 2) the unsolvable mathematical expression of EHEPF is derived using Padé approximant to clearly distinguish between no solution and lower-branch (inoperable) solution; 3) the voltage sensitivity and SVS indexes of EHEPF combining different control strategies of DGs are formulated to analyze the weak bus and SVS of ADNs; 4) the DGs integration capacity is quantified by balancing SVS and network loss under voltage distribution calculated in EHEPF. Case studies are carried out on 12 bus, IEEE 33 and IEEE 123 bus systems. Numerous test results are analyzed to verify the applicability, convergence and effectiveness of proposed EHEPF for SVS and DGs integration capacity quantification in ADNs.

The rapid proliferation of electric vehicles necessitates accurate forecasting of charging pile capacity for urban power system planning, yet existing methods for medium- to long-term prediction lack effective mechanisms to capture complex multi-factor relationships. To address this gap, a hybrid cointegration–BiLSTM framework is proposed for medium- to long-term load forecasting. Cointegration theory is leveraged to identify long-term equilibrium relationships between EV charging capacity and socioeconomic factors, effectively mitigating spurious regression risks. The extracted cointegration features and error correction terms are integrated into a bidirectional LSTM network to capture complex temporal dependencies. Validation using data from 14 cities in Hunan Province demonstrated that cointegration analysis surpassed linear correlation methods in feature preprocessing effectiveness, while the proposed model achieved enhanced forecasting accuracy relative to conventional temporal convolutional networks, support vector machines, and gated recurrent units. Furthermore, a 49% reduction in MAE and RMSE was observed when ECT-enhanced features were adopted instead of unenhanced groups, confirming the critical role of comprehensive feature engineering. Compared with the GRU baseline, the BiLSTM model yielded a 26% decrease in MAE and a 24% decrease in RMSE. The robustness of the model was confirmed through five-fold cross-validation, with ECT-enhanced features yielding optimal results. This approach provides a scientifically grounded framework for EV charging infrastructure planning, with potential extensions to photovoltaic capacity forecasting.

In islanded microgrids with high-proportion renewable energy, the disconnection from the main grid leads to the characteristics of low inertia, weak damping, and high impedance ratio, which exacerbate the safety risks of frequency and voltage. To balance the requirements of system operation economy and frequency–voltage safety, a coordinated optimization scheduling method for frequency and voltage in islanded microgrids considering the active support of battery energy storage (BES) is proposed. First, to prevent the state of charge (SOC) of BES from exceeding the frequency regulation range due to rapid frequency adjustment, a BES frequency regulation strategy with an adaptive virtual droop control coefficient is adopted. The frequency regulation capability of BES is evaluated based on the capacity constraints of grid-connected converters, and a joint frequency and voltage regulation strategy for BES is proposed. Second, an average system frequency model and an alternating current power flow model for islanded microgrids are established. The influence of steady-state voltage fluctuations on active power frequency regulation is analyzed, and dynamic frequency safety constraints and node voltage safety constraints are constructed and incorporated into the optimization scheduling model. An optimization scheduling method for islanded microgrids that balances system operation costs and frequency–voltage safety is proposed. Finally, the IEEE 33-node system in islanded mode is used as a simulation case. Through comparative analysis of different optimization strategies, the effectiveness of the proposed method is verified.

In response to the challenges posed by the high proportion of photovoltaic (PV) in electrolytic aluminum (EA) industrial isolated microgrids, such as the low carbon economy problem and the dynamic dispatchability of EA and its combined heat and power (CHP) unit, a multi-timescale optimal dispatching method considering the dynamic temperature characteristics of an aluminum electrolytic cell is proposed for an EA isolated microgrid. Firstly, based on an electrothermal coupling model, the electrolyte dynamic temperature expression of aluminum electrolytic is derived, and the optimal dispatching method of an EA load considering the dynamic temperature characteristics of EA is proposed. Secondly, based on the carbon emission models of CHP units and EA loads, and with the optimization objective of maximizing the operating revenue of industrial isolated microgrids, a day-ahead-intraday multi-timescale optimal dispatching model considering the participation of EA loads in the demand response (DR) for isolated microgrids was established. Finally, numerical results for an industrial isolated microgrid have verified the effectiveness of the proposed method in improving the PV consumption rate and realizing low-carbon and economic operation of industrial islanded microgrids.

The emerging offshore wind farms (OWFs) with increasing installed capacity have an increasing impact on the frequency and voltage stability of onshore power grids. It is a challenge to enable OWFs to participate in frequency and voltage regulation considering the support ability of distributed OWFs and the anti-disturbance ability of onshore grid-connected nodes. To address this challenge, a frequency-voltage synergy support (FVSS) strategy for VSC-MTDC integrated distributed OWFs is proposed with four components: 1) A distributed coordination strategy with leader-follower consensus algorithm is developed for WTs to fairly provide support power; 2) An active/reactive power quantification strategy, which considers equivalent impedance characteristics of local loads and line power flow influence, is established for power requirements of ground side voltage source converters (GSVSCs) for frequency support (FS) and voltage support (VS); 3) A frequency strength quantification (FSQ) and voltage strength quantification (VSQ) strategies are conducted to characterize the anti-disturbance ability of GSVSC; 4) An adaptive power coordination strategy, which considers FSQ and VSQ, is proposed to achieves active/reactive power allocation for FS/VS. Extensive simulation results have validated the effectiveness and correctness of the proposed FVSS under different scenarios.

The existing imprecise fault current calculation, due to incomplete stage division of whole fault process of DFIG-based wind farms (DBWFs), brings great hidden dangers to safety and stable operation of local grid. To tackle this challenge, a fault current multi-stages calculation (FCMSC) method is proposed to accurately calculate DFIG-based wind farm's output symmetrical and asymmetrical fault currents under grid whole fault process that including fault occurrence, fault ride-through and fault recovery. The main content of FCMSC method includes: 1) Whole fault process equivalent aggregation model, which contains protection response stage, first crowbar protection stage, demagnetization operation stage, reactive current injection stage, and second crowbar protection stage, is completely established while second crowbar protection stage is firstly dissected in detail. 2) Fault current contribution mechanism, considering wind speed, is revealed to have GSC injection and absorption modes under asymmetrical grid fault conditions. 3) Fault current universal expression, which covers whole fault process operation stages and scenarios, is conducted by replacing differential equations with simple algebraic operations for improving calculation accuracy, timeliness and universality. 4) Fault current characteristic components, which contain DC components, AC stable components, and AC attenuated components, is extracted for providing key data for fault identification and protection. Extensive test results under symmetrical and asymmetrical faults are illustrated for verifying the correctness of proposed FCMSC method.

The lack of relevant protection schemes and standards brings significant challenges to the promotion of direct current microgrid (DCMG) technologies. The existing line fault diagnosis methods usually require additional measuring devices to obtain fault signals. Although reducing the number of sensors can lower the system costs, it also increases the difficulty of diagnosis. Pole-to-pole (PP) and positive pole-to-ground (PPG) fault classification under unknown fault resistance, and negative-to-ground (NPG) fault detection under unobvious positive pole current characteristics are two major difficulties. To solve the above issues, a fuzzy granulation interval (FGI) theory-based line fault diagnosis method is proposed in this paper. Only locally measured bus-side voltage and positive pole current signals shared with the converter controller inputs are required. Firstly, the fault characteristics and diagnosis difficulties are analyzed. Then a new NPG fault index interval range (IR) is designed to extract the abnormal post-fault voltage fluctuations. Moreover, the PP/PPG fault classification strategy is designed according to the interval characteristics and capacitor discharge process. Finally, the performance of the proposed method has been evaluated through MATLAB/Simulink simulations and hardware-in-the-loop (HIL) tests. The results demonstrate that the proposed method can accurately discriminate different line faults within 1.5 ms under different fault conditions.

This paper proposes a fast fault diagnosis scheme to realize fault detection and classification with fewer sensors for ring bus DC microgrids. After the analysis on mechanisms of line faults in the microgrids, the measurements of the local converter, including the voltage of the DC-link capacitor and the output current, are used to detect pole-to-pole (PP) faults and pole-to-ground (PG) faults, employing the sum of multi-step difference. Based on the deviation between the estimate and the actual output voltages, a simple and effective fault classification method is proposed in this research. The detection results of two neighboring units are exchanged to locate the fault line with low bandwidth distributed communication. Apart from PP faults, PG faults in both poles can be detected and distinguished, sharing the voltage and current sensors with the controllers of the converters, and the construct cost of the system can be reduced. The performance of the proposed scheme in different cases has been tested in MATLAB/Simulink, including high impedance faults, close-in faults and signal with noises. Further, the effectiveness of the scheme is validated under Hardware-in-loop (HIL) platform.

The onshore local grid is facing the challenge to avoid continuously increasing fault current caused by frequency regulation (FR) of broad-scale offshore wind farms (OWFs) integrated by voltage source converter based multi-terminal high voltage direct current (VSC-MTDC) system. To tackle this challenge, an active fault current limitation (AFCL) method is proposed in four aspects: 1) a fault current contribution factor (FCCF) is introduced for grid side VSC (GSVSC) to quantify the incremental degree of fault current caused by FR of GSVSC under different fault types; 2) a current phase angle control (CPAC) strategy based on vector analysis is conducted for GSVSC to actively mitigate the fault current increment; 3) according to FCCF and CPAC, an active and reactive current quantification (ARCQ) strategy is developed for GSVSC to satisfy bilateral demands of AFCL and FR; 4) an adaptive frequency regulation (AFR) strategy, which considers FCCF and the operating conditions of the offshore system (e.g., rotor speed and DC voltage), is formulated for OWFs to quantify and generate the active power required for FR and AFCL. Numerous test results are analyzed to verify the effectiveness and performance of the proposed AFCL method in satisfying system fault current limitation during FR of OWFs.