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The power dispatching network forms the backbone of efforts to automate and modernize power grid dispatching, rendering it an indispensable infrastructure element within the power system. However, accurately forecasting future flows remains a formidable challenge due to the network's intricate nature, variability, and extended periods of missing data resulting from equipment maintenance and anomalies. Vital to enhancing prediction precision is the interpolation of missing values aligned with the data distribution across other time points, facilitating the effective capture of nonlinear patterns within historical flow sequences. To address this, we propose a transfer learning approach leveraging the gated recurrent unit (GRU) for interpolating missing values within the power dispatching network's flow sequence. Subsequently, we decompose the generation of future flow predictions into two stages: first, extracting historical features using the GRU, and then generating robust predictions via eXtreme Gradient Boosting (XGBoost). This integrated process termed the GRU-XGBoost module, is applied in experiments on four flow sequences obtained from a power grid company in southern China. Our experimental findings illustrate that the proposed flow prediction model outperforms both machine learning and neural network models, underscoring its superiority in short-term flow prediction for power-dispatching networks. [ABSTRACT FROM AUTHOR]

This paper presents the dynamic voltage stability index based on the voltage oscillation loop for power systems integrated with multiple permanent magnet synchronous generators (PMSGs) to assess the dynamic interaction on voltage stability. First, the model of power systems integrated with multi-PMSGs using a Q--V sensitivity matrix as feedback to connect all PMSGs is established. The transfer function model between voltage and reactive power is derived, and the voltage oscillation loop can be derived, which exists in each PMSG. Next, the dynamic voltage stability index is theoretically derived and given, the impact of dynamic interaction among multi-PMSGs on voltage stability can be quantified, and the source of voltage oscillation can be identified and determined. Then, the voltage stability is recovered by shedding the trouble-making PMSG. The parameters of PMSGs could be tuned with the guidance of the dynamic voltage stability index to reduce the risk of voltage oscillation. Finally, the example of a test system with PMSGs is used to validate the correctness of the dynamic stability index. [ABSTRACT FROM AUTHOR]

Multiple microgrids interconnect to form a microgrid cluster. To fully exploit the comprehensive benefits of the microgrid cluster, it is imperative to optimize dispatch based on the matching degree between the sources and loads of each microgrid. The power of distributed energy sources such as wind and photovoltaic systems and the sensitive loads in microgrids is related to the regional weather characteristics. Given the relatively small geographical scope of microgrid areas and the fact that distributed energy sources and loads within the grid share the same weather characteristics, simultaneous ultra-short-term forecasting of power for both sources and loads is essential in the same environmental context. Firstly, the introduction of the multi-variable uniform information coefficient (MV-UIC) is proposed for extracting the correlation between weather characteristics and the sequences of source and load power. Subsequently, the application of factor analysis (FA) is introduced to reduce the dimensionality of input feature variables. Drawing inspiration from the concept of combination forecasting models, a combined forecasting model based on Error Back Propagation Training (BP), Long Short-Term Memory (LSTM), and Bidirectional Long Short-Term Memory Neural Network (BiLSTM) is constructed. This model is established on the MV-UIC-FA foundation for the joint ultra-short-term forecasting of source and load power in microgrids. Simulation is conducted using the DTU 7K 47-bus system as an example to analyze the accuracy, applicability, and effectiveness of the proposed joint forecasting method for sources and loads. [ABSTRACT FROM AUTHOR]

Municipal water supply system (WSS) consist of different pumping stages viz. intake, water treatment plant (WTP) and intermediate pumping station (IPS). Usually, the power supply for WSS is obtained through public power tapping sources. However, this often leads to load shedding and disruption of the water supply. This paper focuses on the concept, considering WSS as a multi-source multi-area microgrid scheme, this includes renewable energy sources (RES) such as solar, wind, etc. Moreover, the study incorporates a Battery Energy Storage System (BESS) and a Diesel Engine Generator (DEG) to provide power supply during peak demand at each pumping station. Frequency control is essential for optimizing system performance. This paper proposes Enhanced Harris Hawks Optimization Algorithm (EHHO) based PID controller for regulating the frequency in the multi-microgrid-based water supply system. The proposed controller is implemented in MATLAB simulation software, and its response is compared with other optimization methods such as Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO). Moreover, implementation and comparison of higher degree order controller such as 3DOF-FOPIDN controller and 3DOF-TIDN controllers are tested under PSO method to observe the performance as well as robustness of the controller. The results indicate that the proposed controller provides better performance in controlling the load frequency deviation, thus improving the efficiency and reliability of the multi-microgrid system for consideration of municipal water supply. [ABSTRACT FROM AUTHOR]

Nowadays, electricity theft is a major issue in many countries and poses a significant financial loss for global power utilities. Conventional Electricity Theft Detection (ETD) models face challenges such as the curse of dimensionality and highly imbalanced electricity consumption data distribution. To overcome these problems, a hybrid system Multi-Layer Perceptron (MLP) approach with Gated Recurrent Units (GRU) is proposed in this work. The proposed hybrid system is applied to analyze and solve electricity theft using data from the Chinese National Grid Corporation (CNGC). In the proposed hybrid system, first, preprocess the data; second, balance the data using the k-means Synthetic Minority Oversampling Technique (SMOTE) technique; third, apply the GTU model to the extracted purified data; fourth, apply the MLP model to the extracted purified data; and finally, evaluate the performance of the proposed system using different performance measures such as graphical analysis and a statistical test. To verify the consistency of our proposed hybrid system, we use three different ratios for training and testing the dataset. The outcomes show that the proposed hybrid system for ETD is highly accurate and efficient compared to the other models like Alexnet, GRU, Bidirectional Gated Recurrent Unit (BGRU) and Recurrent Neural Network (RNN). [ABSTRACT FROM AUTHOR]

The linkage, coordination, and complementary cooperation of energy supply can improve the efficiency of transportation and utilization. At present, the level of new energy consumption needs to be improved, the coordination of the source network load storage link is insufficient, and the insufficient complementarity of various types of power sources in the power system. This article fully explores the differences and complementarities of various types of wind-solar-hydrothermal-storage power sources, a hierarchical environmental and economic dispatch model for the power system has been established. Among them, the upper level model takes the flexible consumption of new energy as the optimization goal, the middle level model uses a combination of hydropower station and energy storage to minimizes the fluctuation variance and peak-to-valley difference of the net load curve, the lower level model aims to achieve optimal environmental and economic benefits of the power system, comprehensively considers the coal consumption cost, startup and shutdown cost, energy storage operation cost, and pollutant emissions of thermal power units, determines the startup and shutdown mode and output power of thermal power units. Finally, an improved IEEE 6-machine 30-node system is used as an example for simulation analysis, the results show that after applying the proposed hierarchical environmental and economic dispatch strategy of the power system, the fluctuation variance and the peak-to-valley difference of the net load curve have been reduced by 46.3% and 31.5%, respectively, and the environmental and economic benefits of the system is improved by 5.1% compared with the traditional economic dispatch strategy. It can meet the requirements of energy system cleaning and decarbonization while improving the operation economy, which verifies the effectiveness of the proposed environmental economic dispatch model. [ABSTRACT FROM AUTHOR]

With the progress of communication technology, the cost of optical fiber and 5G continues to decrease, and data transmission becomes more convenient and fast, making it possible to realize differential protection of distribution network by various intelligent algorithms using signal waveforms. Aiming at the problem that the traditional relay protection device can not meet the actual demand when the single-phase ground fault occurs in the distribution network with distributed generation, this paper proposes a new differential protection scheme. The characteristic mode decomposition improved by the whale optimization algorithm is used to decompose the zero-sequence current waveform collected at both ends of the line. Based on the basic principle of current differential protection, the derivative dynamic time warping of the component with the largest fault feature can effectively solve the problem that the grounding current of the distribution network cannot meet the working requirements of the differential protection device, and ensure the safe and stable operation of the system. Finally, based on MATLAB software, the performance of this method is comprehensively evaluated by simulating different fault conditions, so as to ensure the feasibility and accuracy of this method in the case of diversified faults when the distributed generation is used as part of the power supply. [ABSTRACT FROM AUTHOR]

Microgrids are becoming a realistic choice for residential buildings due to the increasing need for affordable and sustainable energy solutions in developing nations. Through modeling and simulation, the main goal is to evaluate the viability and performance of a solar microgrid system. Residential load modeling is used, which is vital to developing an effective Energy Management System (EMS) for the microgrid. A residential household's load metering data is examined using statistical methods, including time series and regression analysis. For the residential community load in this research, Proportional-Integral-Derivative (PID) controllers and Fuzzy Logic Controllers (FLC) are used to generate the necessary Direct Current (DC) microgrid voltage. The simulation research shows that FLC have benefits over PID controllers. The FLC technique performs better at reducing total harmonic distortion, which improves the microgrid system's overall power quality. The Seasonal Autoregressive Integrated Moving Average (SARIMA) model was found to be the most appropriate and reliable model for the dataset after the performance of the models was evaluated using the metrics. The optimization results also showed that FLC optimization improves the microgrid system's stability. The exponential Gaussian process regression (GPR) produced the highest R-squared measure of 0.49 and RSME measure of 7.9646, making it the best goodness fit for modeling the total daily energy usage and the peak daily usage. [ABSTRACT FROM AUTHOR]

Accurate wind power forecasting is essential for both optimal grid scheduling and the massive absorption of wind power into the grid. However, the continuous changes in the contribution of various meteorological features to the forecasting of wind power output under different time or weather conditions, and the overlapping of wind power sequence cycles, make forecasting challenging. To address these problems, a short-term wind power forecasting model is established that integrates a gated recurrent unit (GRU) network with a dual attention mechanism (DAM). To compute the contributions of different features in real time, historical wind power data and meteorological information are first extracted using a feature attention mechanism (FAM). The feature sequences collected by the FAM are then used by the GRU network for preliminary forecasting. Subsequently, one-dimensional convolution employing several distinct convolution kernels is used to filter the GRU outputs. In addition, a multi-head time attention mechanism (MHTAM) is proposed and a Gaussian bias is introduced to assign different weights to different time steps of each modality. The final forecast results are produced by combining the outputs of the MHTAM. The results of the simulation experiment show that for 5-h, 10-h, and 20-h short-term wind power forecasting, the establishedÁ DAM-GRU model performs better than comparative models on the basis of Root Mean Square Error (RMSE), Mean Absolute Error (MAE), R-squared (R2), Square sum error (SSE), Mean absolute percentile error (MAPE), and Relative root mean square error (RRMSE) index. [ABSTRACT FROM AUTHOR]

The calculation method of the external fault short-circuit current of large units with clear mechanisms and practicality is of great value in engineering practice. Due to the special AC excitation structure and control mode, the external fault short-circuit characteristics of variable-speed pumped storage units (VSPSUs) are very different from those of conventional units. Therefore, this paper proposes a calculation method for external fault short-circuit current based on a time-domain dynamic circuit. According to the excitation and control characteristics of VSPSUs under external fault, the VSPSU under external fault is divided into two cases: continuous excitation and jumper action. Based on space vector analysis, the time-domain dynamic circuit models are established, respectively. On this basis, the analytical formula of the external fault short-circuit current of VSPSUs is derived by combining the transition boundary conditions of the two cases and the dynamic characteristics of the stator flux linkage. Finally, the comparison with PSCAD/EMTDC simulation results shows that the proposed VSPSUs' external fault short-circuit current calculation method has high accuracy and practical value, which can meet the needs of primary equipment selection and relay protection of variable-speed pumped storage power plants. [ABSTRACT FROM AUTHOR]

Controlling variable speed wind turbines during transient state is challenging. The use of variable speed wind turbines based on permanent magnet synchronous generator (PMSG) is on the rise due to some of the features of the wind turbine. According to the grid code requirements, grid connected wind turbine systems should achieve active power control and provide low voltage ride through (LVRT) capability. Thus, the primary target of the wind turbine control system is to keep the turbine connected to the grid during grid disturbances or failures. In this article, the Series Dynamic Braking Resistor (SDBR), and the Bridge fault current limiter (BFCL) were used to improve the LVRT of PMSG wind turbines. The topology of the PMSG grid side voltage source converter, with the SDBR and BFCL, was modeled during steady and transient states. The performance of both schemes on the PMSG was analyzed and compared during severe balanced fault scenario. In addition, a scenario without any of the schemes was also considered. For fair comparison, the PMSG wind turbine was operating at its rated speed during the low voltage and the same conditions of operation were used for all the considered scenarios. The study was done using Power System Computer Aided Design and Electromagnetic Transient Including DC. [ABSTRACT FROM AUTHOR]