Transformer-based correction scheme for short-term bus load prediction in holidays

To tackle the problem of inaccurate short-term bus load prediction,especially during holidays,a Transformer-based scheme with tailored architectural enhancements is proposed.First,the input data are clustered to reduce complexity and capture inherent characteristics more effectively.Gated residual connections are then employed to selectively propagate salient features across layers,while an attention mechanism focuses on identifying prominent patterns in multivariate time-series data.Ultimately,a pre-trained structure is incorporated to reduce computational complexity.Experimental results based on extensive data show that the proposed scheme achieves improved prediction accuracy over comparative algorithms by at least 32.00%consistently across all buses evaluated,and the fitting effect of holiday load curves is outstanding.Meanwhile,the pre-trained structure drastically reduces the training time of the proposed algorithm by more than 65.75%.The proposed scheme can efficiently predict bus load results while enhancing robustness for holiday predictions,making it better adapted to real-world prediction scenarios.

Investigating the Effects of Slack Bus Selection in Load Flow Studies: A Comparative Analysis of Robust and Weak Grids

Load flow studies play a critical role in the analysis of power systems. They enable the computation of voltage, current, and power flows in a power system. They provide valuable insights into the steady-state performance of the power system under different operating conditions. Choosing a slack bus is a vital step in conducting load flow simulations. A slack bus is a PV bus that includes a generator and is used to balance real and reactive power during load flow studies. Many studies have been conducted on the selection of slack buses in load flow analysis. However, varied conclusions regarding the impact on system losses and power flows were obtained during these studies. Therefore, using the IEEE-14 bus test system, this study investigated the effects of slack bus selection in strong and weak grids by alternating slack buses among PV buses and observing the effects on bus voltage magnitude, bus voltage phase angle, total power flows, and active and reactive power losses. The study noted that the effect of slack bus selection on these system quantities is contingent upon the voltage stability of the grid. Whereas in a robust grid, system losses and power flows remained constant irrespective of the choice of slack bus, a weak grid experienced some variations in these system quantities under similar circumstances. The simulation results led to the conclusion that, to a large extent, the voltage stability of the grid plays a significant role in determining the degree to which slack bus selection affects system losses and other quantities in load flow studies.

Load Dependent Series-Parallel Systems with Common Bus Performance Sharing Mechanism

A series-parallel system was proposed with common bus performance sharing in which the performance and failure rate of the element depended on the load it was carrying. In such a system,the surplus performance of a sub-system can be transmitted to other deficient sub-systems. The transmission capacity of the common bus performance sharing mechanism is a random variable. Effects of load on element performance and failure rate were considered in this paper. A reliability evaluation algorithm based on the universal generating function technique was suggested. Numerical experiments were conducted to illustrate the algorithm.

Analysis of the Load Flow Problem in Power System Planning Studies

Load flow is an important tool used by power engineers for planning, to determine the best operation for a power system and exchange of power between utility companies. In order to have an efficient operating power system, it is necessary to determine which method is suitable and efficient for the system’s load flow analysis. A power flow analysis method may take a long time and therefore prevent achieving an accurate result to a power flow solution because of continuous changes in power demand and generations. This paper presents analysis of the load flow problem in power system planning studies. The numerical methods: Gauss-Seidel, Newton-Raphson and Fast Decoupled methods were compared for a power flow analysis solution. Simulation is carried out using Matlab for test cases of IEEE 9-Bus, IEEE 30-Bus and IEEE 57-Bus system. The simulation results were compared for number of iteration, computational time, tolerance value and convergence. The compared results show that Newton-Raphson is the most reliable method because it has the least number of iteration and converges faster.

Analysis of Commutation Failure in Multi-Infeed HVDC System under Different Load Models

HVDC technology has been widely used in modern power system. On one hand, HVDC has the advantages of economy, high efficiency and strong controllability. While on the other hand, it makes the dynamic characteristics of the power system becoming more and more complex. That puts forward a new challenge to system stability and raises new questions for power system simulation. This paper focuses on the interaction between AC and DC systems, especially the problem of commutation failure caused by AC system fault. Based on the data of China Southern Power Grid, this paper calculates the fault regions that may cause commutation failure and calculates the system critical clearance time under different load models, analyzes the impacts of different load models on commutation failure and the stability of AC/DC hybrid system.

Balance control of grid currents for UPQC under unbalanced loads based on matching-ratio compensation algorithm

In three-phase four-wire systems, unbalanced loads can cause grid currents to be unbalanced, and this may cause the neutral point potential on the grid side to shift. The neutral point potential shift will worsen the control precision as well as the performance of the threephase four-wire unified power quality conditioner(UPQC),and it also leads to unbalanced three-phase output voltage,even causing damage to electric equipment. To deal with unbalanced loads, this paper proposes a matching-ratio compensation algorithm(MCA) for the fundamental active component of load currents, and by employing this MCA,balanced three-phase grid currents can be realized under 100% unbalanced loads. The steady-state fluctuation and the transient drop of the DC bus voltage can also be restrained. This paper establishes the mathematical model of the UPQC, analyzes the mechanism of the DC bus voltage fluctuations, and elaborates the interaction between unbalanced grid currents and DC bus voltage fluctuations;two control strategies of UPQC under three-phase stationary coordinate based on the MCA are given, and finally, the feasibility and effectiveness of the proposed control strategy are verified by experiment results.

Frontier of continuous structural health monitoring system for short&medium span bridges and condition assessment

It is becoming an important social problem to make maintenance and rehabilitation of existing short and medium span(10-20 m)bridges because there are a huge amount of short and medium span bridges in service in the world.The kernel of such bridge management is to develop a method of safety(condition)assessment on items which include remaining life and load carrying capacity.Bridge health monitoring using information technology and sensors is capable of providing more accurate knowledge of bridge performance than traditional strategies.The aim of this paper is to introduce a state-of-the-art on not only a rational bridge health monitoring system incorporating with the information and communication technologies for lifetime management of existing short and medium span bridges but also a continuous data collecting system designed for bridge health monitoring of mainly short and medium span bridges.In this paper,although there are some useful monitoring methods for short and medium span bridges based on the qualitative or quantitative information,mainly two advanced structural health monitoring systems are described to review and analyse the potential of utilizing the long term health monitoring in safety assessment and management issues for short and medium span bridge.The first is a special designed mobile in-situ loading device(vehicle)for short and medium span road bridges to assess the structural safety(performance)and derive optimal strategies for maintenance using reliability based method.The second is a long term health monitoring method by using the public buses as part of a public transit system(called bus monitoring system)to be applied mainly to short and medium span bridges,along with safety indices,namely,"characteristic deflection"which is relatively free from the influence of dynamic disturbances due to such factors as the roughness of the road surface,and a structural anomaly parameter.

Optimal location of interline power flow controller for controlling multi transmission line： A new integrated technique

In this paper, an interline power flow controller （IPFC） is used for controlling multi transmission lines. However, the optimal placement of IPFC in the transmis-sion line is a major problem. Thus, we use a combination of tabu search （TS） algorithm and artificial neural network （ANN） in the proposed method to find out the best placement locations for IPFC in a given multi transmission line system. TS algorithm is an optimization algorithm and we use it in the proposed method to determine the optimum bus combination using line data. Then, using the optimum bus combination, the neural network is trained to find out the best placement locations for IPFC. Finally, IPFC is connected at the best locations indicated by the neural network. Furthermore, using Newton-Raphson load flow algorithm, the transmission line loss of the IPFC connected bus is analyzed. The proposed methodology is implemen- ted in MATLAB working platform and tested on the IEEE-14 bus system. The output is compared with the genetic algorithm （GA） and general load flow analysis. The results are validated with Levenberg-Marquardt back propagation and gradient descent with momentum network training algorithm.