Current Harmonic Aggregation Cases for Contemporary Loads

Power electronic circuits in modern power supplies have improved the conversion efficiency on the one hand but have also increased harmonic emissions. Harmonic currents from the operation of these units affect the voltage waveforms of the network and could compromise the reliability of the network. Load and source non-linearity can, therefore, limit the renewable source’s hosting capacity in the grid, as a large number of inverter units may increase the harmonic distortions. As a result, voltage and current distortions could reach unbearable levels in devices connected to the network. Harmonic estimation modelling often relies on measurement data, and differences may appear in mathematical simulations as the harmonic aggregation or cancellation may generate different results due to the inaccuracies and limitations of the measurement device. In this paper, the effect of harmonic currents cancellation on the aggregation of different load currents is evaluated to show its impact in the network by presenting a comparison between the measurement and mathematical aggregation of harmonics. Furthermore, the harmonic cancellation phenomenon is also qualified for multiple loads connected to the power supply.

Analisis Pengaruh Penambahan Penyulang Dan Pemisahan Beban Terhadap Susut Daya Menggunakan Metode Simple Branch Exchange (Studi Kasus PT PLN ULP Lima Puluh, Sumatera Utara)

During the distribution process there will be a loss of some of the energy that is channeled. This phenomenon is known as losses. This is caused by technical and non-technical factors. In the State Electricity Service (PLN) system, distribution losses or energy losses is calculated by measuring the difference between kWh produced and kWh sell. This kWh difference is the electrical energy lost during the starting process from the generation or secondary side of the Substation to customers’ APP. Cumulatively, the amount of kWh at all base sources is 73,769.524 kWh while the distribution loss that occurs in JTM is 5,835.008 or 7.91%. One way to overcome and minimize distribution losses in the 20 kV Procurement Service Unit (ULP) of Lima Puluh distribution system is to analyze the distribution network system, add new feeders and break the load on the electrical system. The simple branch exchange method is used to separate the network load, which is done by adding a switch by turning the on or off channel and searching for the configuration that produces the smallest power loss and calculating the power loss based on the network load. Based on the simulation results using the ETAP 12.6 software, the results of the energy loss of Procurement Service Unit (ULP) of Lima Puluh is 5,864,112 kWh then decreased after load separation of 4,341,348 kWh. The value of power loss before load separation is 1,955 kW and a decrease in power loss after load separation is 1,484.5 kW. The investment cost incurred for the construction of a new feeder is RP. 22,000,000,000,- with a payback of 9.9 years. Keywords: Feeder, Power Loss, Energy Loss, ETAP 12.6.

Is Synthetic The New Real? Performance Analysis of Time Series Generation Techniques with Focus on Network Load Forecasting

This paper explores whether Generative Adversarial Networks (GANs) can produce realistic network load data that can be utilized to train machine learning models in lieu of real data. In this regard, we evaluate the performance of three recent GAN architectures on the Telecom Italia data set across a set of qualitative and quantitative metrics. Our results show that GAN generated synthetic data is indeed similar to real data and forecasting models trained on this data achieve similar performance to those trained on real data.

Is Synthetic The New Real? Performance Analysis of Time Series Generation Techniques with Focus on Network Load Forecasting

This paper explores whether Generative Adversarial Networks (GANs) can produce realistic network load data that can be utilized to train machine learning models in lieu of real data. In this regard, we evaluate the performance of three recent GAN architectures on the Telecom Italia data set across a set of qualitative and quantitative metrics. Our results show that GAN generated synthetic data is indeed similar to real data and forecasting models trained on this data achieve similar performance to those trained on real data.

Optimization of Sports Event Management System Based on Wireless Sensor Network

In recent years, wireless sensor network technology has developed rapidly and its role in managing systems for sports events has been widely used. Wireless sensor networks not only have low wiring cost, high monitoring accuracy, and good fault tolerance but also can be monitored remotely and have outstanding advantages in fault diagnosis and safety monitoring. In this paper, firstly, the wireless sensor network hierarchical routing protocol is studied and its network model and workflow are analyzed; according to the energy consumption of the wireless sensor network, the selection method of the optimal number of cluster heads is proposed to analyze the advantages and disadvantages existing in the protocol. Secondly, the improvement of the routing protocol is proposed to address the problems of uneven distribution of cluster heads and cluster head election without considering the residual energy of nodes in the protocol. When dividing clusters, the number of neighboring nodes is considered so that cluster heads are distributed more evenly in the network; when electing cluster heads, the residual energy of nodes in the cluster is considered to balance the whole network load, and when electing cluster heads, the residual energy of nodes in the cluster is considered to balance the whole network load. Finally, simulation experiments are conducted in this paper using simulation software, and the simulation results show that the data fusion algorithm is more effective than the protocol in reducing the average energy consumption of nodes and extending the network lifetime; these features make wireless sensors more beneficial for better management of sporting events as well as better optimization.