The fifth-generation cellular networks (5G)has been proposed as a solution for the accelerating growth in data traffic. As part of 5G, millimetre-wave (mmWave) is suggested as one of the potential spectrum candidates due to the vastly available bandwidth. Accordingly, both indoor and outdoor propagation measurements on mmWave have been widely conducted over the recent years. These field measurements were heavily dependent on utilizing expensive channel-sounders and tools.

Photovoltaic (PV) power generation forecasting is an important topic in field of power system, energy conversion and smart grid construction. The PV power generation has the properties of randomness and volatility is due to the variability of solar irradiance, temperature and other meteorological factors. In order to reduce the volatility, accurate PV power generation forecasting techniques are demanded.

RSSI-Dataset

The RSSI-Dataset provides a comprehensive set of Received Signal Strength Indication (RSSI) readings from within two indoor office buildings. Four wireless technologies were used:

• Zigbee (IEEE 802.15.4),
• WiFi (IEEE 802. 11),
• Bluetooth Low Energy (BLE) and
• Long Range Area-Wide Network (LoRaWAN).

For experimentation Arduinos Raspberry Pi, XBees, Gimbal beacons Series 10 and Dragino LoRa Shield were also used.  

These data are the input data of the simulation for the paper "Studies on Robust Parameter Identification Methods for Distribution Line Based on Micro-PMU".

This is the data for the grounding current of a radial structured distribution network, when subject to a single-phase earth fault.

Research on Optimizing the Integration of Renewable Energy Sources into the Electrical Power Systems

In this project one model the photovoltaic and wind power sources in order to analyze how to optimally integrate them in the electrical power systems. Integration requirements like transient regimes associated with fault occurrence, identification of the electrical power systems responsible for disturbances, and optimization of the integration are focus points of the research.

This is the Smulation Data for Power System State Estimation.

This dataset contains the numerical results and Excel graphing used to create the results images in the main paper.

Advances in Wireless Sensor Network Technology (WSN) have provided the availability of small and low-cost sensor with capability of sensing various types of physical and environmental conditions, data processing and wireless communication. In WSN, the sensor nodes have a limited transmission range, and their processing and storage capabilities as well as their energy resources are limited. Triple Umpiring System (TUS) has already been proved its better performance on Wireless Sensor Networks. Clustering technique provides an effective way to prolong the lifetime of WSN.

This work presents a novel Anti-Islanding (AI) protection of Photovoltaic (PV) Systems based on monitoring the dc-link voltage of the PV inverter. A PV System equipped with AI protection like frequency relays, a rate of change of frequency (ROCOF) relay, and respectively the proposed dc-link voltage relay is simulated under the conditions of islanding and the detection time for all these AI techniques are compared. The study shows under which conditions our proposed dc-link voltage AI relay is the most efficient.