High penetration of distributed generation and renewable energy sources in power systems has created control challenges in the network, which requires the coordinated management of these resources. Using virtual power plants (VPPs) on a large scale has solved these challenges to a significant extent. VPPs can be considered systems consisting of distributed generations, energy storage, controllable loads, electric vehicles (EVs), and other types of resources to provide energy and ancillary services. VPPs face various challenges such as energy management, operation, resource uncertainty, participation in electricity markets, etc. This paper discusses an overview of the basic challenges of VPPs, including control and communication issues, electricity markets, its different models, and energy management issues. The main purpose is to investigate the performance of VPP in different markets, energy management of VPP in different operating conditions and strategies, and compare different planning methods for VPP. Note that the application of blockchain to control and improve VPP performance has been investigated, taking into account the different layers of this technology.

The ultra-high voltage gain DC-DC converters are extremely required because of the low voltage level of many non-polluting power resources. This paper proposes an ultra-high voltage gain converter based on interleave technique and using three-winding coupled inductor and voltage multiplier cell. The interleave technique is useful for reducing the size of the filter components. In the proposed converter, high voltage gain is achieved without extreme duty cycle of solid-state switches. The voltage stress across the semiconductor devices can be reduced by increasing the turn ratio of the secondary of the coupled inductors. In addition, because of the implementation of the interleave structure, peak to peak variation of main input current and switching losses are substantially reduced. The steady state principles of proposed converter in continues conduction mode operation is given. Also, design equations is presented. Validity and performance of the proposed converter is surveyed by simulation and experimental results of an 120W prototype.

Partial Discharge (PD) is one of the symptoms of an electrical insulation problem, and its permanence can lead to the complete deterioration of the electrical insulation in high-voltage equipment such as power transformers. The acoustic emission (AE) method is a well-known technique used to detect and localize PD activity inside oil-filled transformers. However, the commercially available monitoring systems based on acoustic sensors still have a high cost. This paper analyses the ability of low-cost piezoelectric sensors to identify PDs within oil-filled power transformers. To this end, two types of low-cost piezoelectric sensors were fully investigated using time-domain, frequency-domain, and time-frequency analysis, separately. Thereafter, the effectiveness of these sensors for PD detection and monitoring was studied. A three-phase distribution transformer filled with oil was examined. PDs were produced inside an oil-immersed transformer by applying a high voltage over two copper electrodes, and the AE sensors were coupled to the housing of the transformer. By extracting typical features from the AE signals, the PD signals were differentiated from on-site noise and interference. The AE signals were analyzed using acoustic signal metrics such as peak value, energy criterion, and other statistical parameters. The obtained results indicated that the used low-cost piezoelectric sensors have the capability of PD monitoring within power transformers.

This paper addresses the localization of Partial Discharge through a 3D Finite Element Method analysis of acoustic wave propagation inside a 3-phase 35kV transformer with the help of COMSOL Multiphysics software. Due to the complexity inside transformers, acoustic waves generated by PDs cannot simply be detected with typical acoustic sensors, especially when PDs happen inside inner windings. These waves are distorted and attenuated along with their propagation. The type, number, and position of sensors are essential factors in PD localization inside a transformer. A new installation arrangement of fiber-optic acoustic sensors inside the transformers is proposed with this information. This array of acoustic sensors has significant effects on PD localization accuracy and has immunity from on-site noise and interference; more importantly, they can be installed after transformer manufacturing. They are reachable if needed to be repaired or replaced. Several numerical studies have been carried out considering different PD source positions, and the Levenberge-Marquardt algorithm is employed for solving localization equations.