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The hybrid microgrid (HMG) is an arrangement for empowering the society by using the renewable energy sources (RESs) connected with common DC bus terminal. The effective operation of the HMG relies on the transient response of the DC bus as well as the stability of the system state that may change due to the stochastic behavior of RESs and industrial loads. This work is motivated to develop a two‐level decentralized control strategy consisting of a non‐linear and linear control scheme to augment the transient stability and tracking performance of an HMG. Firstly, a non‐linear partial feedback linearization control framework combined with a PI regulator (PFLC‐PI) is designed for the transient stability enhancement of the common bus. Secondly, a linear unified controller (UC) is developed to guarantee the constant load voltages over the industrial loads through the control of the load‐side inverter. The UC effectiveness is measured by varying the load parameters associated with single‐ and three‐phase load networks. The obtained results are then compared with the existing controllers to guarantee the augmented performance of proposed two‐level controller. Additionally, an external parametric uncertainty is intentionally added to the single‐phase load network dynamics and studied to ensure the robustness of the controller. [ABSTRACT FROM AUTHOR]

Renewable energy (RE) sources play an important role that not only reduces the pressure on fossil fuels but also produces safe and clean energy by developing the microgrid (MG) technology that fulfills the excess demand for power throughout the world. The technological development and the blessing of information and communication technology converts the MG technology to a smarter one, termed as smart grid (SG) and virtual power plant, by establishing a two‐way communication between the consumers and service provider with the aid of smart metering infrastructure, dynamic pricing scheme, energy management system, smart transmission and distribution system. The transformation of the traditional power system to SG enhances the efficiency, flexibility, resiliency, and robustness of the power system due to the increasing level of cyber security and automation. A directional pathway from conventional to smart power system has been carried out in this paper by addressing the present status of the power system, challenges during the operations, and possible solutions. Initially, the control operation of MG with RE and energy storage system has been investigated which is essential to understand the operation complexity and challenges due to the variable nature of the RE, load dynamics, and uncertainties. But the facilities of end‐user feedback, dynamic pricing scheme, cyber security, and smart metering system are not present in MG technology that hampers the proper regulation of controlling operation, generating and distributing energy as well as energy losses. The development of SG with smart technologies overcomes these problems by proper controlling of power usage. Finally, this paper provides a path to move the MG toward SG by analyzing the technical and critical challenges of smart devices, equipment integration, and their control issues and provides possible solutions to overcome the integration and control challenges for a reliable and sustainable operation. [ABSTRACT FROM AUTHOR]

The reliable operation of power systems becomes a formidable job these days due to the high amount of complexities in the expanded power system networks. The power system networks often comprise microgrids that encounter over 80% of faults due to their exposure to unpredictable weather conditions, which reduce the insulation strength of the conductors which damaged the distribution system. Therefore, detection, classification, and location of such faults in the distributing systems are a must to ensure the flawless operation of the power systems. Machine learning methodologies are getting more attention to detect these types of faults due to their capability to handle complex fault information. Nevertheless, the obstacles are even now on the board as the traditional machine learning techniques rely on oversimplified frameworks that are incapable of analyzing a wide range of latent and explicit parameters and are also time-consuming. In this work, a unique defect diagnosis technique based on a multiblock deep belief network (DBN) and the fundamental discrete wavelet transform (DWT) is proposed, allowing the architecture to identify the deterministic reconstructing throughout its inputs. This method enables a strong multilevel generative network to utilize fault-related properties, decodes high variability functionalities, and requires minimal previous knowledge. The suggested approach is validated using a wide set of input data at various sampling frequencies. To evaluate the efficiency of DBN, a benchmark methodology based on the International Electrotechnical Commission (IEC) standard was used. White Gaussian Noise (WGN) was also implemented to test the envisioned network's resilience. The findings show that the approach is capable of executing exact diagnosis procedures. [ABSTRACT FROM AUTHOR]

This paper describes the usefulness of renewable energy throughout the world to generate power. Renewable energy adds a remarkable scope in power system. Renewable energy sources act as the prime mover of a microgrid. The Microgrid is a small network of power system with distributed generation (DG) units connected in parallel. The integration challenges of renewable energy sources and the control of microgrid are described in this paper. The varied nature of DG system produces voltage and frequency deviation. The unknown nature of the load produces un-modeled dynamics. This un-modeled dynamic introduces measurable effects on the performance of the microgrid. This paper investigates the performance of the microgrid against different scenarios. The voltage of the microgrid is controlled by using different controllers and their results are also investigated. The performance of controllers is investigated using MATLAB/Simulink SimPowerSystems. [ABSTRACT FROM AUTHOR]

• Microgrid is a small grid that uses renewable energy sources to generate power. • Performance of microgrid may deteriorate due to the uncertainty in load dynamics. • A controller is proposed to control the voltage, current and power of a microgrid. • The controller is designed for both single and three phase islanded microgrid. • Performance of the controller is measured and compared against various loads. Future grids will consist of many small and large microgrids that will require complex control of grid interaction as well as islanding operation. This paper addresses the control of islanded microgrids under dynamic system conditions. In this paper, a robust model reference modified adaptive proportional integral derivative (PID) controller is designed for voltage and current control augmentation of islanded microgrid against various load dynamics. The variation of load dynamics may cause the unsafe operation of the microgrid. The objective of the designed controller is to confirm the safe operation against voltage and current control under different load dynamics. The controller is designed based on selecting the desired reference model and controlling parameters. The effectiveness of the proposed controller is evaluated against the presence of load dynamics, harmonic sources, asynchronous machines, nonlinear and unknown loads. The results show that the proposed controller is capable of providing high tracking performance and safe operation for both the single and three phase islanded microgrid system. [ABSTRACT FROM AUTHOR]