Marco Adonis

Electric power distribution systems have been undergoing a transformation that can be attributed to factors such as the deregulation of the electric power supply industry, growing public concern over energy security and the environmental impact of energy generation and utilization, and technological advancements that have given impetus to concerted efforts to modernize the power grid in the framework of smart grid initiatives. The traditionally passive distribution network is increasingly becoming active due to the steady increase in the amount of distributed energy resources being integrated into the network. This has, in turn, given rise to a higher need for flexibility resources that can be used to handle the increased uncertainty caused by stochastic and intermittent distributed resources, such as variable renewable power generation. The provision of demand-side flexibility has largely been the purview of large industrial and commercial energy consumers. This article discusses the role that the aggregator can play in facilitating the provision of flexibility resources by small-scale consumers and prosumers and presents a case study on small-scale renewable generation and residential demand forecasting, which form an integral part of demand flexibility aggregation.

Voltage source converters (VSCs) have emerged as the key components in modern power systems, facilitating efficient energy conversion and flexible power flow control. Understanding the fundamental circuit model of VSCs is essential for their accurate modeling and analysis in power system studies. A basic voltage source converter circuit model connected to an LC filter is essential because it lowers the harmonic distortions and enhances the overall power quality of the micro-grid. This guarantees a clean and steady power supply, which is necessary for the integration of multiple renewable energy sources and sensitive loads. A comprehensive methodology for developing a basic circuit model of VSCs, focusing on the key components and principals involved, is presented in this paper. The methodology includes the modeling of space vector pulse-width modulation (SVPWM) as well as the direct quadrature zero synchronous reference frame. Different design controls, including the design of current control loop in the S-domain, the design of the direct current (DC) bus voltage control loop in the S-domain, and the design of the alternating current (AC) voltage control loop in the S-domain, are explored to capture the dynamic behavior and control strategies of VSCs accurately. The proposed methodology provides a systematic framework for modeling VSCs, enabling engineers and researchers to analyze their performance and assess their impact on power system stability and operation. Future studies can be conducted by using case studies and simulation scenarios to show the efficiency and applicability of the developed models in analyzing VSC-based power electronics applications, including high-voltage direct current (HVDC) transmission systems and flexible alternating current transmission systems (FACTS). The significance of this work lies in its potential to advance the understanding and application of VSCs, contributing to more resilient and efficient power systems. By providing a solid foundation for future research and development, this study supports the ongoing integration of renewable energy sources and the advancement of modern electrical infrastructure.

This paper presents an energy management strategy using a Stateflow controller related to DC microgrids with the important penetration of renewable energy. The increase in world electricity demand is one of the principal drivers of the exhaustion of fossil fuels and increased greenhouse gas emissions. To solve these problems, several countries have adopted actions for widespread renewable energy deployment, which includes wind energy, solar power, biomass power, tidal, and hydropower. These sources are considered as significant in delivering clean energy and reducing greenhouse gas emissions for sustainable improvement. As these sources play an increasingly vital role in the global energy landscape, the efficient management of these intermittent sources is essential for grid stability and sustainability. This paper aimed to develop an energy management strategy for DC microgrids to supply power to a DC microgrid system. The main objective of this paper was to implement an energy management system to ensure the proper operation of DC microgrid systems utilizing Simulink blocks available in MATLAB/Simulink 2020b software. The simulation results demonstrated that the developed energy management algorithm was unconditionally reliable, ensuring the proper operation of the microgrid systems. Additionally, the results demonstrated that the energy management strategy exhibited robust performance across different scenarios, effectively balancing energy generation and consumption while ensuring the reliable operation of the microgrid system. Moreover, the developed algorithm model presents another advantage, as it enables users to access and to change any control parameters within the DC microgrid. By comparing these results with the literature, the developed energy management algorithm provides safety and the automatic control of the microgrid.

In recent years, energy challenges such as grid congestion and imbalances have emerged from conventional electric grids. Furthermore, the unpredictable nature of these systems poses many challenges in meeting various users’ demands. The Battery Energy Storage System is a potential key for grid instability with improved power quality. The present study investigates the global trend towards integrating battery technology as an energy storage system with renewable energy production and utility grid systems. An extensive review of battery systems such as Lithium-Ion, Lead–Acid, Zinc–Bromide, Nickel–Cadmium, Sodium–Sulphur, and the Vanadium redox flow battery is conducted. Furthermore, a comparative analysis of their working principles, control strategies, optimizations, and technical characteristics is presented. The review findings show that Lead–Acid, Lithium-Ion, Sodium-based, and flow redox batteries have seen increased breakthroughs in the energy storage market. Furthermore, the use of the BESS as an ancillary service and control technique enhances the performance of microgrids and utility grid systems. These control techniques provide potential solutions such as peak load shaving, the smoothing of photovoltaic ramp rates, voltage fluctuation reduction, a large grid, power supply backup, microgrids, renewable energy sources time shift, spinning reserve for industrial consumers, and frequency regulation. Conclusively, a cost summary of the various battery technologies is presented.

This paper introduces an energy management strategy for a hybrid renewable micro-grid system. The efficient operation of a hybrid renewable micro-grid system requires an advanced energy management strategy able to coordinate the complex interactions between different energy sources and loads. This strategy must consider some factors such as weather fluctuations and demand variations. Its significance lies in achieving the overarching objectives of these systems, including optimizing renewable energy utilization, reducing greenhouse gas emissions, promoting energy independence, and ensuring grid resilience. The intermittent nature of renewable sources necessitates a predictive approach that anticipates the energy availability and adjusts the system operation. The aim of this study was to develop an energy management system for a hybrid renewable micro-grid system to optimize the deployment of renewable energy resources and increase their integration in the power system. Therefore, the main objective of this work was to develop an energy management strategy that controls the flow of energy between the hybrid micro-grid system and the load connected directly as well as the load connected to the utility grid using MATLAB/Simulink software. The second objective was to control the charging and discharging of the battery. The results show that the developed algorithm was able to control the energy flow between the hybrid micro-grid system and the utility grid and also to ensure a proper relation between the charging /discharging rate of the battery based on their operating conditions. In this application, the battery was charged at higher power. It was seen that a higher charging power enables to fully recharge the battery in a shorter amount of time than usual. The results have shown that it is possible to maximize the charging time by using a greater power and this algorithm ensures the state of charge (SOC) of battery to remain in the admissible limits (between 20 and 100%).

Synchronous generators provide an inherent inertial response to frequency deviations because of their huge revolving mass that is electro-mechanically tied to the electrical network. Contrariwise, the power converters isolate the revolving mass of variable-speed wind turbines from the electric network. Therefore, they are not able to provide an inherent inertial reaction to frequency events on the electric network. This reduces the effective network inertia, which is essential for marinating the power system’s frequency. To address this problem in cases of using a wind energy doubly fed induction generator, this study introduces a kinetic energy recovery controller to the rotor-side converter.

This paper presents an energy management strategy for hybrid renewable micro-grid system. The optimal operation of a hybrid renewable micro-grid system necessitates a sophisticated energy management strategy that can orchestrate the intricate interplay of diverse energy sources and loads while considering factors such as weather variability, demand fluctuations, and equipment limitations. This strategy is crucial in achieving the overarching goals of such systems: maximizing renewable energy utilization, minimizing greenhouse gas emissions, enhancing energy independence, and ensuring grid resilience. Furthermore, the intermittent and weather-dependent nature of renewable sources necessitates a predictive approach that anticipates energy availability and adapts the operation of the system accordingly. The aim of this study was to develop an energy management system for a hybrid renewable micro-grid system to optimize the deployment of renewable energy resources and increase their integration in the power system. Therefore, the main objective of this proposed work was to develop an energy management strategy that controls the flow of energy between the hybrid micro-grid system and the load connected directly as well as the load connected to the utility grid using MATLAB/Simulink software. The second objective was to control the charging and discharging of the battery energy storage. The results show that the developed algorithm was able to control the energy flow between the hybrid micro-grid system and the variable AC load directly connected as well as connected to the utility grid and also to ensure a proper relation between the charging / discharging rate of the battery energy storage system based on their operating conditions and finally, it ensured the SOC of battery remained in the admissible limits (between 20% and 100%).

This paper presents an energy management strategy using stateflow controller related to DC micro-grids with an important penetration of renewable energy. The increase in world electricity demand is one of the principal drivers of the exhaustion of fossil fuels and expanded greenhouse gas emissions. To solve these problems, several countries have adopted actions for large renewable energy deployment, which includes wind energy, solar power, biomass power, tidal, and hydropower. These sources are considered as significant in delivering clean energy and reducing greenhouse gas emissions for sustainable improvement. In such a case, these are referred to as distributed generation systems. Distributed generation can impact negatively on the performance of the distribution network as the distribution network will no longer operate with a unidirectional power flow pattern. To address these issues, micro-grids are being used as a platform to integrate distributed generation systems, as they provide significant benefits to end-users and to the distribution network. The objective of this paper was to implement an energy management system to ensure the proper operation of the developed DC microgrid and this was developed using Simulink blocks available in the MATLAB/Simulink software. The simulation results shown that this control strategy is unconditionally reliable to ensure proper operation of the microgrid systems. Moreover, the developed algorithm model presents another advantage, which enables the users to access and to change any control parameters within the DC microgrid. By comparing these results with the literature, the developed energy management algorithm provides safety and automatic control of the microgrid.

Vigilant fault diagnosis and preventive maintenance has the potential to significantly decrease costs associated with wind generators. As wind energy continues the upward growth in technology and continued worldwide adoption and implementation, the application of fault diagnosis techniques will become more imperative. Fault diagnosis and preventive maintenance techniques for wind turbine generators are still at an early stage compared to matured strategies used for generators in conventional power plants. The cost of wind energy can be further reduced if failures are predicted in advance of a major structural failure, which leads to less unplanned maintenance. High maintenance cost of wind turbines means that predictive strategies like fault diagnosis and preventive maintenance techniques are necessary to manage life cycle costs of critical components. Squirrel-Cage Induction Generators (SCIG) are the prevailing generator type and are more robust and cheaper to manufacturer compared to other generator types used in wind turbines. A statistical model was developed using SCADA data to estimate the relationships between winding temperatures and other variables. Predicting faults in stator windings are challenging because the unhealthy condition rapidly evolves into a functional failure.