Integration Of Microgrids Research Articles

Multi-source and Multi-level Coordination of Energy Internet under V2G based on Particle Swarm Optimization Algorithm

In order to effectively improve the excessive load of microgrid during peak hours of urban electricity consumption, a multi-source and multi-level coordination method of energy Internet under V2G based on particle swarm optimization algorithm was proposed. First, a mathematical model for V2G energy integration in microgrids was developed and a scheduling concept based on a particle-by-particle optimization algorithm was used. Second, an improved PSO algorithm is proposed and experimentally validated, and the experimental results are compared with previous particle swarm optimization algorithms. Experiments have shown that as the number of iterations increases, the value of the objective function decreases and the optimal solution can be obtained until the maximum number of iterations is reached. The iteration speed and power processing cost of the improved PSO algorithm are better than before.The original load curve is the load trough period from 23:00 to 6:00, and two load peaks occur from 12:00 to 14:00 and 19:00 to 22:00. The V2G technology basically realizes the coordinated control of microgrid electric energy and achieves the effect of peaking and valley filling. The improved algorithm has obvious improvement compared with the original power grid state. Conclusion: The application of EV V2G technology can smooth the daily load curve of power grid and coordinate the electric energy of micro-grid to achieve ``peak cutting and valley filling'', and the effect of this algorithm is more outstanding than the previous algorithm. Finally, the future development direction and suggestions of V2G technology are put forward.The power grid with V2G discharge depth limit has the ability to basically reduce and eliminate the daily peak load, so the technology has broad research space and development prospects.

Optimizing wind turbine integration in microgrids through enhanced multi-control of energy storage and micro-resources for enhanced stability

This paper explores the integration of microgrids with wind turbines to optimize electricity generation and enhance dispatch to distribution networks. The focus lies on a comprehensive examination of the microgrid configuration linked to a wind turbine, encompassing aspects such as the wind power generation system, variable-speed wind energy determination, fault estimation for stability analysis, and control through fault detection. Microgrid instability during network faults, attributed to limited capacity, is a primary challenge addressed in this study. The use of electronic interface power in islanded mode encounters hurdles due to the insufficient capacity of dispersed generation sources, leading to a slow response to load changes and difficulty in maintaining stability. To address these challenges, a novel microgrid topology and control method are introduced, featuring the integration of a battery to mitigate the slow response of micro-sources to load changes. Additionally, the concept of droop control is elucidated to effectively balance generation and consumption in islanded mode. The proposed approach employs fuzzy logic control systems along with a developed Kalman filter to precisely identify fault areas for stability analysis. Simulation results presented in this paper showcase substantial improvements in fault estimation, stability analysis, and various evaluation criteria. The abstract concludes by highlighting the keywords relevant to the study, emphasizing the significance of microgrids, energy storage systems, power converters, droop control, multiple control, and dynamic stability. In summary, this paper contributes to the discourse on renewable energy systems by presenting a comprehensive investigation into the integration of microgrids with wind turbines, offering valuable insights into improving stability, fault detection, and overall performance.

A two‐stage, four‐layer robust optimisation model for distributed cooperation in multi‐microgrids

AbstractAs the integration of microgrids (MG) and energy storage continues to grow, the need for efficient distributed cooperation between MGs and common energy storage (CES) becomes paramount. A robust optimisation model for the distributed cooperation of MG‐CES is presented, taking into account distributed generation under uncertainty. The proposed model follows a two‐stage, four‐layer ‘min‐min‐max‐min’ structure. In the first stage, the initial layer ‘min’ addresses the distributed cooperation problem between MG and CES, while the second stage employs ‘min‐max‐min’ to optimise the scheduling of MG. To enhance the solution process and expedite convergence, the authors introduce a column‐constrained generation algorithm with alternating iterations of U and D variables (CCG‐UD) specifically designed for the three‐layer structure in the second stage. This algorithm effectively decouples subproblems, contributing to accelerated solutions. To tackle the convergence challenges posed by the non‐convex MG‐CES model, the authors integrate the Bregman alternating direction method with multipliers (BADMM) with CCG‐UD in the final solution step. Real case tests are conducted using three zone‐level MGs to validate the efficacy of the proposed model and methodology. The results demonstrate the practical utility and efficiency of the developed approach in addressing distributed cooperation challenges in microgrid systems with energy storage.

Power Quality Acquire of Intelligent Controller based Superior Gain Re-Lift Luo Converter Intended for PV Linked Microgrid Integration

Power converters-based renewable energy sources such as photovoltaic (PV) and wind energy are more popular for residential and commercial applications. Because, of their eco friendlessness and cost effective operation. A Re-Lift Luo Converter integrated with renewable sources to the utility microgrid along with Intelligent Controller strategies is proposed. The solar photovoltaic system provides voltage to the inverter through a Re-lift Luo converter. The Bidirectional Battery converter along with battery system is used to achieve energy control management for the proposed system. In this paper the grid synchronization with DSTATCOM devices controlled by PI controller with D-Q theory transformation is achieved. Under this work, DSTATCOM has been used to improve the power quality under different loading conditions. The LC filter is employed to develop the output of the inverter. The input of the PV and battery systems are DC bus power source, as well as AC power injected into the grid network. The obtained results indicate that proposed approach delivers better performance with superior efficiency and nominal harmonics. The entire proposed system is validated through a MATLAB simulation and Hardware experimental prototype.

Cooperation for trans-regional electricity trading from the perspective of carbon quota: A cooperative game approach

Trans-regional electricity trading is a meaningful way to optimize resource allocation and achieve carbon peak and carbon neutrality goals. In this paper, we construct the trans-regional electricity trading cooperative game models considering the impact of local microgrid integration. Based on the cooperative game theory with coalition and graph structures, the optimal mode of trans-regional electricity cooperation and the impact of different carbon quota systems on cooperation profits are studied. The profits obtained through the trans-regional electricity trading are reasonably distributed by the profit distribution scheme based on the Owen graph value. The theoretical and numerical simulation results demonstrate that the local microgrid and the bulk power grid form a priori union, and then participate in the trans-regional electricity trading can obtain more profits. In addition, when the low-carbon policy on the demand side of electricity becomes more relaxed, the implementation of a carbon quota shared responsibility between producers and consumers will be more effective than producer responsibility. Compared with the Myerson value, the profit distribution scheme based on the Owen graph value is more suitable for distributing the profits obtained through trans-regional electricity trading.

Modified T<SUP align="right">2</SUP>-DAB converter with bidirectional power flow capability and reduced voltage stress suitable for DC microgrid integration

Modified T<SUP align="right">2</SUP>-DAB converter with bidirectional power flow capability and reduced voltage stress suitable for DC microgrid integration

Modified T<SUP align="right">2</SUP>-DAB converter with bidirectional power flow capability and reduced voltage stress suitable for DC microgrid integration

Modified T<SUP align="right">2</SUP>-DAB converter with bidirectional power flow capability and reduced voltage stress suitable for DC microgrid integration

Multiple Grid-Connected Microgrids with Distributed Generators Energy Sources Voltage Control in Radial Distribution Network Using ANFIS to Enhance Energy Management

Voltage conditions and power quality for customers and utility equipment are significantly impacted by the addition of microgrid-generating sources within distribution networks. Designing the right control for distributed generators for the various generating units of a Microgrid is important in enabling the synchronization of renewable energy generation sources, energy storage unity, and integration of Microgrids into a radial distribution network. This research provides control mechanisms based on an adaptive technique employing ANFIS, to reduce fluctuation of voltage and current difficulties faced when multiple renewable energy sources and storage systems are incorporated into a distribution network. A step-by-step Voltage Source Converter (VSC) Controller was designed for controlling the DC voltage power sources used. The ANFIS training, test system modeling, and the distributed energy source were modeled in MATLAB/SIMULINK 2021a Software. Four microgrids were developed each consisting of a Photovoltaic plant, Wind Turbine, and Battery Storage System. Non-critical and critical loads were considered during the system testing. The simulated result reveals that the proposed control system works effectively in maintaining a constant system voltage of 340VAC which significantly mitigates system voltage and current fluctuation without using any static synchronous compensator (STATCOM) and power system stabilizers.

Sizing with Technical Indicators of Microgrids with Battery Energy Storage Systems: A Systematic Review

Worldwide, governmental organizations are restructuring energy policies, making them cleaner, encouraging transformation and energy transition by integrating renewable sources, engaging in environmental preservation, and, notably, meeting the growing demand for sustainable energy models, such as solar and wind energy. In the electricity sector, reducing carbon emissions is crucial to facilitating the integration of microgrids (MGs) with renewable sources and Battery Energy Storage Systems (BESSs). This work constitutes a systematic review that thoroughly analyzes the sizing of MGs with BESSs. The unpredictability and variability of renewable sources justify the complexity of this analysis and the loads connected to the system. Additionally, the sizing of a BESS depends primarily on the application, battery technology, and the system’s energy demand. This review mapped and identified existing computational and optimization methodologies for structured sizing in technical indicators of an MG with a BESS based on articles published between 2017 and 2021. A protocol was defined in which articles were filtered in multiple stages, undergoing strategic refinements to arrive at the final articles to address the Research Questions (RQs). The final number of articles was 44, and within these, technical indicators related to the RQs were addressed, covering the most relevant works and comparing them technically, including how each explains the objective and result of their work. The rejected articles did not meet the criteria established by the defined protocol, such as exclusion criteria, quality criteria, and RQs. In conclusion, studies employing the integration of machine learning coupled with optimization techniques exhibit a significant contribution to results, as historical data can aid machine learning for data prediction.

Low‐carbon economic optimal operation strategy of rural multi‐microgrids based on asymmetric Nash bargaining

AbstractThe multi‐microgrids operation can greatly improve the proportion of renewable energy integration and power reliability of rural microgrids through energy trading between adjacent microgrids. Therefore, this paper proposes an optimization method for the low‐carbon economic operation of rural microgrids which contain wind power, photovoltaic, biogas, and other common rural renewable energy sources. Using the asymmetric Nash bargaining model which can form the non‐linear energy mapping function to quantify the bargaining power of each microgrid to establish the multi‐microgrids energy trading model, and the non‐convex trading optimization problem is equivalently transformed into two convex optimization subproblems, subproblem 1 is microgrids alliance costs containing the emission costs, and subproblem 2 is cooperative benefits distribution. Then, the accelerated Alternating Direction Method of Multipliers (ADMM) method is used to solve subproblem 1 and subproblem 2, respectively, and the privacy of transaction information is also protected. The results show that: compared with the single‐microgrid operation, the combined operation of rural multi‐microgrids with biogas can greatly improve the renewable energy consumption rate, reduce carbon emission, and improve the profit income of the alliance and each microgrid. Meanwhile, the accelerated ADMM algorithm used can greatly improve the solution speed.

Revolutionizing Green Transport: An Extensive Review of Hybrid Electric Vehicle Charging Stations and Electric Microgrid Integration

Electric vehicles (EVs), recognized as a strategic approach to reducing oil consumption and greenhouse gas emissions, rely on electricity instead of traditional fuels like petrol or diesel for battery charging, positioning them as a significant player in future energy landscapes. The anticipated decline in oil demand aligns with the increasing prevalence of EVs, making attention to charging infrastructure crucial. This paper extensively explores charging infrastructure considerations, emphasizing their significance in both urban and rural contexts, especially in regions with unstable or absent power supplies. Examining off-grid, grid-connected, and hybrid charging modes, the research delves into various EV designs, including those utilizing fuel cells or batteries.
 A thorough understanding of energy-source-based charging techniques and diverse power-level charging stations is presented, catering to readers' interests. With a focus on enhancing the longevity and efficiency of electric vehicles, researchers are investigating innovative charging methods, including microgrid concepts within charging stations. Recognizing electric vehicles as multi-energy systems, the paper underscores the importance of effective power management and control for optimal energy utilization.
 Additionally, the review scrutinizes the impact of electric vehicles on utility grid infrastructure & maintenance, evaluating various power management and control systems. This comprehensive review serves as a valuable resource for electric vehicle operators and research engineers, offering insights into the current state of the field and potential avenues for future exploration.

Combined Control Strategy for Proportional Current Sharing in DC Microgrid Clusters

The integration of adjacent DC microgrids (MGs) results in the formation of a DC MG cluster which can increase the system power supply capacity. This study proposes a control strategy for DC MG clusters which combines communication-free control and distributed fixed-time control to simultaneously achieve current sharing and voltage regulation with excellent transient characteristics. Firstly, a communication-free control, which presents greater flexibility than the distributed control, is used in the DC MG layer. Subsequently, the distributed fixed-time control is used in the DC MG cluster layer to balance the output current of each MG. The optimal control parameters are obtained by using the zero-pole distribution diagram and establishing a small-signal model of the DC MGs; the stability of the proposed control strategy is also verified. Different scenarios are considered to validate the plug-and-play capability and controller performance by using a DC MG experimental prototype. Real-time hardware-in-the-loop (HIL) verification containing three MGs is conducted using two RT-boxes to prove the scalability of the proposed cluster control.

Impact of intra-hourly scheduling on state of health of battery for electric vehicle integration in smart residential microgrid

Impact of intra-hourly scheduling on state of health of battery for electric vehicle integration in smart residential microgrid

Microgrid Integration Based on Deep Learning NARMA-L2 Controller for Maximum Power Point Tracking

This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength. This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time. Moreover, the proposed controller is tested under static and dynamic load conditions. The simulation and models are done by using MATLAB/Simulink. The simulation results from the proposed NARMA-L2 controller have been compared with existing Perturb and observe PO-MPPT and Incremental Conductance INC -MPPT methods.

Mapping the Research Landscape: A Bibliometric Study of Fuel Cell Technologies and Microgrid Systems

The potency of renewable energy sources in power systems, particularly for rural areas, represents a transformative force that addresses energy challenges and brings about sustainable development. Fuel cells offer a transformative role in providing electricity to rural areas, addressing a reliable and off-grid power solution. This study aims to map the research landscape through the bibliometric study of fuel cell technologies and microgrid systems. The analysis includes author analysis, affiliation analysis, country or territory analysis, source analysis, keyword analysis, trend topic analysis, and thematic map analysis. Bibliometric analysis aids policymakers, industry professionals, and academics navigate the wealth of information, ensuring that fuel cell and microgrid integration efforts align with current research trajectories and contribute meaningfully to improving clean and resilient energy solutions. The results would be a valuable compass, guiding stakeholders through the expansive and dynamic landscape of fuel cell and microgrid research, facilitating evidence-based decision-making, and fostering a deeper understanding of the field’s trajectory.

A Review on Microgrids for Remote Areas Electrification-Technical and Economical Perspective

The main objective of this study is to review microgrids from both a technical and financial standpoint in order to electrify rural places. Making a microgrid in rural area is challenging due to its technical and economical perspective. Technical and Economic analysis could investigate power quality and system stability for a local community in a nation. The technical and economic aspects of microgrid design and operation are covered, along with a number of other parts such power sources, energy storage, and control systems. Installation and maintenance cost has been discussed with respect to technological and economical view point in this paper. The report ends with a review of the prospects and problems for implementing microgrids in remote locations. Various challenges of microgrid and prospective solutions have also been discussed for the betterment of microgrid technically and economically. Microgrid planning has also been explained in this paper in rural regions entails the process of creating, developing, and deploying microgrid systems to provide dependable and sustainable power. Some influential factors such as technological factors, economic factors, socio-political factors and environmental factors on which microgrid depends have been discussed in this paper. The study offers a thorough discussion of microgrids as a potential method for electrifying rural areas. The study shows that microgrid is economically more beneficial to be developed in any rural area, as well as complying the minimum technical requirement of local grid code. Therefore, it can be said that any locality of a nation is a more viable and economic location to implement microgrid for the development. This review will assist the decision-makers in adopting microgrids for the electrification of rural areas and hold establishing regulations that are helpful and clear for the operation and integration of microgrids. System effectiveness, energy storage, and grid management breakthroughs may result from research and development of microgrid technology.

Identification and Analysis of Technical Impacts in the Electric Power System Due to the Integration of Microgrids

In a modern and technological world that has a great demand for energy, a versatile energy market, and a renewed electric infrastructure capable of expanding the electric power system under the premise of universal access to electricity, that seeks to minimize the effects of climate change, and that requires an improvement in its reliability, security, and resilience, microgrids are born as one of the systems that have the potential to supply each of these requirements in order to guarantee an adequate decarbonization, decentralization, digitalization, diversification, and democratization of the future grid. However, the integration of microgrids into the electric power system will generate impacts that are currently under study. This paper identifies and analyzes the technical impacts in the electric power system due to the implementation of microgrids, based on what has been recognized in the literature, so that those who have purposes of installation, creation, innovation, and research of microgrids, such as grid operators, technology providers, companies, and researchers, can establish criteria and indicators through which the feasibility of projects involving microgrids can be determined. The concept, importance, and characteristics of microgrids are given, along with a technical justification of the impacts. In addition, technical impacts on some study cases of real microgrids around the globe are identified. Finally, an analysis of the identified technical impacts is offered, and conclusions are drawn.

Integration of renewable energy resources into the water-energy-food nexus–Modeling a demand side management approach and application to a microgrid farm in Morocco

This paper introduces a framework aimed at analyzing the water-energy-food nexus (WEF) within the context of sustainable farming practices utilizing renewable energy sources, specifically Solar PV, to optimize water management efficiency. The focus lies on investigating the interplay between the water-energy-food nexus and both technical and institutional factors. The study particularly delves into the utilization of distributed energy systems and microgrids for electricity distribution. To achieve the objectives outlined, the framework is applied to a case study involving an off-grid farm in Morocco, aligned with the country's “Green Morocco Plan” of 2008. The study employs the AnyMOD open-source modeling framework in combination with the publicly available decision support tool CropWat (Version 8.0). Through this coupling, a linear optimization model is created to assess various irrigation practices, thus evaluating the energy and water supply variations across different crop growth stages. By employing scenario analysis, the study reveals that the integration of a smart microgrid alongside storage technologies proves beneficial in terms of reducing overall system costs. This integration presents cost-effective solutions and enables the establishment of a sustainable energy supply driven by renewable energy resources. Furthermore, the investigation highlights that constraining irrigation to specific hours of the day results in increased storage requirements and higher associated costs. In conclusion, the study underscores that enhancing the water-energy-food nexus through the integration of a renewable-based microgrid is a complex task. However, it significantly contributes to the development of sustainable farming solutions. This research sheds light on the challenges and opportunities associated with aligning renewable energy, water management, and agricultural practices, ultimately facilitating the pursuit of environmentally conscious and efficient farming methodologies.

Multi-objective model predictive control for microgrid applications

Integration of microgrids may introduce significant power quality challenges to the power distribution networks that may necessitate additional enforcement such as installing new Power Quality Improvement Devices (PQID), which is costly and not always possible option. This paper proposes a control approach that enables the existing power electronics devices within the microgrid to perform multiple functions to address the resultant power quality problems. The proposed method introduces flexibility in harmonic and fundamental power sharing and controlling switching frequency through an improved cost function. Grid connected operation-mode, harmonic compensation capabilities as well as improved dynamic response of controller to fast reference changes have been studied and experimentally verified on a microgrid prototype. Finally, the experimental results of the proposed control method are compared with the results from most recent relevant research activities in the field, evidencing its superiority as compared to the existing control methods presented in the literature.

Analysis of fuel cell integration with hybrid microgrid systems for clean energy: A comparative review

Microgrids have received a lot of attention in the past few decades and researchers are evaluating the integration of renewable resources especially fuel cells to overcome the energy crisis. This review article aims to provide an in-depth analysis of fuel cells, including the technical complexities and challenges encountered in integration with microgrid systems. Additionally, it explores combined heat and power systems that leverage waste heat recovery. The findings indicated that the solid oxide fuel cells (SOFCs) have extensive applicability in various microgrid systems, including grid-connected, backup, and stand-alone setups. These systems can achieve an efficiency of 95% when combined with the heat and power technique. Electricity generation capacity can be attained up to 100 MW using SOFC-based microgrid systems and generates an average of 33.6 kWh utilizing 1-kg hydrogen. In conclusion, this article provides valuable insights for researchers related to the challenges and future directions in fuel cell integrated microgrids.