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1
Muqeet, Hafiz Abdul, Haseeb Javed, Muhammad Naveed Akhter, Muhammad Shahzad, Hafiz Mudassir Munir, Muhammad Usama Nadeem, Syed Sabir Hussain Bukhari, and Mikulas Huba. "Sustainable Solutions for Advanced Energy Management System of Campus Microgrids: Model Opportunities and Future Challenges." Sensors 22, no. 6 (March 18, 2022): 2345. http://dx.doi.org/10.3390/s22062345.
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Distributed generation connected with AC, DC, or hybrid loads and energy storage systems is known as a microgrid. Campus microgrids are an important load type. A university campus microgrids, usually, contains distributed generation resources, energy storage, and electric vehicles. The main aim of the microgrid is to provide sustainable, economical energy, and a reliable system. The advanced energy management system (AEMS) provides a smooth energy flow to the microgrid. Over the last few years, many studies were carried out to review various aspects such as energy sustainability, demand response strategies, control systems, energy management systems with different types of optimization techniques that are used to optimize the microgrid system. In this paper, a comprehensive review of the energy management system of campus microgrids is presented. In this survey, the existing literature review of different objective functions, renewable energy resources and solution tools are also reviewed. Furthermore, the research directions and related issues to be considered in future microgrid scheduling studies are also presented.
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Vivas, Francisco José, Francisca Segura, José Manuel Andújar, Adriana Palacio, Jaime Luis Saenz, Fernando Isorna, and Eduardo López. "Multi-Objective Fuzzy Logic-Based Energy Management System for Microgrids with Battery and Hydrogen Energy Storage System." Electronics 9, no. 7 (June 30, 2020): 1074. http://dx.doi.org/10.3390/electronics9071074.
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This paper proposes a fuzzy logic-based energy management system (EMS) for microgrids with a combined battery and hydrogen energy storage system (ESS), which ensures the power balance according to the load demand at the time that it takes into account the improvement of the microgrid performance from a technical and economic point of view. As is known, renewable energy-based microgrids are receiving increasing interest in the research community, since they play a key role in the challenge of designing the next energy transition model. The integration of ESSs allows the absorption of the energy surplus in the microgrid to ensure power supply if the renewable resource is insufficient and the microgrid is isolated. If the microgrid can be connected to the main power grid, the freedom degrees increase and this allows, among other things, diminishment of the ESS size. Planning the operation of renewable sources-based microgrids requires both an efficient dispatching management between the available and the demanded energy and a reliable forecasting tool. The developed EMS is based on a fuzzy logic controller (FLC), which presents different advantages regarding other controllers: It is not necessary to know the model of the plant, and the linguistic rules that make up its inference engine are easily interpretable. These rules can incorporate expert knowledge, which simplifies the microgrid management, generally complex. The developed EMS has been subjected to a stress test that has demonstrated its excellent behavior. For that, a residential-type profile in an actual microgrid has been used. The developed fuzzy logic-based EMS, in addition to responding to the required load demand, can meet both technical (to prolong the devices’ lifespan) and economic (seeking the highest profitability and efficiency) established criteria, which can be introduced by the expert depending on the microgrid characteristic and profile demand to accomplish.
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Chaudhary, Gaurav, Jacob J. Lamb, Odne S. Burheim, and Bjørn Austbø. "Review of Energy Storage and Energy Management System Control Strategies in Microgrids." Energies 14, no. 16 (August 11, 2021): 4929. http://dx.doi.org/10.3390/en14164929.
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A microgrid (MG) is a discrete energy system consisting of an interconnection of distributed energy sources and loads capable of operating in parallel with or independently from the main power grid. The microgrid concept integrated with renewable energy generation and energy storage systems has gained significant interest recently, triggered by increasing demand for clean, efficient, secure, reliable and sustainable heat and electricity. However, the concept of efficient integration of energy storage systems faces many challenges (e.g., charging, discharging, safety, size, cost, reliability and overall management). Additionally, proper implementation and justification of these technologies in MGs cannot be done without energy management systems, which control various aspects of power management and operation of energy storage systems in microgrids. This review discusses different energy storage technologies that can have high penetration and integration in microgrids. Moreover, their working operations and characteristics are discussed. An overview of the controls of energy management systems for microgrids with distributed energy storage systems is also included in the scope of this review.
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Bazmohammadi, Najmeh, Amjad Anvari-Moghaddam, Ahmadreza Tahsiri, Ahmad Madary, Juan C. Vasquez, and Josep M. Guerrero. "Stochastic Predictive Energy Management of Multi-Microgrid Systems." Applied Sciences 10, no. 14 (July 14, 2020): 4833. http://dx.doi.org/10.3390/app10144833.
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Next-generation power systems will require innovative control strategies to exploit existing and potential capabilities of developing renewable-based microgrids. Cooperation of interconnected microgrids has been introduced recently as a promising solution to improve the operational and economic performance of distribution networks. In this paper, a hierarchical control structure is proposed for the integrated operation management of a multi-microgrid system. A central energy management entity at the highest control level is responsible for designing a reference trajectory for exchanging power between the multi-microgrid system and the main grid. At the second level, the local energy management system of individual microgrids adopts a two-stage stochastic model predictive control strategy to manage the local operation by following the scheduled power trajectories. An optimal solution strategy is then applied to the local controllers as operating set-points to be implemented in the system. To distribute the penalty costs resulted from any real-time power deviation systematically and fairly, a novel methodology based on the line flow sensitivity factors is proposed. Simulation and experimental analyses are carried out to evaluate the effectiveness of the proposed approach. According to the simulation results, by adopting the proposed operation management strategy, a reduction of about 47% in the average unplanned daily power exchange of the multi-microgrid system with the main grid can be achieved.
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Pradip, C., Dr M. S. P. Subathra, and R. P. Amritha. "Energy Management Strategy for PV- Grid Connected Residential Microgrid System." Journal of Advanced Research in Dynamical and Control Systems 11, no. 12-SPECIAL ISSUE (December 31, 2019): 546–54. http://dx.doi.org/10.5373/jardcs/v11sp12/20193250.
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Al Sumarmad, Khaizaran Abdulhussein, Nasri Sulaiman, Noor Izzri Abdul Wahab, and Hashim Hizam. "Energy Management and Voltage Control in Microgrids Using Artificial Neural Networks, PID, and Fuzzy Logic Controllers." Energies 15, no. 1 (January 3, 2022): 303. http://dx.doi.org/10.3390/en15010303.
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Microgrids, comprising distributed generation, energy storage systems, and loads, have recently piqued users’ interest as a potentially viable renewable energy solution for combating climate change. According to the upstream electricity grid conditions, microgrid can operate in grid-connected and islanded modes. Energy storage systems play a critical role in maintaining the frequency and voltage stability of an islanded microgrid. As a result, several energy management systems techniques have been proposed. This paper introduces a microgrid system, an overview of local control in a microgrid, and an efficient EMS for effective microgrid operations using three smart controllers for optimal microgrid stability. We designed a microgrid consisting of renewable sources, Li-ion batteries, the main grid as a backup system, and AC/DC loads. The proposed system control was based on supplying loads as efficiently as possible using renewable energy sources and monitoring the battery’s state of charge. The simulation results using MATLAB Simulink demonstrate the performance of the three proposed microgrid stability strategies (PID, artificial neural network, and fuzzy logic). The comparison results confirmed the viability and effectiveness of the proposed technique for energy management in a microgrid which is based on fuzzy logic controllers.
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Benavides, Darío, Paúl Arévalo, Luis G. Gonzalez, and José A. Aguado. "Analysis of Different Energy Storage Technologies for Microgrids Energy Management." E3S Web of Conferences 173 (2020): 03004. http://dx.doi.org/10.1051/e3sconf/202017303004.
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The importance of energy storage systems is increasing in microgrids energy management. In this study, an analysis is carried out for different types of energy storage technologies commonly used in the energy storage systems of a microgrid, such as: lead acid batteries, lithium ion batteries, redox vanadium flux batteries and supercapacitors. In this work, it is analyzed the process of charging and discharging (slow and fast) in these systems, the calculation of energy efficiency, performance and energy supplied under different load levels, in its normal operating conditions and installed power capacity is developed. The results allow us to choose the optimal conditions of charge and discharge at different levels of reference power, analyzing the strengths and weaknesses of the characteristics of each storage system within a microgrid.
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Reddy Salkuti, Surender. "Optimal operation management of grid-connected microgrids under uncertainty." Indonesian Journal of Electrical Engineering and Computer Science 16, no. 3 (December 1, 2019): 1163. http://dx.doi.org/10.11591/ijeecs.v16.i3.pp1163-1170.
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<span>This paper proposes a new optimal operation of Microgrids (MGs) in a distribution system with wind energy generators (WEGs), solar photovoltaic (PV) energy systems, battery energy storage (BES) systems, electric vehicles (EVs) and demand response (DR). To reduce the fluctuations of wind, solar PV powers and load demands, the BES systems and DR are utilized in the proposed hybrid system. The detailed modeling of WEGs, solar PV units, load demands, BES systems and EVs has been presented in this paper. The objective considered here is the minimization of total operating cost of microgrid, and it is formulated by considering the cost of power exchange between the main power grid and microgrid, cost of wind and solar PV energy systems, cost of BES systems, EVs and the cost due to the DR in the system. Simulations are performed on a test microgrid, and they are implemented using GAMS software. Various case studies are performed with and without considering the proposed hybrid system.</span>
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Arrar, Sara, and Li Xioaning. "Energy Management in Hybrid Microgrid using Artificial Neural Network, PID, and Fuzzy Logic Controllers." European Journal of Electrical Engineering and Computer Science 6, no. 2 (April 11, 2022): 38–47. http://dx.doi.org/10.24018/ejece.2022.6.2.414.
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Microgrids are described as linking many power sources (renewable energy and traditional sources) to meet the load consumption in real-time. Because renewable energy sources are intermittent, battery storage systems are required, typically used as a backup system. Indeed, an energy management strategy (EMS) is required to govern power flows across the entire Microgrid. In recent research, various methods have been proposed for controlling the micro-grids, especially voltage and frequency control. This study introduces a microgrid system, an overview of local control in Microgrid, and an efficient EMS for effective microgrid operations using three smart controllers for optimal microgrid stability. We design the Microgrid, which is made up of renewable solar generators and wind sources, Li-ion battery storage system, backup electrical grids, and AC/DC loads, taking into account all of the functional needs of a microgrid EMS and microgrid stability. In addition, the battery energy storage is managed through the performance control of battery charging and discharging using an efficiency controller. The proposed system control is based on the optimum supply of loads through the available renewable sources and the battery State of Charge (SOC). The simulation results using Matlab Simulink show the performance of the three techniques (PID, ANN, and FL) proposed for microgrid stability.
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Ghosh, Subarto Kumar, Tushar Kanti Roy, Md Abu Hanif Pramanik, Ajay Krishno Sarkar, and Md Apel Mahmud. "An Energy Management System-Based Control Strategy for DC Microgrids with Dual Energy Storage Systems." Energies 13, no. 11 (June 10, 2020): 2992. http://dx.doi.org/10.3390/en13112992.
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In this work, a control strategy is developed for different components in DC microgrids where set points for all controllers are determined from an energy management system (EMS). The proposed EMS-based control scheme is developed for DC microgrids with solar photovoltaic (PV) systems as the primary generation units along with energy storage systems. In this work, the concept of dual energy storage systems (DESSs) is used, which includes a battery energy storage system (BESS) and supercapacitor (SC). The main feature of this DESS is to improve the dynamic performance of DC microgrids during severe transients appearing from changes in load demands as well as in the output power from solar PV units. Furthermore, the proposed EMS-based control scheme aims to enhance the lifetime of the BESS in DC microgrids with DESSs and voltage stability as compared to the same without SCs. The proposed EMS-based control strategy uses proportional-integral (PI) controllers to regulate the switching control actions for different converters within the DC microgrid based on the decision obtained from the EMS in order to achieve the desired control objectives. The performance of the proposed scheme was analyzed through simulation results in terms of improving the voltage stability, maintaining the power balance, and enhancing the lifetime of BESSs within a DC microgrid framework incorporated with the DESS. The simulations are carried out in the MATLAB/SIMULINK simulation platform and compared with a similar approach having only a single energy storage system, i.e., the BESS.
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Ali, Sadaqat, Zhixue Zheng, Michel Aillerie, Jean-Paul Sawicki, Marie-Cécile Péra, and Daniel Hissel. "A Review of DC Microgrid Energy Management Systems Dedicated to Residential Applications." Energies 14, no. 14 (July 17, 2021): 4308. http://dx.doi.org/10.3390/en14144308.
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The fast depletion of fossil fuels and the growing awareness of the need for environmental protection have led us to the energy crisis. Positive development has been achieved since the last decade by the collective effort of scientists. In this regard, renewable energy sources (RES) are being deployed in the power system to meet the energy demand. The microgrid concept (AC, DC) is introduced, in which distributed energy resources (DERs), the energy storage system (ESS) and loads are interconnected. DC microgrids are appreciated due to their high efficiency and reliability performance. Despite its significant growth, the DC microgrid is still relatively novel in terms of grid architecture and control systems. In this context, an energy management system (EMS) is essential for the optimal use of DERs in secure, reliable, and intelligent ways. Therefore, this paper strives to shed light on DC microgrid architecture, control structure, and EMS. With an extensive literature survey on EMSs’ role, different methods and strategies related to microgrid energy management are covered in this article. More attention is centered on the EMS for DC microgrids in terms of size and cost optimization. A very concise analysis of multiple optimization methods and techniques has been presented exclusively for residential applications.
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Shayeghi, Hossein, Elnaz Shahryari, Mohammad Moradzadeh, and Pierluigi Siano. "A Survey on Microgrid Energy Management Considering Flexible Energy Sources." Energies 12, no. 11 (June 5, 2019): 2156. http://dx.doi.org/10.3390/en12112156.
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Aggregation of distributed generations (DGs) along with energy storage systems (ESSs) and controllable loads near power consumers has led to the concept of microgrids. However, the uncertain nature of renewable energy sources such as wind and photovoltaic generations, market prices and loads has led to difficulties in ensuring power quality and in balancing generation and consumption. To tackle these problems, microgrids should be managed by an energy management system (EMS) that facilitates the minimization of operational costs, emissions and peak loads while satisfying the microgrid technical constraints. Over the past years, microgrids’ EMS have been studied from different perspectives and have recently attracted considerable attention of researchers. To this end, in this paper a classification and a survey of EMSs has been carried out from a new point of view. EMSs have been classified into four categories based on the kind of the reserve system being used, including non-renewable, ESS, demand-side management (DSM) and hybrid systems. Moreover, using recent literature, EMSs have been reviewed in terms of uncertainty modeling techniques, objective functions (OFs) and constraints, optimization techniques, and simulation and experimental results presented in the literature.
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Muqeet, Hafiz Abdul, Hafiz Mudassir Munir, Haseeb Javed, Muhammad Shahzad, Mohsin Jamil, and Josep M. Guerrero. "An Energy Management System of Campus Microgrids: State-of-the-Art and Future Challenges." Energies 14, no. 20 (October 11, 2021): 6525. http://dx.doi.org/10.3390/en14206525.
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The multiple uncertainties in a microgrid, such as limited photovoltaic generations, ups and downs in the market price, and controlling different loads, are challenging points in managing campus energy with multiple microgrid systems and are a hot topic of research in the current era. Microgrids deployed at multiple campuses can be successfully operated with an exemplary energy management system (EMS) to address these challenges, offering several solutions to minimize the greenhouse gas (GHG) emissions, maintenance costs, and peak load demands of the microgrid infrastructure. This literature survey presents a comparative analysis of multiple campus microgrids’ energy management at different universities in different locations, and it also studies different approaches to managing their peak demand and achieving the maximum output power for campus microgrids. In this paper, the analysis is also focused on managing and addressing the uncertain nature of renewable energies, considering the storage technologies implemented on various campuses. A comparative analysis was also considered for the energy management of campus microgrids, which were investigated with multiple optimization techniques, simulation tools, and different types of energy storage technologies. Finally, the challenges for future research are highlighted, considering campus microgrids’ importance globally. Moreover, this paper is expected to open innovative paths in the future for new researchers working in the domain of campus microgrids.
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Darshi, Razieh, Saeed Shamaghdari, Aliakbar Jalali, and Hamidreza Arasteh. "Decentralized Reinforcement Learning Approach for Microgrid Energy Management in Stochastic Environment." International Transactions on Electrical Energy Systems 2023 (February 11, 2023): 1–15. http://dx.doi.org/10.1155/2023/1190103.
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Microgrids are considered to be smart power grids that can integrate Distributed Energy Resources (DERs) in the main grid cleanly and reliably. Due to the random and unpredictable nature of Renewable Energy Sources (RESs) and electricity demand, designing a control system for microgrid energy management is a complex task. In addition, the policies of microgrid agents are changing over time to improve their expected profits. Therefore, the problem is stochastic and the policies of the agents are not stationary and deterministic. This paper proposes a fully decentralized multiagent Energy Management System (EMS) for microgrids using the reinforcement learning and stochastic game. The microgrid agents, comprising customers, and DERs are considered as intelligent and autonomous decision makers. The proposed method solves a distributed optimization problem for each self-interested decision maker. Interactions between the decision makers and the environment during the learning phase lead the system to converge to the optimal equilibrium point in which the benefits of all the agents are maximized. Simulation studies using a real dataset demonstrate the effectiveness of the proposed method for the hourly energy management of microgrids.
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Zhang, Ronggang, Sathishkumar V E, and R. Dinesh Jackson Samuel. "Fuzzy Efficient Energy Smart Home Management System for Renewable Energy Resources." Sustainability 12, no. 8 (April 13, 2020): 3115. http://dx.doi.org/10.3390/su12083115.
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This article provides a fuzzy expert system for efficient energy smart home management systems (FES-EESHM), demand management, renewable energy management, energy storage, and microgrids. The suggested fuzzy expert framework is utilized to simplify designing smart microgrids with storage systems, renewable sources, and controllable loads on resources. Further, the fuzzy expert framework enhances energy and storage to utilize renewable energy and maximize the microgrid’s financial gain. Moreover, the fuzzy expert system utilizes insolation, electricity price, wind speed, and load energy controllably and unregulated as input variables to enable energy management. It uses input variables including insolation, electrical quality, wind, and the power of uncontrollable and controllable loads to allow energy management. Furthermore, these input data can be calculated, imported, or predicted directly via grid measurement using any prediction process. In this paper, the input variables are fuzzified, a series of rules are specified by the expert system, and the output is de-fuzzified. The findings of the expert program are discussed to explain how to handle microgrid power consumption and production. However, the decisions on energy generated, controllable loads, and own consumption are based on three outputs. The first production is for processing, selling, or consuming the energy produced. The second output is used for controlling the load. The third result shows how to produce for prosumer’s use. The expert method can be checked via the hourly input of variable values. Finally, to confirm the findings, the method suggested is compared to other available approaches.
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Shafiullah, Md, Akib Mostabe Refat, Md Ershadul Haque, Dewan Mabrur Hasan Chowdhury, Md Sanower Hossain, Abdullah G. Alharbi, Md Shafiul Alam, Amjad Ali, and Shorab Hossain. "Review of Recent Developments in Microgrid Energy Management Strategies." Sustainability 14, no. 22 (November 9, 2022): 14794. http://dx.doi.org/10.3390/su142214794.
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The grid integration of microgrids and the selection of energy management systems (EMS) based on robustness and energy efficiency in terms of generation, storage, and distribution are becoming more challenging with rising electrical power demand. The problems regarding exploring renewable energy resources with efficient and durable energy storage systems demand side management and sustainable solutions to microgrid development to maintain the power system’s stability and security. This article mainly focuses on the overview of the recent developments of microgrid EMS within the control strategies and the implementation challenges of the microgrid. First, it provides energy management strategies for the major microgrid components, including load, generation, and energy storage systems. Then, it presents the different optimization approaches employed for microgrid energy management, such as classical, metaheuristic, and artificial intelligence. Moreover, this article sheds light on the major implementation challenges of microgrids. Overall, this article provides interactive guidelines for researchers to assist them in deciding on their future research.
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Kandari, Ritu, Neeraj Neeraj, and Alexander Micallef. "Review on Recent Strategies for Integrating Energy Storage Systems in Microgrids." Energies 16, no. 1 (December 27, 2022): 317. http://dx.doi.org/10.3390/en16010317.
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Energy security and the resilience of electricity networks have recently gained critical momentum as subjects of research. The challenges of meeting the increasing electrical energy demands and the decarbonisation efforts necessary to mitigate the effects of climate change have highlighted the importance of microgrids for the effective integration of renewable energy sources. Microgrids have been the focus of research for several years; however, there are still many unresolved challenges that need to be addressed. Energy storage systems are essential elements that provide reliability and stability in microgrids with high penetrations of renewable energy sources. This study provides a systematic review of the recent developments in the control and management of energy storage systems for microgrid applications. In the early sections, a summary of the microgrid topologies and architectures found in the recent literature is given. The main contributions and targeted applications by the energy storage systems in the microgrid applications is defined for each scenario. As various types of energy storage systems are currently being integrated for the reliable operation of the microgrids, the paper analyses the properties and limitations of the solutions proposed in the recent literature. The review that was carried out shows that a hybrid energy storage system performs better in terms of microgrid stability and reliability when compared to applications that use a simple battery energy storage system. Therefore, a case study for a DC microgrid with a hybrid energy storage system was modelled in MATLAB/Simulink. The presented results show the advantages of hybrid energy storage systems in DC microgrids.
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Azuara-Grande, Luis Santiago, Santiago Arnaltes, Jaime Alonso-Martinez, and Jose Luis Rodriguez-Amenedo. "Comparison of Two Energy Management System Strategies for Real-Time Operation of Isolated Hybrid Microgrids." Energies 14, no. 20 (October 17, 2021): 6770. http://dx.doi.org/10.3390/en14206770.
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The propagation of hybrid power systems (solar–diesel–battery) has led to the development of new energy management system (EMS) strategies for the effective management of all power generation technologies related to hybrid microgrids. This paper proposes two novel EMS strategies for isolated hybrid microgrids, highlighting their strengths and weaknesses using simulations. The proposed strategies are different from the EMS strategies reported thus far in the literature because the former enable the real-time operation of the hybrid microgrid, which always guarantees the correct operation of a microgrid. The priority EMS strategy works by assigning a priority order, while the optimal EMS strategy is based on an optimization criterion, which is set as the minimum marginal cost in this case. The results have been obtained using MATLAB/Simulink to verify and compare the effectiveness of the proposed strategies, through a dynamic microgrid model to simulate the conditions of a real-time operation. The differences in the EMS strategies as well as their individual strengths and weaknesses, are presented and discussed. The results show that the proposed EMS strategies can manage the system operation under different scenarios and help power system operator obtain the optimal operation schemes of the microgrid.
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Samanta, Hiranmay, Abhijit Das, Indrajt Bose, Joydip Jana, Ankur Bhattacharjee, Konika Das Bhattacharya, Samarjit Sengupta, and Hiranmay Saha. "Field-Validated Communication Systems for Smart Microgrid Energy Management in a Rural Microgrid Cluster." Energies 14, no. 19 (October 4, 2021): 6329. http://dx.doi.org/10.3390/en14196329.
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This paper demonstrates a smart energy management scheme for solar photovoltaic-biomass integrated grid-interactive microgrid cluster system. Three interconnected microgrids were chosen as a cluster of microgrids for validation of the proposed community energy management scheme. In this work, a Global System for Mobile (GSM)-based bidirectional communication technique was adopted for real-time coordination among the renewable energy sources and loads. To realize the common phenomenon of local grid outage in rural distribution networks, a practical case study is designed in this work. The optimized scheduling of the energy sources and loadsof different microgrids and the distribution grid were implemented to ensure zero loss of power supply probability (LPSP) for dynamic load profiles. The laboratory-scale prototype of the proposed microgrid clustering was first developed in this work by establishing real-time communication among multiple energy sources and loads through different energymeters located at different places inside the academic campus. The field validation was performed with a microgrid cluster consisting of 45 kWP solar photovoltaic, 50 kVA biogas plant, community loads in a village. The developed smart energy management solution is a generalized one and applicable to satisfy scalable community energy demands as well.
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Chekira, Ouadiâ, Ali Boharb, Tijani Lamhamdi, Hassan El Moussaoui, Hassane El Markhi, and Mohamed Amine Beniss. "Frequency Control and Energy Management of Microgrid with Distributed Energy Storage." E3S Web of Conferences 351 (2022): 01047. http://dx.doi.org/10.1051/e3sconf/202235101047.
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The purpose of the Energy Management System (EMS) is to ensure a high degree of efficiency, stability, and dependability. And the electrical system should have the ability to adjust to the majority of changes such as renewable energy integration. In some situations, the power generated by distributed power sources is greater than the local demand. This has an effect on the microgrid's stability and frequency. Smart energy management in a microgrid is proposed in this research., consisting of a wind power generator, photovoltaic and storage energy system for frequency regulation, and system balance. The above paper's main contribution is a system for managing energy. based on a clever strategy using MATLAB/Simulink. The results of the simulation and analyses demonstrate that the suggested microgrid energy management system is efficient at balancing energy.
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García Vera, Yimy E., Rodolfo Dufo-López, and José L. Bernal-Agustín. "Energy Management in Microgrids with Renewable Energy Sources: A Literature Review." Applied Sciences 9, no. 18 (September 13, 2019): 3854. http://dx.doi.org/10.3390/app9183854.
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Renewable energy sources have emerged as an alternative to meet the growing demand for energy, mitigate climate change, and contribute to sustainable development. The integration of these systems is carried out in a distributed manner via microgrid systems; this provides a set of technological solutions that allows information exchange between the consumers and the distributed generation centers, which implies that they need to be managed optimally. Energy management in microgrids is defined as an information and control system that provides the necessary functionality, which ensures that both the generation and distribution systems supply energy at minimal operational costs. This paper presents a literature review of energy management in microgrid systems using renewable energies, along with a comparative analysis of the different optimization objectives, constraints, solution approaches, and simulation tools applied to both the interconnected and isolated microgrids. To manage the intermittent nature of renewable energy, energy storage technology is considered to be an attractive option due to increased technological maturity, energy density, and capability of providing grid services such as frequency response. Finally, future directions on predictive modeling mainly for energy storage systems are also proposed.
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Ramli, Makbul A. M., H. R. E. H. Bouchekara, and Abdulsalam S. Alghamdi. "Efficient Energy Management in a Microgrid with Intermittent Renewable Energy and Storage Sources." Sustainability 11, no. 14 (July 14, 2019): 3839. http://dx.doi.org/10.3390/su11143839.
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Substituting a single large power grid into various manageable microgrids is the emerging form for maintaining power systems. A microgrid is usually comprised of small units of renewable energy sources, battery storage, combined heat and power (CHP) plants and most importantly, an energy management system (EMS). An EMS is responsible for the core functioning of a microgrid, which includes establishing continuous and reliable communication among all distributed generation (DG) units and ensuring well-coordinated activities. This research focuses on improving the performance of EMS. The problem at hand is the optimal scheduling of the generation units and battery storage in a microgrid. Therefore, EMS should ensure that the power is shared among different sources following an imposed scenario to meet the load requirements, while the operational costs of the microgrid are kept as low as possible. This problem is formulated as an optimization problem. To solve this problem, this research proposes an enhanced version of the most valuable player algorithm (MVPA) which is a new metaheuristic optimization algorithm, inspired by actual sporting events. The obtained results are compared with numerous well-known optimization algorithms to validate the efficiency of the proposed EMS.
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Liu, Jicheng, Fangqiu Xu, Shuaishuai Lin, Hua Cai, and Suli Yan. "A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm Optimization." Energies 11, no. 12 (November 25, 2018): 3286. http://dx.doi.org/10.3390/en11123286.
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The optimal operation of microgrids is a comprehensive and complex energy utilization and management problem. In order to guarantee the efficient and economic operation of microgrids, a three-layer multi-agent system including distributed management system agent, microgrid central control agent and microgrid control element agent is proposed considering energy storage units and demand response. Then, based on this multi-agent system and with the objective of cost minimization, an operation optimization model for microgrids is constructed from three aspects: operation cost, environmental impact and security. To solve this model, dynamic guiding chaotic search particle swarm optimization is adopted and three scenarios including basic scenario, energy storage participation and demand response participation are simulated and analyzed. The results show that both energy storage unit and demand response can effectively reduce the cost of microgrid, improve the operation and management level and ensure the safety and stability of power supply and utilization.
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Sumarmad, Khaizaran Abdulhussein Al, Nasri Sulaiman, Noor Izzri Abdul Wahab, and Hashim Hizam. "Microgrid Energy Management System Based on Fuzzy Logic and Monitoring Platform for Data Analysis." Energies 15, no. 11 (June 3, 2022): 4125. http://dx.doi.org/10.3390/en15114125.
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Energy management and monitoring systems are significant difficulties in applying microgrids to smart homes. Thus, further research is required to address the modeling and operational parts of the system’s future results for various applications. This paper proposes a new technique for energy management in a microgrid using a robust control approach and the development of a platform for real-time monitoring. The developed controller is based on a fuzzy logic method used in the energy Internet paradigm with connected distributed generators (DGs) in the microgrid. The developed method regulates the power flow of the microgrid, and frequency/voltage regulation improved the load-management performance and monitoring system using the ThingSpeak platform for real-time data analysis. The MATLAB. simulation results show the feasibility and effectiveness of the proposed strategy and the introduced approach in microgrid control under various operating conditions. Additionally, the results show that the proposed monitoring platform facilitates real-time data analysis.
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Yan, Mengxuan, Dongxiao Wang, Chun Sing Lai, and Loi Lei Lai. "A Review on Thermal Energy Modelling for Optimal Microgrids Management." Thermo 1, no. 1 (April 25, 2021): 63–76. http://dx.doi.org/10.3390/thermo1010006.
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Microgrids have become increasingly popular in recent years due to technological improvements, growing recognition of their benefits, and diminishing costs. By clustering distributed energy resources, microgrids can effectively integrate renewable energy resources in distribution networks and satisfy end-user demands, thus playing a critical role in transforming the existing power grid to a future smart grid. There are many existing research and review works on microgrids. However, the thermal energy modelling in optimal microgrid management is seldom discussed in the current literature. To address this research gap, this paper presents a detailed review on the thermal energy modelling application on the optimal energy management for microgrids. This review firstly presents microgrid characteristics. Afterwards, the existing thermal energy modeling utilized in microgrids will be discussed, including the application of a combined cooling, heating and power (CCHP) and thermal comfort model to form virtual energy storage systems. Current trial programs of thermal energy modelling for microgrid energy management are analyzed and some challenges and future research directions are discussed at the end. This paper serves as a comprehensive review to the most up-to-date thermal energy modelling applications on microgrid energy management.
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Tomoiaga, Bogdan, Mircea D. Chindris, Andreas Sumper, and Mousa Marzband. "The Optimization of Microgrids Operation through a Heuristic Energy Management Algorithm." Advanced Engineering Forum 8-9 (June 2013): 185–94. http://dx.doi.org/10.4028/www.scientific.net/aef.8-9.185.
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The concept of microgrid was first introduced in 2001 as a solution for reliable integration of distributed generation and for harnessing their multiple advantages. Specific control and energy management systems must be designed for the microgrid operation in order to ensure reliable, secure and economical operation; either in grid-connected or stand-alone operating mode. The problem of energy management in microgrids consists of finding the optimal or near optimal unit commitment and dispatch of the available sources and energy storage systems so that certain selected criteria are achieved. In most cases, energy management problem do not satisfy the Bellman's principle of optimality because of the energy storage systems. Consequently, in this paper, an original fast heuristic algorithm for the energy management on stand-alone microgrids, which avoids wastage of the existing renewable potential at each time interval, is presented. A typical test microgrid has been analysed in order to demonstrate the accuracy and the promptness of the proposed algorithm. The obtained cost of energy is low (the quality of the solution is high), the primary adjustment reserve is correspondingly assured by the energy storage system and the execution runtime is very short (a fast algorithm). Furthermore, the proposed algorithm can be used for real-time energy management systems.
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Polimeni, Simone, Alfredo Nespoli, Sonia Leva, Gianluca Valenti, and Giampaolo Manzolini. "Implementation of Different PV Forecast Approaches in a MultiGood MicroGrid: Modeling and Experimental Results." Processes 9, no. 2 (February 9, 2021): 323. http://dx.doi.org/10.3390/pr9020323.
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Microgrids represent a flexible way to integrate renewable energy sources with programmable generators and storage systems. In this regard, a synergic integration of those sources is crucial to minimize the operating cost of the microgrid by efficient storage management and generation scheduling. The forecasts of renewable generation can be used to attain optimal management of the controllable units by predictive optimization algorithms. This paper introduces the implementation of a two-layer hierarchical energy management system for islanded photovoltaic microgrids. The first layer evaluates the optimal unit commitment, according to the photovoltaic forecasts, while the second layer deals with the power-sharing in real time, following as close as possible the daily schedule provided by the upper layer while balancing the forecast errors. The energy management system is experimentally tested at the Multi-Good MicroGrid Laboratory under three different photovoltaic forecast models: (i) day-ahead model, (ii) intraday corrections and (iii) nowcasting technique. The experimental study demonstrates the capability of the proposed management system to operate an islanded microgrid in safe conditions, even with inaccurate day-ahead photovoltaic forecasts.
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Azeem, Omar, Mujtaba Ali, Ghulam Abbas, Muhammad Uzair, Ayman Qahmash, Abdulmohsen Algarni, and Mohammad Rashid Hussain. "A Comprehensive Review on Integration Challenges, Optimization Techniques and Control Strategies of Hybrid AC/DC Microgrid." Applied Sciences 11, no. 14 (July 6, 2021): 6242. http://dx.doi.org/10.3390/app11146242.
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The depletion of natural resources and the intermittence of renewable energy resources have pressed the need for a hybrid microgrid, combining the benefits of both AC and DC microgrids, minimizing the overall deficiency shortcomings and increasing the reliability of the system. The hybrid microgrid also supports the decentralized grid control structure, aligning with the current scattered and concentrated load scenarios. Hence, there is an increasing need to explore and reveal the integration, optimization, and control strategies regarding the hybrid microgrid. A comprehensive study of hybrid microgrid’s performance parameters, efficiency, reliability, security, design flexibility, and cost-effectiveness is required. This paper discusses major issues regarding the hybrid microgrids, the integration of AC and DC microgrids, their security and reliability, the optimization of power generation and load management in different scenarios, the efficient management regarding uncertainty for renewable energy resources, the optimal placement of feeders, and the cost-effective control methodologies for the hybrid microgrid. The major research areas are briefly explained, aiming to find the research gap that can further improve the performance of the grid. In light of the recent trends in research, novel strategies are proposed that are found most effective and cost-friendly regarding the hybrid microgrid. This paper will serve as a baseline for future research, comparative analysis, and further development of novel techniques regarding hybrid microgrids.
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Abid, Samia, Turki Ali Alghamdi, Abdul Haseeb, Zahid Wadud, Abrar Ahmed, and Nadeem Javaid. "An Economical Energy Management Strategy for Viable Microgrid Modes." Electronics 8, no. 12 (December 1, 2019): 1442. http://dx.doi.org/10.3390/electronics8121442.
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In the last couple of decades, numerous energy management strategies have been devised to mitigate the effects of greenhouse gas emission, hence introducing the concept of microgrids. In a microgrid, distributed energy generators are used. Microgrid enables a point which ameliorates in exchanging power with the main grid during different times of day. Based on the system constraints, in this work, we aim to efficiently minimize the operating cost of the microgrid and shave the power consumption peaks. For this purpose, we introduce an improved binary bat (iBBat) algorithm which helps to schedule the load demand of smart homes and energy generation from distributed generator of microgrid to the load demand and supply. The proposed energy management algorithm is applied to both grid-connected and islanded modes of the microgrid. The constraints imposed on the algorithm ensure that the load of electricity consumer does not escalate during peak hours. The simulation results are compared with BBat and binary flower pollination algorithm, which validate that the iBBat reflects substantial reduction in operating cost of microgrid. Moreover, results also show a phenomenal reduction in the peak-to-average ratio of load demand from main the main grid.
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Battula, Amrutha Raju, Sandeep Vuddanti, and Surender Reddy Salkuti. "Review of Energy Management System Approaches in Microgrids." Energies 14, no. 17 (September 2, 2021): 5459. http://dx.doi.org/10.3390/en14175459.
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To sustain the complexity of growing demand, the conventional grid (CG) is incorporated with communication technology like advanced metering with sensors, demand response (DR), energy storage systems (ESS), and inclusion of electric vehicles (EV). In order to maintain local area energy balance and reliability, microgrids (MG) are proposed. Microgrids are low or medium voltage distribution systems with a resilient operation, that control the exchange of power between the main grid, locally distributed generators (DGs), and consumers using intelligent energy management techniques. This paper gives a brief introduction to microgrids, their operations, and further, a review of different energy management approaches. In a microgrid control strategy, an energy management system (EMS) is the key component to maintain the balance between energy resources (CG, DG, ESS, and EVs) and loads available while contributing the profit to utility. This article classifies the methodologies used for EMS based on the structure, control, and technique used. The untapped areas which have scope for investigation are also mentioned.
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Aybar-Mejía, Miguel, Lesyani León-Viltre, Félix Santos, Francisco Neves, Víctor Alonso Gómez, and Deyslen Mariano-Hernández. "Modeling and Control of a Microgrid Connected to the INTEC University Campus." Applied Sciences 11, no. 23 (November 30, 2021): 11355. http://dx.doi.org/10.3390/app112311355.
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A smart microgrid is a bidirectional electricity generation system—a type of system that is becoming more prevalent in energy production at the distribution level. Usually, these systems have intermittent renewable energy sources, e.g., solar and wind energy. These low voltage networks contribute to decongestion through the efficient use of resources within the microgrid. In this investigation, an energy management strategy and a control scheme for DG units are proposed for DC/AC microgrids. The objective is to implement these strategies in an experimental microgrid that will be developed on the INTEC university campus. After presenting the microgrid topology, the modeling and control of each subsystem and their respective converters are described. All possible operation scenarios, such as islanded or interconnected microgrids, different generation-load possibilities, and state-of-charge conditions of the battery, are verified, and a seamless transition between different operation modes is ensured. The simulation results in Matlab Simulink show how the proposed control system allows transitions between the different scenarios without severe transients in the power transfer between the microgrid and the low voltage network elements.
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Jabeur, Reda, Youness Boujoudar, Mohamed Azeroual, Ayman Aljarbouh, and Najat Ouaaline. "Microgrid energy management system for smart home using multi-agent system." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 2 (April 1, 2022): 1153. http://dx.doi.org/10.11591/ijece.v12i2.pp1153-1160.
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This paper proposes a multi-agent system for energy management in a microgrid for smart home applications, the microgrid comprises a photovoltaic source, battery energy storage, electrical loads, and an energy management system (EMS) based on smart agents. The microgrid can be connected to the grid or operating in island mode. All distributed sources are implemented using MATLAB/Simulink to simulate a dynamic model of each electrical component. The agent proposed can interact with each other to find the best strategy for energy management using the java agent development framework (JADE) simulator. Furthermore, the proposed agent framework is also validated through a different case study, the efficiency of the proposed approach to schedule local resources and energy management for microgrid is analyzed. The simulation results verify the efficacy of the proposed approach using Simulink/JADE co-simulation.
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Gad, Yehia, Hatem Diab, Mahmoud Abdelsalam, and Yasser Galal. "Smart Energy Management System of Environmentally Friendly Microgrid Based on Grasshopper Optimization Technique." Energies 13, no. 19 (September 23, 2020): 5000. http://dx.doi.org/10.3390/en13195000.
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A microgrid is a group of distributed energy resources and interconnected loads that may be operated either in isolated mode or connected mode with the main utility within electrical boundaries. Microgrids may consist of different types of renewable energy resources such as photovoltaic panels, wind turbines, fuel cells, micro turbines, and storage units. It is highly recommended to manage the dependency on these resources by implementing an energy management unit to optimize the energy exchange so that the minimum cost is achieved. In this paper, an energy management system based on the grasshopper optimization algorithm (GOA) is proposed to determine the optimal power generated by the distributed generators in the microgrid which is required to minimize the total generation cost. The proposed unit is applied to a microgrid that consists of five generating units feeding residential, commercial, and industrial loads, and results are compared to other available research in literature to validate the proposed algorithm.
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Worku, Muhammed Y., Mohamed A. Hassan, and Mohamed A. Abido. "Real Time-Based under Frequency Control and Energy Management of Microgrids." Electronics 9, no. 9 (September 10, 2020): 1487. http://dx.doi.org/10.3390/electronics9091487.
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In this paper, an efficient under frequency control and the energy management of a distributed energy resources (DERs)-based microgrid is presented. The microgrid is composed of a photovoltaic (PV), double-fed induction generator (DFIG)-based wind and diesel generator with critical and non-critical loads. The system model and the control strategy are developed in a real time digital simulator (RTDS). The coordination and power management of the DERs in both grid-connected and islanded operation modes are implemented. During power imbalances and frequency fluctuations caused by fault or islanding, an advanced automatic load shedding control is implemented to regulate and maintain the microgrid frequency at its rated value. One distinct feature implemented for the load shedding operation is that highly unbalanced critical loads are connected to the microgrid. The diesel generator provides the required inertia in the islanded mode to maintain the microgrid rated frequency by operating in the isochronous mode. The International Council on Large Electric Systems (CIGRE) medium voltage (MV) test bench system is used to implement the DERs and their controller. The proposed control approach has potential applications for the complete operation of microgrids by properly controlling the power, voltage and frequency in both grid-connected and island modes. The real time digital simulator results verify the effectiveness and superiority of the proposed control scheme in grid connected, island and fault conditions.
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Casolino, Giovanni, Mario Russo, Pietro Varilone, and Daniele Pescosolido. "Hardware-in-the-Loop Validation of Energy Management Systems for Microgrids: A Short Overview and a Case Study." Energies 11, no. 11 (November 1, 2018): 2978. http://dx.doi.org/10.3390/en11112978.
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The energy management system (EMS) of a microgrid often presents a complex structure and a large number of control functions, which must be validated to ensure a reliable and optimal operation of the microgrid. Control system validation is typically performed by using hardware-in-the-loop (HIL) architectures in which the microgrid is simulated in real time and interfaced with the actual system under test. The simulation must ensure both an accurate representation of the microgrid and a reliable replica of the field communication of the EMS with all the control devices. In this paper, an overview of the various HIL architectures proposed in the literature is firstly outlined. Then, an HIL validation facility is presented and used to validate the EMS of an industrial microgrid. Finally, some results of the validation tests are reported to give evidence of the effectiveness of the proposed facility. In the proposed architecture, the soft real-time digital simulator of the microgrid is interfaced with the actual EMS using the same communication system and protocol as on the field. The main advantages of the proposed testing facility are: (i) the use of commercial PCs and the absence of dedicated interface modules, resulting in inexpensive hardware components; (ii) the capability to validate both control and communication functions of the EMS; (iii) the applicability to microgrids of different types (industrial, commercial, residential), as well as of various dimensions, including large microgrids; (iv) the easiness in changing the microgrid and the EMS under validation by only software modifications of the simulator tasks and of the exchange interface. As drawbacks, the proposed testing facility presents the need to adapt the software interface between EMS and the field to the EMS under test and the possibility of testing only the EMS functions and not fast-acting local controllers of the microgrid such as the protection systems.
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Granados Hernández, Elkin Dario, Nelson Leonardo Diaz Aldana, and Adriana Carolina Luna Hernández. "Energy Management Electronic Device for Islanded Microgrids Based on Renewable Energy Sources and Battery-based Energy Storage." Ingeniería e Investigación 41, no. 1 (January 29, 2021): e83905. http://dx.doi.org/10.15446/ing.investig.v41n1.83905.
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Energy management systems are one of the most important components in the operation of an electric microgrid. They are responsible for ensuring the supervision of the electrical system, as well as the coordination and reliability of all loads and distributed energy resources in order for the microgrid to be operated as a unified entity. Because of that, an energy management system should be fast enough at processing data and defining control action to guarantee the correct performance of the microgrid. This paper explores the design and implementation of an energy management system deployed over a dedicated electronic device. The proposed energy management device coordinates the distributed energy resources and loads in a residential-scale islanded microgrid, in accordance with a rule-based energy management strategy that ensures reliable and safe operation of the battery-based energy storage system. A hardware-int-he-loop test was performed with a real-time simulation platform to show the operation of the electronic device
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Albarakati, Aiman J., Younes Boujoudar, Mohamed Azeroual, Reda Jabeur, Ayman Aljarbouh, Hassan El Moussaoui, Tijani Lamhamdi, and Najat Ouaaline. "Real-Time Energy Management for DC Microgrids Using Artificial Intelligence." Energies 14, no. 17 (August 26, 2021): 5307. http://dx.doi.org/10.3390/en14175307.
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Microgrids are defined as an interconnection of several renewable energy sources in order to provide the load power demand at any time. Due to the intermittence of renewable energy sources, storage systems are necessary, and they are generally used as a backup system. Indeed, to manage the power flows along the entire microgrid, an energy management strategy (EMS) is necessary. This paper describes a microgrid energy management system, which is composed of solar panels and wind turbines as renewable sources, Li-ion batteries, electrical grids as backup sources, and AC/DC loads. The proposed EMS is based on the maximum extraction of energy from the renewable sources, by making them operate under Maximum Power Point Tracking (MPPT) mode; both of those MPPT algorithms are implemented with a multi-agent system (MAS). In addition, management of the stored energy is performed through the optimal control of battery charging and discharging using artificial neural network controllers (ANNCs). The main objective of this system is to maintain the power balance in the microgrid and to provide a configurable and a flexible control for the different scenarios of all kinds of variations. All the system’s components were modeled in MATLAB/Simulink, the MAS system was developed using Java Agent Development Framework (JADE), and Multi-Agent Control using Simulink with Jade extension (MACSIMJX) was used to insure the communication between Simulink and JADE.
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Ge, Teng Yu, Bu Han Zhang, Jun Li Wu, Bing Jie Jin, Shuang Zhao, and Kai Min Zhang. "Design of Microgrid Energy Management System Based on LabVIEW." Advanced Materials Research 960-961 (June 2014): 1562–66. http://dx.doi.org/10.4028/www.scientific.net/amr.960-961.1562.
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Microgrid can be applied in different locations, relative to traditional power technology. It can improve the reliability of users of electricity and power system operation. Distributed power in microgrid needs real-time and multi-objective optimization management. This paper discusses functions and structure of microgrid energy management system(MGEMS) when connected with the main grid. Problems in long-term and short-term energy management of microgrid are discussed. From the point of view of the software platform, the system structure of MGEMS software are proposed. On this basis, this paper discusses the way to construct modules of MGEMS and their functions.
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Elgamal, Mohamed, Nikolay V. Korovkin, Ahmed Refaat, and Akram Elmitwally. "Optimal operation of a hybrid-energy microgrid with energy storage system." E3S Web of Conferences 138 (2019): 01003. http://dx.doi.org/10.1051/e3sconf/201913801003.
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In this paper, a day-ahead profit-maximizing energy management scheme for a grid-tied microgrid operation is proposed. The microgrid contains various types of distributed energy resources (DERs) and an inverter-interfaced battery-bank storage system. The average of day-ahead hourly forecasted data for loads, wind speed, and solar radiation are inputted into the framework of energy management (EMF). To optimize the microgrid performance, EMF determines the hourly dispatch of reactive and active power for each DER. Also, it specifies the discharging and charging times of the energy storage system and the onload tap changer position setting of the transformer connected to the main grid. The main aim is to maximize the revenue of microgrid meeting all technical limitations. The main grid can sell/buy reactive and active powers to/from the microgrid with a variable daily energy price of the market. A collective rule base-BAT algorithm is implemented as a solver of the energy management optimization problem for a grid-tided microgrid. Furthermore, the ability of the suggested EMF is proved in comparison with recent approaches.
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Wu, Haotian, Hang Li, and Xueping Gu. "Optimal Energy Management for Microgrids Considering Uncertainties in Renewable Energy Generation and Load Demand." Processes 8, no. 9 (September 2, 2020): 1086. http://dx.doi.org/10.3390/pr8091086.
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This paper proposes an efficient power management approach for the 24 h-ahead optimal maneuver of Mega–scale grid–connected microgrids containing a huge penetration of wind power, dispatchable distributed generation (diesel generator), energy storage system and local loads. The proposed energy management optimization objective aims to minimize the microgrid expenditure for fuel, operation and maintenance and main grid power import. It also aims to maximize the microgrid revenue by exporting energy to the upstream utility grid. The optimization model considers the uncertainties of the wind energy and power consumptions in the microgrids, and appropriate forecasting techniques are implemented to handle the uncertainties. The optimization model is formulated for a day-ahead optimization timeline with one-hour time steps, and it is solved using the ant colony optimization (ACO)-based metaheuristic approach. Actual data and parameters obtained from a practical microgrid platform in Atlanta, GA, USA are employed to formulate and validate the proposed energy management approach. Several simulations considering various operational scenarios are achieved to reveal the efficacy of the devised methodology. The obtained findings show the efficacy of the devised approach in various operational cases of the microgrids. To further confirm the efficacy of the devised approach, the achieved findings are compared to a pattern search (PS) optimization-based energy management approach and demonstrate outperformed performances with respect to solution optimality and computing time.
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Naji Alhasnawi, Bilal, Basil H. Jasim, and M. Dolores Esteban. "A New Robust Energy Management and Control Strategy for a Hybrid Microgrid System Based on Green Energy." Sustainability 12, no. 14 (July 16, 2020): 5724. http://dx.doi.org/10.3390/su12145724.
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The recent few years have seen renewable energy becoming immensely popular. Renewable energy generation capacity has risen in both standalone and grid-connected systems. The chief reason is the ability to produce clean energy, which is both environmentally friendly and cost effective. This paper presents a new control algorithm along with a flexible energy management system to minimize the cost of operating a hybrid microgrid. The microgrid comprises fuel cells, photovoltaic cells, super capacitors, and other energy storage systems. There are three stages in the control system: an energy management system, supervisory control, and local control. The energy management system allows the control system to create an optimal day-ahead power flow schedule between the hybrid microgrid components, loads, batteries, and the electrical grid by using inputs from economic analysis. The discrepancy between the scheduled power and the real power delivered by the hybrid microgrid is adjusted for by the supervisory control stage. Additionally, this paper provides a design for the local control system to manage local power, DC voltage, and current in the hybrid microgrid. The operation strategy of energy storage systems is proposed to solve the power changes from photovoltaics and houses load fluctuations locally, instead of reflecting those disturbances to the utility grid. Furthermore, the energy storage systems energy management scheme will help to achieve the peak reduction of the houses’ daily electrical load demand. Also, the control of the studied hybrid microgrid is designed as a method to improve hybrid microgrid resilience and incorporate renewable power generation and storage into the grid. The simulation results verified the effectiveness and feasibility of the introduced strategy and the capability of proposed controller for a hybrid microgrid operating in different modes. The results showed that (1) energy management and energy interchange were effective and contributed to cost reductions, CO2 mitigation, and reduction of primary energy consumption, and (2) the newly developed energy management system proved to provide more robust and high performance control than conventional energy management systems. Also, the results demonstrate the effectiveness of the proposed robust model for microgrid energy management.
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Solano, Javier, Diego Jimenez, and Adrian Ilinca. "A Modular Simulation Testbed for Energy Management in AC/DC Microgrids." Energies 13, no. 16 (August 5, 2020): 4049. http://dx.doi.org/10.3390/en13164049.
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This paper introduces a modular testbed to simulate AC/DC microgrids. The testbed is implemented in Matlab Simulink and is based on the energetic macroscopic representation (EMR) formalism. It is designed to be a tool to evaluate energy management strategies in AC/DC microgrids. The microgrid simulation model includes a photovoltaic generator, a fuel cell system, ultracapacitors, and batteries on the DC side. It includes voltage source converters (VSC) to couple the DC side with the AC side of the microgrid, which includes a variable AC load and a synchronous generator. Two case studies illustrate the use of the testbed. The model is implemented in Matlab Simulink and made openly available for the scientific community. Using this model, researchers can develop and evaluate energy management strategies in AC/DC microgrids.
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Jimeno, Joseba, Jon Anduaga, José Oyarzabal, and Asier Gil de Muro. "Architecture of a microgrid energy management system." European Transactions on Electrical Power 21, no. 2 (March 2011): 1142–58. http://dx.doi.org/10.1002/etep.443.
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Pan, Tinglong, Hui Liu, Dinghui Wu, and Zeliang Hao. "Dual-Layer Optimal Dispatching Strategy for Microgrid Energy Management Systems considering Demand Response." Mathematical Problems in Engineering 2018 (July 8, 2018): 1–14. http://dx.doi.org/10.1155/2018/2695025.
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The continuous development of microgrid’s technology creates favorable conditions for the access of distributed energy. Firstly, in order to consider the interests of the demand side and the power side, this paper presents a dual-layer optimal dispatching model of microgrid based on demand response. The objective of the first-layer optimization is to obtain the maximum load satisfaction and to optimize the load curve. The objective of the second-layer optimization is to make the microgrid system economical and environmentally friendly and to optimize the power utilization ratio. And a microsource control strategy based on the isolated microgrid is proposed, which can optimize the operation state of battery and improve the economy of the system. Finally, the Nondominated Sorting Genetic Algorithm-II (NSGA-II) is adopted to solve the optimal scheduling problem of the isolated microgrid. The simulation results indicate that the microsource scheduling strategy proposed in this paper can improve the operation economy and environmental conservation of the system. It can improve the reliability of microgrid power supply and reduce energy waste.
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Sidea, Dorian O., Andrei M. Tudose, Irina I. Picioroaga, and Constantin Bulac. "Two-Stage Optimal Active-Reactive Power Coordination for Microgrids with High Renewable Sources Penetration and Electrical Vehicles Based on Improved Sine−Cosine Algorithm." Mathematics 11, no. 1 (December 22, 2022): 45. http://dx.doi.org/10.3390/math11010045.
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As current global trends aim at the large-scale insertion of electric vehicles as a replacement for conventional vehicles, new challenges occur in terms of the stable operation of electric distribution networks. Microgrids have become reliable solutions for integrating renewable energy sources, such as solar and wind, and are considered a suitable alternative for accommodating the growing fleet of electrical vehicles. However, efficient management of all equipment within a microgrid requires complex solving algorithms. In this article, a novel two-stage scheme is proposed for the optimal coordination of both active and reactive power flows in a microgrid, considering the high penetration of renewable energy sources, energy storage systems, and electric mobility. An improved sine-cosine algorithm is introduced to ensure the day-ahead optimal planning of the microgrid’s components aiming at minimizing the total active energy losses of the system. In this regard, both local and centralized control strategies are investigated for multiple generations and consumption scenarios. The latter proved itself a promising control scheme for the microgrid operation, as important energy loss reduction is encountered when applied.
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Wang, Longze, Shucen Jiao, Yu Xie, Saif Mubaarak, Delong Zhang, Jinxin Liu, Siyu Jiang, Yan Zhang, and Meicheng Li. "A Permissioned Blockchain-Based Energy Management System for Renewable Energy Microgrids." Sustainability 13, no. 3 (January 27, 2021): 1317. http://dx.doi.org/10.3390/su13031317.
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Peer-to-peer (P2P) energy management is one of the most viable solutions to incentivize prosumers in renewable energy microgrids. As the application of blockchain expends from the finance field to energy field, blockchain technology provides a new opportunity for distributed energy systems. However, a distributed energy system based on blockchains allows any node in the whole network to read data. In many application scenarios, user privacy cannot be effectively protected, and there is a security problem that the attack cannot be traced. In this paper, we propose an energy management mode based on a permissioned blockchain for a renewable energy microgrid. The novel permissioned blockchain framework uses entity mapping with a unique identity for each enterprise, natural person, or device, in order to avoid ineligible participants to join the microgrid. Each peer entity keeps the transaction information index of the whole network, but only keeps its own specific transaction information, so they can retrieve the transaction information of other peer entities but cannot obtain the details without permission. Moreover, this model could avoid communication delays and promote plug-and-play due to the distributed nature of the permissioned blockchain. The performance of the proposed method is evaluated with a demonstration program which is designed and deployed on a Hyperledger Fabric permissioned blockchain. Simulation results show the feasibility of the proposed method, and the model is conducive to the protection privacy and P2P energy management for decentralized energy systems.
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Bilbao, Javier, Eugenio Bravo, Olatz García, Carolina Rebollar, and Concepción Varela. "Optimising Energy Management in Hybrid Microgrids." Mathematics 10, no. 2 (January 11, 2022): 214. http://dx.doi.org/10.3390/math10020214.
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This article deals with the optimization of the operation of hybrid microgrids. Both the problem of controlling the management of load sharing between the different generators and energy storage and possible solutions for the integration of the microgrid into the electricity market will be discussed. Solar and wind energy as well as hybrid storage with hydrogen, as renewable sources, will be considered, which allows management of the energy balance on different time scales. The Machine Learning method of Decision Trees, combined with ensemble methods, will also be introduced to study the optimization of microgrids. The conclusions obtained indicate that the development of suitable controllers can facilitate a competitive participation of renewable energies and the integration of microgrids in the electricity system.
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Choi, Yeon-Ju, Byeong-Chan Oh, Moses Amoasi Acquah, Dong-Min Kim, and Sung-Yul Kim. "Optimal Operation of a Hybrid Power System as an Island Microgrid in South-Korea." Sustainability 13, no. 9 (April 29, 2021): 5022. http://dx.doi.org/10.3390/su13095022.
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The microgrid is a power distribution system that supplies power from distributed generation to end-users. Demonstration projects and R&D regarding microgrids are currently in development in several advanced countries. In South Korea, renewable energy-based microgrid demonstration projects are carried out mainly as island or university campus grids. These R&D efforts aim to popularize microgrid systems in South Korea while considering the limited land availability, which impedes the widespread distribution of photovoltaic systems and the microgrid market’s growth. This study presents a floating photovoltaic system configured as an island microgrid combined with a hybrid power system. The floating photovoltaic system is configured on an idle water body integrated with an existing pumped hydroelectric system. The integration of a current pumped hydroelectric system minimizes a battery energy storage requirement, which compensates for the renewable energy sources’ intermittent power output. We evaluate the optimal power flow of the setup using a reliability index to ensure a stable power supply within the standalone microgrid and maximize the supply power range according to the demand response.
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Liu, Guodong, Maximiliano F. Ferrari, Thomas B. Ollis, and Kevin Tomsovic. "An MILP-Based Distributed Energy Management for Coordination of Networked Microgrids." Energies 15, no. 19 (September 23, 2022): 6971. http://dx.doi.org/10.3390/en15196971.
Full textAbstract:
An MILP-based distributed energy management for the coordination of networked microgrids is proposed in this paper. Multiple microgrids and the utility grid are coordinated through iteratively adjusted price signals. Based on the price signals received, the microgrid controllers (MCs) and distribution management system (DMS) update their schedules separately. Then, the price signals are updated according to the generation–load mismatch and distributed to MCs and DMS for the next iteration. The iteration continues until the generation–load mismatch is small enough, i.e., the generation and load are balanced under agreed price signals. Through the proposed distributed energy management, various microgrids and the utility grid with different economic, resilient, emission and socio-economic objectives are coordinated with generation–load balance guaranteed and the microgrid customers’ privacy preserved. In particular, a piecewise linearization technique is employed to approximate the augmented Lagrange term in the alternating direction method of multipliers (ADMM) algorithm. Thus, the subproblems are transformed into mixed integer linear programming (MILP) problems and efficiently solved by open-source MILP solvers, which would accelerate the adoption and deployment of microgrids and promote clean energy. The proposed MILP-based distributed energy management is demonstrated through various case studies on a networked microgrids test system with three microgrids.
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Bharatee, Anindya, Pravat Kumar Ray, Bidyadhar Subudhi, and Arnab Ghosh. "Power Management Strategies in a Hybrid Energy Storage System Integrated AC/DC Microgrid: A Review." Energies 15, no. 19 (September 29, 2022): 7176. http://dx.doi.org/10.3390/en15197176.
Full textAbstract:
The limited availability of fossil fuel and the growing energy demand in the world creates global energy challenges. These challenges have driven the electric power system to adopt the renewable source-based power production system to get green and clean energy. However, the trend of the introduction of renewable power sources increases the uncertainty in the production, control, and operation of power systems due to the erratic nature of the environment. To overcome these meteorological conditions, some support systems, such as storage devices, are integrated with renewable energy sources (RES). A number of storage devices are hybridized to get the hybrid energy storage system (HESS) to get a potential solution for these microgrid problems. For maintaining the robustness and reliability of the power system, proper control, and management of power in the microgrid is very important. In this paper, an analytical study related to power management strategies is given along with different interconnection topologies for the HESS. Analysis and control of storage devices are necessary to avoid the premature degradation of the devices and to get their optimal utilization. Therefore, this article attempts to include different power management schemes used in AC/DC microgrids. Furthermore, various control techniques specific to different energy storage devices are reviewed extensively, which would serve as a complete guide for the design and implementation of a hybrid AC/DC microgrid.