Relevant bibliographies by topics / Microgrid energy management system

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Academic literature on the topic 'Microgrid energy management system'

Author: Grafiati
Published: 19 February 2023

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Journal articles on the topic "Microgrid energy management system"

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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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Dissertations / Theses on the topic "Microgrid energy management system"

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Garmabdari, Rasoul. "Multi-Energy Microgrid Systems Planning and Energy Management Optimisation." Thesis, Griffith University, 2020. http://hdl.handle.net/10072/398878.

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Conventional power systems are predominantly composed of centralised large-scale generation sites that provide electricity to a large number of customers in a top-down unidirectional fashion and through transmission and distribution networks. To increase penetration of Renewable Energy Resources (RES) into this traditional power system and promotion of Distributed Energy Resources (DER) concept as an effective solution to deal with the challenges being faced in the conventional power system such as the energy losses, peak demand, peak generation, the infrastructure depreciation, and environmental effect, Microgrid (MG) concept is introduced. MG is defined as a locally controlled small unit of the power system that usually is in interaction with the main grid and is regarded as the building blocks of future Smart Grids (SGs). However, these systems are also capable of operating independently and isolated from the main grid, particularly in remote areas where access to the main grid is impossible or there is a disruptive event on the power system. The emergence of cutting-edge advances in the energy conversion and energy storage technologies and their commercial availability as well as introduction of various lucrative grid services that both grid and customers can benefit from derived the planners and engineers to further expand the flexibility, resilience and efficiency of MGs. To achieve this, Multi-Energy Microgrid System (MEMGS) concept as an expanded definition of MG was introduced to improve the efficiency of conventional energy systems, reduce air pollution as well as energy utilisation. MEMGS incorporates various energy technologies such as axillary boiler, gas turbine, RESs, thermal and battery energy storage systems that are fed by multiple energywares such as gas and electricity to supply multiple types of demands simultaneously such as electrical, heating and cooling loads. However, the integration of clusters of various technologies and concurrent delivery of different energy services causes additional complexities into the modelling and optimisation of these systems due to the potential interactions of energy vectors and various technologies at the consumer level. The economic viability of MGs and MEMGSs rely on the configuration and operating management of the technologies. Therefore, is a need to develop an effective and efficient planning framework that can handle the interaction complexities and nonlinearities of the system, determining the most appropriate architecture, selecting the energy conversion and energy storage technologies and energy supply alternatives from a candidate pool. This thesis aims at addressing these challenges by initially developing a comprehensive and accurate dynamic model for MGs and MGESs components, investigating the technical and economic aspects, the nonlinear behaviour, maintenance and degradation phenomena, and uncertainties associated with technologies through Mixed-Integer Linear Programming (MILP) and Mixed Integer Quadratic Programming (MIQP). Then the established model is employed to establish and propose a multi-objective linearised planning optimisation approach. The architecture and choice of equipment of MEMGSs involve various elements such as availability and costs of the energy sources and equipment, and characteristics of the energy demand. Considering these factors, the proposed strategy allocates the size of the components utilised in the MGs and EMMGSs while meeting the defined performance indices such as degradation factor, reliability and grid power fluctuations smoothing indices. Once, the configuration and capacity of components are optimally determined, efficient energy management is required. The last part of this research focuses on energy management system scheduling and optimisation where the EMS scheduling module for MGs and MEMGSs are inspected considering the Time of Use tariff, peak shaving and valley filling functions, degradation of energy storage devices, along with the operating criteria and cost of the energy conversion units. Moreover, a real-time EMS solution is provided to deal with intermittent behaviour of RESs while participating in arbitrage market. The real-time EMS manages the energy flow optimally according to the acquired real-time data and its deviation from the original schedule attained in the scheduling optimisation stage. The primary objective of the EMS module development is to maximise profit while improving the performance of the MEMGSs. Throughout this research, the MILP and MIQP optimisation approach is adopted to achieve a fast convergence while avoiding complexity and long computation time that would cause due to the nonlinear behaviour and complex interaction of the technologies. Finally, having a practical insight into the challenges and concerns with connection adjacent MGs in distribution networks, an efficient centralised EMS optimisation framework is proposed to cope with the limitations and optimise the performance of the system, considering power losses, voltage deviations and nonlinear degradation of the components. The primary objective of this section of research is to achieve the optimal techno-economic solution.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Eng & Built Env
Science, Environment, Engineering and Technology
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Tayab, Usman Bashir. "Novel Forecasting and Scheduling for Microgrid Energy Management System." Thesis, Griffith University, 2021. http://hdl.handle.net/10072/408937.

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The high penetration of renewable energy resources brought new challenges to the modern grid; therefore, new solutions and concepts need to be developed. The idea of a microgrid (MG) has been introduced to overcome the upcoming issues in modern grids. MG is a small-scale grid composed of renewable energy resources, energy storage, and load demand. MG makes decisions by itself and can operate in grid-connected or islanded mode depending on functionality. The microgrid energy management system (M-EMS) is the decision-making centre of MG. An M-EMS is composed of four modules which are known as forecasting, scheduling, data acquisition, and human-machine interface. However, the forecasting and scheduling modules are considered as the major modules among the four of them. The forecasting module is required in the M-EMS to predict the future power generation and consumption. The forecast data is the input to the scheduling module of M-EMS. Employing forecasting system in the M-EMS would increase the accuracy of the scheduling module. The scheduling module is responsible for controlling the power flow from/to the main grid. Additionally, it performs optimal day-ahead scheduling of available power generation resources to feed the load demand in a grid-connected MG for economical operation. Consequently, this research work presents four contributions in the area of M-EMS for grid-connected MG. The first contribution of this research is to presents a hybrid strategy for short-term forecasting of load demand in M-EMS, which is a combination of best-basis stationary wavelet packet transform and the Harris hawks algorithm-based feedforward neural network. The Harris hawks algorithm is applied to the feedforward neural network as an alternative learning algorithm to optimized the weights and biases of neurons. The proposed model is applied for load demand prediction of the Queensland electric market and compared with existing competitive models. The simulation results prove the effectiveness of the proposed method. The second contribution of this research is to design and proposed an ensemble forecasting strategy for solar PV power forecasting. The proposed ensemble strategy is based on a systematic combination of the tunicate swarm algorithm (TSA)-based multilayer perceptron neural network (TSA-MLPNN), TSA based least-square support vector machine (TSA-LSSVM), whales optimization algorithm (WOA) based MLPNN (WOAMLPNN), and WOA based LSSVM (WOA-LSSVM). The output of all the models is combined using the Bayesian model averaging method. The proposed ensemble strategy is validated through simulation of the real-time data of building N-78 Griffith University, Queensland. The simulation results demonstrated that the proposed strategy shows excellent performance in comparison with several existing competitive approaches. The third contribution of this research is to propose an optimum scheduling strategy, using a weighted salp swarm algorithm for M-EMS, to perform the optimal scheduling of available power resources to meet consumer demand and minimize the operating cost of grid-connected MG. The performance of the proposed scheduling strategy is validated through simulation using MATLAB and compared with standard particle swarm optimization (PSO) based scheduling strategy. The comparison shows that the proposed strategy outperforms the PSO based strategy. The final contribution of this research is to propose an M-EMS using an ensemble forecasting strategy and grey wolf optimization (GWO). In the proposed M-EMS, an ensemble forecasting strategy is used to accomplish short-term forecasting of PV power and load while the GWO is applied to perform the optimum scheduling of available power resources in grid-connected MG. A small-scale experiment is conducted using Raspberry Pi 3 B+ via python programming language to validate the effectiveness of the proposed M-EMS. The experimental results of the proposed M-EMS for the selected case prove the effectiveness of the proposed M-EMS. In summary, several forecasting and scheduling strategies have been proposed and validated for the M-EMS of a grid-connected MG.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Eng & Built Env
Science, Environment, Engineering and Technology
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Vosloo, Arno. "Agent-based energy management system for remote community microgrid." Thesis, Cape Peninsula University of Technology, 2015. http://hdl.handle.net/20.500.11838/1188.

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thesis submitted in partial fulfilment of the requirements for the degree: Master of Technology: Electrical Engineering in the Faculty of Electrical Engineering at the Cape Peninsula University of Technology
Rural communities are often unable to access electrical energy due to their distant location away from the national grid. Renewable energy sources (RESs) make it possible to provide electrical energy to these isolated areas. Sustainable generation is possible at a local level and is not dependant on connection to a national power grid. Microgrids are small scale, stand-alone electricity networks that harness energy at its geographical location, from natural resources. These small scale power grids are either connected to a national grid or operate separately by obtaining their power from an RES. Microgrids are becoming increasingly popular because they can provide electricity, independently of the national grid. The size of microgrid systems are dependent on the amount of energy that needs to be drawn and the amount of energy that has to be stored. Mechanical and electrical system component sizes become bigger due to increased operational energy requirements. Increases in component sizes are required on growing power networks when higher current levels are drawn. Energy management of microgrids must thus be introduced to prevent overloading the power grid network and to extend the operational life of the storage batteries. Energy management systems consist of different components which are seen as operational units. Operational units are responsible for measurement, communication, decision–making and power supply switching control, to manipulate the power output to meet the energy demands. Due to the increasing popularity of DC home appliances, it is important to explore the possibility of keeping these microgrids on a DC voltage basis. Electrical generation equipment such as photovoltaic panels can be used to generate DC at designed voltage levels. The energy management system connects the user loads and generation units together to form the microgrid. The aim of this study was to carry out the design of an agent–based energy management system for rural and under-developed communities. It investigates how the control of the output of the energy management system can be carried out to service the loads. The simulations were done using the following software packages: Simulink, Matlab, and SimPowerSystems. PV sources, energy management system (EMS) and user load parameters are varied in the simulation software to observe how the control algorithm executes load shedding. A stokvel-type charge share concept is dealt with where the state-of-charge (SOC) of batteries and user consumption will determine how grid loads are managed. Load shedding within the grid is executed by monitoring energy flow and calculating how much energy is allowed to be used by each consumer. The energy management system is programmed to always provide the largest amount of energy to the consumer with the lowest energy consumption for each day. The batteries store surplus electrical energy during the day. Load shedding starts at 18:00 each day. Users will be disconnected from the grid whenever their allotted energy capacity were depleted.
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Wang, Xueying. "Energy management for islanded microgrid with energy storage systems." Thesis, Wang, Xueying (2018) Energy management for islanded microgrid with energy storage systems. Honours thesis, Murdoch University, 2018. https://researchrepository.murdoch.edu.au/id/eprint/44767/.

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Microgrid is a new form of electrical network interconnected with renewable energy resources mainly used for remote areas. A microgrid has two operational modes, grid-connected and isolated modes. In isolated mode operation, the microgrid needs to overcome the intermittent power generated by renewable energy resources (PV or wind turbines) as the amount of generation is largely affected by weather condition. In order to optimise the power dispatch and maintain power-quality for an islanded microgrid, an energy management system for a low-voltage islanded microgrid with an energy storage system (battery in this thesis) is presented. The main objective of this energy management system is to optimise power dispatch and to make effective use of power generated by renewable resources (solar power in this paper) for an islanded microgrid to achieve the purpose of installing an environmental friendly power grid. The proposed energy management system is divided into two parts. Firstly, the system determines the battery charging/discharging state and the backup DG operating time based on the power generated by PV, base DG and load demand in each time step. From the decision-making process, the battery power, battery state of charge and the backup DG operating time is available for the next stage of the energy management system. Secondly, the modified Gauss-Seidel load flow iteration process is run in MATLAB for computing the bus voltage and transmission line power losses in each time step. The Gauss-Seidel load flow analysis is a typical calculation strategy for evaluating the operation of power flow in an electrical network. In order to verify the effectiveness of the proposed energy management system, four case studies are provided in this report under different power profiles and load profiles. The energy management system is used not only for optimizing power dispatch for an isolated microgrid with renewable energy resources and an energy storage system, but also for sizing battery and diesel generators before the installation of the microgrid with reasonable prediction of load demand and renewable power generation.
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Moghimi, Mojtaba. "Modelling and Optimization of Energy Management Systems in Microgrids and Multi-Microgrids." Thesis, Griffith University, 2018. http://hdl.handle.net/10072/385882.

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With the new challenges brought by the high penetration of Renewable Energy Resources (RESs) into the modern grid, developing new solutions and concepts are necessary. Microgrid (MG) is one of the new concepts introduced to overcome upcoming issues in the modern electricity grids. MGs and Multi-Microgrids (MMGs) are defined as the building blocks of smart grids. MGs are the small units, where power generation and consumption happen at the same location and MG makes the decisions by itself. MGs can operate grid-connected or island mode depending on the functionality of the MG. Energy Management System (EMS) is the decision making centre of the MG. The data from the devices is received by the EMS and after processing, the commands are sent to the controllable components. Management of voltage, active and reactive power, neutral current, unit commitment and economic dispatch are of the tasks of EMS. In this PhD thesis, an optimal EMS for MGs and MMGs is developed. The main objective of this project by developing the EMS is to optimize the energy flow in the MGs and MMGs to obtain peak load shaving in a cost beneficial system. In order to achieve an efficient EMS, communication system, forecasting system, scheduling system, and optimization system are modelled and developed. Different types of EMS operation, centralized, decentralized and distributed, are investigated in this work to achieve the best combination for MMG EMS operation. The communication system is mainly utilizing Modbus TCP/IP protocol for data transmission at local level and Internet of Things (IoT) protocols (MQTT) for the global communication level. A communication operation algorithm is proposed to manage the MMG EMS under different communication operation modes and communication failure conditions. Furthermore, a monitoring system is developed to collect the data from different devices in the MG. The data is processed in the MG EMS and the commands are sent to components through the communication infrastructure. The link between MGs and MMGs is through the proposed two-level communication system, where the expansion of MGs to a MMG is investigated. In the MMG, MGs are functioning as a unit while having different priorities and operating under different policies. Each MG has its own MG EMS and the EMSs transfer information through the communication system between each other in either centralized, decentralized, distributed, or no communication modes under the MMG EMS. The forecasting system is required in the EMS to predict the future MG characteristics such as power generation and consumption. The forecasted data is the input to the optimization and scheduling system of EMS. Employing the forecasting system in the EMS would increase the accuracy of the optimization and scheduling systems. In this thesis, the timeseries-based forecasting algorithms are employed to predict next day’s active power using the load data, generation data, weather data and temperature data as the inputs. The heart of EMS is the scheduling and optimization system. The purpose of the scheduling system is to define the amount and the time of energy flow in the MG for different generation sources and consumption loads. Furthermore, scheduling system is responsible for peak load shaving and valley filling. On the other hand, the optimization system has the task of minimizing the operation costs of the MGs. The role of market in the scheduling and optimization is important. Time of Use (ToU) tariff is the pricing system, which determines the peak and off peak hours for energy usage pricing. In order to apply the optimization system, a model of the system, an objective function and systems constraints are defined, where aging of battery energy storage system (BESS), operational cost of components and MG cost benefits are considered. To operate the EMS scheduling and optimization system, IBM CPLEX Optimization Studio solver conducts the optimization while for the scheduling system, objective function and constraints are defined in MATLAB. In this thesis, a rule-based, MILP and MIQP optimization system for commercial MGs including electric vehicles (EVs) are proposed to investigate performance of MG EMS for different case studies. In this thesis, the literature for different scheduling and forecasting systems is investigated and different optimization algorithms are analysed. The communication protocols utilized in this research are described and compared to other protocols in the literature. In different chapters of this thesis, the modelling of MGs and MMG EMS, different modules of EMS, forecasting, optimization, scheduling and communication systems are described and analysed. A novel communication system for MMG EMS operation is proposed for commercial buildings. The performance of MG EMS and MMG EMS is examined for power and neutral current sharing, operation cost optimization, and demand peak shaving applications and results are compared to investigate the performance of proposed algorithms.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Eng & Built Env
Science, Environment, Engineering and Technology
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He, Youbiao. "The Energy Management of Next-generation Microgrid Systems." University of Akron / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=akron1500907510831555.

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Darden, Kelvin S. "Smart Microgrid Energy Management Using a Wireless Sensor Network." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1404560/.

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Modern power generation aims to utilize renewable energy sources such as solar power and wind to supply customers with power. This approach avoids exhaustion of fossil fuels as well as provides clean energy. Microgrids have become popular over the years, as they contain multiple renewable power sources and battery storage systems to supply power to the entities within the network. These microgrids can share power with the main grid or operate islanded from the grid. During an islanded scenario, self-sustainability is crucial to ensure balance between supply and demand within the microgrid. This can be accomplished by a smart microgrid that can monitor system conditions and respond to power imbalance by shedding loads based on priority. Such a method ensures security of the most important loads in the system and manages energy by automatically disconnecting lower priority loads until system conditions have improved. This thesis introduces a prioritized load shedding algorithm for the microgrid at the University of North Texas Discovery Park and highlight how such an energy management algorithm can add reliability to an islanded microgrid.
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Moussa, Hassan. "Contribution to the Decentralized Energy Management of Autonomous AC-Microgrid." Thesis, Université de Lorraine, 2017. http://www.theses.fr/2017LORR0161/document.

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Cette thèse porte sur des micro-réseaux AC isolées qui permettent l’intégration des ressources énergétiques distribuées (DER) pouvant fournir leur énergie d'alimentation existante de manière contrôlée pour assurer le bon fonctionnement global du système. L'interconnexion d'un DER à une micro-réseau s'effectue habituellement en utilisant un convertisseur d'interface distribué (DIC) (i.e. un bloc d'interface d'électronique de puissance générale) qui est constitué d’un module de convertisseur à l'entrée de la source, un onduleur de tension (VSI), un module d'interfaçage de sortie, et le module de commande. Dans cette thèse on réalise plusieurs lois de commande basées sur des méthodes décentralisées. L'accent principal est mis sur les fonctions "Droop" qui ont la tâche de maintenir un équilibre de distribution d'énergie entre les différentes sources énergétiques connectées à la micro-réseau. L'objectif est d'assurer la stabilité du système et d’améliorer les performances dynamiques en partageant la puissance entre les différents générateurs d’électricité distribués (DGs) en fonction de leur puissance nominale. Le développement d'une analyse de stabilité en boucle fermée s’avère utile pour étudier la dynamique du système afin d'obtenir une réponse transitoire souhaitée qui permet d'identifier les paramètres de contrôle de boucle appropriés. L'amélioration de la qualité d’énergie des micro-réseaux est également un objectif de cette thèse. La réduction des distorsions harmoniques de la tension de sortie en présence de charges linéaires et non linéaires est prise en compte dans nos travaux. D'autres aspects seront étudiés sur la façon de traiter les charges constantes connectées au réseau et les grandes perturbations qu’ils produisent. Cela donne lieu à d'autres études de recherche portant sur la stabilité grand signal des micro-réseaux
This thesis deals with islanded AC microgrid that allows any integration of Distributed Energy Resources (DERs) that may provide their existing supply energy in a controlled manner to insure overall system functioning. The interconnection of a DER to a microgrid is done usually by using a Distributed Interface Converter (DIC), a general power electronics interface block, which consists of a source input converter module, a Voltage Source Inverter module (VSI), an output interface module, and the controller module. The thesis realizes several control laws based on decentralized methods. The major focus is on the Droop functions that are responsible for providing a power distribution balance between different Energy Resources connected to a microgrid. The aim is to insure system stability and better dynamic performance when sharing the power between different DGs as function to their nominal power. Developing a closed loop stability analysis is useful for studying system dynamics in order to obtain a desired transient response that allows identifying the proper loop control parameters. Power Quality enhancement in microgrids is also a purpose of this research. The reduction of harmonic distortions of the output voltage when supplying linear and non-linear loads are taken in consideration in this thesis. Further aspects will be studied about how to deal with constant power loads connected to the grid and the large perturbations exerted. This results to further research studies that deal with large-signal stability of microgrids
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Lanas, Montecinos Fernando José, and Estevez Guillermo Jiménez. "Design of a robust energy management system for a grid-connected microgrid providing services." Tesis, Universidad de Chile, 2019. http://repositorio.uchile.cl/handle/2250/172645.

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Tesis para optar al grado de Magíster en Ciencias de la Ingeniería, Mención Eléctrica
Se define una microrred como una agrupación de cargas y recursos energéticos distribuidos que funciona como un único sistema controlable, capaz de operar en paralelo o aislado de la red eléctrica. Las microrredes son proveedores de energía locales que pueden reducir los gastos de energía, reducir las emisiones, aumentar la confiabilidad y son alternativas de energización emergentes. El correcto uso de sus recursos energéticos disponible permite lograr una operación más eficiente en una microrred, por ejemplo; reducir sus costos, mejorar ingresos, alargar la vida útil de los equipos y limitar el impacto ambiental. Algunos de estos objetivos se contraponen y es por esto que es necesario compensarlos para obtener el mejor despacho energético. Por esta razón el uso de un sistema de gestión de energía para microrredes cobra gran importancia. En este trabajo se desarrollaron modelos matemáticos y luego se implementaron en una herramienta computacional para el despacho energético óptimo de microrredes, con énfasis en tres aspectos. Primero, los servicios complementarios que una microrred puede ofrecer: arbitraje de energía, reducción de emisiones, reducción de potencia punta, reserva de potencia en giro y ofertas de reducción de consumo. Segundo, un modelo de almacenamiento de baterías enfocado en seis fenómenos: envejecimiento cíclico y calendario, la ley de Peukert, la pérdida de capacidad, autodescargas y la limitación de carga/descarga. Tercero, se incluye un módulo maestro-esclavo para lidiar con la estocasticidad ante problemas intempestivos en la red, manteniendo así la confiabilidad de la microrred cuando se aísla, aun si esta ofrece servicios. Estos tres aspectos son integrados en un modelo de programación lineal entera mixta para el despacho óptimo de una microrred, minimizando los costos de operación y reinversión. En el presente trabajo, se simulan la operación de tres microrredes reales bajo diferentes escenarios cada uno. El primer caso es la microrred aislada de Huatacondo, el segundo es la microrred conectada de CIGRE y el tercero es la microrred conectada de la cárcel de Santa Rita. Los resultados obtenidos muestran reducción en los costos de hasta 4.3% en la microrred de Huatacondo, hasta 2.9% para CIGRE y hasta 7% para Santa Rita al considerar servicios y utilizando un modelo detallado de almacenamiento. En el caso de la microrred aislada de Huatacondo, la reducción se basó principalmente en la extensión de la vida útil del banco de baterías. Para las dos microrredes conectadas los servicios más atractivos fueron ofrecer sus capacidades flexibles no utilizadas a la red. Esto considera servicios como reducción de consumo, reducción de demanda punta o reserva en giro. Servicios enfocados en transferencia de altos volúmenes de energía, como el arbitraje de energía, no fueron atractivos dado el costo asociado al uso de equipos de almacenamiento.
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Zia, Muhammad Fahad. "On energy management optimization for microgrids enriched with renewable energy sources Microgrids energy management systems: a critical review on methods, solutions, and prospects, in Applied Energy 222, July 2018 Optimal operational planning of scalable DC microgrid with demand response, islanding, and battery degradation cost considerations, in Applied Energy 237, March 2019 Energy management system for an islanded microgrid with convex relaxation, in IEEE Transactions on Industry Applications 55, Nov.-Dec. 2019 Microgrid transactive energy: review, architectures, distributed ledger technologies, and market analysis, in IEEE Access, January 2020." Thesis, Brest, 2020. http://theses-scd.univ-brest.fr/2020/These-2020-SPI-Genie_electrique-ZIA_Muhammad_Fahad.pdf.

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Le réseau électrique actuel est confronté à plusieurs défis liés aux exigences environnementales, à l'augmentation de la demande mondiale d'électricité, aux contraintes de fiabilité élevées, à la nécessité d’une énergie décarbonisée et aux restrictions de planification. Afin d’évoluer vers un système d'énergie électrique respectueux de l’environnement et intelligent, les installations de production centralisées sont de nos jours transformées en de plus petites centrales de génération distribuées. Le concept de micro-réseau émerge ainsi. Le micro-réseau peut être considéré comme un système de distribution basse tension avec un ensemble de charges contrôlables et de ressources énergétiques distribuées, qui peuvent inclure de nombreuses sources d'énergie renouvelables et des systèmes de stockage d'énergie. La gestion d’énergie d'un grand nombre de ressources énergétiques distribuées est nécessaire au bon fonctionnement d'un micro-réseau afin d’en assurer la stabilité, la fiabilité et la disponibilité. Par conséquent,un système de gestion d'énergie est au coeur de l'exploitation des micro-réseaux afin d’en assurer un développement économique et durable. À cet égard, cette thèse se focalise sur la proposition de modèles d'optimisation de système de gestion de l'énergie pour une exploitation optimale des micro-réseaux. Une gestion d’énergie optimale requiert la prise en compte de plusieurs contraintes techniques, économiques et environnementales. De plus, ces travaux de recherche prennent en considération un modèle pratique du coût de dégradation des batteries Li-ion. Le problème de gestion d’énergie optimale se traduit ainsi par un problème d’optimisation sous contraintes. La fonction objective regroupe le coût d'exploitation des générateurs distribués, le coût des émissions de gaz à effet de serre des sources de production conventionnelles, l’obligation d’une utilisation maximale des sources d'énergie renouvelables, le coût de dégradation des batteries, les différentes incitations afin de modifier le profil de la demande et des pénalités en cas de délestage. Les contraintes quant à elles sont liées aux contraintes techniques des différents sous-systèmes du micro-réseau. Par ailleurs, un modèle conceptuel complet à sept couches est également développé afin de fournir des informations normalisées sur la mise en oeuvre d’une nouvelle économie de l’énergie
The current electric power system isfacing the challenges of environmental protection,increasing global electricity demand, high reliability requirement, cleanliness of energy, and planning restrictions. To evolve towards green and smart electric power system, centralized generating facilities are now being transformed into smaller and more distributed generations. As a consequence, the concept of microgrid emerges, where a microgrid can operate as a single controllable system and can be assumed as a cluster of loads and distributed energy resources, which may include many renewable energy sources and energy storage systems. The energy management of large numbers of distributed energy resources is needed for reliable operation of microgrid system. Therefore, energy management is the fundamental part of the microgrid operation for economical and sustainable development. In this regard, this thesis focuses on proposing energy management optimization models for optimal operation of microgrid system that include proposed practical Li-ion battery degradation cost model. These different energy management models include objective functions of operating cost of distributed generators, emission cost of conventional generation source, maximum utilization of renewable energy sources, battery degradation cost, demand response incentives, and load shedding penalization cost, with microgrid component and physical network constraints. A comprehensive conceptual seven layer model is also developed to provide standardized insights in implementing real transactive energy systems
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Books on the topic "Microgrid energy management system"

1

Khan, Baseem, Sanjeevikumar Padmanaban, Hassan Haes Alhelou, Om Prakash Mahela, and S. Rajkumar. Artificial Intelligence-Based Energy Management Systems for Smart Microgrids. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/b22884.

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Frederic, March, and Cohen Tim (Timothy), eds. Inside energy: Developing and managing an ISO 50000 energy management system. Boca Raton, Fla: CRC, 2011.

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Birtles, A. B. Performance of a PSA trial energy management system. Watford: Building Research Establishment, 1985.

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Al-Hinai, Amer, and Hassan Haes Alhelou. Energy Management System for Dispatchable Renewable Power Generation. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003307433.

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Jentgen, Lawrence A. Implementing a prototype energy and water quality management system. Denver, CO: Awwa Research Foundation, 2003.

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United States. Dept. of Energy. Office of Civilian Radioactive Waste Management. Program management system manual. 3rd ed. Washington, DC: U.S. Dept. of Energy, Office of Civilian Radioactive Waste Management, 1989.

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Roberts, Martin. A heat metering system for energy management on an industrial site. Birmingham: University of Aston. Department of Production Technology and Production Management, 1985.

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Tripathi, Saurabh Mani, Kirti Pal, and Shruti Pandey. Advanced Control & Optimization Paradigms for Energy System Operation and Management. New York: River Publishers, 2023. http://dx.doi.org/10.1201/9781003337003.

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Narrin, Janeanne. One degree beyond: A Reiki journey into energy medicine. 2nd ed. Seattle, Wash: Little White Buffalo Publishing, 1998.

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May, William B. Building emulation computer program for testing of energy management and control system algorithms. [Gaithersburg, MD]: U.S. Dept. of Commerce, National Bureau of Standards, 1985.

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Book chapters on the topic "Microgrid energy management system"

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So, Janet. "Energy Management System." In Smart Microgrids, 161–92. Taylor & Francis Group, 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742: CRC Press, 2016. http://dx.doi.org/10.1201/9781315372679-7.

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de Graaf, Florijn, and Simon Goddek. "Smarthoods: Aquaponics Integrated Microgrids." In Aquaponics Food Production Systems, 379–92. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-15943-6_15.

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AbstractWith the pressure to transition towards a fully renewable energy system increasing, a new type of power system architecture is emerging: the microgrid. A microgrid integrates a multitude of decentralised renewable energy technologies using smart energy management systems, in order to efficiently balance the local production and consumption of renewable energy, resulting in a high degree of flexibility and resilience. Generally, the performance of a microgrid increases with the number of technologies present, although it remains difficult to create a fully autonomous microgrid within economic reason (de Graaf F, New strategies for smart integrated decentralised energy systems, 2018). In order to improve the self-sufficiency and flexibility of these microgrids, this research proposes integrating a neighbourhood microgrid with an urban agriculture facility that houses a decoupled multi-loop aquaponics facility. This new concept is called Smarthood, where all Food–Water–Energy flows are circularly connected. In doing so, the performance of the microgrid greatly improves, due to the high flexibility present within the thermal mass, pumps and lighting systems. As a result, it is possible to achieve 95.38% power and 100% heat self-sufficiency. This result is promising, as it could pave the way towards realising these fully circular, decentralised Food–Water–Energy systems.
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Wu, Hongxia. "Microgrid energy management system and intelligent control technology." In Machinery, Materials Science and Engineering Applications, 579–84. CRC Press/Balkema P.O. Box 11320, 2301 EH Leiden, The Netherlands: CRC Press/Balkema, 2016. http://dx.doi.org/10.1201/9781315375120-83.

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Yadav, Raj Kumar, and Dipti Saxena. "An Energy Management System for Microgrid Resilience Improvement." In Innovations in Cyber Physical Systems, 667–73. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4149-7_60.

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Mathur, Divya, Neeraj Kanwar, and Sunil Kumar Goyal. "Battery Energy Management for Community Microgrid." In Intelligent Computing Techniques for Smart Energy Systems, 723–31. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0252-9_65.

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Zhang, Di, Songsong Liu, and Lazaros G. Papageorgiou. "Energy Management of Smart Homes with Microgrid." In Advances in Energy Systems Engineering, 507–33. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-42803-1_17.

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Al Hasani, Muntaser, Amer Al-Hinai, Hassan Haes Alhelou, Ahmed Al Maashri, and Hassan Yousef. "Renewable Microgrid Modeling, Simulation, and Results Analysis." In Energy Management System for Dispatchable Renewable Power Generation, 45–78. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003307433-2.

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Jain, Rashmi, Sachin Jain, and Sanchit Jain. "Smart Microgrid-Based Energy Management Using Blockchain." In Blockchain for Smart Systems, 177–93. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003203933-15.

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Vijayalakshmi, K., N. Pavithra, R. Amrutha, and T. K. Santhosh. "Energy Management System for Stand-Alone Microgrid with Renewable Energy Resource." In Lecture Notes in Electrical Engineering, 367–76. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0193-5_30.

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Wee, Ng Rong, and J. J. Jamian. "Rule-Based-Iterative Energy Management System for Islanded Hybrid Microgrid System." In Lecture Notes in Electrical Engineering, 291–303. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8690-0_27.

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Conference papers on the topic "Microgrid energy management system"

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Sharma, Ratnesh K., and Koji Kudo. "Integrated Management of Energy Storage for Sustainable Operation of Energy Microgrids." In ASME 2011 International Mechanical Engineering Congress and Exposition. ASMEDC, 2011. http://dx.doi.org/10.1115/imece2011-65711.

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Energy microgrids are a key building block of smart grids. Energy microgrids can not only provide voltage and VAR support to the power grid but also reduce the emission footprint of the overall power generation infrastructure. While it provides added advantages like grid decongestion and reduced operating cost for system operators, it creates significant challenges in stable operation and meeting economic goals of the microgrid owners. Currently, energy microgrids are heavily subsidized through government grants/rebates and require high maintenance in terms of skilled operating staff and advance control systems. In this paper, we propose a microgrid energy storage architecture that could reduce the cost of ownership and simplify control and management of energy microgrids while retaining the advantages of reduced emissions and resource consumption. The controls existing in normal energy storage also offers unique opportunities in simplifying the control system of such distributed generation infrastructure and improving the reliability of microgrid in meeting local demand constraints. From a utility operator’s perspective, energy storage provides a reliable and dispatchable source as opposed to intermittent distributed energy resources.
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Kowalczyk, Albert, Adrian Wlodarczyk, and Jaroslaw Tarnawski. "Microgrid energy management system." In 2016 21st International Conference on Methods and Models in Automation and Robotics (MMAR). IEEE, 2016. http://dx.doi.org/10.1109/mmar.2016.7575125.

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Moussavou, A. A. Aminou, M. Adonis, and A. K. Raji. "Microgrid energy management system control strategy." In 2015 International Conference on the Industrial and Commercial Use of Energy (ICUE). IEEE, 2015. http://dx.doi.org/10.1109/icue.2015.7280261.

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Qingping Wang and Peng Zhang. "Energy management system for multi-microgrid." In 2014 China International Conference on Electricity Distribution (CICED). IEEE, 2014. http://dx.doi.org/10.1109/ciced.2014.6991834.

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Kun, Yin, Liu Yajuan, Yi Guowei, and Zhou Peng. "Considering Energy Storage System Energy Management in Microgrid." In 2015 Seventh International Conference on Measuring Technology and Mechatronics Automation (ICMTMA). IEEE, 2015. http://dx.doi.org/10.1109/icmtma.2015.78.

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Oureilidis, Konstantinos O., and Charis S. Demoulias. "Microgrid wireless energy management with energy storage system." In 2012 47th International Universities Power Engineering Conference (UPEC). IEEE, 2012. http://dx.doi.org/10.1109/upec.2012.6398684.

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Polprasert, Jirawadee, Khanittha Wannakhong, Pongsakorn Narkvichian, and Anant Oonsivilai. "Home Energy Management System and Optimizing Energy in Microgrid Systems." In 2021 International Conference on Power, Energy and Innovations (ICPEI). IEEE, 2021. http://dx.doi.org/10.1109/icpei52436.2021.9690685.

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Sheikh, Imran. "Hybrid energy management system for microgrid applications." In 2016 International Conference on Energy Efficient Technologies for Sustainability (ICEETS). IEEE, 2016. http://dx.doi.org/10.1109/iceets.2016.7583781.

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Bhavsar, Yogesh S., Prasad V. Joshi, and Sonali M. Akolkar. "Simulation of Microgrid with energy management system." In 2015 International Conference on Energy Systems and Applications. IEEE, 2015. http://dx.doi.org/10.1109/icesa.2015.7503418.

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Ding, Ming, Zhengkai Zhang, and Xuefeng Guo. "CIM Extension of Microgrid Energy Management System." In 2009 Asia-Pacific Power and Energy Engineering Conference. IEEE, 2009. http://dx.doi.org/10.1109/appeec.2009.4918216.

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Reports on the topic "Microgrid energy management system"

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Singh, Ravindra, Jim Reilly, Albert Phan, Eric Stein, Dimitrije Kotur, Mladen Petrovic, Will Allen, and Monica Smith. Microgrid Energy Management System Integration with Advanced Distribution Management System. Office of Scientific and Technical Information (OSTI), September 2020. http://dx.doi.org/10.2172/1706120.

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Liu, Guodong, Michael R. Starke, and Andrew N. Herron. Microgrid Controller and Advanced Distribution Management System Survey Report. Office of Scientific and Technical Information (OSTI), July 2016. http://dx.doi.org/10.2172/1287035.

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Bose, Sumit. Smart Microgrid Energy Management Controls for Improved Energy Efficiency and Renewables Integration at DoD Installations. Fort Belvoir, VA: Defense Technical Information Center, April 2013. http://dx.doi.org/10.21236/ada600329.

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Singh, Ravindra, James T. Reilly, Jianhui Wang, Xiaonan Lu, and Ning Kang. Foundational Report Series: Advanced Distribution Management Systems for Grid Modernization, DMS Integration of Distributed Energy Resources and Microgrids. Office of Scientific and Technical Information (OSTI), March 2017. http://dx.doi.org/10.2172/1351116.

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Mohanpurkar, Manish, Yusheng Luo, Rob Hovsapian, and Anudeep Medam. Real-time Modeling and Testing of Microgrid Management System for the Blue Lake Rancheria - Performance Assurance Report. Office of Scientific and Technical Information (OSTI), November 2017. http://dx.doi.org/10.2172/1426889.

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Mohanpurkar, Manish, Yusheng Luo, Rob Hovsapian, and Anudeep Medam. Real-time Modeling and Testing of Microgrid Management System for the Blue Lake Rancheria - Performance Assurance Report. Office of Scientific and Technical Information (OSTI), November 2017. http://dx.doi.org/10.2172/1466985.

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Zandi, Helia, Teja Kuruganti, David Fugate, and Edward Allan Vineyard. VOLTTRON-enabled Home Energy Management System. Office of Scientific and Technical Information (OSTI), January 2019. http://dx.doi.org/10.2172/1510585.

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Majewski, Susan, Mordecai Cooke, and Derek Canady. Energy Management System Study : Phase I. Office of Scientific and Technical Information (OSTI), April 1989. http://dx.doi.org/10.2172/5318810.

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Fowler, Kimberly M., Christopher J. Anderson, and Benjamin E. Ford. Energy Data Management System Commercial Product Summary. Office of Scientific and Technical Information (OSTI), September 2017. http://dx.doi.org/10.2172/1400350.

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Author, Not Given. Energy Management System Lowers U.S. Navy Energy Costs Through PV System Interconnection (Fact Sheet). Office of Scientific and Technical Information (OSTI), April 2014. http://dx.doi.org/10.2172/1127270.

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