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Academic literature on the topic 'Networked microgrid'

Author: Grafiati

Published: 5 June 2025

Last updated: 24 June 2025

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Journal articles on the topic "Networked microgrid"

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Mohd Yassim, Halyani, Mohd Noor Abdullah, and Chin Kim Gan. "A COMPARISON OF POWER FLOW BASED ON BUS ADMITTANCE MATRIX FOR NETWORKED MICROGRID ENERGY MANAGEMENT GY MANAGEMENT." ASEAN Engineering Journal 14, no. 2 (2024): 27–35. http://dx.doi.org/10.11113/aej.v14.20603.

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A networked microgrid with an energy management system connects several microgrids to exchange power for cost-effective and reliable operation. The feasibility study is required as a basis for developing an efficient networked microgrid energy management plan. This paper presented a detailed power flow analysis of a networked microgrid. Multiple IEEE microgrids are interconnected in the networked microgrid system, and various types of distributed generators are modeled based on PQ and PV control schemes. Different power flow algorithms based on the bus admittance matrix are used in the MATLAB simulation. Several case studies demonstrated the feasibility of the networked microgrid in grid connected and islanded modes as well as the effectiveness of the Fast-Decoupled (BX version) method in facilitating power exchange between microgrids to maintain supply-demand balance under normal and abnormal conditions. The results proved that the Fast- Decoupled (BX version) method is significantly faster than the Fast- Decoupled (XB version) and Newton-Raphson methods and has better convergence than the Gauss-Seidel method.

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Hussein, Hossam M., S. M. Sajjad Hossain Rafin, Mahmoud S. Abdelrahman, and Osama A. Mohammed. "Hardware Implementation of a Resilient Energy Management System for Networked Microgrids." World Electric Vehicle Journal 15, no. 5 (2024): 209. http://dx.doi.org/10.3390/wevj15050209.

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A networked microgrid is composed of multiple nearby microgrids linked together to gain additional flexibility for resilient operations. Networked microgrids collaborate to prevent power shortages in microgrid clusters by sharing critical renewable and energy storage resources. However, controlling the local resources of each microgrid, including the energy storage systems’ charging and discharging, maintaining the DC bus voltage, and even overseeing the power shared by multiple microgrids, is challenging. Therefore, a microgrid control technique and distributed energy management are used cooperatively in this study to handle the shared power between a system of networked microgrids incorporating photovoltaics and battery energy storage systems. Numerical simulation results from a networked microgrid system verify the accuracy and soundness of the suggested distributed energy management under several operating conditions, including renewable uncertainties and sequential load variations in different zones. The applicability of the suggested technique is confirmed by hardware implementation, and several operational scenarios further evaluate the proposed system on a practical two-microgrid system located in the Florida International University (FIU) testbed.

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Bula, Carlos Mauricio, Muhammad Atiq Ur Rehman, Sergio Rivera, and Suheel Abdullah. "Fault-Tolerant Optimization and Control of a Microgrid Operation in Networked Microgrids." WSEAS TRANSACTIONS ON POWER SYSTEMS 20 (May 14, 2025): 101–13. https://doi.org/10.37394/232016.2025.20.10.

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Networked microgrid operation and control is supported by fault-tolerant optimization. In networked microgrids, the microgrid failure or dysconnectivity from the network is obvious and must be rectified and restored in real-time. For this purpose, we need advanced algorithms for fault-tolerant optimization and its control in networked microgrids operation. We have introduced a multi-objective genetic algorithm (MOGA) to solve the multi-objective optimization problem. Genetic algorithms being meta-heuristic techniques are used to solve formulated complex optimization problems; fault-tolerant optimization problems (FTOP). A fault-tolerant optimization problem (FTOP) has the possibility of partial components of the system failing or generating errors during the operation of networked microgrids. For this problem, we have determined the best possible solution which is obtained even in the presence of failure or errors as well. We have minimized the total cost of the system and provision of a consistent supply of energy in case of failure of a microgrid in the networked microgrids to get stable and reliable energy. FTOP problems mostly occur in critical and uncertain systems like microgrids in which reliable power is the demand from the customers with continuous availability.

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Liu, Guodong, and Michael Starke. "Networked Microgrid Energy Management Considering Ownership and Control Structures: A Comparison." Energies 18, no. 5 (2025): 1115. https://doi.org/10.3390/en18051115.

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With the growing deployment of microgrids, networked microgrids have emerged for their additional advantages of economy, reliability and resilience by coordinating the operation of multiple microgrids. As microgrids are operated with different ownership, objectives and functionalities, the formed networked microgrids show characteristics of mixed ownership, inconsistent objectives and various functionalities. To enable the coordinated operation of networked microgrids, three control structures, i.e., centralized, distributed and decentralized, have been constructed in the literature. However, the data sharing enabling these different paradigms and the resulted value propositions are not well defined, leading to poor resource management and resilience, etc. To solve this issue, a complete comparison of networked microgrid energy management under centralized, distributed and decentralized structures are performed. As a novel contribution, the required minimum data exchange of networked microgrid energy management under three control structures are identified, respectively. The value propositions are calculated and compared against each other by the results of case studies.

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Sharma, Desh Deepak. "Token-Based Smart Power Contract for Interoperable Blockchains of Networked Microgrid System." New Energy Exploitation and Application 2, no. 1 (2023): 8–20. http://dx.doi.org/10.54963/neea.v2i1.118.

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Designing the secure and privacy-protected smart power contract between electricity suppliers and consumers, considered agents, of different microgrids, is a challenging task in the networked- microgrid system. A framework is suggested in which each microgrid implements a heterogeneous or isomorphic blockchain based platform. The blockchain interoperability, inherently, is present in different blockchains implemented by various microgrids. This paper reviews the interoperability issues and smart contract designs in blockchain based systems. The paper proposes new mechanisms to cater blockchain interoperability challenges to facilitate the design of secure and seamless smart contracts among different blockchains of microgrids. A network hub of heterogeneous or isomorphic blockchains of network microgrids has been created. A methodology has been developed to transfer tokens between interoperable blockchains. Distributed identity-based microgrid (DIBM) scheme is incorporated to make the networked microgrid system secure and trustworthy. This paper suggests an effective consensus protocol for cross-chain architecture that improves the tokenization system and smart power contract designs. For simulation purposes, MATLAB and python programming have been used with real-time data of microgrids.

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Ali, Muyeen, Bizhani, and Ghosh. "Comparative Study on Game-Theoretic Optimum Sizing and Economical Analysis of a Networked Microgrid." Energies 12, no. 20 (2019): 4004. http://dx.doi.org/10.3390/en12204004.

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In this paper, two techniques of game theory are considered for sizing and comparative analysis of a grid-connected networked microgrid, based on a multi-objective imperialistic competition algorithm (ICA) for system optimization. The selected networked microgrid, which consists of two different grid-connected microgrids with common electrical load and main grid, might have different combinations of generation resources including wind turbine, photovoltaic panels, and batteries. The game theory technique of Nash equilibrium is developed to perform the effective sizing of the networked microgrid in which capacities of the generation resources and batteries are considered as players and annual profit as payoff. In order to meet the equilibrium point and the optimum sizes of generation resources, all possible coalitions between the players are considered; ICA, which is frequently used in optimization applications, is implemented using MATLAB software. Both techniques of game theory, Shapley values and Nash equilibrium, are used to find the annual profit of each microgrid, and results are compared based on optimum sizing, and maximum values of annual profit are identified. Finally, in order to validate the results of the networked microgrid, the sensitivity analysis is studied to examine the impact of electricity price and discount rates on maximum values of profit for both game theory techniques.

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Ediriweera, W. E. P. Sampath, N. W. A. Lidula, and R. Samarasinghe. "Ring connected microgrid clusters for improved resiliency in distribution systems with high solar PV penetration." AIMS Energy 12, no. 4 (2024): 872–904. http://dx.doi.org/10.3934/energy.2024041.

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<p>A ring-connected microgrid cluster can be formed by connecting geographically closed microgrids for mutual power sharing to increase the system's reliability. Real-time power balance within individual microgrids and power sharing among the microgrids of an islanded microgrid cluster would be challenging during contingencies if they are not properly sized and controlled. We propose a technique to design a ring-connected microgrid cluster that has several distributed energy resources. The amount of power flow via interconnecting cables was decided considering the size of the energy storage of the neighboring microgrids. A control system was designed to minimize the effect of severe transients in the neighboring microgrids in the network. The performance of the proposed technique was verified using a ring-connected microgrid cluster with four microgrids derived based on a real distribution system. The results illustrated that the proposed ring-connected microgrid cluster could maintain the power balance of the networked microgrid during the contingencies of neighboring microgrids, increasing the resiliency of the system compared to the radial and islanded operations.</p>

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Khalghani, Mohammad Reza, Vishal Verma, Sarika Khushalani Solanki, and Jignesh M. Solanki. "Resilient Networked Control of Inverter-Based Microgrids against False Data Injections." Electronics 11, no. 5 (2022): 780. http://dx.doi.org/10.3390/electronics11050780.

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Inverter-based energy resource is a fast emerging technology for microgrids. Operation of micorgrids with integration of these resources, especially in an islanded operation mode, is challenging. To effectively capture microgrid dynamics and also control these resources in islanded microgrids, a heavy cyber and communication infrastructure is required. This high reliance of microgrids on cyber interfaces makes these systems prone to cyber-disruptions. Hence, the hierarchical control of microgrids, including primary, secondary, and tertiary control, needs to be developed to operate resiliently. This paper shows the vulnerability of microgrid control in the presence of False Data Injection (FDI) attack, which is one type of cyber-disruption. Then, this paper focuses on designing a resilient secondary control based on Unknown Input Observer (UIO) against FDI. The simulation results show the superior performance of the proposed controller over other standard controllers.

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Rehman, Muhammad Atiq Ur, Sergio Rivera, Muhammad Sajjad Khan, and Suheel Abdullah. "Multi-Objective Optimization for Load Balancing and Trading Scheduling in Networked Microgrids." WSEAS TRANSACTIONS ON SYSTEMS 23 (December 16, 2024): 339–53. https://doi.org/10.37394/23202.2024.23.38.

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Renewable energy resources are considered an integral part of networked microgrids. Networked microgrids provide an optimal solution for stable and reliable energy to the end consumers even in case of its islanded mode of operation. There are several explicit analytical mathematical formulations for optimization of operations of networked microgrids including load balancing and trade scheduling of energy. Mostly, the scheduling problem in networked microgrids is the job of distribution operators to use common scheduling tools. In this paper, we present the mathematical formulation of multi-objective cost functions and their optimization by using the multi-objective particle swarm optimization (MOPSO) algorithm. Multi-objective cost functions and duality gap are designed and then the problem is solved by introducing MOPSO which has more than one objective function. The total energy cost function is then optimized in order to get swarm swarm-optimal solution. This algorithm computed the local energy generation and demand of each networked microgrid and made the decision of what energy is needed to buy or sell supported by each iteration of the operation of networked microgrids. We used an optimization formulation and its dual conception in order to propose the problem as a multi-objective formulation. The proposed method can deal with convex and nonconvex cost functions. In the case of non-convex functions, we have used the uncertainty cost functions for renewable sources attached to the networked microgrids.

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Ali, Asfand Yar, Akhtar Hussain, Ju-Won Baek, and Hak-Man Kim. "Optimal Operation of Networked Microgrids for Enhancing Resilience Using Mobile Electric Vehicles." Energies 14, no. 1 (2020): 142. http://dx.doi.org/10.3390/en14010142.

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The increased intensity and frequency of natural disasters have attracted the attention of researchers in the power sector to enhance the resilience of power systems. Microgrids are considered as a potential solution to enhance the resilience of power systems using local resources, such as renewable energy sources, electric vehicles (EV), and energy storage systems. However, the deployment of an additional storage system for resilience can increase the investment cost. Therefore, in this study, the usage of existing EVs in microgrids is proposed as a solution to increase the resilience of microgrids with outages without the need for additional investment. In the case of contingencies, the proposed algorithm supplies energy to islanded microgrids from grid-connected microgrids by using mobile EVs. The process for the selection of EVs for supplying energy to islanded microgrids is carried out in three steps. Firstly, islanded and networked microgrids inform the central energy management system (CEMS) about the required and available energy stored in EVs, respectively. Secondly, CEMS determines the microgrids among networked microgrids to supply energy to the islanded microgrid. Finally, the selected microgrids determine the EVs for supplying energy to the islanded microgrid. Simulations have shown the effectiveness of the proposed algorithm in enhancing the resilience of microgrids even in the absence of power connection among microgrids.

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Dissertations / Theses on the topic "Networked microgrid"

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Zhang, Fan. "Operation of Networked Microgrids in the Electrical Distribution System." Case Western Reserve University School of Graduate Studies / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=case1467974481.

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Yao, Lisha. "Distributed Consensus, Optimization and Computation in Networked Systems." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1404555/.

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In the first part of this thesis, we propose a distributed consensus algorithm under multi-layer multi-group structure with communication time delays. It is proven that the consensus will be achieved in both time-varying and fixed communication delays. In the second part, we study the distributed optimization problem with a finite-time mechanism. It is shown that our distributed proportional-integral algorithm can exponentially converge to the unique global minimizer when the gain parameters satisfy the sufficient conditions. Moreover, we equip the proposed algorithm with a decentralized algorithm, which enables an arbitrarily chosen agent to compute the exact global minimizer within a finite number of time steps, using its own states observed over a successive time steps. In the third part, it is shown the implementation of accelerated distributed energy management for microgrids is achieved. The results presented in the thesis are corroborated by simulations or experiments.

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Irwin, Robert. "Evaluation of a Generator Networked Control System in the Presence of Cyberattacks." Master's thesis, Temple University Libraries, 2017. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/433164.

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Educational Psychology<br>M.S.E.E.<br>With the advancement of technology, there has been a push to transition from the conventional electric grid to a smart grid. A smart grid is an electric delivery system that uses technology such as electronic sensors and digital communication networks to improve the reliability, resilience, and efficiency of the system. The transition toward a smart grid has increased the importance of networked control systems (NCS), which are the infrastructure that allows sensors, actuators and controllers to exchange information via a digital communication network. The research presents the development of an islanded generator NCS, and a grid connected NCS, and the investigation of the effects of cyberattacks on the NCS. This research considers two types of cyberattacks, such as Denial-of-Service (DoS) attack, and false data injection in the generator control loop. DoS attacks greatly increase the rate of packet loss and the duration of packet delay in a network. A high degree of packet drop and delay degrade the performance of the controller, which causes problems in the synchronization of the generator with the rest of the grid. False data injection in the sensors alters the generator terminal voltage and power output, and can cause the generator to lose synchronism. A mathematical model of the generator NCS systems is developed which includes the data acquisition and network characteristics, as well as the generator dynamics. The stability analysis of each NCS is performed which provides a mathematical approach to understanding the severity of cyberattacks that the system can tolerate before becoming unstable. The performance of the controllers, with respect to voltage control, is experimentally evaluated.<br>Temple University--Theses

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Omara, Ahmed Mohamed Elsayed. "Predictive Operational Strategies for Smart Microgrid Networks." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/40101.

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There have been significant advances in communication technologies over the last decade, such as cellular networks, Wi-Fi, and optical communication. Not only does the technology impact peoples’ everyday lives, but it also helps cities prepare for power outages by collecting and exchanging data that facilitates real-time status monitoring of transmission and distribution lines. Smart grids, contrary to the traditional utility grids, allow bi-directional flow of electricity and information, such as grid status and customer requirements, among different parties in the grid. Thus, smart grids reduce the power losses and increase the efficiency of electricity generation and distribution, as they allow for the exchange of information between subsystems. However, smart grids is not resilient under extreme conditions, particularly when the utility grid is unavailable. With the increasing penetration of the renewable energy sources (RES) in smart grids, the uncertainty of the generated power from the distributed generators (DGs) has brought new challenges to smart grids in general and smart microgrids in particular. The rapid change of the weather conditions can directly affect the amount of the generated power from RES such as wind turbine and solar panels, and thus degrading the reliability and resiliency of the smart microgrids. Therefore, new strategies and technologies to improve power reliability,sustainability, and resiliency have emerged. To this end, in this thesis, we propose a novel framework to improve the smart microgrids reliability and resiliency under severe conditions. We study the transition to the grid-connected operational mode in smart microgrids,in the absence of the utility grid, as an example of emergency case that requires fast and accurate response. We perform a comparative study to accurately predict upcoming grid-connected events using machine learning techniques. We show that decision tree models achieve the best average prediction performance. The packets that carry the occurrence time of the next grid-connected transition are considered urgent packets. Hence, we per-form an extensive study of a smart data aggregation approach that considers the priority of the data. The received smart microgrids data is clustered based on the delay-sensitivity into three groups using k-means algorithm. Our delay-aware technique successfully reduces the queuing delay by 93% for the packets of delay-sensitive (urgent) messages and the Packet Loss Rate (PLR) by 7% when compared to the benchmark where no aggregation mechanism exists prior to the small-cell base stations. As a mitigation action of the utility grid unavailability, we use the electrical vehicles (EVs) batteries as mobile storage units to cover smart microgrids power needs until the utility grid recovery. We formulate a Mixed Integer Linear Programming (MILP) model to find the best set of electrical vehicles with the objective of minimum cost. The EVs participating in the emergency power supply process are selected based on the distance and throughput performance between the base station and the EVs

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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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Constante, Flores Gonzalo Esteban. "Conservation Voltage Reduction of Active Distribution Systems with Networked Microgrids." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1531861356445195.

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Qiu, Quanwei. "Networked Model Predictive Control for Microgrids with Distributed PV Generators." Thesis, Griffith University, 2020. http://hdl.handle.net/10072/400460.

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More and more renewable energy sources are being integrated into microgrids—and while this causes many control challenges for microgrids, it can also yield numerous economic and environmental benefits. Therefore, it is necessary to develop proper control schemes for microgrids to address the different control issues in their hierarchical structure while adapting to the different time scales of the three control levels. Conversely, because model predictive control (MPC) has significant advantages—the inclusion of forecasts, the simplicity of the algorithm, and the flexibility to handle hard constraints—it has attracted significant attention in industrial control systems. Motivated by these factors, this research focuses on implementing MPC techniques in microgrids, which are solely supplied by photovoltaic (PV) generators, to address different control problems. For primary control of the microgrid hierarchy, which is mainly responsible for the inner control of the local distributed generation units, MPC can be applied to control of the power converters that serve as interfaces between the sources and the loads. Therefore, in this control level, a novel output-feedback MPC technique based on ellipsoidal set-membership state estimation is designed for a direct current to direct current (DC-DC) converter, considering the unknown-but-bounded external disturbances. A long-horizon finite-states (FS) MPC strategy is designed for the direct current to alternating current (DC-AC) inverter to reduce the sampling and switching frequency through a multi-step implementation approach and a control sequence rearrangement method. For secondary control, which is in charge of the compensation for the frequency and voltage deviations and is usually communication-based, the distributed MPC strategy can be used to realize the desired cooperative control among the geographically dispersed units. Thus, a novel distributed model predictive controller is developed to enhance system performance. It takes into account the fact that the distributed controllers’ communication network might be subject to switching topology due to the disconnection and reconnection of controllers, random failures, and recoveries of the links between controllers. A Markov chain with a time-varying probability transition matrix is used to describe the stochastic topology evolution of the control network. Tertiary control is used to coordinate the power flow between the microgrid and the utility grid and offers economic operations for microgrids. Since the integration of renewable energy sources causes low inertia and power fluctuation in microgrids, battery energy storage is essential to addressing these issues. To coordinate the charging/discharging schedule of the battery storage units, a networked MPC strategy can be adopted to realize the communication between different microgrid components and make use of the forecasts for PV power generation and load demand. The multi-microgrid system is considered subject to partial fault because of non-functional generators, batteries, or even transmission lines in this research. Hence, both the connection status of the electrical grid and the communication network are incorporated into the system modeling. In addition, the set-membership estimation is adopted to deal with the possible state unavailability caused by non-functional batteries or communication failures. In the theoretical section of this thesis, different sufficient conditions are established to ensure the stability of the investigated systems, and the optimal control inputs are obtained by solving the corresponding optimization problems. For easy implementation with MATLAB solvers, all the constraints and conditions of the optimization problems are transformed into linear matrix inequalities. Different recursive MPC algorithms are designed to control the target systems, and some extended algorithms are also developed to assist with the computation to determine the optimal solutions. In the demonstration section of this thesis, the designed controllers are all implemented in the numerical simulations or Simulink tests to verify their effectiveness, and an experimental test based on Raspberry Pi is conducted to demonstrate the wireless communication employing the designed networked model predictive controller.<br>Thesis (PhD Doctorate)<br>Doctor of Philosophy (PhD)<br>School of Eng & Built Env<br>Science, Environment, Engineering and Technology<br>Full Text

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Islam, Mojaharul. "Control and Optimisation of Grid-Connected Microgrids for Tie-line Smoothing." Thesis, Griffith University, 2021. http://hdl.handle.net/10072/404162.

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Renewable energy resources (RESs) are significantly integrated in distribution networks to promote green technologies in future power systems. The idea of microgrids (MGs) is developed for the efficient use of RESs through an appropriate control, monitoring and management system. Control and management of MGs are challenging tasks along with numerous economic and environmental benefits. The challenges of MGs operation include tie-line power fluctuations that have an adverse effect on the stability and quality of distribution networks. Tie-line power control in a residential MG is difficult due to dependency on RESs as a primary generation unit in MGs. Motivated by these, this thesis investigates the tie-line power control issues in grid-connected residential MGs and applies several controls and optimisation methods to achieve a smooth tie-line power satisfying system boundary conditions. First, a dynamic energy management system (EMS) is designed to reduce the tie-line fluctuation in a grid-connected MG through an indirect grid power control strategy. A fuzzy logic-based EMS is proposed to control the battery power due to the variations in generations and loads. The net power demand and battery state of charge (SoC) of an MG are considered inputs of the fuzzy controller to determine the battery power by keeping the battery SoC within limits. An offline optimisation method is used to optimise the membership functions and rules to shape the performance parameters. Thereafter, a golden section search-based non-linear programming method is applied to design a battery power management system to minimise the tie-line fluctuation in an MG counting the system constraints and disturbances. Two other rule-based methods are also demonstrated for comparative analysis of the proposed methods in terms of predefined performance parameters. Afterward, a dynamic grid power control method is presented to control the interlink inverters in grid-connected MGs. A grid power controller is designed based on a complete model of the MG systems to achieve a constant tie-line power on typical days of the year. The designed controller can effectively smooth tie-line fluctuation in a grid-connected residential MG. The charging/ discharging of the battery is controlled by a DC-DC converter which is also responsible to provide a stable DC bus to the input of an interlink inverter. The reference tie-line power is determined by a MG controller based on statistical power generations, load demand and battery SoC. Moreover, an eigenvalue-based stability analysis is performed to show the sensitivity of system parameters on system stability. Furthermore, the tie-line power control in a networked MG (NMG) is investigated to obtain a smooth tie-line power in an NMG connected to a common bus. A model predictive control-based distributed power flow controller is proposed to control the interlink inverters of the NMG in a distributed manner. Charging/ discharging of battery is controlled by a decentralised model predictive power controller to provide a stable DC voltage for MGs. Communication between MGs is performed for sharing the status of the tie-line power along with the scheduled tie-line reference. The information from the network is used to determine the instantaneous reference grid power of individual MGs for achieving a smooth tie-line power for the network. Inverter switching actions are performed to minimise the difference between predictions and references. In addition, a comparative study with a decentralised operation of MGs is conducted to show the benefits of networked operation. All the proposed methods are tested through rigorous case studies to validate the performance despite the variations in input and output system disturbances. Comparative analysis among different methods is also conducted to demonstrate the performance variations through adopting different methods. For the simulation experiment set up, MATLAB SIMULINK Simscape Electrical is used to develop a designed system model of MGs and experimental models of the proposed methods. Experiments are performed using real weather and residential load information in Queensland, Australia. The results demonstrate that the proposed methods have achieved the design objectives to solve the tie-line fluctuation problem of grid-connected residential MGs.<br>Thesis (PhD Doctorate)<br>Doctor of Philosophy (PhD)<br>School of Eng & Built Env<br>Science, Environment, Engineering and Technology<br>Full Text

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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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Гузов, Анатолій Геннадійович. "Модифікована система управління мережею MicroGrid на основі Інтернету Речей". Master's thesis, КПІ ім. Ігоря Сікорського, 2020. https://ela.kpi.ua/handle/123456789/39339.

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Робота містить 69 сторінки, 20 рисунків та 25 таблиць. Було використано 32 джерела. Мета роботи: Покращити ефективність системи управління мережею MicroGrid за рахунок її модифікації при застосуванні Інтернету речей. Проаналізовано різні існуючі типи структур інтелектуальних мереж. Зокрема Smart Grid, Smart Power Grid, SCADA системи та MicroGrid. Підсумовано і підтверджено актуальність розробки концепції контролю Інтернету речей над MicroGrid. Розглянуті проблематики, які виникають при впровадженні і експлуатації даної концепції системи. Поставлено за завдання модифікувати створену імітаційну модель управління ІоТ над MicroGrid. Для вирішення поставленного завдання запропонована аналітична модель, заснована на принципах існуючих конецепцій інтелектуальних мереж Smart Grid та Microgrid з урахуванням Інтернету речей з використанням хмарних технологій. У рамках даної імітаційної моделі визначено правила взаємодій елементів системи. Застосування запропонованого рішення дозволяє мати певне представлення системи при її проектуванні, яке відповідає заданій предметній області. Метод мусить передбачати відсутність участі людини, але при формуванні на стільки великої системи не дозволяє ліквідувати її контроль над не контрольованими елементами мережі. Отримані результати доводять на основі імітаційної моделі, що запропонована модифікація є енергоефективною та відмовостійкою.<br>The work contains 69 pages, 20 figures and 25 tables. 32 sources were used. Purpose: To improve the efficiency of the MicroGrid network management system by modifying it when using the Internet of Things. Various existing types of intelligent network structures are analyzed. In particular Smart Grid, Smart Power Grid, SCADA systems and MicroGrid. The relevance of developing the concept of Internet of Things control over MicroGrid is summarized and confirmed. The problems that arise during the implementation and operation of this system concept are considered. The task is to modify the created simulation model of IoT control over MicroGrid. To solve this problem, an analytical model based on the principles of existing concepts of intelligent networks Smart Grid and Micro Grid, taking into account the Internet of Things using useless technologies. Within the framework of this simulation model the rules of interactions of system elements are defined. The application of the proposed solution allows you to have a certain representation of the system in its design, which corresponds to a given subject area. The method must provide for the absence of human participation, but when forming such a large system does not allow to eliminate its control over uncontrolled elements of the network. The obtained results prove on the basis of the simulation model that the proposed modification is energy efficient and fault tolerant.

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Books on the topic "Networked microgrid"

1

Ding, Lei, Qing-Long Han, and Boda Ning. Distributed Control and Optimization of Networked Microgrids. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95029-3.

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Peter, Crossley, Chowdhury S. P, and Knovel (Firm), eds. Microgrids and active distribution networks. Institution of Engineering and Technology, 2009.

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Zhang, Peng. Networked Microgrids. Cambridge University Press, 2021.

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Zhang, Peng. Networked Microgrids. University of Cambridge ESOL Examinations, 2021.

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Zhang, Peng. Networked Microgrids. Cambridge University Press, 2021.

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Chowdhury, S., S. P. Chowdhury, and P. Crossley. Microgrids and Active Distribution Networks. Institution of Engineering & Technology, 2009.

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Chowdhury, S., S. P. Chowdhury, and P. Crossley. Microgrids and Active Distribution Networks. Institution of Engineering and Technology, 2009. http://dx.doi.org/10.1049/pbrn006e.

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Ding, Lei, Qing-Long Han, and Boda Ning. Distributed Control and Optimization of Networked Microgrids: A Multi-Agent System Based Approach. Springer International Publishing AG, 2022.

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Distributed Control and Optimization of Networked Microgrids: A Multi-Agent System Based Approach. Springer International Publishing AG, 2023.

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Benarroch, Eduardo E. Neuroscience for Clinicians. Oxford University Press, 2021. http://dx.doi.org/10.1093/med/9780190948894.001.0001.

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The aim of this book is to provide the clinician with a comprehensive and clinical relevant survey of emerging concepts on the organization and function of the nervous system and neurologic disease mechanisms, at the molecular, cellular, and system levels. The content of is based on the review of information obtained from recent advances in genetic, molecular, and cell biology techniques; electrophysiological recordings; brain mapping; and mouse models, emphasizing the clinical and possible therapeutic implications. Many chapters of this book contain information that will be relevant not only to clinical neurologists but also to psychiatrists and physical therapists. The scope includes the mechanisms and abnormalities of DNA/RNA metabolism, proteostasis, vesicular biogenesis, and axonal transport and mechanisms of neurodegeneration; the role of the mitochondria in cell function and death mechanisms; ion channels, neurotransmission and mechanisms of channelopathies and synaptopathies; the functions of astrocytes, oligodendrocytes, and microglia and their involvement in disease; the local circuits and synaptic interactions at the level of the cerebral cortex, thalamus, basal ganglia, cerebellum, brainstem, and spinal cord transmission regulating sensory processing, behavioral state, and motor functions; the peripheral and central mechanisms of pain and homeostasis; and networks involved in emotion, memory, language, and executive function.

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Book chapters on the topic "Networked microgrid"

1

Mahmoud, Magdi S., and Fouad M. AL-Sunni. "Networked Control of Microgrid System of Systems." In Power Systems. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16910-1_6.

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Wu, Lizhen, Xusheng Yang, Hu Zhou, and Xiaohong Hao. "Modeling and Stability Analysis for Networked Hierarchical Control of Islanded Microgrid." In Proceedings of the 2015 Chinese Intelligent Automation Conference. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-46463-2_11.

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Roeder, Georg, Raffael Schwanninger, Peter Wienzek, Moritz Kerscher, Bernd Wunder, and Martin Schellenberger. "AI for Stability Optimization in Low Voltage Direct Current Microgrids." In Unlocking Artificial Intelligence. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-64832-8_14.

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AbstractLow voltage direct current (LVDC) is an enabling technology to foster a sustainable resilient energy supply. LVDC microgrids comprising energy generators, storage systems, and loads work as independently controlled units in connection with common alternating current networks. Precise digitized control applying intelligent power converters enables new AI-based approaches for DC microgrid layout and operation. In this work, a new method involving connected machine learning and optimization is established together with a novel measurement system, which enables the measurement and improvement of microgrid stability. The application is successfully validated by experimental assessment on a testbed with a four-terminal DC network operating at a voltage of 380 VDC and the advantages of the AI-based approach are demonstrated.

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Jalali, Mehdi, Manijeh Alipour, and Kazem Zare. "Real-Time Perspective in Distributed Robust Operation of Networked Microgrids." In Microgrids. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-59750-4_8.

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Sinha, Pampa, and Chitralekha Jena. "Application of Probabilistic Neural Network and Wavelet Analysis to Classify Power Quality." In Microgrids. CRC Press, 2021. http://dx.doi.org/10.1201/9781003121626-10.

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Amoura, Yahia, André Pedroso, Ângela Ferreira, José Lima, Santiago Torres, and Ana I. Pereira. "Multi-objective Optimal Sizing of an AC/DC Grid Connected Microgrid System." In Communications in Computer and Information Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-53036-4_23.

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AbstractConsidering the rising energy needs and the depletion of conventional energy sources, microgrid systems combining wind energy and solar photovoltaic power with diesel generators are promising and considered economically viable for usage. To evaluate system cost and dependability, optimizing the size of microgrid system elements, including energy storage systems connected with the principal network, is crucial. In this line, a study has already been performed using a uni-objective optimization approach for the techno-economic sizing of a microgrid. It was noted that, despite the economic criterion, the environmental criterion can have a considerable impact on the elements constructing the microgrid system. In this paper, two multi-objective optimization approaches are proposed, including a non-dominated sorting genetic algorithm (NSGA-II) and the Pareto Search algorithm (PS) for the eco-environmental design of a microgrid system. The k-means clustering of the non-dominated point on the Pareto front has delivered three categories of scenarios: best economic, best environmental, and trade-off. Energy management, considering the three cases, has been applied to the microgrid over a period of 24 h to evaluate the impact of system design on the energy production system’s behavior.

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Tvrdik, Petr, Kathryn N. Kearns, Khadijeh A. Sharifi, M. Filip Sluzewski, Scott T. Acton, and M. Yashar S. Kalani. "Calcium Imaging of Microglial Network Activity in Stroke." In Microglia. Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9658-2_19.

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Li, Yan. "Cyber-Communication Network for Microgrids." In Cyber-Physical Microgrids. Springer International Publishing, 2012. http://dx.doi.org/10.1007/978-3-030-80724-5_9.

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Mohammadi, Ali, and Sanaz Rabinia. "A Comprehensive Study of Game Theory Applications for Smart Grids, Demand side Management Programs and Transportation Networks." In Smart Microgrids. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-02656-1_5.

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Mahmud, Rasel, and Arash Nejadpak. "Laboratory-Scale Microgrid System for Control of Power Distribution in Local Energy Networks – Part I: Theory and Design." In Smart Microgrids. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-02656-1_2.

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Conference papers on the topic "Networked microgrid"

1

Chakraborty, Sourav, Kunal Kumar, and Susmita Kar. "Hierarchical Control Framework in Networked Microgrid." In 2024 IEEE International Conference on Smart Power Control and Renewable Energy (ICSPCRE). IEEE, 2024. http://dx.doi.org/10.1109/icspcre62303.2024.10674869.

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Yassim, Halyani Mohd, Mohd Noor Abdullah, Chin Kim Gan, Asif Ahmed, Wei Hown Tee, and Azralmukmin Azmi. "Hierarchical Energy Management Strategy for an Islanded Networked Microgrid Considering Flexible Inter-Microgrid Power Exchange." In 2024 IEEE Sustainable Power and Energy Conference (iSPEC). IEEE, 2024. https://doi.org/10.1109/ispec59716.2024.10892510.

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Bhowmick, Arpan, and Altaf Q. H. Badar. "Bi-Level Optimization for Energy Management of Networked Microgrid." In 2024 IEEE 4th International Conference on Sustainable Energy and Future Electric Transportation (SEFET). IEEE, 2024. http://dx.doi.org/10.1109/sefet61574.2024.10718199.

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Yang, Junlin, Xue Li, Yurou Zhu, Yawei Li, and Dajun Du. "Economic Dispatch for Networked Microgrid under False Data Injection Attacks." In 2024 The 9th International Conference on Power and Renewable Energy (ICPRE). IEEE, 2024. https://doi.org/10.1109/icpre62586.2024.10768471.

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Mahala, Vikas Ranveer Singh, Anshul Kumar Yadav, D. Saxena, and Rajesh Kumar. "Bi-Level Optimization Framework for Energy Management in Networked Microgrid." In 2024 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES). IEEE, 2024. https://doi.org/10.1109/pedes61459.2024.10961080.

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Sundararajan, Aditya, Guodong Liu, Michael Starke, Radha Krishna Moorthy, and Christopher Irwin. "Networked Microgrid Ownership, Data, and Control Implications: Challenges and Open Questions." In 2024 IEEE Power & Energy Society General Meeting (PESGM). IEEE, 2024. http://dx.doi.org/10.1109/pesgm51994.2024.10688903.

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Joshi, Aditya, and Mo-Yuen Chow. "Hierarchical Distributed Consensus Based Networked Microgrid Energy Management For Disaster Relief." In 2024 IEEE 19th Conference on Industrial Electronics and Applications (ICIEA). IEEE, 2024. http://dx.doi.org/10.1109/iciea61579.2024.10665212.

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Mahala, Vikas Ranveer Singh, Anshul Kumar Yadav, Dipti Saxena, and Rajesh Kumar. "Uncertainty Estimation of PV and Load Using Deep Learning for Networked Microgrid." In 2024 IEEE 4th International Conference on Sustainable Energy and Future Electric Transportation (SEFET). IEEE, 2024. http://dx.doi.org/10.1109/sefet61574.2024.10718218.

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Ferrari, Maximiliano, Michael Starke, John Smith, Ben Ollis, Aditya Sundararajan, and Yuly Garcia. "A Networked Microgrid Framework and Testbed for Communication, Controls, and Optimization Testing." In 2024 IEEE Energy Conversion Congress and Exposition (ECCE). IEEE, 2024. https://doi.org/10.1109/ecce55643.2024.10860879.

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Liu, Weiliang, Xiaolei Yang, and Jianfeng Ye. "Stochastic Planning Method of Energy Storage Capacity of Networked Microgrid Considering Power Supply Risk." In 2024 4th International Conference on Energy Engineering and Power Systems (EEPS). IEEE, 2024. https://doi.org/10.1109/eeps63402.2024.10804446.

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Reports on the topic "Networked microgrid"

1

Giraldez Miner, Julieta, Annabelle Pratt, and Francisco Flores-Espino. Networked Microgrid Optimal Design and Operations Tool: Regulatory and Business Environment Study. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1659812.

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Sangoleye, Fisayo, Jay Johnson, Adrian Chavez, et al. Networked Microgrid Cybersecurity Architecture Design Guide - A New Jersey TRANSITGRID Use Case. Office of Scientific and Technical Information (OSTI), 2022. http://dx.doi.org/10.2172/1900087.

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Starke, Michael R. Networked Microgrids Scoping Study. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1329135.

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Trinklei, Eddy, Gordon Parker, Wayne Weaver, et al. Scoping Study: Networked Microgrids. Office of Scientific and Technical Information (OSTI), 2014. http://dx.doi.org/10.2172/1433071.

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Backhaus, Scott N., Larisa Dobriansky, Steve Glover, et al. Networked Microgrids Scoping Study. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1334654.

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Bent, Russell Whitford. Resilient Operations of Networked Microgrids (RONM). Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1638627.

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Hossain-McKenzie, Shamina, Matthew Reno, Russell Bent, and Adrian Chavez. Cybersecurity of Networked Microgrids: Challenges Potential Solutions and Future Directions. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1738879.

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Ropp, Michael, Matthew Reno, Ward Bower, James Reilly, and S. Venkata. Secondary Networks and Protection: Implications for DER and Microgrid Interconnection. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1738874.

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Hossain-McKenzie, Shamina, Matthew Reno, John Eddy, and Kevin Schneider. Assessment of Existing Capabilities and Future Needs for Designing Networked Microgrids. Office of Scientific and Technical Information (OSTI), 2019. http://dx.doi.org/10.2172/1761847.

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Du, Yuhua, Yuxi Men, Xiaonan Lu, Jianzhe Liu, Feng Qiu, and Bo Chen. Coastal Community Resiliency Enhancement Using Marine Hydrokinetic (MHK) Resources and Networked Microgrids. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1767164.

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