Search

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. [ABSTRACT FROM AUTHOR]

The impact of communication disturbances on microgrids (MGs) needs robust and scalable Information Communication Technology (ICT) infrastructure for efficient MG control. This work builds on advances in the Internet of Things (IoT) to provide a practical platform for testing the impact of various cyber-attacks on a distributed control scheme for a Multi-Agent System (MAS). This paper presents a Controller Hardware-in-the-Loop (CHIL) testbed to investigate the impact of various cyber-attacks and communication disruptions on MGs. A distributed consensus secondary control scheme for a MAS within an MG cyber-physical system (CPS) is proposed. The proposed cyber-physical testbed integrates a real-time islanded AC microgrid on RT-Lab, secondary controllers implemented on single-board computers, and an attacker agent on another single-board computer. Communication occurs via a UDP/IP network between OPAL-RT and controller agents, as well as between the agents. Through meticulous experimentation, the efficacy of the proposed control strategy using the developed platform is validated. Various attacks were modeled and launched including deception attacks on sensors, actuators, and their combinations, as well as disruption attacks. The ramifications of both deception and disruption cyber-attacks on system performance are analyzed. [ABSTRACT FROM AUTHOR]

The integration of communication infrastructures into traditional power systems, transforming them into cyber-physical power systems (CPPS), accentuates the significance of communication in influencing system performance and sustainability. This paper presents a versatile, innovative cyber-physical co-simulation framework that integrates the physical power system and communication networks, uniting OPAL-RT, a network simulator (ns3), and Docker containers into a sophisticated platform, facilitating intensive studies into CPPS dynamics. The proposed experimental study provides an innovative way to assess the frequency control response of a cyber-physical inverter-based microgrid (MG), addressing the MG sustainability challenges. We consider diverse real-world scenarios, focusing on communication delays and distributed denial of service (DDoS) attacks within the communication channels. We propose a precise ns3-based communication model that bridges the MG's primary and secondary control layers, an aspect often overlooked in previous studies; this is a noteworthy contribution to elucidating the adverse impacts of communication latency on MG frequency performance. The experimental results demonstrate the effectiveness of the centralized secondary controller in eliminating the frequency deviations. Furthermore, the findings offer insights into stable and unstable regions, revealing how the communication delay value affects the frequency stability under different operating conditions. In addition, the developed real-time DDoS attacks model within the proposed communication surface unveils crucial insights into the MG's resilience to cyber threats. This work's revelations offer a foundational awareness of MG vulnerabilities, paving the way for designing robust and resilient communication networks and control strategies within the cyber-physical inverter-based microgrids. [ABSTRACT FROM AUTHOR]

Multi-microgrids (MMGs) revolutionize integrating and managing diverse distributed energy resources (DERs), significantly enhancing the overall efficiency of energy systems. Unlike traditional power systems, MMGs comprise interconnected microgrids that operate independently or collaboratively. This innovative concept adeptly addresses challenges posed by pulsed load effects, capitalizing on the cooperative nature of interconnected microgrids. A coordinated MMG system effectively redistributes and shares the impact of pulsed loads, mitigating voltage fluctuations and ensuring sustained system stability. The proposed cooperative MMG scheme optimizes power distribution and load prioritization, facilitating the seamless allocation of surplus energy from neighboring microgrids to meet sudden surges in demand. This study focuses on DC standalone multi-microgrid systems, showcasing their inherent adaptability, resilience, and operational efficiency in managing pulse, variable, and unpredictable generation deficits. Several experiments on a laboratory-scale DC multi-microgrid validate the system's robust performance. Notably, transient current fluctuations during pulse loads are promptly stabilized through the effective collaboration of microgrids. Variable load experiments reveal distinct behaviors, shedding light on the profound influence of control strategies. This research reveals the transformative potential of MMGs in addressing energy challenges, with a particular focus on DC standalone multi-microgrid systems. The findings underscore the adaptability and resilience of the proposed cooperative scheme, marking a significant stride in the evolution of modern power systems. [ABSTRACT FROM AUTHOR]

Batteries are considered critical elements in most applications nowadays due to their power and energy density features. However, uncontrolled charging and discharging will negatively affect their functions and might result in a catastrophic failure of their applications. Hence, a battery management system (BMS) is mandated for their proper operation. One of the critical elements of any BMS is the state of charge (SoC) estimation process, which highly determines the needed action to maintain the battery's health and efficiency. Several methods were used to estimate the Lithium‐ion batteries (LIBs) SoC, depending on the LIBs model or any other suitable technique. This article provides a critical review of the existing SoC estimation approaches and the main LIB models with their pros and cons, their possibility to integrate with each other's for precise estimation results, and the applicability of these techniques in electric vehicles and utility applications with the commonly used standards and codes in these sectors. Moreover, this study will also explore a future framework for integrating digital twins (DTs) with BMSs for improved and advanced management. Based on this comprehensive review, it can be concluded that merging the model‐based estimation techniques with the data‐driven approaches with their promising development to determine the dynamic patterns inside the battery can efficiently achieve precise estimation results while reducing the complexity of these models. This integration will align also with the integration of digital twin technology to provide complete and accurate supervision for the BMSs. This article is categorized under:Emerging Technologies > Energy StorageEmerging Technologies > DigitalizationEnergy and Power Systems > Distributed Generation [ABSTRACT FROM AUTHOR]

Networked microgrids (NMGs) are developing as a viable approach for integrating an expanding number of distributed energy resources (DERs) while improving energy system performance. NMGs, as compared to typical power systems, are constructed of many linked microgrids that can function independently or as part of a more extensive network. This allows NMGs to be more flexible, dependable, and efficient. The present study comprehensively investigates architecture, communication, and cybersecurity issues in NMGs. This comprehensive study examines various aspects related to networked microgrids (NMGs). It explores the architecture of NMGs, including control techniques, protection, standards, and the challenges associated with their adoption. Additionally, it investigates communication in NMGs, focusing on the technologies, protocols, and the impact of communication on the functioning of these systems. Furthermore, this study addresses cybersecurity challenges specific to NMGs, such as diverse cyberattack types, detection and mitigation strategies, and the importance of awareness training. The findings of this study offer valuable insights for NMG researchers and practitioners, emphasizing critical aspects that must be considered to ensure the safe and efficient operation of these systems. [ABSTRACT FROM AUTHOR]

A high share of distributed energy resources (DERs) in power distribution grids has posed many challenges for system operation and control. Microgrid (MG) application with different distributed control approaches for DERs has been drawn a lot of attention from the research community to provide more flexibility, reliability and resilience for the system. This paper develops a distributed secondary control for DERs in MGs and on top of that using synchronous condenser (SC) participating in the secondary control for voltage support. The proposed distributed secondary control framework of MGs is designed to obtain four objectives as follows: (i) frequency restoration, (ii) average voltage restoration, (iii) arbitrary active power sharing among SGs and BESSs and (iv) arbitrary reactive power sharing among all SGs, BESSs and SCs. The comparison results under different scenarios show that with SC participating in the distributed secondary control in MGs, the system frequency and voltage response are much improved and quickly recovered to the nominal values thanks to the natural inertia response and fast reactive power control of SC sharing with other DERs in the MGs. Additionally, a multi-agent system is implemented to realize the proposed control method in hardware environment. [ABSTRACT FROM AUTHOR]

The increased rate of cyber-attacks on the power system necessitates the need for innovative solutions to ensure its resiliency. This work builds on the advancement in the IoT to provide a practical framework that is able to respond to multiple attacks on a network of interconnected microgrids. This paper provides an IoT-based digital twin (DT) of the cyber-physical system that interacts with the control system to ensure its proper operation. The IoT cloud provision of the energy cyber-physical and the DT are mathematically formulated. Unlike other cybersecurity frameworks in the literature, the proposed one can mitigate an individual as well as coordinated attacks. The framework is tested on a distributed control system and the security measures are implemented using cloud computing. The physical controllers are implemented using single-board computers. The practical results show that the proposed DT is able to mitigate the coordinated false data injection and the denial of service cyber-attacks. [ABSTRACT FROM AUTHOR]

One of the main challenges to design a proper protection scheme for a microgrid is the dynamic characteristics in the architecture for the microgrid. The relay settings need to change with every configuration in the system to properly isolate a fault. This article proposes a centralized control approach using a cosimulation platform to monitor operational modes and multiple microgrid topologies to find fault and clear them optimally. The simulation software, embedded microcontrollers, and a real communication architecture are collectively used to perform the protection scheme platform. The data distribution service middleware is used to link between the hardware and software environments. The proposed technique helps to identify the shortest path from the source to the fault location. The proposed main control center is responsible for adjusting the relay settings based on the active topology and the shortest path to the fault. This technique is investigated on IEEE 14 bus microgrid system for all the possible fault paths. The proposed scheme can clear the fault by isolating the minimum part of the system and improving the endurance of the power to supply the different loads in the system. [ABSTRACT FROM AUTHOR]

A new transformerless bidirectional buck-boost converter is proposed in this paper. The proposed converter has a simple circuit structure, low component count, low voltage stress on the power transistors, and a wide voltage gain range. This makes it applicable in the energy storage charge/discharge systems, such as electric vehicles (EV), microgrids and nanogrids with energy storage units, and uninterruptible power supplies. In addition, synchronous rectification between the complementary transistors is employed to improve the converter efficiency. A comprehensive analysis of the steady-state operation, small-signal model, component parameters design, and efficiency analysis of the proposed converter operating in a continuous conduction mode is given. Finally, a 1.6-kW scaled-down prototype was built using Silicon Carbide MOSFETS to validate the effectiveness and feasibility of the proposed converter. [ABSTRACT FROM AUTHOR]

Microgrid protection schemes require a fast, reliable, and a robust communication system, to adjust relay settings for the appropriate current levels according to the microgrid's operation mode. However, risks of communication link failures and cyber security threats are major challenges for the implementation of protection scheme. This paper presents a co-simulation platform for microgrid based on multiagent system (MAS) when the communication is available in the system. IEC 61850 is used to emulate the proposed protection scheme. The data distribution service (DDS) middleware is used to link between the hardware and software environments. During islanded mode, the system is capable of riding-through communication failures by the aid of a lithium-ion battery. When the communication is attacked, the battery plays an important role and contribute to the fault current for helping the circuit breaker to trip during islanded mode. The design of the control algorithm for the battery's ac/dc converter is developed with single mode operation to eliminate the reliance on communicated control command signals to shift the controller between different modes. [ABSTRACT FROM AUTHOR]

This paper proposes a multiagent-based energy market for multimicrogrid systems using game-theoretic and hierarchical optimization approaches. The proposed method is tailored to achieve the optimal operation of smart microgrids in distribution systems. Because of rapid load variations in distribution systems, it is necessary to develop fast optimization algorithms which minimize the power mismatch in and among microgrids. In this paper, a three-level market framework is proposed. The first level comprises a game-theoretic double-auction mechanism for the day-ahead market while the next two levels are optimal rescheduling and intermicrogrid reverse auction model for the hour-ahead and real-time markets, respectively. Using the hierarchical optimization algorithm in a multiagent-based area, it is anticipated to not only minimize the optimization solution time, but also reduce the dependency on the network in grid-connected mode or load shedding in islanded mode. Using this approach, load demand response capabilities along with rescheduling of Distributed Energy Storage Systems and distributed generations could be utilized in all market levels, which will lead to optimal operation of multimicrogrid systems. Agents are developed in DIgSILENT PowerFactory and dynamic data exchange is activated for communication among agents communicating through a data distribution service which utilizes the real-time publish-subscribe communication protocol. The developed framework is applied to the modified 37-bus IEEE distribution test feeder system to validate the effectiveness of this market structure. [ABSTRACT FROM AUTHOR]

Adaptive protection techniques used for a microgrid rely on a stable communication link to and from protective devices at the point of common coupling to adjust the settings within these corresponding devices for either a grid-connected or islanded mode of operation. However, during communication outages or in the event of a cyberattack, relays’ settings are not changed. Thus, adaptive protection schemes are rendered unsuccessful. Due to their fast response, supercapacitors, which are present in the microgrid to feed pulsed loads, could also be utilized to enhance the resiliency of adaptive protection schemes against communication outages. Proper sizing of the supercapacitors is therefore important in order to maintain a stable system operation and the cost of the protection scheme. This paper presents a two-level optimization scheme for minimizing the supercapacitor size along with optimizing its controllers’ parameters. The latter will lead to a reduction of the supercapacitor fault current contribution and an increase in that of other ac resources in the microgrid in the extreme case of having a fault occurring simultaneously with a pulsed load. It was also shown that the size of the supercapacitor can be reduced if the pulsed load is temporarily disconnected during the transient fault period. Simulation results showed that the resulting supercapacitor size and the optimized controller parameters were feeding enough fault currents for several types of faults in different locations and minimizing the cost of the protection scheme. Experimental results on a hardware microgrid setup validated the simulation results. [ABSTRACT FROM AUTHOR]

A main challenge in the practical implementation of a microgrid is the design of an adequate protection scheme in both grid-connected and islanded modes of operation. Microgrid protection requires a fast, reliable, and robust communication system to adjust relay settings to the appropriate current level according to the operation mode. Various approaches have been implemented to deal with this problem, yet the most promising ones are the use of adaptive protection techniques abiding by the International Electrotechnical Commission (IEC) 61850 communication standard. This paper presents a review of the technical challenges for the use of classical protection techniques and the need for an enhanced, adaptive, smart protection system. However, the risk of communication link failures and cyber security threats still remain a challenge in implementing a reliable adaptive protection scheme. A contingency is essential in the event that a communication failure prevents a relay from adjusting between grid-connected and islanded mode. An adaptive protection scheme is proposed, which utilizes energy storage devices to enhance resiliency against communication outages. The proposed solution does not incur additional costs to the network, as the energy storage devices are already utilized for other purposes. A case study experimentally verifies this contingency under a worst-case scenario, where a fault occurs simultaneously with a pulsed load while operating in islanded mode with a communication failure. [ABSTRACT FROM AUTHOR]

This paper presents a cloud-based and hybrid wireless mesh communication framework for bilevel, nested, distributed optimization of networked clusters of microgrids. The proposed optimization framework implements a diffusion-based, fully distributed algorithm on local wireless network and a quasi-distributed approach on wide-area internet-based cloud. The lower level of the bilevel optimization implements a distributed optimal economic dispatch solution for intramicrogrid among distributed energy resources, and the upper level implements a global optimal dispatch for intermicrogrid energy exchange. To demonstrate industrial applicability of the proposed framework, the IEC 61850 interoperability protocol is adopted to achieve a certain delay performance so that the distributed optimization convergence is guaranteed. First, hardware-based prototype intelligent electronic devices are developed using embedded systems. Then, the bilevel nested optimization algorithm is implemented for integration of networked microgrids. Finally, experimental results are demonstrated from a real-time smart grid testbed featuring realistic microgrids. The results demonstrate that the proposed framework meets communication requirements for distributed optimization of networked microgrids. [ABSTRACT FROM PUBLISHER]

The smart grid is seen as a power system with real-time communication and control capabilities between the consumer and the utility. This modern platform facilitates the optimization in energy usage based on several factors including environmental, price preferences, and system technical issues. In this paper, a real-time energy management system (EMS) for microgrids or nanogrids was developed. The developed system involves an online optimization scheme to adapt its parameters based on previous, current, and forecasted future system states. The communication requirements for all EMS modules were analyzed and are all integrated over a data distribution service Ethernet network with appropriate quality-of-service profiles. The developed EMS was emulated with actual residential energy consumption and irradiance data from Miami, Florida, and proved its effectiveness in reducing consumers’ bills and achieving flat peak load profiles. [ABSTRACT FROM PUBLISHER]

As intermittent generation profiles introduce more stress due to the sudden imbalance in supply and demand, power systems are becoming more dependent on online aggregated support of networked utility-independent private microgrids. During the aggregation process, microgrid operators’ preferences and bidding behaviors are priority. New aggregation approaches are required considering the individual behaviors of the networked and geographically dispersed independent microgrids. In this paper, we present a novel bidding behavior modeling and an auction architecture consisting of a central aggregator and networked microgrid agents. The bidding behavioral states of the microgrid agents are formalized as partially observable Markov processes for the belief updates and short-term policy determination in order to maximize the individual profit. A reverse auction model is adopted to enable competitive negotiations between the central aggregator and networked microgrid agents. The auction and aggregation processes were implemented in a power system control area along with an automatic generation control (AGC) scheme to contribute frequency control. The proposed AGC and auction mechanism were verified with an industrial multi-agent framework in a laboratory-based real-time application. [ABSTRACT FROM PUBLISHER]

This paper proposes a multiagent-based optimal microgrid control scheme using a fully distributed diffusion strategy. A two-level cooperative optimization multiagent system is adapted for distributed energy resources economic dispatch. The lower level implements an adaptive droop scheme based on online no-load frequency adjustments. The upper level implements distributed communication using diffusion between neighboring agents for optimal microgrid management. The proposed control scheme enables peer-to-peer communication among the agents without the necessity of a centralized controller, and simultaneously performs resource optimization while regulating the system frequency. The results are compared with centralized and consensus-based optimization algorithms. We have concluded that the proposed algorithm is superior over consensus algorithms in terms of convergence speed and utilizes reduced communication infrastructure compared to centralized controllers. Simulation demonstrations were conducted along with experimental results from a hardware-based microgrid using an industrial multiagent framework. The simulation and experimental results show that the proposed method and the agent framework can be deployed in real-world microgrids and offer superior decision making on optimal microgrid control. [ABSTRACT FROM PUBLISHER]

This paper proposes a communication-assisted fault localization, isolation, and restoration method for microgrids based on a multi-agent system. The proposed system comprises distributed agents, located in the middle and at the two ends of a protection section, which will detect a fault through phase angle comparison of current signals at both sides of a given distribution line. The agents then send trips signal to corresponding circuit breakers accordingly. The importance of the proposed protection technique is twofold. First, it eliminates the use of voltage transformers and thus reduces costs. Second, it does not require transfer of data along long distances, which decreases the delay time for fault isolation. Power restoration processes following the fault clearance considering voltage, frequency, and power flow constraints in the microgrid under study were also performed. Simulation of the proposed protection methodology was presented followed by experimental verification. The experimental results showed excellent agreement with the simulated protection scheme. [ABSTRACT FROM PUBLISHER]

This paper presents a real-time implementation of autonomous microgrid protection using agent-based distributed communication. Protection of an autonomous microgrid requires special considerations compared to large-scale distribution networks due to the presence of power converters and relatively low inertia. In this paper, we introduce a practical overcurrent and a frequency-selectivity method to overcome conventional limitations. The proposed overcurrent scheme defines a selectivity mechanism considering the remedial action scheme of the microgrid after a fault instant based on feeder characteristics and the location of the intelligent electronic devices (IEDs). A synchrophasor-based online frequency-selectivity approach is proposed to avoid pulse loading effects in low inertia microgrids. Experimental results are presented for verification of the proposed schemes using a laboratory-based microgrid. The setup was composed of actual generation units and IEDs using the IEC 61850 protocol. The experimental results were in excellent agreement with the proposed protection scheme. [ABSTRACT FROM AUTHOR]

This paper presents a real-time coordinated control of the hybrid ac/dc microgrids involving energy storage and pulsed loads. Grid-isolated hybrid microgrid applications require special considerations due to the intermittent generation, online energy storage control, and pulsed loads. In this study, we introduce a comprehensive frequency and voltage control scheme for a hybrid ac/dc microgrid consisting of a synchronous generator, solar generation emulator, and bidirectional (ac/dc and dc/dc) converters. A bidirectional controlled ac/dc converter with an active and reactive power decoupling technique is used to link the ac bus with the dc bus, while regulating the system voltage and frequency. A dc/dc boost converter with a maximum power point tracking function is implemented to maximize the intermittent energy generation from solar generators. Current-controlled bidirectional dc/dc converters are applied to connect each lithium-ion battery bank to the dc bus. Lithium-ion battery banks act as energy storage devices that serve to increase the system resiliency by absorbing or injecting power. Experimental results are presented for verification of the introduced hybrid ac/dc power flow control scheme. [ABSTRACT FROM AUTHOR]

DC microgrid systems with hybrid energy resources are of significant interest in shipboard and spacecraft applications. In such a system, coordinated operation of circuit breakers (CBs) and disconnecting switches (DSs) can rapidly isolate short-circuit faults and restore the system very fast. In this paper, we investigate a new protection scheme for a Multi-Bus dc systems based on an event classification approach. The proposed protection scheme transfers less data when compared with commonly used data-based protection methods and does not require high-speed communication and synchronization. The results show that the developed protection scheme is able to identify the type of fault accurately, isolate the faulted area, and restore the system very quickly while maintaining continuous power to the loads. [ABSTRACT FROM PUBLISHER]

This paper presents the design and implementation of an advanced battery management system (BMS). The basic concept is to divide each series battery array into sub-arrays where each battery is individually monitored and managed. The proposed BMS continuously monitors the voltage, current, and energy of each battery. Based on these measurements, the BMS can calculate individual state of charge (SoC) levels and C-rates. Furthermore, the system has the capability to isolate each individual battery to apply different charging profiles and advanced diagnostics to detect the correct problems. Pulsed charging is deployed using different duty cycles for SoC balancing. The isolated battery is bypassed to maintain uninterrupted supply to the load despite reduced series array voltage. An unidirectional dc–dc boost converter maintains a constant output voltage level to the load, regardless of the number of batteries connected, until the problem is corrected. A hardware implementation of the proposed BMS is explained in detail. The performance of the system is tested experimentally under different loading conditions, including heavy pulsed loads. [ABSTRACT FROM PUBLISHER]

In this paper, a new energy control scheme is proposed for actively controlled hybrid dc microgrid to reduce the adverse impact of pulsed power loads. The proposed energy control is an adaptive current–voltage control (ACVC) scheme based on the moving average measurement technique and an adaptive proportional compensator. Unlike conventional energy control methods, the proposed ACVC approach has the advantage of controlling both the voltage and current of the system while keeping the output current of the power converter at a relatively constant value. For this study, a laboratory-scale hybrid dc microgrid is developed to evaluate the performance of the ACVC strategy and to compare its performance with other conventional energy control methods. Using experimental test results, it is shown that the proposed strategy highly improves the dynamic performance of the hybrid dc microgrid. Although the ACVC technique causes slightly more bus voltage variation, it effectively eliminates the high current and power pulsation of the power converters. The experimental test results for different pulse duty ratios demonstrated a significant improvement achieved by the developed ACVC scheme in enhancing the system efficiency, reducing the ac grid voltage drop and the frequency fluctuations. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate an event-based protection scheme for a multiterminal dc power system, which includes hybrid energy resources and various loading schemes. The proposed protection scheme transfers less data when compared with commonly used data-based protection methods, and does not require high-speed communication and synchronization. Each protection unit is able to autonomously identify the type of event using the current derivative fault identification method, employing an artificial inductive line impedance. In order to accurately set the protection relays, detailed fault current analysis considering low pass resistor capacitor filter effects are presented. The decision for fault isolation is made based on the unit judgment and the data received through high-level data communication from other interconnected units. The performance of the proposed protection scheme was evaluated under different dc feeder and bus faults. The results show that this scheme is able to accurately identify the type of fault, isolate the faulted area, and restore the system quickly while limiting the load voltage drop to its preset limit. [ABSTRACT FROM PUBLISHER]

This paper presents a real-time implementation of a multiagent-based game theory reverse auction model for microgrid market operations featuring conventional and renewable distributed energy resources (DER). Studies were conducted on a grid connected microgrid consisting of a synchronous generator, two inverter-based generation units, and a combined load. The multiagent-based platform was applied to monitor, control, and perform the reverse auction process of DERs. A competitive game-theory reverse auction model was investigated to schedule the DER unit commitment with an hour-ahead market approach for the 24 h of the day. The proposed methodology was realistically implemented and operated at the Florida International University smart grid test system. The investigation shows that the proposed algorithm and the industrial hardware-based infrastructure can be implemented in the existing electric utility grid as new assets of the system are added. [ABSTRACT FROM PUBLISHER]

This paper investigates the real-time control and energy management of a dc microgrid incorporating hybrid energy sources with various loading schemes. In the proposed dc microgrid, a supercapacitor bank, a power buffer, and a pulse load are directly connected to a dc bus. The proposed system configuration highly improves the grid redundancy and reduces the total power losses. Moreover, the supercapacitor bank not only supplies the pulse load, but also supports the grid during transient periods when it is highly loaded. However, the energy management and control of such a system is more complex, since the heavy pulse load can cause high power pulsation and voltage drop. To reduce the adverse effects of the pulse load, a new real-time energy management system (EMS) with an adaptive energy calculator (AEC) based on the moving average measurement technique is developed. The proposed microgrid was implemented in hardware and experimentally tested. The results were compared with other methods, such as direct voltage control and continuous current averaging approaches. The results show that the developed EMS with AEC technique properly share the power and control the bus voltage under different loading conditions, while the adverse effects of the pulse load are highly reduced. [ABSTRACT FROM PUBLISHER]

In this paper, the real-time operation and the harmonic analysis of isolated and nonisolated dc microgrid are investigated. The microgrid features hybrid energy sources with various loading schemes. This hybrid dc microgrid was supplied by an internal generator and the ac utility grid. A supercapacitor bank functions by acting as a power buffer to satisfy the high power requirements of the dc microgrid. In order to properly manage the energy and prevent the ac grid power pulsation, a current–voltage control technique based on master–slave control concept is proposed. In this technique, the supercapacitor bank operates as the master and controls the dc bus voltage. The other converters are working in current control mode to share the required power. The controllers of the converters are equipped with hysteresis voltage control, which monitors the entire supercapacitor bank. Additionally, an analog hysteresis voltage protection circuit board was designed and implemented to protect the supercapacitor cells from overvoltages that can occur due to uneven charge distribution during the fast charging processes. The protection circuit, which was developed and built here, was experimentally tested, and its error was analyzed. Various operating modes based on different power sharing patterns were defined. The experimental test was carried out for both galvanically isolated and nonisolated dc grid systems. The results show that the proposed energy management algorithm properly shares power and control the voltage. In addition, depending on the power sharing pattern, the isolation of the dc microgrid significantly affects the harmonic content of the current. [ABSTRACT FROM AUTHOR]

Energy management and control of hybrid microgrids is a challenging task due to the varying nature of operation between AC and DC components which leads to voltage and frequency issues. This work utilizes a metaheuristic-based vector-decoupled algorithm to balance the control and operation of hybrid microgrids in the presence of stochastic renewable energy sources and electric vehicles charging structure. The AC and DC parts of the microgrid are coupled via a bidirectional interlinking converter, with the AC side connected to a synchronous generator and portable AC loads, while the DC side is connected to a photovoltaic system and an electric vehicle charging system. To properly ensure safe and efficient exchange of power within allowable voltage and frequency levels, the vector-decoupled control parameters of the bidirectional converter are tuned via hybridization of particle swarm optimization and artificial physics optimization. The proposed control algorithm ensures the stability of both voltage and frequency levels during the severe condition of islanding operation and high pulsed demands conditions as well as the variability of renewable source production. The proposed methodology is verified in a state-of-the-art hardware-in-the-loop testbed. The results show robustness and effectiveness of the proposed algorithm in managing the real and reactive power exchange between the AC and DC parts of the microgrid within safe and acceptable voltage and frequency levels. [ABSTRACT FROM AUTHOR]

The real-time operation of the energy management system (RT-EMS) is one of the vital functions of Microgrids (MG). In this context, the reliability and smooth operation should be maintained in real time regardless of load and generation variations and without losing the optimum operation cost. This paper presents a design and implementation of a RT-EMS based on Multiagent system (MAS) and the fast converging T-Cell algorithm to minimize the MG operational cost and maximize the real-time response in grid-connected MG. The RT-EMS has the main function to ensure the energy dispatch between the distributed generation (DG) units that consist in this work on a wind generator, solar energy, energy storage units, controllable loads and the main grid. A modular multi-agent platform is proposed to implement the RT-EMS. The MAS has features such as peer-to-peer communication capability, a fault-tolerance structure, and high flexibility, which make it convenient for MG context. Each component of the MG has its own managing agent. While, the MG optimizer (MGO) is the agent responsible for running the optimization and ensuring the seamless operation of the MG in real time, the MG supervisor (MGS) is the agent that intercepts sudden high load variations and computes the new optimum operating point. In addition, the proposed RT-EMS develops an integration of the MAS platform with the Data Distribution Service (DDS) as a middleware to communicate with the physical units. In this work, the proposed algorithm minimizes the cost function of the MG as well as maximizes the use of renewable energy generation; Then, it assigns the power reference to each DG of the MG. The total time delay of the optimization and the communication between the EMS components were reduced. To verify the performance of our proposed system, an experimental validation in a MG testbed were conducted. Results show the reliability and the effectiveness of the proposed multiagent based RT-EMS. Various scenarios were tested such as normal operation as well as sudden load variation. The optimum values were obtained faster in terms of computation time as compared to existing techniques. The latency from the proposed system was 43% faster than other heuristic or deterministic methods in the literature. This significant improvement makes this proposed system more competitive for RT applications. [ABSTRACT FROM AUTHOR]

In this paper, a smart distributed DC/DC converter synchronization advanced technique and phase angle optimization algorithm are proposed using to reduce the DC bus overall ripple. A global positioning system-based scheme is used to synchronize the carrier among the distributed converters. The carrier phase angle optimization among the different converters is inspired by Carrier-Sense Multiple Access protocol. The proposed system is simulated and analyzed using Matlab/Simulink program. As a proof of concept of the proposed technique, two case studies have been investigated under equal and unequal load sharing among the distributed generators. The proposed algorithm shows a significant reduction in the DC bus voltage ripple. To prove the concept, a laboratory test-bed has been built and the proposed algorithm has been implemented to validate the theoretical and simulation results. The close agreement between the experimental and simulation results demonstrates the effectiveness and validity of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, a novel PWM carrier synchronization method is proposed for distributed DC–DC converters in DC-Microgrids. The synchronization method is based on carrier frequency extraction from DC-bus voltage ripple. In addition, an advanced phase shift control algorithm for the synchronized carriers is implemented to reduce the DC bus voltage ripple contents. A DC-Microgrid encompassing different distributed energy resources with their DC–DC converters is modeled using Matlab\Simulink to test the proposed synchronization method and control algorithm. Then, a small power scale experimental testbed is built in order to validate the simulation results. The simulation and the experimental results demonstrated that the proposed method and algorithm are very promising to minimize DC-bus ripple contents in DC-Microgrid applications. [ABSTRACT FROM AUTHOR]

In this paper, a real-time tertiary control algorithm for DC microgrids will be developed and implemented. Tertiary control, in the context of this paper, refers to the control layer that transcends the boundaries of a single microgrid, and hence supervises a group of microgrid central controllers (MGCC). Microgrids are considered as dynamic resources and loads that can inject or draw active and/or reactive power to/from the grid, depending on their loading condition. This paper focuses on microgrids with high penetration of renewable resources. To overcome renewable energy intermittency, the developed algorithm virtually aggregates neighboring microgrids into clusters, which virtually exchange energy through the distribution grid infrastructure stabilizing the main power infeed. For improved short-term planning, the developed algorithm periodically forecasts the net available energy from each microgrid. In addition, it solves a set of load flow equations, governed by predefined constraints, to determine (near-) optimal set points to the various microgrids, which consequently improves the efficiency and voltage stability of the distribution network, and increase its level of survivability. This study highlights some key examples of how the microgrids can be used to support the operation of the main grid, e.g. enhancing the voltage profile on a distribution feeder. The algorithm was validated experimentally using a laboratory scale testbed setup. [ABSTRACT FROM AUTHOR]

Islanded microgrids do not have sufficient resources to contribute enough fault current to legacy protection devices to continue operation. Therefore, when a fault happens in an islanded microgrid, relays with high fault current setting will fail to detect and clear the fault. Contemporary adaptive protection schemes rely on communication technologies to adjust the relay settings to adapt to the microgrids’ modes of operation; grid-connected or islanded. However, the risk of communication link failures and cyber security threats such as denial-of-service represent major challenges in implementing a reliable adaptive protection scheme. In order to address this issue, this paper proposes an adaptive protection scheme which utilize super capacitive energy storage to enhance resiliency against communication outages. This paper also introduces an autonomous control algorithm developed for the super-capacitor’s AC/DC converter. The proposed control is capable of deciding upon charging, discharging of the super-capacitor, and whether or not to feed fault currents in the AC side, based on direct voltage and frequency measurements from its connection point with the microgrid. This eliminates the need for a control command to be sent from the point of common coupling of the microgrid with main grid to adjust the controller’s mode of operation and thus reducing the risk of controller failure due to cyber-attacks or other communication issues. Additionally, the paper proposes a solution to avoid installing a larger super-capacitor by temporarily disconnecting the uncritical pulsed load during the fault instant. The proposed protection scheme was investigated through simulation for various fault types and showed successful results using the proposed scheme in eliminating the aforementioned faults when the communication were available or attacked. [ABSTRACT FROM AUTHOR]

This paper presents an advanced Real-Time Energy Management System (RT-EMS) for Microgrid (MG) systems. The proposed strategy of RT-EMS capitalizes on the power of Genetic Algorithms (GAs) to minimize the energy cost and carbon dioxide emissions while maximizing the power of the available renewable energy resources. MATLAB-dSPACE Real-Time Interface Libraries (MLIB/MTRACE) are used as new tools to run the optimization code in Real-Time Operation (RTO). The communication system is developed based on ZigBee communication network which is designed to work in harsh radio environment where the control system is developed based on Advanced Lead-Lag Compensator (ALLC) which its parameters are tuned online to achieve fast convergence and good tracking response. The proposed RT-EMS along with its control and communication systems is experimentally tested to validate the results obtained from the optimization algorithm in a real MG testbed. The simulation and experimental results using real-world data highlight the effectiveness of the proposed RT-EMS for MGs applications. [ABSTRACT FROM AUTHOR]