Networked Microgrid System Research Articles

Hardware Implementation of a Resilient Energy Management System for Networked Microgrids

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.

Distributed robust data-enabled predictive control based voltage control for networked microgrid system

The networked microgrid system (NMG) has become an effective alternative for integrating various types of distributed energy resources (DERs). However, because of the increasing share of DERs and high R/X ratio in the system, the uncertainty and variability of DERs' power generation may cause significant voltage violations in the system. To address these issues, this paper introduces a novel distributed data-driven voltage control strategy based on data-enabled predictive control (DeePC) to address voltage violations problems in the NMG. The DeePC algorithm uses only historical system trajectories, eliminating the need for parameter identification procedures of power system. Based on the system data model, the proposed controller coordinates MGs in the NMG in a distributed manner by employing a consensus version of the fast alternating direction method of the multiplier algorithm (FADMM), which achieves a better privacy and scalability. Simulation studies in a modified two-MG NMG demonstrate the effectiveness and superiority of the proposed algorithm.

Performance evaluation of communication networks for networked microgrids

The main goal of cyber-physical power systems (CPPSs) is to provide seamless collaboration between the physical and cyber systems, bridging disciplines, such as communication networks and control systems. Controlling the operation of Microgrids (MGs) as a cyber-physical power system must include both the physical and cyber layers. Generally, the microgrid control center MGCC is employed for reliable operation management between the different local controllers within the networked microgrids (NMGs). Therefore, an excessive number of communication channels between the MGCC and the local controllers will exist, affecting the control performance of the NMGs. This paper focuses on developing an innovative communication network emulation model for standalone DC networked microgrids using a Network Simulator (NS3), miming the communication infrastructure to control the networked microgrid system. Through the real-time simulation, the performance of the proposed communication network model was evaluated by employing two transmission protocols, User Datagram Protocol (UDP) and Transmission Control Protocol (TCP), to facilitate the data exchange between the MGCC and the local controllers in each MG while operating under different traffic loads. The comparative results of using these protocols in terms of the key performance indicators (KPIs) of the communication performance metrics, such as the mean delay, percentage of packet loss, and transmitted and received bitrate, reveal notable insights into their suitability in data transmission for controlling and managing the operation of the NMGs.

A Control Architecture for Regulating Voltage and Power Flows in a Networked Microgrid System

This paper presents a unique control system to regulate power exchanges and load bus voltage in a networked microgrid (NMG) system comprising AC and DC microgrids. During the islanding of a microgrid in this NMG system, load voltage and power balance can get disturbed. A control system and associated converter and inverter control methods are presented to rectify these issues. An efficient model predictive control (MPC) method, which gives a tracking error of 50% lower than a conventional proportional-integral (PI) controller, is used to control multiple inverters in the NMG system. Simulation studies are conducted to test the NMG in islanding and load change scenarios. With the help of these studies, it is verified that the MPC-controlled inverters can provide better tracking accuracy in achieving desired power flows in the NMG system.

Asynchronous blockchain‐based federated learning for tokenized smart power contract of heterogeneous networked microgrid system

AbstractIn a networked microgrid system (NMS), various heterogeneous microgrids are interconnected. A networked microgrid system facilitates a new kind of physical design that provides numerous advantages such as distributed economic optimization, reliability, resiliency, and focusing on distributed generations and customers. Designing the secure and privacy‐protected smart power contract between electricity suppliers and consumers, considered as agents, of different microgrids, is a challenging task in the networked‐ microgrid system. Each microgrid implements a heterogeneous or isomorphic blockchain based platform. The blockchain interoperability, inherently, presents in different blockchains implemented by various microgrids. This paper reviews the interoperability issues and smart contract designs in blockchain‐based systems and 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 blockchains of network microgrids has been proposed. A methodology has been developed to transfer tokens between interoperable blockchains. A 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. Asynchronous blockchain based federated learning for peer‐to‐peer smart power exchange has been implemented in learning process of interoperable and heterogeneous blockchain based network hub of microgrid. For simulation purposes, MATLAB and python programming have been used with real‐time data of microgrids.

Token-Based Smart Power Contract for Interoperable Blockchains of Networked Microgrid System

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.

A Comprehensive Review of Architecture, Communication, and Cybersecurity in Networked Microgrid Systems

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.

Frequency Regulation of Interlinked Microgrid System Using Mayfly Algorithm-Based PID Controller

The primary goal of this article is to design and implement a secondary controller with which to control the system frequency in a networked microgrid system. The proposed power system comprises of Renewable energy sources (RESs), energy-storing units (ESUs), and synchronous generator. RESs include photovoltaic (PV) and wind turbine generator (WTG) units. The ESU is composed of a flywheel and a battery. Because renewable energy sources are not constant in nature, their values fluctuate from time to time, causing an effect on system frequency and power flow variation in the tie line. The nonlinear output from the RESs is balanced with the support of ESUs. In order to address this situation, a proportional integral derivative (PID) controller based on the Mayfly algorithm (MA) is proposed and built. Comparing the responses of controllers based on the genetic algorithm (GA), differential evolution (DE), and particle swarm optimization (PSO) technique-optimized to demonstrate the superiority of the MA-tuned controller.. The results of the validation comparisons reveal that the implemented MA-PID controller delivers and is capable of regulating system frequency under various load demand changes and renewable energy sources. A robustness analysis test was also performed in order to determine the effectiveness of the suggested optimization technique (1%, 2%, 5%, and 10%) step load perturbation (SLP) with ±25% and ±50% variation from the nominal governor and reheater time constant).

Robust Stabilization of a Microgrid with Communication Delay and Uncertainties

In this paper, the robust stabilization for the networked microgrid system is presented. A microgrid implements master-slave control architecture where the communication channel is utilized to exchange the reference current signals. With this structure, a time delay exists in the reference control signal which may lead to instability. The analysis of the control strategy is carried out in dq reference frame. The microgrid is constituted by PV and wind energy sources supplying a load through voltage source inverters. The stochastic nature of renewable energy sources introduces uncertainties which can be represented as fluctuations in the voltage and the current. The main contribution of the paper is formulating the controller design of the microgrid with communication delay and uncertainties in the model as H∞ control problem and Lyapunov–Krasovskii functional is utilized to develop stability criterion in bilinear matrix inequality form. Grey wolf optimizer is used to minimize the performance index and derive the stabilizing controller. The microgrid performance is tested through simulation using the time-varying nonlinear model of the microgrid. The results prove that satisfactory current and power-sharing are attained even with the existence of time delays and uncertainties.

A cost-efficient Based Cooperative Model for Relible Energy Management Of Networked Microgrids Within a Smart Island

This paper mainly focuses on investigating a stochastic energy management approach to enhance reliability of the networked microgrids within a smart island. In this regard, a networked microgrid is considered in the smart island, which is integrated with a multi-energy hub (multi-EH) system aiming to simultaneously support the electrical, thermal, and water demands of the island, isolated from the main grid. The objective function is organized as the cost of operation and reliability of the networked microgrid and is solved using a modified bat algorithm. The uncertainty of stochastic parameters is modelled using the 2-m point estimate method, which has notable advantages in terms of accuracy and simplicity of implementation. Different scenarios are considered both in critical and normal conditions to evaluate the performance of the studied model. Both GAMS and MATLAB software’s were employed to study the proposed model. The proposed model improved the reliability of the networked microgrid system and results reveal that the proposed cooperative approach could decrease total operation and investment cost of the networked microgrid by 13%.

Optimal scheduling strategy of grid-connected microgrid with ladder-type carbon trading based on Stackelberg game

Aiming at the problems of promoting new energy consumption, reducing carbon emissions, load fluctuations, and multi-agent conflict of interests in the networked microgrid system, this article proposes a microgrid optimization operation strategy based on demand response and reward-penalty ladder-type carbon trading mechanism. First, in order to determine the electricity sales price of the system, an optimal scheduling model for microgrid operators is established, including gas cost, electricity profit for users, and surplus power supply network profit. Second, a demand response strategy on electricity price and low-carbon compensation incentives is proposed on the user side. The transaction model is embedded between microgrid operators and users into the master–slave game framework, and a multi-slave game collaborative optimization model is established with microgrid operators as leaders and users as followers. The existence and uniqueness of Stackelberg game are proved, and the differential evolution algorithm and CPLEX solver are used to solve the proposed model. Finally, an example of a microgrid system including three community users is provided to show the effectiveness of the proposed model and strategy.

Hour Block Based Demand Response for Optimal Energy Trading Profits in Networked Microgrids

Microgrids are a small-scale power system that integrates Distributed Generation, Energy Storage Systems and controllable loads. The intermittent and variable nature of renewable generation leads to a complex control mechanism required for Microgrids. Microgrids that are geographically close to each other are interconnected to form Networked Microgrids. Networked Microgrids provide enhanced benefits of resource sharing to Microgrids, thus, improving the reliability and operation costs while reducing the environmental impact. The Microgrids, based on their generation and load profiles, can perform energy trading within the Networked Microgrid system for achieving optimized operational costs. In this paper, the impact of a novel hour block-based demand response program in Networked Microgrids is explored. In the proposed model, hour blocks are formed in a Networked Microgrids environment, dependent on generation and load imbalance, the role of Microgrids and the Time-of-Use tariff system. The Particle Swarm Optimization method is used to optimize the individual and overall economic benefits of Microgrids in the Networked Microgrid system. The simulations of the proposed method are performed on a Networked Microgrid system having 4 Microgrids. The results show a credible reduction in costs of operation for all Microgrids and the system as a whole.

Distributed Model Predictive Frequency Control of Inverter-Based Networked Microgrids

This paper proposes a distributed frequency control method for an off-grid inverter-based networked microgrid system (NMS) with loads, renewable generators and energy storage devices (ESDs). The frequency regulation problem is formulated as a model predictive control (MPC) problem that aims to maintain the supply-demand power balance within each microgrid and scheduled net power interchange among connected microgrids at minimal regulation costs. The charging/discharging efficiencies as well as energy capacities of ESDs, and constraints on bus voltages are also considered. The proposed MPC problem is solved by a distributed projection-based algorithm via information sharing between adjacent buses. The effectiveness of the proposed method is validated by simulations implemented in Matlab/Simulink.

Design of Networked Microgrid‟s Control towards Power Coordination and Voltage Frequency Regulation

One of the state-of-the-arts of smart grid system is the concept of networked microgrid that provides flexible integration and coordination of distributed renewable energy resources in multiple microgrids. However, due to the variable nature of renewable generations, load changes and grid contingencies, the system suffers from significant fluctuations of power, voltage and frequency. This paper seeks to present comprehensive converter control solutions for power sharing coordination and stabilization of voltages and frequency to ensure high power quality and reliability in a networked microgrid system regardless of its grid-connected and islanded modes of operation. The control solutions are provided in d-q axes for both active and reactive powers. The multilevel inverter topology that is designed to interface the distributed energy resources results in better suppression of output harmonics compared to that with a conventional 2-level inverter. The paper also features an interlinking algorithm framework of particle swarm optimization (PSO) to tune the control parameters for the optimized performance of converters. A prototype of grid-connected system of three microgrids is simulated in PSCAD platform to validate the efficacy of the proposed solution.

Nested Formation Approach for Networked Microgrid Self-Healing in Islanded Mode

This paper proposes a novel nested restoration decision system (NRDS), which aims to minimize unused capacity of distributed generation (DG) for service restoration due to contingency during islanding stage. The proposed algorithm is based on the concept of nested microgrid formation, where the network control schemes are framed on a layered structure. The power-sharing strategy between neighboring microgrids in the network is from outer to inner microgrid loads, where the outermost microgrid exchanges power with utility grid only. The first stage refers to pre-fault scenario, which finds a solution for networked microgrid distributed generation as the initial setting. Furthermore, the second stage calculates additional redistribution requirements based on respective microgrid's deficiency using a solution index matrix. The proposed control has been evaluated on a networked microgrid system, while performing islanding.

Distributed Formal Analysis for Power Networks With Deep Integration of Distributed Energy Resources

A scalable distributed formal analysis (DFA) via reachable set computation is presented to efficiently evaluate the stability of large-scale interconnected power networks under heterogeneous disturbances induced by high penetration of distributed energy resources (DERs). Based on rigorous mathematical derivation, DFA is able to directly compute the boundaries of all possible dynamics and provide stability information, which is unattainable by traditional time-domain simulations or direct methods. An $N+M$ decomposition approach is established to decouple a large-scale networked system and enable distributed reachable set calculations while also preserving the privacy of each subsystem. Numerical examples on a networked microgrid system show that DFA facilitates the efficient calculation and analysis of the impact DER disturbances can have on power network dynamics, which provides a potent means of optimizing the system's operation. Therefore, DFA provides an invaluable tool for designing and operating the interconnected power networks of the future, which will feature the deep integration of DERs.

A Two-Layer Distributed Cooperative Control Method for Islanded Networked Microgrid Systems

This paper presents a two-layer distributed cooperative control method for networked microgrid (NMG) systems, taking into account the proprietary nature of microgrid (MG) owners. The proposed control architecture consists of an MG-control layer and an NMG-control layer. In the MG layer, the primary and distributed secondary controls realize accurate power sharing among distributed generators (DGs) and the frequency/voltage reference following within each MG. In the NMG layer, the tertiary control enables regulation of the power flowing through the point of common coupling (PCC) of each MG in a decentralized manner. Furthermore, distributed quaternary control restores the system frequency and critical bus voltage to their nominal values and ensures accurate power sharing among MGs. A small-signal dynamic model is developed to evaluate the dynamic performance of NMG systems with the proposed control method. Time-domain simulations and experiments on NMG test systems are performed to validate the effectiveness of the proposed method.

Networked microgrid stability through distributed formal analysis

A scalable distributed formal analysis (DFA) via reachable set computation is presented to efficiently evaluate the stability of networked microgrids under disturbances induced by distributed energy resources (DERs). With mathematical rigor, DFA can efficiently compute the boundaries of all possible dynamics in a distributed way, which are unattainable via traditional time-domain simulations or direct methods. A distributed quasi-diagonalized Geršgorin (DQG) theory is then combined with DFA to identify systems’ stability margins. A microgrid-oriented decomposition approach is established to decouple a networked microgrid system and enable calculations of DFA and DQG while also preserving the privacy of each subsystem. Numerical tests on a networked microgrid system validate that DFA and DQG facilitate the efficient calculation and analysis of networked microgrids’ stability.

Formal Analysis of Networked Microgrids Dynamics

A formal analysis via reachable set computation (FAR) is presented to efficiently assess the stability of networked microgrids in the presence of heterogeneous uncertainties induced by high penetration of distributed energy resources. FAR with mathematical rigor directly computes the bounds of all possible dynamic trajectories and provides stability information unattainable by traditional time-domain simulations or direct methods. An advanced Gersgorin theory with a quasi-diagonalization technique is then combined with FAR to estimate eigenvalues of those scenarios pertaining to the reachable set boundary to identify systems’ stability margins. Extensive tests show that FAR enables efficient analysis on impacts of disturbances on networked microgrid dynamics and offers a potent tool to evaluate how far the networked microgrid system is from its stability margins. These salient features make FAR a powerful tool for planning, designing, monitoring, and operating future networked microgrids.