Microgrid Central Controller Research Articles

A two-layer energy management for islanded microgrid based on inverse reinforcement learning and distributed ADMM

The development of a scheduling strategy for an islanded microgrid (IMG) is critical for ensuring the system’s stability and economic efficiency. Traditional scheduling strategies for IMGs predominantly utilize centralized management by the microgrid central controller (MGCC), which introduces a vulnerability to a single point of failure. To address this limitation, this paper presents a two-layer energy management strategy for IMGs based on the improved alternating direction method of multipliers (ADMM) and inverse reinforcement learning (IRL). First, the framework of the proposed strategy, comprising a scheduling layer and a real-time dispatch layer, is outlined. Next, the problem formulation of the scheduling layer is analyzed, and the proposed IRL-based management strategy for the energy storage system (ESS) is presented. Then, a distributed optimization algorithm based on the improved ADMM is proposed for the management of controllable distributed generators (CDGs) in the real-time dispatch layer. Lastly, the case study demonstrates the efficacy of the proposed strategy in diminishing MGCC dependency. The comparative analysis indicates that the proposed strategy outperforms existing scheduling strategies in terms of cost-effectiveness when the forecast error exceeds 3%. Moreover, in contrast to existing scheduling strategies, the proposed strategy mitigates the risk associated with a single point of failure.

A Lightweight_PAEKS-based energy scheduling model considering priority in MicroGrid

Priority-based energy scheduling is proposed, whereby the data utility of measured user information in smart meters, including the priority and power demand of power consumers and the maximum power supply of power suppliers, is leveraged to ensure that in the case of limited power resources within islanded microgrids, energy is allocated to power consumers in the order of high to low priority. Nonetheless, in terms of data utility, most existing strategies only consider high-priority power consumers, neglecting the priority of power suppliers and low-priority power consumers, thus damaging the fairness of low-priority consumers and the interests of power suppliers, to the detriment of these groups. Moreover, smart meters are vulnerable to data integrity attacks, which may result in the manipulation of measured user information during the forwarding process, thereby disrupting normal priority-based energy scheduling. Therefore, focusing on data utility without considering data security is insufficient. Researchers have extensively investigated how to secure smart meters within advanced metering infrastructure (AMI), primarily employing cryptography-based methods to encrypt user information in measured meters and decrypt it at the microgrid central controller (MGCC), thereby protecting the data confidentiality of user information during the forwarding process and preventing data tampering. However, the prevailing cryptographic methods used to secure smart meters are extremely complex, and make smart meters and local controllers on the forwarding path unable to obtain any user information in which embedded consumers’ priority and cannot leverage the data utility of priority to forward information accordingly. In other words, existing models cannot simultaneously achieve data confidentiality and data utility during the forwarding process. To solve these issues, this study investigates a Lightweight_PAEKS-based energy scheduling model considering priority in microgrid (LPESCP). As a lightweight solution, the LPESCP comprehensively considers data confidentiality and data utility, as well as the priority and fairness of all users, to ensure the security of smart meters and optimize energy scheduling. In particular, the data utility problem is solved by using an optimization model that aims to maximize the global satisfaction degree of all users in terms of priority and fairness. The Lightweight_PAEKS and Paillier encryption scheme are used so that nodes on the forwarding path can successfully match priority-related keyword and forward information in order of the keyword corresponding emergency coefficient indicating the urgency levels of information, ensuring data utility, while do not know the specific keyword, emergency coefficient and other information, ensuring data confidentiality. To verify the effectiveness of the LPESCP, experiments are conducted for three cases generated based on random numbers. The results show that the LPESCP model can effectively ensure energy supply to consumers, comprehensively considering data confidentiality and utility as well as priority and fairness of all users. In addition, the global satisfaction degree and time overhead are introduced as metrics to verify that the LPESCP strategy is more effective in providing greater global satisfaction degree and lower time overhead than existing priority-based energy scheduling models.

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.

Encryption-based Coordinated Volt/Var Control for Distribution Networks With Multi-Microgrids

This paper proposes a data-driven coordinated volt/var control (VVC) strategy for active distribution networks (ADN) with multi-microgrids, which can achieve online economic and secure operations under false data injection attacks (FDIA). Based on voltage and power measurements, the microgrid central controller (MGCC) obtains optimal reactive power supports at the point of common coupling (PCC) and sends them to the distribution system operator (DSO). The MGCC is formulated with a convolution neural network (CNN) to emulate the optimal behaviors in microgrids (MGs), which can reduce computational burdens and facilitate its online application. The DSO then performs centralized optimization to dispatch VVC devices and update voltages at PCC. A voltage sensitivity-based reactive power adjustment method is also developed to simplify the iterative optimization process between ADN and MGs without deteriorating the VVC performance in each MG. Finally, data integrity and privacy are protected through an encrypted communication process against FDIA. The GGH (Goldreich-Goldwasser-Halevi) encryption algorithm directly prevents attackers from accessing the original transmitted data, while the RSA (Rivest-Shamir-Adleman) digital signature algorithm helps detect malicious tampering with the ciphertext during communication. Numerical simulations on a modified IEEE 33-bus ADN with three EU 16-bus MGs verify the effectiveness of the proposed method in mitigating voltage violations, reducing voltage regulation costs and protecting data security.

Cloud–Edge Cooperative Load Frequency Control for Isolated Microgrid Using Emergent Computation-Based Large-Scale Meta-Machine Learning

In the isolated microgrid, each unit is managed by different operators, and their interests conflict greatly. To balance the interests of different stakeholders in the electric grid sector, this paper proposes an Edge-Cloud cooperative data-driven load frequency control (ECCDD-LFC) method for isolated microgrids, which can deliver improved frequency control performance and reduce regulation cost. This method replaces the LFC controller in the conventional microgrid control center with a Cloud-based agent and sets each unit as an independent-decision Edge-based agent. It enables the units to make decisions independently and realize Cloud-Edge cooperative control. In addition, an emergent computation large-scale multi-agent deep meta-deterministic policy gradient (ECLSMA-DMDPG) is proposed. In this algorithm, a centralized training and decentralized execution policy are used to achieve the collaboration of multiple agents, a meta-learning technique is used to improve the robustness of the algorithm, and emergent computation is used to produce high-value samples for a higher-performance policy. The effectiveness of the proposed method is demonstrated in a simulation of the Zhuzhou isolated microgrid of the China Southern Grid (CSG) <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">.</i>

An Adaptive Centralized Protection and Relay Coordination Algorithm for Microgrid

To meet the increased customer demands, microgrid evolved. The structure of microgrid changes dynamically due to the intermittent nature of renewable-based generation, status of the distributed generator and opening of breakers for fault/maintenance. Hence, the magnitude of fault current is dynamic in nature. In order to deal with these dynamic changes, this paper addresses an adaptive central microgrid controller-based protection and relay coordination scheme, which revises the relay settings dynamically (both radial and looped configuration) for every change in topology. In the proposed algorithm, the primary relay responds to a fault immediately since the individual relays are given with fault level setting. For any abnormality in the network, the fault location is determined both via local relay and microgrid central controller (MCC). Hence, even though the local relay fails to identify the fault due to high fault impedance, the MCC locates the fault accurately and isolates the minimum faulty part. The coordination between relays is carried out by MCC in a time-graded manner based on microgrid central protection and relay coordination algorithm. The proposed algorithm is tested using Matlab in a microgrid built based on the IEEE 33 bus distribution network.

A hybrid smell agent symbiosis organism search algorithm for optimal control of microgrid operations.

This paper presents a hybrid Smell Agent Symbiosis Organism Search Algorithm (SASOS) for optimal control of autonomous microgrids. In microgrid operation, a single optimization algorithm often lacks the required balance between accuracy and speed to control power system parameters such as frequency and voltage effectively. The hybrid algorithm reduces the imbalance between exploitation and exploration and increases the effectiveness of control optimization in microgrids. To achieve this, various energy resource models were coordinated into a single model for optimal energy generation and distribution to loads. The optimization problem was formulated based on the network power flow and the discrete-time sampling of the constrained control parameters. The development of SASOS comprises components of Symbiotic Organism Search (SOS) and Smell Agent Optimization (SAO) codified in an optimization loop. Twenty-four standard test function benchmarks were used to evaluate the performance of the algorithm developed. The experimental analysis revealed that SASOS obtained 58.82% of the Desired Convergence Goal (DCG) in 17 of the benchmark functions. SASOS was implemented in the Microgrid Central Controller (MCC) and benchmarked alongside standard SOS and SAO optimization control strategies. The MATLAB/Simulink simulation results of the microgrid load disturbance rejection showed the viability of SASOS with an improved reduction in Total Harmonic Distortion (THD) of 19.76%, compared to the SOS, SAO, and MCC methods that have a THD reduction of 15.60%, 12.74%, and 6.04%, respectively, over the THD benchmark. Based on the results obtained, it can be concluded that SASOS demonstrates superior performance compared to other methods. This finding suggests that SASOS is a promising solution for enhancing the control system of autonomous microgrids. It was also shown to apply to other sectors of engineering optimization.

Interoperability of single-controllable clusters: Aggregate response of low-voltage microgrids

Microgrid clusters are complex systems that require the implementation of management strategies to control multiple elements and regulate the offering energy services. This paper proposes a management approach capable of aggregating the operation of clusters of multifunctional microgrids, aiming at improving the resiliency of distribution and transmission systems, as well as enhancing the microgrids’ power quality, under predictable and unpredictable events. Since the approach manages microgrids inserted into cluster to operate as single-controllable entities, a variety of ancillary services can be offered (e.g., energy time shifting, peak shaving, islanded operation, and many others). Consequently, operational goals can be pursued locally (i.e., at the point of common coupling of each microgrid) and systematically (i.e., at specific medium and high-voltage circuit branches). To demonstrate the applicability of the proposed energy management system, simulations were carried out using Matlab/Simulink, considering customized blocks in phasor domain, and taking the CIGRE’s European benchmark as reference model for the low-, medium- and high-voltage power systems. Different from previous studies, the simulations fully emulate the interoperability among microgrid central controllers, microgrid system operators and distribution system operator, demonstrating that a wide range of ancillary services can be put into action by means of the aggregate response of microgrids and based on price signals, without causing electrical overload. It is also demonstrated in the results that the active and reactive power flow in the high voltage grid is flexibly regulated, the power factor is increased up to 0.955 at different circuit branches, and the power quality is improved in the distribution level during absence of power generation at the medium voltage grid.

Time delay margin for islanded microgrid with parameter uncertainty using fractional order proportional‐integral‐derivative controller

AbstractIn this article, an islanded microgrid (MG) consisting of the diesel generator (DEG), the photovoltaic panel (PV), the wind turbine generator (WTG), the battery energy storage system (BESS), and the control unit is considered. In the islanded MGs, the control signals are exchanged on the open communication network, which results in the time delays in the input and the output of the islanded MG central controller (MGCC). The time delay has a destructive effect on the islanded MG stability. Thus, finding the maximum allowable time delay bound (MADB) is a significant issue. Since it is shown that the fractional order systems have larger stability region and more robustness rather than the corresponding integer order systems, in this research, we propose the fractional order proportional‐integral‐derivative (FOPID) controller as the MGCC to achieve a larger MADB value. As another innovation, in this article, a method is presented in which the MADB of the islanded MG system is determined considering the parametric uncertainties related to the damping coefficient (D) and the inertia constant (H). It is shown that the percentage improvement in the MADB of the uncertain MG system with the designed FOPID controller over the integer order proportional‐integral‐derivative (IOPID) controller is 9.64%. The accuracy of the proposed method is verified by simulation results in Matlab.

A Price-Based Strategy to Coordinate Electric Springs for Demand Side Management in Microgrids

Electric springs (ESs) have proven effective for integrating renewable generation into power systems. An ES connected in series with a non-critical load forms a smart load whose consumption can be dynamically controlled for voltage regulation and demand side management. In most existing applications, smart loads have been devoted to providing services to the grid without accounting for their own interests. The novelty of this paper is to propose a price-based strategy to coordinate the operation of multiple ESs in microgrids. Smart loads consisting of ESs connected to electric water heaters are modeled as rational agents that locally optimize their own objectives by adjusting their consumption schedules in response to price/control signals. Such signals are determined at the microgrid central controller (MGCC) when solving the microgrid operation scheduling problem formulated to minimize the microgrid operation cost taking into account the smart loads’ consumption schedules. An iterative optimization algorithm determines the equilibrium between the microgrid and smart loads’ objectives requiring only the exchange of price/control signals and power schedules between the local controllers and the MGCC. Case studies show the effectiveness of the proposed strategy to economically benefit both the microgrid and smart loads when scheduling their operation.

Market-based Real Time Congestion Management in a Smart Grid Considering Reconfiguration and Switching Cost

Network Real-Time Congestion (RTC) is a bottleneck that limits energy transfer from the generation units or up-grid to the loads. Some factors, such as intermittent generation of renewable resources and forced outages of generating units and load forecasting errors, can lead to Real-Time Congestion Management (RTCM) in a smart grid network. RTCM is a set of methods to eliminate congestion in real-time. To implement RTCM, some approaches can be employed, including network reconfiguration by Remote Control Switches (RCS), load shedding generation and up-grid power rescheduling. In this paper, a two-stage programming model is proposed to find the optimal solution for RTCM using the integration of reconfiguration and market-based approaches. Therefore, following the occurrence of congestion, at the first stage, microgrid central controller (MGCC) or central energy manager implements reconfiguration as the lowest-cost approach to mitigating RTC. The Soccer League (SL) algorithm is employed at the first stage to find the optimal network topology. Subsequently, based on the results obtained from the first stage, a programming model is applied at the second stage to completely eliminate the RTC. The proposed model minimizes a weighted objective function that includes the generation and up-grid rescheduling cost, load shedding cost, switching cost, and congestion clearing time. In order to model switching costs, a new index is defined to prevent risky switching and the depreciation caused by frequent switching. This index is determined based on the critical locations in the network and the age of RCSs. The numerical results demonstrate the efficacy of the proposed model.

Enhancement of a microgrid operation in blackouts using central control scheme and network reconfiguration: A case study

Due to recent advancements in photovoltaic technology and cost reduction, photovoltaic systems are nowadays added to existing microgrids with originally installed backup sources. Microgrid owners expect to lower their electricity and diesel bills, improve the reliability of the backup system in blackouts, and reduce air pollution. Despite the expected gains, the unplanned and progressive changes of the original microgrid lead to structural and control complexities. In this research, the microgrids at Birzeit University Campus are used as a case study. Microgrid central control scheme and minimally invasive network reconfiguration are employed to enhance the holistic operations of the microgrid. Moreover, power-sharing in off-grid operations is illustrated. The microgrid model and operation scenarios are developed and simulated in Matlab/Simulink. Results showed that the proposed solutions lowered the operation costs, improved microgrid reliability, and minimized the use of diesel consumption and consequently air pollution.

Analysis of LoRa Transmission Delay on Dynamic Performance of Standalone DC Microgrids

One important aspect toward proper and stable functioning of a communication-based controlled microgrid is data transmission. Consequently, an analysis of the effect of data transmission delay is of significance for any chosen communication protocol. This paper focuses on the effect of employing LoRa for data transfer at the secondary control level of a standalone DC microgrid. It analyses the effect of LoRa transmission delay on the dynamic performance of DC microgrids. This paper simulates a community DC microgrid that operates in three modes: PV mode, battery mode and generator mode. This microgrid operates as a centralized communication-based controlled microgrid, with the secondary control level operating as an event-driven level. The system incorporates a hierarchical system where data is transferred between the various distributed energy resources (DERs) local controllers and the microgrid central controller (MGCC). Simulations for three scenarios are presented. In the first scenario, the microgrid is designed and simulated without a communication delay to observe the system behavior. Then LoRa transmission delay is calculated for the various signals transferred between the MGCC and the local controllers. This delay is introduced into the simulation as transport delays and the system exhibits a level of stability degradation. Subsequently, a time delay compensation system is incorporated into the system for more robust operation. The delay compensation is applied in two simulation scenarios. In the first scenario, the system inductor (L) and capacitor (C) components are re-calculated, and the system is re-simulated to get a stable system even with the applied communication delay. In the second scenario, the proportional integrator (PI) controller in the microgrid central controller is re-designed to a more robust form to compensate for the delay caused by the LoRa transmission. The results obtained from the two modified simulations realize a stable DC microgrid. This system modification allows for system stability again, similar to the simulation when the microgrid operated without any communication delay. This, therefore, demonstrates that with proper system design and implementation, low bandwidth communication systems such as LoRa can be effectively employed for data transfer in event-driven communication-based controlled DC microgrids.

Hierarchical and Distributed Optimal Control Strategy for Power and Power Quality of Microgrid Based on Finite-Time Consistency

Droop control is one of the main control strategies of islanded microgrid (MG), but the droop control cannot achieve reasonable power distribution of microgrid, resulting in frequency and voltage deviation from the rating value, which needs the upper control link to eliminate the deviation. However, at present, most layered control requires a centralized control center, which excessively relies on microgrid central controller (MGCC) and real-time communication among distributed generation (DG), which has certain limitations. To solve the above problems, this paper proposes a hierarchical distributed power and power quality optimization strategy based on multi-agent finite time consistency algorithm (MA-FTCA). Firstly, based on the first layer droop control, MA-FTCA is applied to introduce frequency and voltage compensation to stabilize the system frequency and voltage at the rated value. Secondly, in the third layer, the MA-FTCA is adopted to estimate the total active power and total reactive power spare capacity of the system, to realize the reasonable distribution of active power and reactive power output of each DG according to its proportion of spare capacity when the system load side changes. The control strategy proposed in this paper adopts a completely distributed control method and does not need a centralized control center in each layer of control. Finally, MATLAB/Simulink simulation platform is used to verify the correctness and effectiveness of the proposed optimization strategy.

Towards Incentive for Electrical Vehicles Demand Response With Location Privacy Guaranteeing in Microgrids

The rapid and wide adoption of microgrids (MGs) and the increasing popularity of electric vehicles (EVs) have created a unique opportunity for the integration of these technologies. In this article, we address the issue of demand response of EVs during MG outages by leveraging Vehicle-to-Grid (V2G) technology. Particularly, we investigate an auction trading market that allows EVs with surplus energy to act as sellers, and EVs that want to be charged to act as buyers. A novel distributed double auction scheme is proposed to allow each buyer EV to submit multiple bids to seller EVs in different parking lots. Nonetheless, the locations of buyer EVs could be inferred by an adversary through analyzing the valuations, posing serious privacy and security risks. In this regard, a valuation-based attack scheme is investigated to validate the potential privacy risk. To defend against such an attack, we present a location privacy-preserving double auction scheme, in which the MicroGrid Central Controller (MGCC) acts as the auctioneer, solving the social welfare maximization problem of matching buyers to sellers, and the cloud is used to conduct calculations for the auctioneer, protecting the privacy of participants via homomorphic encryption. Theoretical analysis is conducted to validate our auction scheme in satisfying the designed economic and privacy properties (e.g., strategy-proofness and <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula> -anonymity). The experimental results show that our auction scheme can not only mitigate the demand response problem in MGs, but also provides good performance with respect to social welfare, satisfaction ratio, computational and communication overhead, and privacy leakage.

Adaptive Harmonic Impedance Reshaping Control Strategy Based on a Consensus Algorithm for Harmonic Sharing and Power Quality Improvement in Microgrids With Complex Feeder Networks

In islanded microgrids with complex feeder networks, distributed generation units (DGs) and loads can be freely connected to any node, leading to changes in the feeder impedance between nodes and the microgrid structure. However, traditional harmonic sharing control methods encounter difficulties with microgrids with complex topologies. Additionally, existing techniques essentially require constructing additional harmonic virtual impedance, possibly resulting in conflict between voltage quality and harmonic sharing effectiveness. To address this issue, this paper proposes an adaptive harmonic impedance reshaping method based on a consensus algorithm. The proposed method adaptively reshapes the inverter harmonic impedance by introducing harmonic current feedforward compensation control and impedance reshaping factor adaptive control, which can achieve accurate harmonic sharing while greatly improving the voltage quality of the microgrid. The proposed method avoids constructing additional harmonic virtual impedance and can be applied to microgrids with complex feeder networks and variable structures without acquiring prior microgrid configuration knowledge. Moreover, the proposed method is a fully distributed control, where the microgrid central controller (MGCC) is not required. Furthermore, the control parameter design method based on modeling and stability analysis is discussed in detail. Finally, simulations and experiments verify the feasibility and effectiveness of the proposed method.

Multi-agent dual strategy based adaptive protection for microgrids

This paper presents an adaptive protection dual strategy based on Relay Agents distributed along strategic locations of a microgrid. The architecture is based on the application of Relay Agents and three additional agents named Selectivity, Configurator, and Coordinator, executed in a microgrid central controller. The multi-agent strategy is divided in two complementary approaches, named online and offline. The online approach operates on fast protection, centralizing key information and selecting actions based on expert systems, thus requiring a communication infrastructure to eventually operate circuit breakers. The offline approach works as a backup protection in case of communication failures and delays, operating by adjusting relay settings in real time. The dual multi-agent protection strategy has been simulated to verify the performance of microgrid protection both in connected and isolated modes.

A decentralized control for Non-error frequency regulation in an islanded microgrid containing multiple VSGs

Secondary control in the hierarchical control of microgrids can achieve frequency restoration and accurate proportional power sharing among distributed generators (DGs) but depends on complicated communication systems. The flexibility and reliability of microgrids can be significantly improved by reducing the dependence on the communication system. Therefore, in this paper, a new decentralized control strategy for non-error frequency regulation with no intercommunication is proposed in an islanded microgrid containing multiple virtual synchronous generators (VSGs). In the proposed strategy, the frequency recovery link of the VSG, i.e., Proportional Integral (PI) controller, is split into an integral link and a proportional link that are connected in series. The integral link rapidly regulates the microgrid frequency to its rated value, while the proportional link achieves accurate proportional power sharing among VSGs. The whole process can be completed only by local measured signals by each VSG and through local frequency feedback instead of relying on the microgrid central controller (MGCC) and the information interaction between the adjacent VSG. The proposed control strategy enables multiple VSGs to collectively achieve frequency restoration, thus avoiding the problem of frequency regulation overload of a single VSG. The impact of VSG control parameters over the control system is also analyzed by the root locus. Finally, the simulation and experimental results verify the effectiveness of the proposed control strategy in this paper. The results show that the proposed control strategy can achieve frequency restoration and accurate proportional power sharing among VSGs simultaneously with no intercommunication.

An Interoperable Communication Framework for Grid Frequency Regulation Support from Microgrids.

Renewable energy sources, which are controllable under the management of the microgrids with the contribution of energy storage systems and smart inverters, can support power system frequency regulation along with traditionally frequency control providers. This issue will not be viable without a robust communication architecture that meets all communication specification requirements of frequency regulation, including latency, reliability, and security. Therefore, this paper focuses on providing a communication framework of interacting between the power grid management system and microgrid central controller. In this scenario, the microgrid control center is integrated into the utility grid as a frequency regulation supporter for the main grid. This communication structure emulates the information model of the IEC 61850 protocol to meet interoperability. By employing IoT’s transmission protocol data distribution services, the structure satisfies the communication requirements for interacting in the wide-area network. This paper represents an interoperable information model for the microgrid central controller and power system management sectors’ interactions based on the IEC 61850–8–2 standard. Furthermore, we evaluate our scenario by measuring the latency, reliability, and security performance of data distribution services on a real communication testbed.

Reliability Evaluation of Smart Microgrids Considering Cyber Failures and Disturbances under Various Cyber Network Topologies and Distributed Generation’s Scenarios

Smart microgrids (SMGs), as cyber–physical systems, are essential parts of smart grids. The SMGs’ cyber networks facilitate efficient system operation. However, cyber failures and interferences might adversely affect the SMGs. The available studies about SMGs have paid less attention to SMGs’ cyber–physical features compared to other subjects. Although a few current research works have studied the cyber impacts on SMGs’ reliability, there is a research gap about reliability evaluation simultaneously concerning all cyber failures and interferences under various cyber network topologies and renewable distributions scenarios. This article aims to fill such a gap by developing a new Monte Carlo simulation-based reliability assessment method considering cyber elements’ failures, data/information transmission errors, and routing errors under various cyber network topologies. Considering the microgrid control center (MGCC) faults in comparion to other failures and interferences is one of the major contributions of this study. The reliability evaluation of SMGs under various cyber network topologies, particularly based on an MGCC’s redundancy, highlights this research’s advantages. Moreover, studying the interactions of uncertainties for cyber systems and distributed generations (DGs) under various DG scenarios is another contribution. The proposed method is applied to a test system using actual historical data. The comparative test results illustrate the advantages of the proposed method.