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Grid modernization and innovations in clean energy are leading to a rapid increase in the penetration of inverter-based resources (IBRs) like wind power and solar photovoltaic (PV) plants in the bulk power system (BPS). To study the implications on BPS dynamics and mitigate potential risks to grid reliability, the second-generation generic renewable energy system model has been developed earlier. However, this model has three modules with eighty-six user-defined parameters and eight control flags to facilitate the utility-scale solar PV plant operation in different control modes. It presents a major challenge to the transmission system planning engineers. There is a critical need to identify the key parameters of the dynamic model that are highly sensitive to grid events causing large-scale voltage and frequency disturbances. In this work, a sensitivity analysis based on modified Sobol method is proposed for identification of the key parameters in the utility-scale solar PV plant model. The total Sobol sensitivity index captures even the higher-order effects of the variations in the parameters. Validation of the identified key parameters was carried out on a modified IEEE 9-bus system and 200-bus synthetic grid using PSSE for plant-level control and local coordinated control operation of the solar PV plant.

The International Electrotechnical Commission (IEC) 62351-6 standard prescribes provisions to secure IEC 61850-8-1 generic object-oriented substation events (GOOSE) communications from cyber threats. The GOOSE authentication schemes recommended by IEC 62351-6 have shortcomings, such as long authentication-value computation times, large signature lengths, the usage of symmetric keys, and susceptibility to quantum computer attacks. To overcome these, this paper proposes the usage of the rainbow signature scheme (RSS), a quantum cryptographic method to secure GOOSE messages. The RSS offers fast signature generation and verification using asymmetric keys, making it very attractive to meet the time-latency and security requirements of the GOOSE protocol. The adaptation of the RSS cryptography method for its application to the GOOSE protocol is presented in this paper. The algorithms for key generation, signature computation and message verification are discussed in detail. A first-of-its-kind C library that incorporates security features within the GOOSE protocol in compliance with the IEC 62351-6–stipulated format, is developed. The superior features of the RSS in comparison with the other IEC 62351-6 security schemes are demonstrated.

The reactive power capability of distributed photovoltaic (PV) inverters could be exploited to mitigate voltage violations under high PV penetration in the distribution grid. Coordinating the reactive power dispatch of individual PV inverters to obtain desired voltage regulation performance is a major challenge. In this article, a decentralized method is proposed to enable PV inverters to autonomously regulate terminal node voltages. The proposed method minimizes the effect of a terminal node's reactive power contribution on the voltage profile of its respective parent-to-terminal node. This ensures that the interference between the voltage regulation of terminal nodes by individual PV inverters is minimized. The performance of the proposed decentralized scheme is verified by extensive powerflow simulations on the EPRI Circuit 24 test feeder in open-source distribution system simulation platform OpenDSS.

Faults in dc microgrids require quicker interruption than those in traditional ac power systems. This is due to the reduced stiffness of dc microgrids being powered by low inertia distributed energy resources interfaced through power electronic converters. For a high impedance fault, the limited magnitude of the fault current poses additional challenges in detection and identification of fault location in the system, with difficulty in distinguishing the fault condition from the normal operating condition. This article proposes a new cost-effective protection system for fast identification, selective isolation of short circuit and high impedance faults, and system restoration in such dc microgrids. It is achieved through proper coordination of source converters with intelligent three tie contactor switch units (ICU) and there are no solid-state circuit breakers in action. The high impedance faults are identified through multi resolution analysis of the locally measured current signals with discrete wavelet transform and K -nearest neighbor-based classifier at each source converter and contactor. The selectivity is achieved through adaptive resistance time curves set by the programmable relay units installed at each ICU node in the system.

Recently, prime-mover stalling phenomenon was observed in a synchronous generator-based distributed energy resource (DER) for large step load changes during experimental testing at the Consortium for Electric Reliability Technology Solutions Microgrid. It is found to highly impact the generator's survivability during transient overload conditions. The stalling occurs in synchronous generator-based DER because of a sustained imbalance between electrical load demand and mechanical power available from the prime mover, thus depleting the generator's stored kinetic energy. In particular, mechanical power capability of the prime mover and stored kinetic energy in the rotating mass are the causal factors. This article evaluates two different types of prime movers—reciprocating engine and combustion gas turbine—for the DER survivability. The characteristics of these two commonly used prime movers are investigated during transient overload conditions by simulation case studies using PSCAD/EMTDC software.

Modern shipboard power systems (SPSs) with advanced cyber infrastructure need urgent attention because they have higher risk of cyber attacks. In particular, false data injection (FDI) attacks can interfere with state estimation by tampering with measurement devices, or they may also directly target the central control system. This paper proposes a twofold strategy to mitigate the effects of such an unconventional FDI attack, using battery to actively reduce load curtailment. To detect signs of malicious data, a multiagent system (MAS) that checks commands from the central energy management system is employed. A novel bilevel optimization problem is formulated to model the interaction between the battery and the compromised SPS. A heuristic defense parameter is developed to improve the detection of corrupted commands. The merits of the proposed scheme are evaluated using a risk analysis model. The results of the case studies prove that a combination of autonomous battery with MAS-based heuristic method is effective in mitigating the effects of the cyber attack.

This study proposes a strategy for coordinated operation of networked microgrids (MGs), distributed energy resources (DERs), and volt-VAR control devices in the implementation of volt-VAR optimisation (VVO). The authors’ formulation is focused on implementing conservation voltage reduction, although it can be extended for any other VVO problems. They consider the voltage–power control modes of DERs contemplated in IEEE Std. 1547, namely, constant power factor, voltage–reactive power, active–reactive power, and constant reactive power. DERs are considered at the distribution network (DN) and within the MGs. The problem is formulated as a bi-level optimisation problem where the DN operator (DNO) is in the upper-level and each MG in the lower-level. The DNO and each MG are assumed to be players with their individual objective functions. Finally, they validate their formulation in two test systems: a 9-node system and a modified IEEE 33-node system. On average the proposed method can improve the efficiency of the grid by 4% compared to the economic operation scenario. The results of the study show that the different control modes of the DERs can have better performance depending on the objective of the VVO formulation. The findings of this study are compelling for the implementation of VVO in active distribution systems with networked MGs.

Inverter-based distributed energy resources (DERs) can supply high-quality ac power in a microgrid due to their fast dynamic response. To achieve high reliability in an islanded microgrid, they are normally operated as voltage-controlled sources. However, the net load supplied by voltage-controlled inverter-based DERs can exceed their rated capacity, particularly during their transition from the grid-connected operation mode. Therefore, a comprehensive analysis of the DER survivability for overload conditions is crucial. Several experimental tests were conducted at the Consortium for Electric Reliability Technology Solutions Microgrid Testbed on the prime-mover powered inverter-based DER for learning about its survivability during overload conditions. In this paper, a thorough investigation of the inverter-based DER's survivability is carried out based on the prime-mover stalling phenomenon. Analytical expressions are derived for key design parameters of load-shedding algorithms, such as time-to-threshold frequency, maximum time delay , and maximum survivability time . The theoretical estimates are validated with the results obtained from the experimental testing. Furthermore, the minimum load-shedding estimate is determined for any prime-mover powered inverter-based DER to survive a transient overload condition.

High-volume synchrophasor data generated by wide area measurement system (WAMS) presents new challenges for the design of scalable and robust communication architectures suitable for large-scale deployment in power grid monitoring and control applications. Features of information and communication technology (ICT) can be harnessed to devise a more flexible infrastructure than the conventional unicast-based hierarchical architecture. Multicast has been suggested as a potential solution for scalability issues in the current WAMS architecture. This paper proposes a decentralized dynamic multicast routing management algorithm that manages network traffic efficiently, improves scalability, and makes the system resilient to component failures. The algorithm models creation of alternate links as a stochastic process using random-graph theory and manages connections between end hosts at the session layer. This protocol can be implemented using existing ICT protocols with minimal cost. Numerical simulations show that the proposed algorithm improves the topological efficiency and resilience of the network.

Converter-interfaced wind turbines (WTs) can contribute to inertial frequency regulation through appropriate control of the converter interface. The kinetic energy (KE) of the WT rotor blades is the transient power reserve for inertial frequency support. This work demonstrates that the partial loss of power extracted from the wind when the WT decelerates to release its KE into the network restricts the maximum deviation of the WT rotational speed from the Maximum Power Point (MPP). For higher amount of transient deviation from the MPP, the WT is found to be susceptible to instability. These insights are drawn from Lyapunov's theory for the robust stability of non-linear dynamic systems, applied to the converter-interfaced WT system. The state-space equations governing the operation of the system around the MPP, and modeling of the wind power output are presented. Further, this work quantifies the stability-constrained maximum allowable deviation from the MPP speed, and presents a formulation using Lyapunov's methods to compute this quantity. The robust stability limit provides insights for designing the inertial frequency support contribution of the WT. For this, a control method that uses a virtual synchronous generator (VSG) control loop in the converter interface is presented.

Inter-substation Generic Object Oriented Substation Events (GOOSE) communications that are used for critical protection functions have several cyber-security vulnerabilities. GOOSE messages are directly mapped to the Layer 2 Ethernet without network and transport layer headers that provide data encapsulation. The high-status-number attack is a malicious attack on GOOSE messages that allows hackers to completely take over intelligent electronic devices (IEDs) subscribing to GOOSE communications. The status-number parameter of GOOSE messages, stNum is tampered with in these attacks. Given the strict delivery time requirement of 3 ms for GOOSE messaging, it is infeasible to encrypt the GOOSE payload. This work proposes to secure the sensitive stNum parameter of the GOOSE payload using systematically encoded polynomial codes. Exploiting linear codes allows for the security features to be encoded in linear time, in contrast to complex hashing algorithms. At the subscribing IED, the security feature is used to verify that the stNum parameter has not been tampered with during transmission in the insecure medium. The decoding and verification using syndrome computation at the subscriber IED is also accomplished in linear time.

Battery energy storage (BES) has become very attractive to electric utilities due to its promising frequency response characteristics. Its fast response under disturbances is particularly appreciated, that is, the BES can take faster actions than traditional synchronous generators (SG) during abrupt load changes. This paper presents a dynamic analysis of an islanded mixed energy source microgrid, containing one BES and one synchronous generator based distributed energy resource. The dynamic model of voltage source converter (VSC) controller is developed, considering distributed droop control scheme. Besides, to track the dynamic behaviors of the system, an extended Kalman filter (EKF) algorithm is employed to derive dynamic state estimation (DSE). Case studies demonstrate the merit of BES in terms of absorbing the abrupt load changes. In addition, the effectiveness of proposed EKF based DSE strategy is validated, as the dynamic behaviors of system state are accurately tracked despite the existence of process and measurement noises.

Advancement in transportation electrification has led to the revolutionary concept of Turbo electric distributed (TeDP) propulsion in aircrafts. NASA’s N3X aims to curb the jet fuel emission by TeDP. There as been a significant number of accidents for commercial aircraft due to various endogenous failure events. Thus, it becomes crucial to analyse the TeDP system under extreme conditions and analyse the survivability under those transient conditions. Reconfiguration under extreme failure events is a way to meet the load demand. However, this creates a transient overload condition due to the fuel map limit of the turboshaft prime mover and affects the DC bus voltage. It is important to understand the survivability of the system during these extreme conditions which can lead to a collapse of the system and can present instability issue because of the CPL. In this work a mathematical analysis of the survivability of the system is presented in order to make it resilient. To prevent the collapse of the system a mitigation strategy has been proposed using the energy storage system which makes the turboshaft to remain in the safe zone. The system was simulated for two different failure conditions in PSCAD and the optimum energy required to make the system survive was obtained.

Power distribution infrastructure is undergoing a major transformation towards a more secure, flexible and resilience network, and microgrids comprising distributed energy resources are believed to facilitate this goal. In this paper, we explore and develop a market mechanism to enable a transactive energy framework among microgrids to provide an alternative market operation strategy. Specifically, the proposed market framework enables peer-to-peer power trading among microgrids to offer the microgrids an alternative channel to sell their surplus power. The major benefit of promoting the proposed framework is to facilitate mutual support among microgrids during the main grid outage, thus enhance the overall resilience of the system. An optimization model based on equilibrium problem with equilibrium constraints framework has been developed to formulate the gameplay among various microgrid participates in the transactive energy market. In addition, we adopt the data from a real-world distribution system located in Medellin, Colombia to demonstrate the merits of proposed framework. The numerical studies indicate that the unserved energy index during main grid outage reduces by 85.6% if the proposed strategy is applied, which validates the value of the strategy in enhancing system resilience.

Resilience of electricity grids to rare but severely disruptive events, such as natural disasters, has emerged in recent years as an important aspect in power system planning. Development of resilience-oriented techniques are needed due to the limitations of reliability-oriented methods in addressing large unexpected outages. This article presents a novel decision analysis approach to enhance the resilience of a power distribution system by leveraging the distributed nature of solar photovoltaic (PV) and battery energy storage system (BESS) resources. The proposed decision-making framework uses an analytic hierarchy process to evaluate different possible allocations of PV and BESS resources to load buses for multiple contingencies based on resilience enhancement and cost. Each allocation plan provides the size of PV arrays and BESS units to be installed at each bus within the distribution system. A deterministic formulation ranks line outage scenarios based on unserved load. The tradeoff between cost and resilience is modeled via cost-effectiveness analysis (CEA) that indicates the preferability of each allocation plan. The main contribution of this article is the development of an adaptable and computationally feasible decision support framework to determine cost-effective configurations of PV arrays and BESSs for mitigating the effects of power line outage contingencies. To evaluate the proposed framework, a case study is carried out on the IEEE 33-bus radial distribution system. The results show that the proposed method can offer effective guidance to the planner for making informed investment decisions and achieving cost-effective resilience enhancement.

The electric power system is facing greater threats each year due to malicious attacks. In the recent decade, multiple attacks on both physical and cyber layers of the power system resulted in significant economic loss. In particular, a cyber-physical coordinated attack is deemed to be a destructive behavior that is likely to cause cascading failures. Therefore, this paper focuses on hedging against a coordinated cyber-physical attack from the standpoint of allocating defending resources. The coordinated attack involves physical short-circuiting of transmission lines after intruding the communication network of protection relays. The paper proposes a tri-level optimization model to formulate the coordinated attack scenario and identify the optimal defending strategy, which is a first of its kind study of defending resource allocation to hedge against the coordinated attack. Upper-level problem represents the actions of the planner and determines the optimal defending resource allocation on transmission lines and communication network of protection relays. Defending strategy achieves the lowest expected unserved energy with coordinated attacks considering multiple representative operating conditions. Middle-level problem formulates the behaviors of the attacker, who identifies the targets and attack time to maximize unserved energy. Lower-level problem simulates the actions of operator for system redispatch aimed at minimizing unserved energy. Sensitivity analyses are conducted on IEEE 14-bus system and IEEE 57-bus system to investigate the effects of attack budget, defend budget and restoration duration on unserved energy. The results indicate greater unserved energy with higher attack budget, lower defend budget, and longer restoration duration. Moreover, significant unserved energy reduction was observed when the proposed optimization model is applied to allocate defending resource.

This paper investigates the effect of uncertainty in the allocation of photovoltaic (PV) generation, solar irradiance, and its impact on the power flow in a distribution network. The solar irradiance available in the National Renewable Energy Laboratory Resource Data Center is clustered into two states: high and low irradiance defined by a threshold. The uncertainty is modeled based on Non-Gaussian distribution, obtained using kernel density estimation. This estimation aids in achieving the probability density function and cumulative distribution functions of the solar irradiance. Moreover, the load demand, wind speed, and generator location are modeled according to Gaussian, Weibull, and discrete uniform distribution functions, respectively. As a part of probabilistic power flow, the backward/forward sweep method is used to solve each scenario of the Monte Carlo simulation. The proposed framework is applied to the 33-node test system considering three different test cases. The first case considers deployment of PV systems in three microgrids of the electric grid, and the other two test cases analyze different levels of penetration of randomly allocated PV and wind power systems. At the end, the results indicate potential reverse power flow through certain branches of the grid, and the renewables have a major impact on the system.

Power system security against attacks is drawing increasing attention in recent years. Battery energy storage systems (BESSs) are effective in providing emergency support. Although the benefits of BESSs have been extensively studied earlier to improve the system economics, their role in enhancing the system robustness in overcoming attacks has not been adequately investigated. This paper addresses the gap by proposing a new battery storage sizing algorithm for microgrids to limit load shedding when the energy sources are attacked. Four participants are considered in a framework involving interactions between a robustness-oriented economic dispatch model and a bilevel attacker-defender model. The proposed method is tested with the data from a microgrid system in Kasabonika Lake of Canada. Comprehensive case studies are carried out to demonstrate the effectiveness and merits of the proposed approach.

A synchronous generator-based distributed energy resource (DER) is commonly employed in microgrids due to its low cost and simple controls. However, there are many challenges to the DER operation when it is sized for supplying the critical loads alone in a microgrid. In particular, the DER would experience an overload condition during the microgrid transition from grid-connection to islanded operation, when the noncritical loads are also supplied momentarily. Therefore, it is very important to have a clear understanding on the survivability of a synchronous generator-based DER for transient overload conditions. Recently, experimental tests on survivability of the DER were carried out in the Consortium for Electric Reliability Technology Solutions Microgrid Testbed at American Electric Power. In this paper, an in-depth analysis of the synchronous generator-based DER operation during transient overload conditions is presented. The key relationships governing the system dynamic behavior of synchronous generator-based DER are analyzed to design the load shedding scheme for its survivability. Several case studies are illustrated to demonstrate the validity of the proposed load shedding method.