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Smart grid enables integration of distributed generations (DGs) to contribute to support the network. In the islanding condition, a section of the system and at least one DG become separated from the main grid and can continue to operate autonomously. This paper proposes a passive islanding detection algorithm using just the DG power factor angle to extract an indicator for islanding detection with a negligible non-detection zone (NDZ). The proposed algorithm guarantees reliable detection of islanding condition even where the system is composed of multiple DGs including different types. In this paper, islanding and non-islanding events are discriminated using the proposed algorithm even in a nested microgrid which is operated autonomously. Moreover, the proposed algorithm provides secure detection in the noisy condition. Also, the proposed algorithm allows reaching the frequency and voltage ride-through requirements quickly by correctly discriminating grid-connected disturbances from islanding condition. The performance of the proposed algorithm is validated by performing extensive simulations and scenarios in different test systems. The results of the IEEE 34 bus test system have been presented in this paper. [ABSTRACT FROM AUTHOR]

This paper proposes a novel distributed noise-resilient secondary control for voltage and frequency restoration of islanded microgrid inverter-based distributed generations (DGs) with an additive type of noise. The existing distributed methods commonly are designed as secondary control system systems that operate on the assumption of ideal communication networks among DGs. However, the channels are prone to stochastic noise, whereas each DG obtains noisy measurements of the states of its neighbors via environmental noises. The existing distributed noise-resilient methods, ignore a complete model of the system. In contrast, this paper proposes consensus protocols that take into account both the noisy measurements and a complete nonlinear model of the system, examines the mean-square average consensus for voltage and frequency restoration of islanded ac microgrids in an uncertain environment, and provides accurate proportional real power sharing. Our proposed consensus protocol contains two parts: the state feedback of the agent and the relative states of the DG and its neighboring DGs. Finally, simulation studies are carried out in MATLAB/SimPowerSystems to evaluate the performance of the control laws. Simulation results and comparison with previous work reveals the effectiveness of the proposed method in regulating microgrid voltage and frequency and providing accurate proportional real power sharing. [ABSTRACT FROM AUTHOR]

To seamlessly transition a microgrid (MG) from islanded to grid-connected mode, it is necessary to synchronize the magnitude, frequency, and phase of the MG voltage to the voltage of the main grid. In this paper, we propose a distributed control strategy to achieve synchronized operation of an islanded MG supported by multiple controllable distributed generators (DGs). The proposed method utilizes a pinning-based consensus algorithm to ensure explicit coordination between magnitude, frequency, and phase angle regulation while ensuring proportional power sharing. System frequency is regulated by all the DGs in proportion to their capacity, while a selected DG eliminates the phase and magnitude regulation errors. Controller design criteria is based on small-signal stability analysis. The proposed control strategy is implemented in hardware controllers and its effectiveness is demonstrated using a real-time hardware-in-the-loop MG testbed. [ABSTRACT FROM AUTHOR]

Due to the uncertainty of feeder impedance, conventional droop control-based power sharing scheme presents poor reactive power sharing accuracy in microgrid. As microgrid configuration becomes more and more complicated, reactive power sharing between various distributed generation (DG) equipment is very challenging. To achieve proper power sharing with a simple control method in microgrid, a new structure and power sharing method is proposed in this paper. Instead of using complicated reactive power sharing scheme, this paper proposes separated energy server (ES) units to provide reactive power. Then, active power supplying and reactive power supplying can be achieved separately by energy routers (ERs) and ESs, respectively. With the introduction of ES, the power sharing between DG units can be easily achieved without any supplementary communications or control algorithms. In addition, to reduce costs,a hybrid reactive power compensation configuration with capacitor banks and ESs is provided. Operation principle and power control strategy for DG units and ESs are explained and analyzed in this paper. In order to properly select the coefficients of the power controllers, sensitivity and stability of the system are investigated. Simulation and experimental results are presented to prove the validity of the proposed power sharing method, showing that ERs can effectively share the active power and ESs can effectively share the reactive power according to their capacity. [ABSTRACT FROM AUTHOR]

The sharing of nonlinear loads among different distributed generation units (DGs) is always a tradeoff between accuracy and voltage quality. This paper proposes a virtual harmonic conductance for each harmonic as a family of droop characteristics in terms of conductance versus current. Assigning a variable conductance for each harmonic current improves the DG controllability, thus offering accurate nonlinear load sharing, which is crucial at the near-rated loading and enhanced voltage quality. This paper also unveils a tuning methodology for the droop characteristics that sets a maximum permissible value for each individual harmonic to comply with international standards. Lastly, a hybrid voltage and current control system is suggested to accurately track the DG harmonic conductance designated by the proposed droop characteristics. While the proposed algorithm is capable of accurately distributing common nonlinear loads among DGs, it also enjoys the advantage of supplying local nonlinear loads by their dedicated DGs. A comprehensive performance evaluation assures the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

In three-phase AC/DC hybrid networked microgrids (NMGs), the operational limits of AC/DC interconnected converters and distributed generator (DG) interface inverters increase the non-convexity of the power flow model, and conventional distributed power flow (DPF) algorithms based on heuristic rule may encounter convergence problems when processing limit. This paper proposed a fully DPF calculation method that can robustly handle the non-smooth reactive power limits of converters and non-smooth voltage regulation of step voltage regulators, also reducing the model dependence on the initial values. In this algorithm, the non-smooth constraints were converted into smooth functions, and based on a bi-level augmented Lagrangian alternating direction inexact Newton (ALADIN) method with the second-order convergence rate the original DPF problem was transformed into the problem of distributed step increment optimization. Accurate power flow results can be obtained by exchanging boundary information between microgrids, and the proposed algorithm can converge rapidly with step increment optimization at the second level. Numerical experiments demonstrated the accuracy, convergence, and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

The current searching schemes in reliability evaluation of radial distribution systems require complicated and extensive codes, that contribute to the majority of the CPU times. This paper proposes a new one-step method operating with a set of binary descriptor matrices, replacing the searching, to calculate load and system reliability indices. In this technique, ‘fuse to branch’ and ‘switch to branch’ are introduced and employed to facilitate the solutions along with the use of bus-injection to branch-current matrices. In this approach, the cross-connects operation, islanding mode of small-scale DGs, and network constraints are also considered as part of the adequacy evaluation. The proposed technique is highly efficient for long-term distribution network planning and optimization where many cross-connects are involved. The proposed technique is applied to RBTS Bus 2 and 4, as well as a realistic 747-node distribution network. Results for the large distribution planning of the 747-node network demonstrate the computational time is reduced from 61 days using the traditional method to 4.6 hours based on the proposed technique. [ABSTRACT FROM AUTHOR]

Future distribution systems are expected to display increased complexity, mainly due to looped/meshed operation, switch between grid-connected and islanded mode and considerable integration of distributed generation. This paper investigates a plug-and-play protection solution for overhead distribution systems with such variable operation conditions, employing existing numerical relay capabilities. This solution is applied by designing plug-and-play, communication-assisted, multifunctional relays with integrated protection element settings, which apply universally to all distribution system conditions, rendering the protection scheme independent of a specific system. Hence, the need for user-defined settings or future revisions due to system changes is eliminated. The scheme ensures coordination between main line relays and backup protection of laterals, without a coordination study. There is no need to replace or modify existing lateral protection means for this purpose; only their known time-overcurrent curves are uploaded to the relays by the user. The scheme is described and evaluated through simulations in two test systems. Meaningful conclusions are finally derived. [ABSTRACT FROM AUTHOR]

The cheap and reliable primal energy source for battery energy storage system (BESS) refueling necessitates a special attention for combining renewable energy resources with plug-in hybrid electric vehicle (PHEV) charging stations in microgrids. Rapid charging is an operation mode of PHEV for drivers which demands fast recharging of BESSs of the electric cars. This charging mode manifests as low impedance short circuit at dc side, making power transient on power grid side. This paper presents a new anti-islanding protection scheme for low-voltage-sourced converter-based microgrids by exploiting support vector machines (SVMs). The proposed anti-islanding protection method exploits powerful classification capability of SVMs. The sensor monitors seven inputs measured at the point of common coupling (PCC), namely, root-mean-square (RMS) value of voltage and current ($RMS_{V}$ , $RMS_{I}$), total harmonic distortion (THD) of voltage and current ($THD_{V}$ , $THD_{I}$), frequency ($f$), and also active and reactive powers ($P$ , $Q$). This approach is based on passive monitoring and therefore, it does not affect the power quality (PQ). In order to cover as many situations as possible, minimize false tripping and remain selective, training, and detection procedures are simply introduced. Based on the presented sampling method and input model, the proposed method is tested under different conditions such as PHEV rapid charging, additional load change and multiple distributed generations at the same PCC. Simulations based on the model and parameters of a real-life practical photovoltaic power plant are performed in MATLAB/Simulink environment, and several tests are executed based on different scenarios and compared with previously reported techniques, this analysis proved the effectiveness, authenticity, selectivity, accuracy, and precision of the proposed method with allowable impact on PQ according to UL1741 standard, and its superiority over other methods. [ABSTRACT FROM AUTHOR]

In this paper, an economic dispatch (ED) problem for a community microgrid is studied. In this microgrid, each agent pursues an ED for its personal resources. In addition, each agent is capable of trading electricity with other agents through a local energy market. In this paper, an energy market operating in the presence of the grid is introduced. The proposed market is mainly developed for an experimental community microgrid at the Missouri University of Science and Technology, Rolla, MO, USA, and can be applied to other distribution level microgrids. To develop the algorithm, first, the microgrid is modeled and a dynamic ED algorithm for each agent is developed. Afterwards, an algorithm for handling the market is introduced. Lastly, simulation results are provided to demonstrate the proposed community market, and show the effectiveness of the market in reducing the operation costs of passive and active agents. [ABSTRACT FROM PUBLISHER]

Microgrids are prone to network-wide disturbances such as voltage and frequency deviations. Detection of disturbances by a microgrid central controller is therefore necessary for improving the network operation. Motivated by this application, this paper presents a new structure for the centralized detection of disturbances with noisy synchrophasor data and packet delay/dropouts. We build the proposed structure starting from the analysis of noise-delay tradeoff in synchrophasor networks and developing a new phasor data concentrator for compensation of data losses. The statistical performance metrics of the disturbance detector are numerically evaluated in the case of islanding detection, corroborating that the centralized detector counteracts the measurement noise and lowers the detection time. Numerical results show that the proposed structure significantly mitigates the probability of false detection. Moreover, it can achieve the lower bound of average detection time in a wide range of packet drop rates. This paper is useful to network designers who need to employ data acquisition systems for reliable and robust microgrid control applications. [ABSTRACT FROM PUBLISHER]

The uncertainty in the direction and magnitude of fault current is a thorny issue for active distribution network (ADN) protection. Current differential protection (CDP) is suitable for ADN with complex operating modes and multiple types of DGs. However, the data synchronization conditions in transmission lines are usually not available in distribution systems with relatively low investment levels. Fault data self-synchronization (FDSS) algorithm is a low-cost data synchronization method specially used for the protection of distribution networks, but there will be large time synchronization errors under some extreme fault conditions. In this paper, the inherent defect of the conventional FDSS algorithm is first analyzed. Then an improved FDSS algorithm is proposed, which uses the current zero-crossing time and current slope polarity to estimate the starting delay difference at both terminals. On this basis, a corresponding CDP scheme is proposed. Compared with traditional CDP, the proposed scheme does not require additional synchronization equipment and high communication bandwidth. Finally, an ADN simulation model was built using PSCAD, and the improved FDSS algorithm program was implemented in MATLAB. Test results prove that the improved FDSS algorithm can effectively reduce the time synchronization error, and the corresponding CDP scheme is effective under various fault conditions. [ABSTRACT FROM AUTHOR]

This paper presents a protection scheme for loop-based microgrids, which is divided into four levels, including load-way, loop-way, feeder, and microgrid. The scheme applies a dual protection strategy at the load-way level and a single protection strategy at the other three levels, which are designed to handle various types of faults in grid-connected and island modes of microgrids. The microgrid primary and back-up protections are taken into consideration at each level for grid-connected and island modes. The plug and play characteristics, time constraints of low voltage ride through, and unbalanced faults are considered for distributed generations. This paper demonstrates that the microgrid reliability is improved by coordinating the logics in the four proposed protection levels. The Illinois Tech microgrid is used as a design testbed to verify the effectiveness of the proposed protection scheme. [ABSTRACT FROM PUBLISHER]

Reactive power control (RPC) strategy is a promising option for islanding detection in distributed generation (DG) systems. Existing RPC methods have drawbacks of not providing the reactive power to improve the load power factor and are not robust against high-frequency transient disturbances. This paper presents a modified RPC method to overcome these limitations in a 220/380 V distribution network. In this method, the reference of reactive power of the DG is designed to improve the load power factor and ensure a fast islanding detection. In addition, the proposed method incorporates a second decision-making criterion based on discrete wavelet transform (DWT) to avoid false islanding detection due to non-islanding events. The proposed islanding detection method (IDM) is tested under various conditions. Simulation and experimental results show that the proposed IDM can detect islanding rapidly and with zero Non-Detection Zone (NDZ) in the situation of load power factor improvement. Moreover, non-islanding events such as capacitor switching are effectively avoided. [ABSTRACT FROM AUTHOR]

This paper presents a distributed voltage regulation method based on multi-agent system control and network self-organization for a large distribution network. The network autonomously organizes itself into small subnetworks through the epsilon decomposition of the sensitivity matrix, and agents group themselves into these subnetworks with the communication links being autonomously determined. Each subnetwork controls its voltage by locating the closest local distributed generation and optimizing their outputs. This simplifies and reduces the size of the optimization problem and the interaction requirements. This approach also facilitates adaptive grouping of the network by self-reorganizing to maintain a stable state in response to time-varying network requirements and changes. The effectiveness of the proposed approach is validated through simulations on a model of a real heavily-meshed secondary distribution network. Simulation results and comparisons with other methods demonstrate the ability of the subnetworks to autonomously and independently regulate the voltage and to adapt to unpredictable network conditions over time, thereby enabling autonomous and flexible distribution networks. [ABSTRACT FROM AUTHOR]

Increasing penetration of distributed generators and flexible loads in a distribution power system triggers the need for transactive mechanisms. This paper proposes a transactive mechanism and model that allow noncontrollable resources to trade their power deviations from schedules with elastic ones. The proposed mechanism can reveal the cost of uncertainty and the scarcity of flexibility. The proposed model is optimized in a fully distributed manner in which the welfare of each prosumer is maximized individually through information exchange between neighbors. A distributed neurodynamic algorithm is applied to handle the global constraints on supply-demand balance and limits on branch flows and voltages with guaranteed optimality and fast convergence. A case is studied on a 118-bus distribution system to demonstrate the effectiveness and efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

The integration of large-scale renewable distributed generation (DG) units in distribution networks brings new challenges for real-time power dispatch, including active power and reactive power (P-Q) coupling and operational uncertainties. To reduce the conservativeness of robust optimization (RO) solutions, this paper proposes a distributionally robust real-time power dispatch model, which characterizes the uncertainty of DG output with the information of first-order and second-order moments. Furthermore, a two-stage scheme, which includes economic dispatch (ED) and corrective control, is incorporated in the model, in which ED optimizes the active power schedule and corrective control strategies of P-Q are generated to eliminate overvoltage problems. The proposed model can be transformed into an equivalent semidefinite programming problem and solved via the delayed constraint generation algorithm. Numerical test results show that the proposed model reduces operational costs and mitigates overvoltage problems significantly compared with the conventional one-stage model. The proposed model also outperforms the conventional RO model by exploiting probability information to achieve statistically optimal dispatch. [ABSTRACT FROM AUTHOR]

Recent studies on power flow analysis of islanded microgrids have become increasingly important and different solutions have been proposed. However, they are often limited to only ac or only dc microgrids and hence, the power flow must be solved separately. This paper proposes a straightforward and efficient method to solve power flows of hybrid ac/dc microgrids simultaneously, based on the well-established Newton–Raphson approach. It considers the lack of slack bus during islanded operation, the coupling of ac frequency and dc bus voltage, as well as the droop control of distributed generators. To achieve power sharing between the ac and dc subgrids, this method incorporates the interlinking converter droop constants in the equation. The algorithm was tested on modified hybrid microgrids involving multiple ac–dc subgrids. The results are compared against results from time-domain simulations to validate the algorithm’s accuracy. The proposed technique can be easily implemented to aid the design and planning process of hybrid microgrids. [ABSTRACT FROM AUTHOR]

Legacy distribution systems need to adapt quickly to upcoming operating scenarios. The expected growth of electromobility and distributed generation will bring forth many challenges regarding efficient operation. Additionally, the limited communication infrastructure of these networks hinders the applicability of heavily centralized control strategies. In this context, this paper proposes a distributed control scheme for photovoltaic generators. The scheme comprises a local real–time control layer for the synthesis of active and reactive power references, using traditional voltage droop control, along with affine policies to handle the uncertainty associated to solar irradiance and demand levels. The characterization and periodic adaptation of such control scheme is achieved via a global, computationally tractable robust model able to co–optimize both droop and affine policy parameters. Performance is benchmarked via extensive computational experiments against other state–of–the–art distributed and local control strategies. Results suggest the proposed scheme is able to outperform all competitive frameworks. Its performance is also evaluated as a strictly local control scheme obtaining superior voltage regulation as compared to the recommendations in the Standard IEEE 1547.8. [ABSTRACT FROM AUTHOR]

To address the uncertain output of distributed generators for reactive power optimization in active distribution networks, the stochastic programming model is widely used. The model is employed to find an optimal control strategy with minimum expected network loss while satisfying all the physical constraints. Therein, the probability distribution of uncertainties in the stochastic model is always pre-defined by the historical data. However, the empirical distribution can be biased due to a limited amount of historical data and thus result in a suboptimal control decision. Therefore, in this paper, a data-driven modeling approach is introduced to assume that the probability distribution from the historical data is uncertain within a confidence set. Furthermore, a data-driven stochastic programming model is formulated as a two-stage problem, where the first-stage variables find the optimal control for discrete reactive power compensation equipment under the worst probability distribution of the second stage recourse. The second-stage variables are adjusted to uncertain probability distribution. In particular, this two-stage problem has a special structure so that the second-stage problem can be directly decomposed into several small-scale sub-problems, which can be handled in parallel without the information of dual problems. Numerical study on two distribution systems has been performed. Comparisons with the two-stage stochastic and robust approaches demonstrate the effectiveness of the proposal. [ABSTRACT FROM AUTHOR]

This paper proposes a decentralized multiagent system (MAS) approach to solve the service restoration problem considering the uncertainty of load demand and renewable distributed generators (RDGs). Service restoration is formulated as a multi-objective optimization problem and solved by implementing controlled DG islanding using the proposed MAS approach. First, the uncertainty of load demand and RDG generation is forecast by generating scenarios using Monte Carlo simulations. Next, the expected nodes to be restored in an island are determined using a heuristic rule-based technique. Finally, the maximum likelihood of the expected island ranges to be restored are estimated using the maximum likelihood estimation method to assist the utility in decision making. Extensive case studies are conducted on 38 bus and 119 bus distribution system to show the efficacy of the proposed restoration strategy. The use of electric vehicles and battery energy storage as flexible sources of energy to alleviate the uncertainties in the system is also highlighted. [ABSTRACT FROM AUTHOR]

Significant outages from weather and climate extremes have highlighted the critical need for resilience-centered risk management of the grid. This paper proposes a multi-stage stochastic robust optimization (SRO) model that advances the existing planning frameworks on two main fronts. First, it captures interactions of operational measures with hardening decisions. Second, it properly treats the multitude of uncertainties in planning. The SRO model coordinates hardening and system operational measures for smart power distribution systems equipped with distributed generation units and switches. To capture the uncertainty in the incurred damage by extreme events, an uncertainty set is developed by integrating probabilistic information of hurricanes with the performance of overhead structures. A novel probabilistic model for the repair time of damaged lines is derived to account for the uncertainty in the recovery process. A solution strategy based on the integration of a differential evolution algorithm and a mixed-integer solver is designed to solve the resilience maximization model. The proposed approach is applied to a modified IEEE 33-bus system with 485 utility poles and a 118-bus system with 1841 poles. The systems are mapped on the Harris County, TX, U.S. Results reveal that optimal hardening decisions can be significantly influenced by resilience operational measures. [ABSTRACT FROM AUTHOR]

The recent rapid uptake of residential solar photovoltaic installations provides many challenges for electricity distribution networks designed for one-way power flow from the generator to residential customers via transmission and distribution networks. For grid-connected installations, large amounts of generation during low load periods or intermittent generation can lead to a difficulty in balancing supply and demand, maintaining voltage and frequency stability, and may even result in outages due to overvoltage conditions tripping protection circuits. In this paper, we present four control methodologies to mitigate these difficulties using small-scale distributed battery storage. These four approaches represent three different control architectures: 1) centralized; 2) decentralized; and 3) distributed control. These approaches are validated and compared using data on load and generation profiles from customers in an Australian electricity distribution network. [ABSTRACT FROM PUBLISHER]

Unlike the existing research that focuses on detecting electricity theft cyber-attacks in the consumption domain, this paper investigates electricity thefts at the distributed generation (DG) domain. In this attack, malicious customers hack into the smart meters monitoring their renewable-based DG units and manipulate their readings to claim higher supplied energy to the grid and hence falsely overcharge the utility company. Deep machine learning is investigated to detect such a malicious behavior. We aim to answer three main questions in this paper: a) What are the cyber-attack functions that can be applied by malicious customers to the generation data in order to falsely overcharge the utility company? b) What sources of data can be used in order to detect these cyber-attacks by the utility company? c) Which deep machine learning-model should be used in order to detect these cyber-attacks? Our investigation revealed that integrating various data from the DG smart meters, meteorological reports, and SCADA metering points in the training of a deep convolutional-recurrent neural network offers the highest detection rate (99.3%) and lowest false alarm (0.22%). [ABSTRACT FROM AUTHOR]

To compensate for the voltage and frequency deviations caused by the droop control in islanded microgrids (MGs), employing an additional control level, called the secondary control, is necessary. Therefore, distributed control methods based on the sparse communication network, are recently employed in secondary control of MGs, because they are more reliable and flexible. However, traditional methods use the centralized communication network, which is neither economical nor efficient due to its large communication burden. Distributed control methods solve many challenges in the secondary layer of MGs, such as disturbances, uncertainties, unmodelled dynamics, noises, delays, attacks, and actuator faults. This paper proposes the novel resilient adaptive consensus-based voltage and frequency control protocols to compensate for the adverse effects of both sensor and actuator faults in communication network channels of islanded MGs. To this end, local adaptive sensor and actuator compensators eliminate the adverse effects of failures on sensors and actuators. The robust stability analysis based on the Lyapunov analysis is given to validate the results. Finally, the understudy islanded MG system is built in MATLAB/SimPowerSystems to verify the theoretical results. It is shown that the proposed secondary control strategies based on the adaptive protocols can highly increase the reliability and resiliency of the MG system compared with the existing distributed resilient methods. [ABSTRACT FROM AUTHOR]

This paper presents a single end fault location scheme for distribution networks with distributed generation (DG). The high frequency transients generated when a fault occurs are used to locate the fault point. An equivalent circuit at high frequencies is derived for both inverter based and synchronous DGs. The voltages and currents measured only at the main substation are used in conjunction with the proposed DG model to create the fault location scheme. The distributed parameter line model is employed in the derivation to account for the line characteristics, e.g., inductive and capacitive mutual coupling and untransposed lines. The inverter based DG model is validated experimentally on a 400 V, three-phase system. The IEEE 34-bus feeder is simulated and used to evaluate the proposed scheme for different operating conditions, e.g., fault resistance and DG conditions. The extensive simulation studies show the accuracy of the proposed scheme with 95.3% of the test cases having an absolute error in estimation of less than 200 m. [ABSTRACT FROM AUTHOR]

Self-governing microgrids may consist of several conventional synchronous generators, converter-based distributed resources, and energy storages. In this paper, an eigenvalue-oriented stability assessment method is established to study the small signal stability of such systems that have complex dynamic characteristics. A new index referred to as the microgrid’s marginal frequency stability index is established. This index is then used to determine the influence and correlation between sizes, quantities and internal parameters of the resources and loads on the microgrid’s stability. Likewise, using this index, the impact of the isolation and coupling impedance amongst resources and loads are studied on the microgrid’s stability. The findings of this study can be employed when designing microgrids to realize more stable systems. [ABSTRACT FROM AUTHOR]

For the distributed generation units (DGs) using virtual synchronous generator (VSG) control algorithm connected to the islanded microgrid with high penetration of nonlinear load, there is always a trade-off between harmonics sharing accuracy and voltage quality when using conventional harmonics sharing methods. To address this issue, an impedance-based adaptively reshaping method is proposed in this paper, which is based on harmonic current feedforward compensation control and impedance reshaping factor adaptive control, assigning a variable harmonic impedance reshaping factor for each VSG to improve the controllability of VSG harmonic impedance, thus simultaneously enhancing nonlinear load sharing and voltage quality. Moreover, a droop-based methodology for impedance reshaping factor tuning is presented to adaptively reshape harmonic impedance for each VSG without acquiring the line parameters in advance. The proposed method also enjoys the advantage of avoiding introducing additional virtual harmonic impedance, and thus it is immune from the inverter closed-loop gain throughout the dominant harmonic frequencies. Furthermore, the stability analysis and the key control parameter design are discussed in detail. Finally, the effectiveness of the proposed method is verified by simulation and experimental results. [ABSTRACT FROM AUTHOR]

Smart grid solutions with enabling technologies such as energy management systems (EMSs) and smart meters promote the vision of smart households, which also allows for active demand side in the residential sector. These technologies enable the control of residential consumption, local small-scale generation, and energy storage systems to respond to time-varying prices. However, shifting loads simultaneously to lower price periods is likely to put extra stress on distribution system assets such as distribution transformers. Especially, additional new types of loads/appliances such as electric vehicles (EVs) can introduce even more burden on the operation of these assets, which is an issue that needs special attention. Such extra stress can cause accelerated aging of distribution system assets and significantly affect the reliability of the system. In this paper, the impact of a smart neighborhood load on distribution transformer aging is investigated. The EMS of each household is designed to respond to prices and other signals emitted by the responsive load serving entity within the relevant demand response strategy. An optimization framework based on mixed-integer linear programming is presented in order to define the EMS structure. Then, the equivalent aging of the distribution transformer is examined with a thermal model under different scenarios. The case studies that are presented indicate that the integration of EVs in residential premises may indeed cause accelerated aging of the distribution transformers, while the need to investigate the efficiency of dynamic pricing mechanisms is rendered evident. [ABSTRACT FROM PUBLISHER]

This paper presents a new islanding detection strategy for low-voltage inverter-interfaced microgrids based on adaptive neuro-fuzzy inference system (ANFIS). The proposed islanding detection method exploits the pattern recognition capability of ANFIS and its nonlinear mapping of relation between inputs. The ANFIS monitors seven inputs measured at point of common coupling (PCC), namely root-mean square (RMS) of voltage and current (RMSU and RMSI), total harmonic distortion (THD) of voltage and current (THDU and THDI), frequency (${f}$), and active and reactive powers (${P}$ , ${Q}$) that are experimentally obtained based on practical measurement in a real-life microgrid. The proposed method is composed of passive monitoring of the mentioned inputs. It does not influence power quality (PQ) and considerably decreases non detection zones (NDZs). In order to cover as many situations as possible, minimize false tripping and still remain selective; type and number of samples are introduced. Here, one of the primary goals is reducing NDZ while keeping PQ in order. Based on the sampled frequency and number of samples, we find that the proposed method has less detection time and better accuracy when compared to the reported methods. Simulations performed in MATLAB/Simulink software environment and several tests performed based on different active load conditions and multiple distributed generation, prove the effectiveness, authenticity, selectivity, accuracy and precision of the proposed method with allowable impact on PQ according to UL1741 standard. [ABSTRACT FROM AUTHOR]

This paper presents a systematic procedure for partitioning smart distribution systems into supply-sufficient microgrids. First, renewable distributed generations (DGs) are optimally allocated in the distribution system. A multiobjective performance index including voltage profile and energy losses indices is utilized in this problem as the objective function. Two alternative control approaches of future smart grids, including on load tap changer control and adaptive power factor control are assessed to maximize potential benefits and increase the penetration level of DGs. Then, optimal allocation of protection devices and energy storage systems for constructing supply-sufficient microgrids is presented for a feeder equipped with capacity-constrained DGs. To this end, two different optimization problems are formulated and proper indices are developed for minimizing power exchange between microgrids and minimizing generation-load imbalance within microgrids. Finally, test results of the proposed models on 33-bus IEEE radial distribution system are presented and discussed. [ABSTRACT FROM AUTHOR]

This paper presents small signal stability analysis of distribution networks with electric springs (ESs) installed at the customer supply points. The focus is on ESs with reactive compensation only. Vector control of ES with reactive compensation is reported for the first time to ensure compatibility with the standard stability models of other components such as the interface inverter of distributed generators (DGs). A linearized state-space model of the distribution network with multiple ESs is developed which is extendible to include inverter-interfaced DGs, energy storage, active loads, etc. The impact of distance of an ES from the substation, proximity between adjacent ESs and the R/X ratio of the network on the small signal stability of the system is analyzed and compared against the case with equivalent DG inverters. The collective operation of ESs is validated through simulation study on a standard distribution network. [ABSTRACT FROM AUTHOR]

The inverse-time operating characteristic of overcurrent relays is the primary protective element in distribution system protection schemes and has been utilized for several decades. As the distribution system becomes increasingly complex due to the growth of distributed generation, the protection task based on existing methodologies will become more difficult. Faster relay operating times while maintaining selectivity is critical. In this paper, a stochastic mixed-integer linear program is formulated to minimize a relay’s tripping time at discrete fault current intervals and considers the cost of tripping a relay as the objective function. The formulation takes into account the probabilistic nature of the fault current observed at each relay, which can be impacted by fault location, fault resistance, device failure, and DG output. Monte Carlo simulation is used to determine the empirical probabilities of each relay observing a particular fault current. Probabilistic fault scenarios are simulated on the IEEE 34-node test feeder. The proposed approach shows a decrease in expected energy loss due to faults up to 11.5% compared to conventional TCC curves for 10 000 Monte Carlo fault scenarios. [ABSTRACT FROM AUTHOR]

The responses of multiple distributed generation (DG) units and voltage regulating devices, such as tap changers and capacitor banks, for correcting the voltage may lead to operational conflicts and oscillatory transients, where distribution systems are subjected to network reconfiguration and availability of the DG units. Therefore, coordinated voltage control is required to minimize control interactions, while accounting for the impact of structural changes associated with the network. This paper proposes a strategy for coordinating the operation of multiple voltage regulating devices and DG units in medium voltage (MV) distribution systems, under structural changes and DG availability, for effective voltage control. The proposed strategy aids to minimize the operational conflicts by allowing voltage regulating devices to operate in accordance with the priority scheme designed based on the electrical-distance between voltage regulating devices and DG units, while maximizing the voltage support by the DG units. The proposed coordination scheme is designed to enact with an aid of a substation centered distribution management system for online voltage control. The control actions of proposed coordination strategy are tested on a MV distribution system, derived from the state of New South Wales, Australia, through simulations, and results are reported. [ABSTRACT FROM PUBLISHER]

This paper presents a mixed-integer second-order cone programing (MISOCP) model to solve the optimal operation problem of radial distribution networks (DNs) with energy storage. The control variables are the active and reactive generated power of dispatchable distributed generators (DGs), the number of switchable capacitor bank units in operation, the tap position of the voltage regulators and on-load tap-changers, and the operation state of the energy storage devices. The objective is to minimize the total cost of energy purchased from the distribution substation and the dispatchable DGs. The steady-state operation of the DN is modeled using linear and second-order cone programing. The use of an MISOCP model guarantees convergence to optimality using existing optimization software. A mixed-integer linear programing (MILP) formulation for the original model is also presented in order to show the accuracy of the proposed MISOCP model. An 11-node test system and a 42-node real system were used to demonstrate the effectiveness of the proposed MISOCP and MILP models. [ABSTRACT FROM PUBLISHER]

The increased deployment of distributed generation calls for the coordination and interaction between the transmission and distribution levels. This requirement is particularly relevant for planning purposes when renewable-based generation is involved. Unfortunately, in current industry practice, transmission and distribution network planners solve their problems independent of each other, thereby leading to suboptimal solutions. Within this context, this paper addresses the integrated expansion planning problem of transmission and distribution systems where investments in network and generation assets are jointly considered. Several alternatives are available for the installation of lines as well as conventional and renewable-based generators at both system levels. Thus, the optimal expansion plan identifies the best alternative for the candidate assets under the uncertainty associated with demand and renewable-based power production. The proposed model is an instance of stochastic programming wherein uncertainty is characterized through a set of scenarios that explicitly capture the correlation between the uncertain parameters. The resulting stochastic program is driven by the minimization of the expected total cost, which comprises the costs related to investment decisions and system operation. The associated scenario-based deterministic equivalent is formulated as a mixed-integer linear program for which finite convergence to optimality is guaranteed. Numerical results show the effective performance of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper proposes a supervisory control scheme to facilitate coupling of remote droop-regulated microgrids (MGs) during power shortfalls. In this scheme, instead of power converters, an instantaneous static switch is incorporated for the interconnection. Therefore a supervisory controller is essential to cope with the associated challenges, which are: 1) the level of supporting power provided by the neighboring MG and 2) isolation procedure of the coupled MGs (CMG) when the power deficiency condition is removed. Droop coefficients of distributed generators of the overloaded MG are dynamically updated by the controller according to the three operating modes defined to address the aforementioned challenges. The transit criteria, as well as the controlling signals, are accurately formulated based only on the local measurements to decrease the dependency on the communication systems. This enhances the reliability level of the coupled system. Effectiveness of the proposed strategy is validated through the results obtained from PSCAD/EMTDC simulations. Also, small-signal stability of the CMG operated by the proposed controller is examined using a developed model in MATLAB. [ABSTRACT FROM AUTHOR]

Microgrid is an effective means to integrate distributed generation (DG) resource. However, uncertain renewable DG such as wind turbine and photovoltaic outputs and load demands can introduce tremendous difficulties for energy management in microgrids. To mitigate such difficulties, price-based demand response (PBDR) can adjust the loads to adapt to the renewables. On the other hand, dispatchable DG such as microturbines can coordinate with the PBDR to further manage the power balance and achieve economic benefits. In this paper, a two-stage robust microgrid coordination strategy is proposed: a PBDR is scheduled a day ahead and microturbine outputs are modified hourly. A two-stage robust optimization model is proposed to address the coordination problem with guaranteed robustness against the uncertainties of renewable DG and load demands. Simulation results show PBDR and multiple DG units can coordinate effectively to accommodate the renewable and demand uncertainties while maximizing the microgrid benefits. [ABSTRACT FROM AUTHOR]

This paper proposes a two-stage method for the outage management of power distribution systems. The first stage is to cluster repair tasks of damaged power generation and delivery components based on their distances from the depots (central crew stations) and the availability of resources, to improve the computational efficiency in solving outage management problems for large distribution systems. The second stage is to co-optimize the repair, reconfiguration, and distributed generation dispatch to maximize the picked-up loads and minimize the repair time. The distribution system repair and restoration problem is formulated as a mixed integer linear program, considering constraints of system operation and routing repair crews. Crews are dispatched considering equipment resources, traveling time, and repair time. The proposed method is tested on modified IEEE 34 and 123-bus distribution test systems with multiple damages. The results demonstrate the advantages of co-optimizing repair and restoration. [ABSTRACT FROM AUTHOR]

Conventional distribution systems are transforming into smarter networks by accommodating renewable energy resources, communication infrastructure, and control devices. While the grids are transforming to be smart grids, issues relating to grid stability and control are emerging due to proximity and interactions among generator units and associated controllers. The existence of low damped oscillations could be harmful to power transfer capacity and generator stability. This paper presents small signal stability and control issue of emerging distribution systems. A robust control methodology for motor load current is proposed for stability enhancement. System loads are ranked based on their relative influence on small signal instability. The proposed methodology controls current of the selected motor load during system disturbances to improve overall small signal stability of the distribution system. The proposed methodology has been successfully implemented on a 16-bus distribution network. [ABSTRACT FROM AUTHOR]

The sizing and siting of renewable resources-based distributed generation (DG) units has been a topic of growing interest, especially during the last decade due to the increasing interest in renewable energy systems and the possible impacts of their volatility on distribution system operation. This paper goes beyond the existing literature by presenting a comprehensive optimization model for the sizing and siting of different renewable resources-based DG units, electric vehicle charging stations, and energy storage systems within the distribution system. The proposed optimization model is formulated as a second order conic programming problem, considering also the time-varying nature of DG generation and load consumption, in contrast with the majority of the relevant studies that have been based on static values. [ABSTRACT FROM AUTHOR]

Hybrid ac-dc microgrid architecture is attracting special attention since it combines the benefits of both ac and dc systems. Control of hybrid microgrid presents a significant research and engineering challenge and hence needs increased research efforts. This paper attempts to review control strategies that are reported in the literature for the hybrid ac-dc microgrid. At first, typical and emerging hybrid microgrid power topologies are presented briefly. Various types of interlinking converters proposed for connecting ac and dc subgrids are discussed subsequently. Following this, a detailed discussion on control strategies for satisfying various control objectives is taken up. Control strategies have been systematically reviewed focusing on each of the broad aspects of control namely modeling, power management, coordinated control, stability analysis, power quality, and protection strategies. Finally, the research gaps observed during the review process and possible solution approaches are outlined. [ABSTRACT FROM AUTHOR]

Cooperative control of power converters in a microgrid offers power quality enhancement at sensitive load buses. Such cooperation is particularly important in the presence of reactive, nonlinear, and unbalanced loads. In this paper, a multi-master–slave-based control of distributed generators interface converters in a three-phase four-wire islanded microgrid using the conservative power theory (CPT) is proposed. Inverters located in close proximity operate as a group in master–salve mode. Slaves inject the available energy and compensate selectively unwanted current components of local loads with the secondary effect of having enhanced voltage waveforms while masters share the remaining load power autonomously with distant groups using frequency droop. The close proximity makes it practical for control signals to be communicated between inverters in one group with the potential to provide rapid load sharing response for mitigation of undesirable current components. Since each primary source has its own constraints, a supervisory control is considered for each group to determine convenient sharing factors. The CPT decompositions provide decoupled current and power references in abc-frame, resulting in a selective control strategy able to share each current component with desired percentage among the microgrid inverters. Simulation results are presented to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The increasing integration of distributed generation introduces severe challenges to the secure operation of active distribution networks (ADNs) due to volatile power injections. One way to ensure ADN operation security is to evaluate acceptable boundaries of distributed generation uncertainties, namely maximum uncertainty boundary (MUB). In this paper, a novel set-based method is proposed to formulate the MUBs of distributed generation and the operation constraints of ADNs as security sets of polytopes. The advantages of the proposed set-based model lie not only in the simplified modeling with extremely high computational efficiency, but also in the potentials to take control instructions into account. The MUBs with operation scheduling (MUB-OS) and with available operation region (MUB-AOR) are further established as security sets of polytopes solvable by the toolbox of computational geometry. This paper proves the theorems that enable the transformation of MUBs from security sets into computational geometry-based descriptions, and then develops the corresponding algorithms on MUB, MUB-OS, and MUB-AOR. A novel evaluation framework is proposed to comprehensively assess the performance of the estimated MUB. The effectiveness and efficiency of the proposed methodology are comprehensively verified on a 3-node system and a modified IEEE 33-node system. [ABSTRACT FROM AUTHOR]

With the increase of load fluctuations and the integration of stochastic distributed generations (DGs), there have been more and more research interests in forecasting-aided state estimation. In this paper, we propose a robust generalized maximum likelihood (GM)-estimator based power system forecasting-aided state estimation, which integrates the statistical characteristics of both loads and DGs, i.e., spatial and temporal correlations. A first order vector auto-regressive model (VAR(1)) is developed to capture the statistical characteristics of load and DGs, facilitating short-term loads and DGs forecasting. These forecasted power injections are further combined with power balance equations to derive a new state transition model, where the relationship between forecasted state vector and predicted power injections is expressed explicitly. After that, a redundant batch regression model that simultaneously processes predicted state vector and received observations is derived, allowing the development of a robust estimator. To this end, we propose a robust GM-estimator that leverages modified projection statistics and a Huber convex score function, to bound the influence of observation outliers while maintaining its high statistical estimation efficiency. Finally, the iteratively reweighted least squares algorithm is adopted to solve the GM-estimator. Numerical comparisons on IEEE benchmark systems with DGs integration demonstrate the efficiency and robustness of the proposed method. [ABSTRACT FROM AUTHOR]

Stability of inverter-based distributed generation units (DGs) is highly dependent on the grid impedance. This paper proposes an adaptive control algorithm for optimally reshaping DG output impedance so that the system dynamic performance is improved. Such adaptation is essential for managing variations in grid impedance and changes in DG operating conditions. The proposed algorithm is generic so that it can be applied for both grid-connected and islanded DGs. It involves mainly two design stages. First, the multivariable DG output impedance is derived mathematically and verified using a frequency sweep identification method. The grid impedance is also estimated using the refined instrumental variable for continuous-time system identification algorithm so that the impedance stability criteria can be formulated. In the second stage, multi-objective programming is formulated using the \varepsilon - constraint method in order to minimize the system response time while obtaining a robust damping performance. The proposed algorithm has been validated in both grid-connected and isolated distribution networks, with the use of OPAL real-time simulators via a hardware-in-the-loop application. [ABSTRACT FROM PUBLISHER]

This paper proposes a phasor estimation algorithm for P-class phasor measurement unit suitable in protection applications using Hilbert transform and convolution of a signal. As the protective relay requires extracted fundamental component of the phasor for its operation, the author’s introduced an algorithm to estimate a robust phasor corresponding to the fundamental component which is close to the actual signal in L2 -norm. Though IEEE C37.118.1a-2014 standard does not specify the accuracy requirements of phasor under transient condition, the performance of phasor estimator is tested under different dynamic conditions as per IEEE C37.118.1a-2014 standard. The effectiveness of proposed algorithm has also been verified on modified two area power system during fault along with the data generated by the experimental setup in laboratory. The results revealed that the proposed algorithm estimates the phasor accurately irrespective of distortion present in the sinusoidal signals. Furthermore, the proposed estimator inherently filters harmonics, immune to decaying dc components, detects sharp changes in a signal during faults, and effectively works under complex modulated conditions. The above scenario appears frequently in a power system with distributed energy sources. The simplicity, robustness, and generality of the proposed algorithm suits for wide area measurement systems to measure the voltage and current phasors during disturbance in the smart power system networks. [ABSTRACT FROM PUBLISHER]

The locational marginal price (LMP) methodology has been discussed for distribution networks/systems under the smart grid initiative. In this paper, a new distribution LMP (DLMP) formulation is presented which includes reactive power prices and voltage constraints. To solve DLMP, three modeling tools, namely, linearized power flow for distribution (LPF-D), loss factors for distribution (LF-D), and linear optimal power flow for distribution (LOPF-D) are proposed. LPF-D solves not only voltage angles but also magnitudes through linear expression between bus injections and bus voltages, specifically for distribution systems. LF-D is solved recursively based on the radial topology of typical distribution systems. With the integration of LPF-D and LF-D, conventional optimal power flow (OPF) can be reformulated as LOPF-D which is essentially a linear programming model. Test results on various systems show that: 1) LPF-D efficiently yields very close results if compared with AC power flow; 2) LOPF-D provides very close dispatch results in both real and reactive power if compared with ACOPF; and 3) the proposed DLMPs calculated with LF-D and LOPF-D give accurate price information if compared with the prices from ACOPF. Further, these three tools are not limited to DLMP but can be potentially applied to other distribution analyses. [ABSTRACT FROM PUBLISHER]

The impact of numerous distributed generators (DGs) coupled with the implementation of virtual inertia on the transient stability of power systems has been studied extensively. Time-domain simulation is the most accurate and reliable approach to evaluate the dynamic behavior of power systems. However, the computational efficiency is restricted by their multi-time-scale property due to the combination of various DGs and synchronous generators. This paper presents a novel projective integration method (PIM) for the efficient transient stability simulation of power systems with high DG penetration. One procedure of the proposed PIM is decomposed into two stages, which adopt mixed explicit-implicit integration methods to achieve both efficiency and numerical stability. Moreover, the stability of the PIM is not affected by its parameter, which is related to the step size. Based on this property, an adaptive parameter scheme is developed based on error estimation to fit the time constants of the system dynamics and further increase the simulation speed. The presented approach is several times faster than the conventional integration methods with a similar level of accuracy. The proposed method is demonstrated using test systems with DGs and virtual synchronous generators, and the performance is verified against MATLAB/Simulink and DIgSILENT PowerFactory. [ABSTRACT FROM PUBLISHER]

This paper proposes a communication assisted dual setting relay protection scheme for micro-grids with grid connected and islanded capability. Previous work on dual setting relays has been applied to grid connected distributed generation systems only, but one major shortcoming is the failure of the backup scheme to operate in a coordinated manner. The proposed scheme relies on the use of dual setting directional overcurrent relays that are capable of operating in both forward and reverse directions, with different settings, and with a low bandwidth communication to maintain proper protection coordination. The problem is formulated as a non-linear constrained programming problem where the relay settings are optimally determined to minimize the overall relay operating time for primary and backup operation. The scheme is tested on a modified version of the IEEE 30 bus test system equipped with distributed generation and with capability of operating in an islanded mode. The proposed scheme is compared against the conventional scheme and the results show that it is capable of overcoming the problem of infeasibility, experienced by the conventional method, without the need of installing fault current limiters. Furthermore, it achieves remarkable reduction in both the primary and backup relay operating times, which was reflected in a reduction in the total relay operating time. [ABSTRACT FROM PUBLISHER]