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The reduced inertia in power system introduces more operation risks and challenges due to the degraded frequency performance. The existing virtual inertia control and fast frequency response to tackle this issue are restricted by the energy resource behind the power converter. In this paper, an improved virtual synchronous machine control is proposed, considering the limitation of energy storage in response speed and energy capacity. The fast-acting energy storage system is used to emulate inertia and damping. The energy consumed by both services in dynamic process and steady-state state is also investigated. An energy recovery control is designed to restore the energy consumed in inertia emulation and damping provision, thereby ensuring constant energy reserve. Besides, the slow-acting energy storage with larger energy capacity, is controlled like the governor regulator of synchronous generator and capable of providing long-term energy service. A design procedure considering storage limitation, control stability and bandwidth separation is proposed. Effectiveness of the proposed control and design is validated by comprehensive simulation and hardware test results.

Low inertia, nonlinearity and a high level of uncertainty (varying topologies and operating conditions) pose challenges to microgrid (MG) systemwide operation. This paper proposes an online adaptive Koopman operator optimal control (AKOOC) method for MG secondary voltage and frequency control. Unlike typical data-driven methods that are data-hungry and lack guaranteed stability, the proposed AKOOC requires no warm-up training yet with guaranteed bounded-input-bounded-output (BIBO) stability and even asymptotical stability under some mild conditions. The proposed AKOOC is developed based on an ensemble Koopman state space modeling with full basis functions that combines both linear and nonlinear bases without the need of event detection or switching. An iterative learning method is also developed to exploit model parameters, ensuring the effectiveness and the adaptiveness of the designed control. Simulation studies in the 4-bus (with detailed inner-loop control) MG system and the 34-bus MG system showed improved modeling accuracy and control, verifying the effectiveness of the proposed method subject to various changes of operating conditions even with time delay, measurement noise, and missing measurements., Accepted by IEEE Transactions on Smart Grid for future publication

The deepening penetration of renewable power generation is challenging how the minute balancing of supply and demand is carried out by power system operators. Several proposals to short-term operational planning rely on robust optimization to offer guarantees on the ability of the operator to meet a wide array of possible scenarios. The main downside of these approaches is their conservative results whose operating costs and/or carbon footprint may be sub-economical. Such results come by because these approaches immunize their solutions for the required level of security against realizations of potential events within their uncertainty set. Moreover, these approaches also often ignore the inherent time and spatial couplings of wind and solar generation variability. In this article, we seek to reduce the conservativeness of the robust solution by proposing the concept of spatio-temporal flexibility requirement envelopes. We show how it is able to efficiently capture and model the temporal trends and spatial correlation of multisite renewable generation and load. A mathematical program for energy scheduling is also developed using the projections of this envelope. We showcase the use and advantages of spatio-temporal flexibility requirement envelopes and their associated scheduling approach in a microgrid and on a modified IEEE Reliability Test System.

With reference to the newly released microgrid standards, design and real-time implementation of a centralized microgrid control system is presented in this article. In the grid-connected mode, the utility grid will provide the voltage and frequency reference at the point of connection. The assets within the microgrid will follow power command references provided by the control system. In the islanded mode, the energy storage system (ESS) can provide the voltage and frequency reference to all other generators. Based on the state-of-charge of the ESS, a rule-based dispatch is proposed, with priority given to diesel generator and then the storage in the middle state of charge range. To alleviate power fluctuations, meet smooth planned islanding requirement, and compensate for the feeder losses ignored in dispatch algorithm, a supplementary slack-bus power control based on closed-loop feedback and first-order filter is proposed. The potential of the storage system in firming short-time power fluctuation and providing long-term load shifting capabilities is exploited. An emergency dispatch function for unplanned islanding considering the speed of response limitation of a diesel generator is also proposed. The proposed control strategy is implemented and tested on a controller hardware-in-the-loop test bench. It demonstrates the capability of the control system to reduce load shedding and renewable curtailment, and to implement power management at the point of interconnection.

This paper presents a new method of instability detection and subsequent stabilization of the power system network using a proposed multi-shot remedial action scheme (RAS) that can extemporaneously detect critical generators based on the dynamic states of generator computed from the terminal phasor measurement units. The instability detector is a moving window classifier that predicts impending instability using rate of change of individual generator transient energy indices evaluated from the d–q axis voltage as well as conventional severity indices based on generator angle and frequency. A comparative performance analysis of a spectral feature based ensemble decision tree classifier with a multivariate long short-term memory network is also presented. The proposed RAS identifies critical generators through individual machine transient energy formulation and recursive coherency matrix, evaluated solely from system-wide generator dynamic states, and maintains stability by tripping adaptively the run-away generators. Performance evaluation of the proposed scheme has been made on IEEE 39-bus network and it has been demonstrated that the proposed RAS is robust with regards to instability prediction and it can effectively identify critical generators and stabilize the network by tripping the same.

Isochronous controlled battery energy storage system (ESS) can maintain constant frequency in an islanded ac microgrid, but its power and state of charge (SoC) may go beyond limit due to intermittent renewable energy resources and impact load change. This paper introduces a control strategy integrated with bang-bang and backlash mechanism to coordinate distributed energy resources (DERs). When overloading will take place, ESS will change from isochronous control to droop control, with droop gain varying based on bang-bang control, by which the overloaded power will be spontaneously transferred from ESS to other DERs. Moreover, frequency will be automatically restored when impact load disappears, which eliminates the effort of secondary frequency control. When SoC of ESS comes to limit, the diesel generator will change from droop control to isochronous control, whereas ESS will adopt virtual inertia and grid-supporting droop control to help stabilize frequency. A backlash mechanism is also employed to latch the control mode near SoC limit. Comprehensive tests on real-time simulator demonstrated the effectiveness of the proposed control strategy.

Integrated battery chargers (IBCs) have been proposed as a low-weight, low-volume, and high-power solution to conventional conductive chargers. However, the design of such chargers is complicated, requiring special components or control techniques to solve inherent issues (such as galvanic isolation, torque generation, and system reconfiguration) associated with their design. Solutions vary based on charging power, drive topology, and motor technology. This chapter introduces designs for IBCs, including solutions as proposed in the literature. It also presents challenges in their industrial adoption. Finally, the chapter presents opportunities for fleet charging applications using IBCs.

In this paper, an SoC-based droop control design is proposed for the vehicle-to-grid (V2G) operating mode of electric vehicles (EVs) in a DC fast charging station (DCFCS). The proposed primary control design aggregates EVs in the V2G mode while balancing EV batteries SoCs during charge and discharge modes to protect EVs from overcharge/overdischarge and increase the time duration at which all connected EVs are able to operate in the V2G mode. The proposed controller employs the output of a sigmoid function as the droop coefficient to allocate power among EV batteries. EV batteries’ energy capacities and SoCs are the variables in the sigmoid function. Compared to the conventional methods, the proposed controller balances SoCs without using the average SoCs to provide complete independence among chargers, considers the effect of different EV batteries energy capacities on the SoC balancing, and balances SoCs faster. The effectiveness of the proposed controller is evaluated through steady-state and transient case studies in the DCFCS with three EVs connected to chargers.

DC fast charging reduces the time for charging electric vehicles, however, it requires large power demand from the grid during each EV charging. DC fast charging is random in nature. At peak load demand periods of the distribution network, the energy requirement may become as high as five times the normal peak load, due to DC fast charging loads. This paper proposes a load management strategy for integrating fast charging infrastructure with the grid. An energy management system with a charge scheduling algorithm is proposed to control the charging rate of the electric vehicles in the DC fast-charging station, effectively decreasing the stress on the grid during peak load. The results of the load management strategy are compared with rulebased system and DC fast charging station devoid of any energy management system. The main contribution of the paper includes an optimized energy management system framework for a DC fast charging station connected to a low voltage distribution network. The performance of the centralized energy management system is tested on a given network – peak charging power due to fast charging on the grid is reduced, the voltage constraints are satisfied (confined within ± 5% band of the system base voltage), and voltage deviation is minimized, without integrating additional ESS or PV system.

The growing penetration of plugin electric vehicles and their charging systems raises concerns from electric utilities due to load addition on their distribution system that may require infrastructure upgrades to serve. Advancements in charging technologies make it possible to manage such loads as charging clusters or aggregated loads. Aggregation not only allows load management as a nonwire alternative (NWA) but can also enable vehicle-to-grid (V2G) services. The services that can be provided depend on the type of chargers along with the power (number of chargers operating concurrently) and energy (aggregated battery size) assembled by the aggregator, as well as the control strategies built into the charging facilities. This chapter introduces the charging technologies and their capabilities on the level of individual chargers. The capabilities of the aggregated chargers in providing V2G services is then presented. Finally, the issues associated with the deployment and implementation of such technologies are discussed.

The low-frequency dynamics of virtual synchronous machine (VSM) depends on multiple factors. In this study, the oscillation mode of a single VSM is first identified by exploring the evolution of oscillation from synchronous mode to sub-synchronous mode with the variation of structure and parameters. The inter-oscillation modes among multiple VSMs modelled in quasi-state phasor domain are then studied by decomposing into mean motion and relative motion. Inspired by and weak-coupling-based coherency identification, the associated VSM group can be fast identified and used for effective stabilizer location. The approximate eigenvalues can be fast obtained by system decomposition in uniform-damping scenarios or by extended-equal-area-criterion approach in non-uniform-damping scenario. An improved design for lead-lag compensation is proposed to damp both synchronous and sub-synchronous oscillation of VSMs. Effectiveness of the proposed control strategy in grid-connected/islanded mode is verified with real-time simulation.

This paper proposes a hybrid modular multilevel dc–dc converter with dc fault ride-through capability. In each phase, the lower arm and shunt arm are composed of half-bridge submodules and full-bridge submodules (FBSMs) respectively, and the upper arm is composed of both types of submodules. The shunt arm eliminates the large ac filter required at the output of dc side. Moreover, it provides the bidirectional fault ride-through capability together with the FBSMs in the upper arm. Required kVA rating of the switches in the proposed topology is analyzed and compared to other topologies. With the optimal number of FBSMs in the upper and shunt arms designed by overmodulation, the proposed topology has a reduced kVA rating of switches, especially for the voltage conversion ratio above 0.54. A control strategy is presented to control the ac circulating current and balance the energy between the three arms. The performance of the proposed topology is validated by real-time simulation and a lab-scale test bench.

Static Var System (SVS) installations are prevalent and play an important role in voltage regulation and stabilization. A design concern for SVS installations is the introduction of harmonics due to inherent operation and amplification of existing power system harmonic distortion. Analysis of the harmonic interaction between proposed SVS installations and the power system is important. This paper presents information and guidelines for SVS design with specific emphasis on harmonic analysis. The main topics addressed are the design input data, the measurement requirements and the impact on SVS design configuration and component rating.

In this paper, a modular generic microgrid controller adaptive to different compositions and applications is presented. The rule-based dispatch strategy is designed to maintain power balance, follow the power reference at the point of interconnection, while reducing renewable generation curtailment and load shedding. The main feature of the controller is the modular architecture and the adaptivity to the removal or addition of assets. When assets are removed from microgrids, the dispatch strategy can adapt to this variation by setting their power constraints as zero. When more assets of the same type are added, they can be aggregated as one group and managed with a weighted and queuing algorithm to distribute power among the group members.

Fast charging station caters to the need for high power requirement for electric vehicles (EVs) charging in a short duration. Integration of local distributed generation resources can reduce the impact of the fast charging station on the grid. However, the intermittency of the distributed generation calls in for energy management system. This paper envisages the development of a rule based-modal control design for the energy management system (EMS) of a multi charger level 3 (50 kW) DC fast charging station (FCS). The paper presents the offline and controller hardware in the loop (CHIL) validation of the implemented design. Finally, three scenarios with respect to available grid energy are explored including the study of power sizing of ESU in order to provide a system level optimization for the performance of the EMS.

Thermostatically Controlled Loads (TCL) have a significant impact on Cold Load Pick-up (CLPU) during distribution system service restoration. Widespread deployment of smart meter devices opens up new opportunities for data-driven load modelling. In this paper, we compare several linear regression approaches to robust short term prediction of hourly energy consumption as a function of the outdoor temperature during the low-temperature season. The goal is to estimate the energy that will not be delivered during an outage for the purpose of a further estimation of the CLPU peak and duration for consumers with TCLs. The prediction is based on smart meter load data and outdoor temperature data. The performance of the proposed regression approaches is analyzed for 25 residential homes from real measured data. Prediction is performed on an hourly basis. The quality of the regression results is compared with the Naive forecast benchmark method. The results show that autoregression approach outperforms the other methods, however, since this approach is highly depended on the existence of the sequence of the previous load measurements, as an alternative approach, ENS prediction is successfully performed using only temperature data.

This chapter focuses on distributed energy resources (DER) and active distribution systems (ADS). More specifically, it addresses the impact of a high penetration of DER in distribution systems. It also addresses methods and approaches to deal with and exploit the potential of DER, at both the distribution and transmission levels, including in the development and operation of active distribution systems.

In this paper, we apply flexibility-based operational planning method to microgrid (MG) unit commitment (UC). The problem is formulated based on model predictive control (MPC) paradigm. Conventionally, such paradigm requires the online solution of a mixed-integer optimization problem, which faces difficulties in practical field implementations in a low-power computing microgrid controller. The explicit model predictive control (EMPC) can address this problem of MPC by computing the control laws of MPC in an explicit form offline to enable fast online computation. However, the complexity of the explicit control laws usually grows exponentially with the dimension of the problem, which hinders the application of EMPC in larger systems. In this paper, we integrate learning and EMPC to develop a computationally efficient and rigorous approach for implementing flexibility-based unit commitment paradigms in a microgrid controller with limited computational power. The computational complexity of the proposed approach can be adjusted to meet the hardware limitation of any given microgrid controller, while preserving as much as possible the optimality of the full-fidelity EMPC. This overcomes the drawbacks of traditional EMPC. Moreover, compared to the existing learning-based methods for accelerating optimization algorithms, the proposed approach is able to handle the variables and constraints of the original unit commitment problem systematically, which guarantees the feasibility of its output unit commitment schedules. We conduct case studies to demonstrate the effectiveness of the proposed approach.

An improved dynamic state estimation scheme that performs estimation for the full plant (states of a generator, exciter field voltage, and governor mechanical torque) using intermittent data from a phasor measurement unit (PMU) connected at generator terminal is presented. Overall fourth-order generator model is assumed in an extended Kalman filter (EKF), while first-order governors and excitation systems are assumed for simplicity of large-scale implementation. State estimation is performed using the EKF with random PMU data dropouts and known inputs, i.e., secondary reference signals P ref and V ref provided to a power plant by the network control center from economic dispatch. The state estimation scheme has been extended to all generators in network and DSE is performed using a computationally decentralized federation of EKFs at a centralized phasor data concentrator where PMU data are aggregated while dealing with a specified stochastic dropout rate. Required modifications have, thus, been made to standard EKF formulation to account for communication channel interruption and inherent delays. Simulation studies performed on the benchmark IEEE 9 and 39 bus system demonstrated performance and resilience of the proposed centralized EKF-based estimation technique. We also found that a centralized estimator can lead to improved wide-area instability indices derived from state estimates rather than PMU data directly.

Direct methods have been a promising development for decades, receiving, however, less attention recently. One of the reasons is the limited capacity to include more realistic models of the power systems equipment. This paper derives a structure-preserving analytical energy function for a sixth-order synchronous generator model with subtransient dynamics included. The procedure used to construct the energy function is demonstrated to be applicable to simple governor models as well. The energy function is used to assess critical clearing times for multiple contingencies via a potential energy boundary surface method in the IEEE 10-generator 39-bus benchmark system. Some comparative analysis with transient fourth-order models is performed. The results are validated against simulations using a commercial transient stability package.

This paper investigates and proposes a mitigation strategy for denial-of-service (DoS) cyber-attacks, targeting the most critical distributed energy resource (DER) in an islanded microgrid featuring a high penetration of renewables; the energy storage system (ESS) operating as the isochronous generator that forms and regulates the microgrid voltage and frequency. A rule-based fallback control strategy is proposed to enhance the resiliency of the microgrid to DoS cyber-attacks by managing the ESS state-of-charge in a decentralized manner, such that it can continue operating as the isochronous DER, while dispatching the remaining DERs in a centralized manner. Supplementary control loops are added to the ESS to manage and coordinate, using local frequency signals, with the remaining DERs, whose local controllers are specifically designed to provide frequency support in the event of DoS cyber-attacks. The proposed scheme is applied on a 25 kV islanded microgrid under two configurations, synchronous machine-based and 100% inverter-interfaced, and its effectiveness is validated on a real-time hardware-in-the loop testing platform.

Future distribution systems are faced with more challenges on islanding detection due to the increasing penetration level of inverter-based distributed generators (DGs). Different DG technologies, inverter control as well as other advanced inverter functions, such as fault ride through are challenging the capability of islanding detection schemes. On the other hand, for multiple feeders network, topological change of feeders and islanding at adjacent feeder increase the vulnerability of islanding detection devices. Furthermore, available islanding detection schemes are suffering from notable non-detection zones (NDZs) under reduced power mismatches. Therefore, to mitigate these issues, this paper proposes an effective methodology for building decision trees-based intelligent relay (IR). This methodology utilizes the NDZ boundaries of existing standard relays and applies a comprehensive training/testing strategy, which effectively reduces the NDZ while maintaining a superior dependability and security performance. To validate the applicability of the proposed methodology, the hardware-in-the-loop simulations are realized by programming the generated IR logics into a real commercial relay.

This paper presents a formulation to determine the appropriate power dispatch of an energy storage system, whose available energy is dependent on the charging/discharging pattern from previous time periods. The implementation structure is consistent with current dispatch algorithms used in microgrids, and the algorithm can be used in either grid-connected or islanded modes of operation. The proposed approach employs a backcasting algorithm to estimate the net stored energy value, against which the current cost of energy is compared to determine how the storage system should be used to perform arbitrage. The contribution of this paper is a means to include the time-dependent resource in traditional economic dispatch algorithms to reduce the cost of energy in a microgrid while enabling the arbitrage algorithm to continuously adapt to changing market conditions. Results show that the backcasting algorithm is able to reduce the average cost of energy by 8.14% and can reduce the average cost of energy by up to 72.3% of the ideal reduction, as determined by a perfect forecasting dispatch.

This paper proposes a torque cancelation strategy for a nonisolated three-phase integrated battery charger topology for light and medium duty electric vehicle drives based on six-phase permanent magnet (PM) synchronous machines. The charger requires a three-phase grid interface and utilizes the machine windings as the input filter inductances after minor reconfiguration. The drive power electronics are used to control the currents drawn from the three-phase grid. The current flowing through the machine windings induces a torque on the PM machine rotor which is eliminated by the proposed torque cancelation strategy in battery charging mode. The torque cancelation strategy is general and works with both symmetric and asymmetrically wound six-phase PM machines. The strategy is also capable of eliminating the torque when the rotor is displaced from the stator $d$ -axis. The linear quadratic regulator with the integral action control scheme is used to accommodate for the asymmetry caused by the dependence of winding inductance on the rotor position. Co-simulation results with Finite-Element Analysis and hardware experiments show the topology based on six-phase PM machines can be used to charge or discharge the battery for grid support functions while the torque on the machine shaft remains canceled.

Compared with multilevel space vector modulation, level-shifted multicarrier sinusoidal pulsewidth modulation (SPWM) for nested neutral point-clamped (NNPC) inverters requires much less calculations and implementation efforts, but the existing conventional SPWM cannot suppress the severe flying-capacitor (FC) voltage ripples under low output-frequency conditions. In order to solve this problem, a multicarrier-based PWM strategy with complete voltage balance control (VBC) capacity is proposed in this paper. For NNPC inverters operating under low output-frequency conditions, two preprocessing steps, the zero-sequence injection and the modulation-signal rearrangement, are proposed before the comparisons between level-shifted carriers and modulating signals. These preprocessing steps make the average currents flowing through FCs zero, which is beneficial to greatly reduce the FC voltage ripples under low output-frequency conditions. Together with additional VBC, the proposed modulation can assure the FC voltages balanced under the entire output-frequency conditions. Principles and implementation processes of proposed modulation techniques and VBC methodsare elaborated in detail and compared with conventional modulation methods. Both simulation results from a 5-MVA system and experimental results based on a 5-kVA platform are presented to verify the effectiveness.

This paper proposes a method to analyze and improve the performance of interconnection protection based on distance relaying for wind power distributed generation (DG) in distribution systems. Of particular importance is distance protection that uses the concept of prefault voltages as reference quantities found to have issues with intermittent behavior of wind power DG. This concept is normally used in different distance protective relaying applications in order to increase the fault resistance coverage capability of the distance relays as well as to ensure selectivity, dependability, and security under extreme undervoltages. The main contributions of this paper are to analyze this issue and propose a method to enhance the performance of distance protection to mitigate this issue. In this methodology, several case studies are investigated with different penetration levels, weather patterns, and configuration topology of DGs under both normal operating conditions as well as fault conditions. Results for a case study are given.

This paper proposes a hierarchical decision making model for a coupled planning and operation problem of an advanced microgrid. The proposed model, is formulated as a bilevel optimization problem and recast as a mathematical program with equilibrium constraints (MPEC) where the decision variables of the two problems are independently controlled. The upper problem determines the strategic investment decision and optimal configuration of the microgrid, the needs for carbon emission permits and peak charges from using neighbouring network capacity, while the lower problem optimizes the output of the distributed energy resources (DER) through the implementation of an energy management system (EMS). The proposed approach was applied to the energy infrastructure of a remote mine. Results obtained through its application show significant savings in the cost of energy and improved benefits to stakeholders. They also show the advantages of a bilevel approach over other state-of-the-art microgrid planning methodologies.

This paper proposes a bi–level formulation for a coupled microgrid power and reserve capacity planning problem, cast within the jurisdiction of a distribution system operator(DSO). The upper level problem of the proposed bi–level model represents a microgrid planner whose goal is to minimize its planning and operational cost, while the lower level problem represents a DSO whose primary duty is to ensure reliable power supply. The microgrid planner, pursues its interest by co–optimizing the design configuration and power output of individual distributed energy resources (DERs), while the DSO maximizes the capacity of flexible reserve resources. The proposed model is recast as a mathematical program with equilibrium constraints (MPEC) wherein the decision variables of the two problems are independently controlled. Application of the proposed approach to the energy infrastructure of a Canadian utility network is discussed. Results obtained through its application are compared to an alternative multi–objective planning model and the improved benefits are assigned to the corresponding stakeholders.

The output current ripple of an inverter shows different variations for sub-fundamental operating cycle and over few fundamental cycles. This paper investigates subfundamental cycle peak-peak current ripple variation of a three-level three-phase inverter over the entire operating modulation index range for the three-level continuous and discontinuous pulsewidth modulation strategies. Furthermore, based on the analytical current ripple variation, a strategy is presented to change the switching frequency within a fundamental cycle while maintaining the peak-peak current ripple similar to the conventional fixed switching frequency strategies. The strategy has been implemented and experimentally validated on a permanent-magnet synchronous motor drive. The results demonstrate that the proposed strategy reduces inverter switching instances and associated losses around 10–30%.

Microgrids are receiving increasing attention from power systems planners as a means to integrate distributed energy resources (DER) including renewable energy resources into the grid, and as a means of balancing the variability of renewable resources and loads with flexible generation. A key to justifying microgrids is establishing their business case. This helps to set the structure and configuration of the microgrid, including defining the DER required to feed part or all of the loads and the level of control required from the microgrid controller. This paper proposes a systematic approach and methodology for formulating and quantifying a microgrid business case. The framework adapts the use case approach to the microgrid context. It defines stakeholders, benefits and beneficiaries and determines the dependency of the business case on microgrid technologies. A method to quantify and allocate benefits is proposed. Applications to practical microgrids are discussed, including remote communities, remote mining sites and grid connected critical distribution grids.

The study proposes a non-isolated three-phase integrated battery charger (IBC) based on electric vehicle drivetrains that have two permanent magnet synchronous motors with shafts coupled via a torque coupler. The windings of both machines are used as input filter inductances after reconfiguration and connected to a three-phase grid in charging mode. Their existing traction inverters are operated as a three-phase charger that controls the charging power from the grid. The total torque produced on the shaft during operation is analysed and a strategy to eliminate it is proposed. The strategy not only maintains a zero-average torque but also eliminates the pulsating torque component on the shaft during operation. The topology allows conversion of the existing drive to an IBC through minor reconfiguration and provides an opportunity to reduce the effective THD injection into the grid via interleaving for machines with low winding inductance. A power balancing control is also proposed to reduce the second harmonic on the DC power output due to machine non-ideality. Simulation and experimental results validate that the topology can be used as both a battery charger and as a distributed resource, while the resultant torque on the shaft remains eliminated by the proposed strategy.

This paper proposes a method to vary the switching frequency within a fundamental cycle to reduce the switching losses of a two-level inverter while maintaining the peak–peak current ripple within a predefined limit. Unlike conventional strategies, the proposed technique utilizes precomputed switching frequency variation factors without relying on prediction or optimization techniques, since the peak–peak current ripple follows a definite trajectory within a fundamental cycle. Moreover, the variation in switching frequency is further controlled based on the operating carrier ratio and modulation index. The proposed strategy has been validated through both the simulation and experimental results on a permanent magnet synchronous motor drive for the space vector and discontinuous pulsewidth modulation patterns, and the results demonstrate that it reduces the two-level inverter switching losses up to 15%.

As the penetration of Distributed Energy resources (DERs) in distribution systems increases, their integration and interconnection to the grid, and their impact on the grid, need to be addressed in a coherent and structured manner. In the case of a large penetration, DER s can be integrated by aggregating the units using a DER energy management system (DERMS) or can form part of the devices constituting a microgrid, in which case they are managed by the microgrid control system. This article stresses the need for standards to facilitate the large-scale deployment of DER in the distribution system within a microgrid.

The increasing penetration level of renewable energy brings new challenges to the field of islanding detection. In this study, a decision-tree (DT)-learning method with hardware-in-the-loop (HIL) simulations is proposed to address the non-detection zone (NDZ) issue of islanding detection in hybrid distributed generation systems including both inverter- and synchronous-machine-based distributed energy resources. This method can effectively reduce the NDZ through advanced relay training strategy and utilise the advantage of real-time simulators on simulation efficiency. In addition, the generated DT can be programmed into a real relay and then get validated through HIL simulations. The HIL implementation adds a practical dimension to the proposed method. With the proposed method, the laboratory testing results indicate promising islanding detection performance in terms of dependability, security, reduced NDZ area and detection time.

Conventional three-level discontinuous pulsewidth modulation (DPWM) templates typically provide maximum switching loss reduction capability for load power factor angles in the range from 30° lagging to 30° leading. This paper proposes three space-vector-based DPWM templates for lower power factors and a generalized DPWM strategy for three-level inverters operating with modulation indices lower than 0.5. For different power factors, the proposed strategy adapts the inverter pulse sequence by combining different portions of the proposed and conventional DPWM templates within one operating fundamental cycle and ensures minimum switching instances when changing templates. Consequently, the strategy aligns the PWM clamping intervals with the respective load-current peaks, achieving around 50% switching loss reduction capability extended to all operating power factor angles (90° lagging to 90° leading). The simulation and experimental results demonstrate the effectiveness of the proposed three-level generalized DPWM strategy over the conventional three-level modulation strategies.

Micro-grid (MG) monitoring and information sharing between them through a central monitoring unit is required in the present day operational environment. The proposed research focuses on developing wide-area monitoring platform for multiple MGs running in parallel. This is achieved by using C37.118.1 complied phasor measurements units (PMUs) which provides accurate and reliable information monitoring at remote ends of the MGs and are further connected to the Phasor Data Concentrator which acts as the central monitoring unit. This process not only retrieves information at different nodes of the MGs equipped with PMUs, but the information can be exchanged between MGs for further action if required during contingencies. The PMUs are used to monitor phasors (amplitude and phases) and frequency of fundamentals which are further used to compute wide-area functions at different operating nodes of the MGs at grid connected and islanded modes of operation including different operating conditions. The proposed PMU and MG models are developed on MATLAB/SIMULINK platform. Extensive test results indicate that the proposed monitoring process is highly essential to retrieve the operational status of the multiple MGs observed at the central monitoring unit.

The reduced inertia due to integration of power-electronic converters brings about large frequency deviation and rate of change of frequency (ROCOF) in power system which may trigger frequency protection or increase the tears and wears of generators. The existing synthetic inertia and fast frequency response based on renewable energy resource is limited by the unidirectional power reserve, while the emerging virtual synchronous machine (VSM) control is limited by the energy storage needed on DC side. In this paper, an enhanced VSM control is proposed, considering the limitation of energy storage in response speed and energy capacity. The fast-acting energy storage system (FAESS), usually having small energy capacity, is used for emulating inertia and damping. An energy recovery control is proposed so that the energy will be automatically recovered after disturbance, thus reducing the energy capacity needed. The slow-acting energy storage system (SAESS) is controlled like governor control of synchronous machine, which adjusts power based on frequency change, thus taking advantage of its high energy capacity. DC and AC coupling of governor-like control and inertia-damping emulation is proposed, which is unanimous under the scheme of grid-forming and grid-following control. Comprehensive simulation results demonstrated the effectiveness of the proposed control strategy.