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The Island Operation Capability service allows operators to split the system (in case of an accident, for instance) and operate as an integral isolated subsystem. This, in turn, increases reliability, resilience, efficiency, and reduces restoration times after a blackout in the islands power systems. The provision of this kind of service from distributed energy resources has recently been introduced in different power systems. This paper outlines a proposal for the implementation of Island Operation Capability in the Colombian electricity market. The proposal considers technical variables, namely, energy not supplied, generation not delivered, and electrical losses. We developed a behavioral simulation model to test the impact of the implementation and an upgrade of the grid. Simulation results show technical benefits for the distribution system operator and economic benefits for investors and project promoters of distributed energy resources. Finally, the simulation’s results show that modernizing the distribution grid is important in order to increase Island Operation Capability and the security of the electrical system.

The paper describes two main approaches of periodic control under variable frequency conditions: frequency adaptive multioscillatory control (FAMOSC) and fractional delay repetitive control (FDRC). The methods are applied in the control system of a grid-tie converter to increase the quality of phase currents in case of distorted grid voltages. The paper compares structures, performance and implementation of FAMOSC, FDRC and the conventional approach of repetitive and multioscillatory control. Performances of the control systems are illustrated with experiments on a laboratory test bench. The article describes tuning process of FDRC and FAMOSC with the usage of Particle Swarm Optimization algorithm. A detailed analyse and research of the techniques in terms of computational complexity is presented. Practical hints for implementation and resource optimization of both techniques on DSP are included. For FAMOSC a fast implementation of prewarping is proposed.

Future grids will consist of many small and large microgrids that will require complex control of grid interaction as well as islanding operation. This paper addresses the control of islanded microgrids under dynamic system conditions. In this paper, a robust model reference modified adaptive proportional integral derivative (PID) controller is designed for voltage and current control augmentation of islanded microgrid against various load dynamics. The variation of load dynamics may cause the unsafe operation of the microgrid. The objective of the designed controller is to confirm the safe operation against voltage and current control under different load dynamics. The controller is designed based on selecting the desired reference model and controlling parameters. The effectiveness of the proposed controller is evaluated against the presence of load dynamics, harmonic sources, asynchronous machines, nonlinear and unknown loads. The results show that the proposed controller is capable of providing high tracking performance and safe operation for both the single and three phase islanded microgrid system.

Renewable generation and power electronic convertors increasingly displace the inertia conventionally provided by synchronous generation in the transition to a low carbon electricity network. Changes in generation profiles influence regions of the grid disproportionately, and areas of low inertia are susceptible to frequency diverging from neighboring areas, creating new risks of Rate Of Change Of Frequency (ROCOF)-based generation trips, underfrequency load shedding and islanding. A novel method of measuring area inertia is presented, with results of simulation and trials on the SP Energy Networks (Scottishpower) transmission system in south Scotland. The fundamentally new understanding of frequency and inertial effects is essential for designing mitigation measures for frequency and network stability, and enables new, flexible services for the transition to low inertia power systems.

For grid-connected inverters, phase-locked loop (PLL) is an indispensable part for grid currents to track grid voltages. Hence, PLL will have a nonnegligible effect on the stability of the interconnected system involving a grid-connected inverter and a power grid. Therefore, it is necessary to model the frequency characteristic of PLL and analyze its effect on the system stability. In this paper, three kinds of the commonly used PLL circuits are firstly employed to model and compare their frequency characteristics. Second, the impedances of the inverter are modeled with the equivalent impedance model of PLL displayed, and the influences of different PLLs on the impedance characteristics of the inverter are compared. Then, the effects of PLLs on the stability of the interconnected system are studied to discuss the stability boundary conditions of the system. Based on the equivalent impedance model of the PLL, the optimized design method of the PLL is proposed from the perspective of optimizing the inverter impedance characteristics to improve the system stability. Finally, the simulation and experimental results are presented to verify the correctness of the PLL frequency characteristics and the inverter impedance models, and confirm the effectiveness of the optimized design method.

A major and very important challenge in dc grid development is maintaining continuous converter operation under dc faults. This paper proposes a novel capacitive energy storage device which improves security of dc grids by avoiding terminal blocking. The device provides current from the capacitor bank during dc faults, reducing fault current contribution and voltage drop of dc grid converters. Moreover, the device also helps in balancing pole voltages which is of particular significance during pole-to-ground faults in symmetrical monopole systems. Other benefits like improved transient grid stability are also demonstrated. Device’s design and performance is assessed using theoretical analysis and verified on a three-terminal offshore dc grid model in PSCAD. The cost of the device’s electronics is minimized and the total cost and weight estimation are also shown.

Modular multilevel converter (MMC) is a type of electronic converter currently used as voltage source in real HVDC transmission systems. This paper presents, as an alternative, a control system designed to operate an MMC as a nonlinear vector current source (NLVCS). From the design point of view, it features advantages such as constant switching frequency, robustness against grid parameters changes and that the algorithm is entirely designed from space vectors. From the application point of view, the main advantages are its fast dynamic response combined with its capability to handle large amounts of electric power. Together, these two features allow the MMC to deal with highly variable renewable energies. To show the advantages of the proposed control system, it has been chosen a very demanding application: wave energy. In this type of applications, the random nature of the sea produces large and fast variations of the generated power, that enters the DC link and that the grid side converter has to handle very fast, injecting it into the grid in order to maintain the DC voltage constant. The capability of the NLVCS for MMC to handle the energy generated has been tested in two different wave energy applications. Firstly, on a single wave energy converter (WEC), a point absorber. This case is characterized by smaller and faster power changes. Secondly, on a wave farm made up of 200 WECs connected to the grid through an MMC. This case is characterized by much larger but smoother power changes. Wave farms, WECs and MMC are large and sophisticated facilities or devices that are almost impossible to gather in the same laboratory. Consequently, the features of the new control system for MMC and the advantages that provide in the connection of wave energy power plants and point absorbers to the grid has been simulated using detailed models. The results demonstrated the capability of the MMC operating as NLVCS to deal with the fast and random power changes present in renewable energy sources.

As a response to the future challenges that power systems will have to face, a gradual growth of present High Voltage Direct Current (HVDC) links is expected, leading to an HVDC supergrid integrating different configurations of HVDC stations. Such stations may suffer contingencies affecting just one pole (asymmetrical contingencies). The effects of these contingencies on an HVDC grid are very dependent on the configuration of the HVDC stations and their earthing system. Furthermore, when symmetrical monopolar stations exist in the DC grid, asymmetrical contingencies will also affect its healthy pole. For that reason, this paper focuses on the influence of the earthing system resistance of symmetrical monopolar stations on the performance of a heterogeneous HVDC grid during asymmetrical operation. The impact on the protection system is also investigated. The analysis concludes that an inappropriate earthing resistance magnitude may lead to a poor performance of heterogenous HVDC grids during asymmetrical operation. In addition, the study also indicates that the decisive factors for the selection of the grounding impedance of a symmetrical monopolar station are the asymmetrical operation of the whole grid and its contribution to pole-to-ground fault currents.

This paper presents an impedance-based interaction and stability analysis of multi-terminal HVDC systems. First, an analytical derivation procedure is presented to obtain the feedback impedance models of a voltage source converter (VSC) as a subsystem, with particular interest on the DC side impedance. Subsequently, in addition to the impedance models of other subsystems, an impedance aggregation method is applied to derive the dynamic closed-loop impedance matrix of the system considering the interconnected structure of the grid. Given the closed-loop impedance matrix, multi-input multi-output (MIMO) relative gain array (RGA) formulation is proposed to analyse nodal interactions between converters and the network. Furthermore, the impedance ratio matrix is proposed for HVDC stability analysis based on impedance models. Remarkably, these formulations are derived compactly without any knowledge of the internal states of any converter and therefore allows the ease of interoperability analysis. Finally, the impact of control architecture and strategy on the dynamic responses, interaction, and stability analysis from an impedance perspective is conducted as a case study. The analysis is done in the frequency domain and validated with the physical model of a three-terminal DC test grid built in SimscapeTM MATLAB/Simulink®.

This work proposes a co-simulation environment that interfaces the OpenDSS, a frequency-domain program, with a time-domain-based electromagnetic transients software, aiming at performing studies on renewable resources penetration in distribution feeders. Each program handles part of the grid in a parallel manner, exchanging information at only predefined instants during the simulation. For the data exchange between time-domain and frequency-based simulations, the second order generalized integrator structure is used for extracting the phasors. Comparisons with the traditional curve fitting method show improved computational efficiency while keeping reasonable accuracy. Results, presented for the IEEE 13-bus distribution system benchmark operating with three photovoltaic plants, show accurate results obtained 12 times faster than the full time-domain simulation.

In this study, an efficient and fast adaptive perturb and observe (AD-PO) maximum power point tracking (MPPT) algorithm based on the variable - speed wind energy conversion system (WECS) is proposed to eradicate drawbacks of conventional fixed step-size P&O (CPO) algorithms and to enhance the operation of variable step-size P&O (VS-PO). The AD-PO divides the power-speed (P-ω) curve into modular sectors that depend on the estimated wind speed. The step-size is varied adaptively in each sector by observing the distance between the theoretical maximum power point (MPP) and operating power point. The AD-PO enhances the speed convergence with low steady-state oscillations around the MPP. The system configuration involves a 1.5 MW five-phase permanent magnet synchronous generator (PMSG). A back-to-back converter (BTBC) with a dc-link capacitor is used to integrate the PMSG with the utility grid. Simulation results confirm the superiority of the AD-PO over the CPO and the VS-PO MPPT algorithms based on speed convergence and oscillation levels. The performance of the proposed control scheme is validated by real wind data (Boulder City, Colorado) using MATLAB/SIMULINK environment.

As the smart grid structure interconnects renewable energy sources and operators, it is inevitably influenced by the conversion technology and communication system. Investigating the effects of both aspects jointly is an intricate task due to its multifaceted characteristic. In this paper, it is proposed a wireless coded predictive direct power control for a general renewable energy system connected to the grid for smart grid environment. The predictive direct power control processes the received power references that are sent through the wireless channel, and selects the optimal voltage vector to be supplied by the three-phase inverter using the power errors. The wireless communication system, which connects the smart grid operator to the energy systems, is based on Low Density Parity Check and Orthogonal Frequency Division Multiplexing, and in this work, it was used, as a reference of performance, a system that employs Convolutional Coding. The behavior of the proposed power control is evaluated experimentally presenting an operational condition with satisfactory performance.

Using a multi-agent system (MAS), the present research offers a model for an interactive decentralized operation of a multi-carrier energy system which includes electrical, thermal, and cooling loads. The novelty of the proposed model is that the photovoltaic (PV) agent as a renewable energy producer can directly influence the clearing price of electrical interaction without any supervisory control and only through communicating with other agents. Using battery storage status and upper grid energy price, this agent calculates its own power generation for each hour which results in optimization of social welfare and personal profit. In the current work, using decentralized private ownership in a multi-energy system leads to a plug and play feature which makes system development and scaling easier. Then, to evaluate decentralized approach, the proposed model is simulated with Any Logic programming package and its numerical results are compared to those of the centralized model. The results show that the effective presence of PV agent in electrical interaction decreases the social welfare while increases personal profit.

Long-term transmission constrained unit commitment (LT-TCUC) is an important tool in generation expansion planning and has got much attention in recent years. When traditional Lagrangian relaxation (LR) and mixed integer programming (MIP) based methods are used to solve LT-TCUC problems, serious challenges related with the solution efficiency are encountered. This paper proposes a fast method for solving TCUC with long time horizon based on horizon splitting. The basic idea is to partition the whole horizon into several short time intervals, and then relax the coupling constraints between consecutive intervals (ramp rate constraints and minimum up/down time constraints). Sub-TCUC problem in each time interval is then solved independently (in parallel) with CPLEX and the solutions are further adjusted based on MIP to satisfy the relaxed coupling constraints. In this way, the feasibility of the solution is guaranteed and the solutions to the sub-TCUC problems are connected. Salient features of the method include that the solution efficiency is guaranteed and the solution quality can be estimated based on the optimality gap. The proposed method is tested on the modified IEEE 24-bus system, 118-bus systems, and a regional grid in China with one-month or one-year time horizon. Numerical results show that the solution method is efficient.

Distributed generation (DG) systems—particularly photovoltaic (PV) systems—that can control reactive power can change the behavior of a power system network in spite of their relatively small individual capacities because of bidirectional power flow and reactive power control. Therefore, power flow algorithms should be able to accurately model the response of a power system network that includes DG systems. Various power flow algorithms have modeled DG systems as either a P-Q or P-V bus. However, small DG systems connected to the grid by a short line, but not a long transmission line, or predefined mutually between utilities and DG system owners can participate in the control of reactive power. They can adaptively adjust the reactive power output according to their bus voltage. Thus, the objective of this study is to present a strategy that participates in the control of bus voltage within its limits and reactive power by either injecting or absorbing reactive power. For this purpose, this study presents a Petri net approach that a bus to which a DG system is connected is modeled as a P-Q or P-V bus with equality and inequality constraints. The proposed bus voltage control strategy is verified using the well-known IEEE test feeders.

Transmission Expansion Planning (TEP) problem aims at identifying when and where new equipment as transmission lines, cables and transformers should be inserted on the grid. The transmission upgrade capacity is motivated by several factors as meeting the increasing electricity demand, increasing the reliability of the system and providing non-discriminatory access to cheap generation for consumers. However, TEP problems have been changing over the years as the electrical system evolves. In this way, this paper provides a detailed historical analysis of the evolution of the TEP over the years and the prospects for this challenging task. Furthermore, this study presents an outline review of more than 140 recent articles about TEP problems, literature insights and identified gaps as a critical thinking in how new tools and approaches on TEP can contribute for the new era of renewable and distributed electricity markets.

In this paper, a novel frequency synchronization method is proposed for fast connection the islanded microgrid to the existing grid. In the conventional frequency synchronization method, the output of the synchronization controller is limited to maintain the voltage quality of the islanded microgrid. Due to this limitation of the output, the micro grid voltage has a nonlinear characteristic during the synchronization process. Conventional methods that do not consider the nonlinear characteristic have a drawback in that the synchronization speed can be slowed depending on the convergence direction of the frequency. To overcome the drawback, the nonlinear characteristic of the conventional method is analysed during the synchronization process. Based on the analysis, the synchronization speed is predicted according to the synchronization direction of the microgrid voltage. Using this prediction, a novel synchronization technique that finds a relatively fast synchronization direction is proposed. A 2MVA microgrid system is constructed using a real-time hardware-in-loop system and experimental results are presented to verify the validity of the proposed method. From experimental results, it is confirmed that the proposed method guarantees a faster synchronization speed than the conventional method.

The transient stability of an offshore-wind farm connected to the main ac grid by a high-voltage direct current (HVDC) system depends on the control settings of the converters, the grid resonances and the system’s operating conditions. This paper focuses n identifying possible sources of resonance interactions that could endanger the overall stability of this kind of system. For this purpose, the ac-side input admittance/impedance of a full-power converter (FPC) wind turbine and an MMC-based HVDC system are derived and frequency-domain stability analysis tools are used to assess the impact of system and control parameters on stability. The analytical findings are verified through time-domain simulations and recommendations to increase system stability are given accordingly.

As the electronically-interfaced distributed energy resources (DERs) grow rapidly in power grid, power demand satisfaction and frequency regulation are two main challenges in control area. However, it is difficult to model the analysis of a large-scale grid as well as design a stable and optimal control scheme. With the support of DERs, this paper proposes an actor-critic neural network that integrates a distributed reinforcement learning control scheme to compensate frequency regulation of power grid. The short-term performance and stability is improved by a deterministic learning algorithm that is used to obtain the approximation of desired control output. Meanwhile, a long-term strategic utility function is estimated by the integrated actor-critic neural network. The mapping from system state and control output to the strategic utility function value is identified by neural network, as well as utilized in sub-optimal control learning for further improvement of long-term system performance. Theoretical analysis guarantees the stability. Frequency deviation, tie-line power flow, and long-term cost are coincident with uniform ultimate boundness (UUB). In addition, the upper bound of long-term system cost is also reckoned. The effectiveness and advantages of proposed scheme are illustrated in two case studies. The simulation results indicate that the proposed scheme has better performance under certain condition, compared with some actor-critic network control schemes in frequency regulation of power grid.

This study presents an improved threshold-based differential protection scheme for micro-grids using time-frequency transform. Variational mode decomposition (VMD) in combination with Hilbert transform is used as the time-frequency transform. The improvements like insensitivity to noise and no modal aliasing effect makes VMD better over wavelet transform and empirical mode decomposition for fault studies. This protection scheme is applied to the currents retrieved at the two ends of the feeder to compute the differential energy for the micro-grid protection in grid connected and islanded modes. The proposed scheme is verified on a standard IEC micro-grid test system operating in different configurations for various events like shunt faults, high impedance fault, and switching events. In addition, it is also validated using the real-time signals obtained through OPAL-RT as a real-time simulator. Comparative results validate that the proposed scheme performs accurately providing improved results than the state-of-the-art differential protection schemes.

This paper presents a multi-stage management scheme for renewable-rich medium voltage distribution network (MVDN) to promote the renewable energy consumption and mitigate the system uncertainty. In the first stage, a day-ahead (DA) dispatch model is proposed to promote the renewable distributed generation (RDG) consumption and decrease the power loss. In the second stage, a model predictive control (MPC) based rolling optimization model for intra-day (ID) operation is proposed to minimize the mismatch of the interactive power at the upstream Grid Supply Point (GSP) between the DA schedule and ID operation. Multiple active management elements such as network reconfiguration and soft open point are integrated and a novel second order cone programming (SOCP) model for the centralized optimal power flow in the DA and ID stages is presented. In the third stage, a decentralized P/Q(V) control strategy of RDG inverter for real-time (RT) voltage regulation is proposed to ensure system safety and mitigate the fast voltage fluctuation. The effectiveness of proposed management scheme is demonstrated in a test system integrating a standard network and real-world data of load and RDG output profiles.

Introduction of the distributed energy resources (DER) and new types of consumer equipment greatly increased the uncertainty in the distribution grid. Due to these changes traditional “worst case” planning algorithm from the passive distribution networks (PDN) will require extensive capital investments with a high probability that the resulted network would be largely underutilized. A prominent solution is to involve active elements (AEs) that can be found on a local level into the grid planning. A generic multi-stage planning framework for incorporating the flexibility from AEs in the distribution grid planning is proposed in this paper. The framework facilitates the transition from PDN to active distribution networks (ADN) and considers all planning stages starting from the data collection to the implementation plan. An example involving flexible demand shows how to use the framework in grid planning and demonstrates the benefits of ADN planning over PDN planning.

This paper proposes a second-order sliding mode control technique for the grid-connected solar photovoltaic system. The proposed technique is tested under grid faults to meet the requirements of low-voltage ride through capability. A dual-mode control technique of the converter and inverter is designed to maintain the required dc-link voltage regulation and the active-reactive power during grid fault. The sliding mode control technique is developed from the model of the grid connected to the converter and the dc-link. The proposed dual-mode control technique is validated using real-time simulator OPAL-RT and experimental three-phase grid-connected photovoltaic inverter system. Simulation and experimental results show that the control technique is quite effective in maintaining the dc-link voltage regulation and the power control. As it shows smooth transitions between the two modes of operation (normal and grid fault). Moreover, the sliding mode control approach is robust against unknown disturbances and uncertainties in the system.

This study presents a control system for a single-phase DC/AC inverter operating in a microgrid with the capability of operating in both grid-connected and islanded mode with no need to reconfigure the control system which offers seamless transition between different modes. In this control scheme, in the grid-connected mode, the adopted control system emerges as an active-reactive power controller, while in the islanded mode; it inherently alters in order to form a microgrid with controlled voltage and frequency. As the control system is the same in both modes, the seamless transition is provided as a result. Moreover, the proposed control system is not reliant on synchronization of DC/AC inverter with the main grid which provides an effective solution for the case in which no communication system is intended or the DC/AC inverter and microgrid point of common coupling (PCC) are far away from each other. The small signal modeling of the proposed controller is used to corroborate the stable operation of the proposed system. Simulation studies in MATLAB and experimental evaluations confirm the effectiveness of the proposed solution.

The microgrids (MGs) are composed of several Distributed Generation (DG) units, storages and loads at the demand side which can work in both islanded and connected to the main grid; in islanded mode, the MGs voltage and frequency must be controlled by individual DG units. As the Plug-in Hybrid Electric Vehicles (PHEVs) in MGs can have both roles of loads and storages, participation of these ever growing elements in the MGs voltage and frequency control problem is investigated in this study. At first, an intelligent droop control for MGs voltage and frequency control is proposed to be implemented on inverter-interfaced DGs except PHEVs. The proposed droop control is independent from the MG lines parameters and can control the voltage and frequency of MG seamlessly. Afterwards, a novel strategy for participating the PHEVs in controlling the voltage and frequency of MGs is proposed. This strategy is implemented on the PHEVs parking lots in the Vehicle-to-grid (V2G) mode. This strategy has a prominent capability to keep the stability of MG even in severe scenarios compared to the other previous strategy. Moreover, the proposed strategy lowers the voltage drops and keeps the frequency constant. In the simulation studies, both proposed (named smart) and previous (named non-smart) charging strategies are implemented and compared. The simulation results show the effectiveness of the proposed strategy in order to keep the stability of MG even in severe scenarios, maintain the frequency and voltage better than another recent strategy.

The addition of an external communication layer to the power system has left it vulnerable to cyberattacks. False data injection (FDI) can be used to manipulate measurements that are used to estimate the state of the power system. Decisions made based on a false evaluation can result in major disturbances in its operation. Recent studies show how, with full knowledge about the system, these types of attacks can be mounted without being detected. This paper shows how, with knowledge limited only to a specific section of the power system, it is still possible to carry out an undetectable attack. The process of performing the attack and a proof of its undetectability is explained in detail and then illustrated through a case study on the widely adopted IEEE 14 bus system. Last but not least, the paper proposes a method to identify a subset of available measurements to be considered for protection against cyberattacks. This would render the entire network or specific parts of it immune to these attacks.

Power balance in the grid relies on distributed generation (DG) from unpredictable sources forming part of the whole energy traded, and the big power plants guaranteeing stability. Nevertheless, as DG continues to grow, matching supply and demand efficiently becomes increasingly difficult. In the area of microgrids, this becomes a major challenge. The majority of existing research deals solely with preserving the stability of the power grid, while some studies have broadened their focus to include the issue of balancing supply and demand. The aim of this study is to present a solution to the power imbalance problem based on the idea of splitting the energy transaction into small energy fragments (EF), simultaneously generated by the producer and obtained by the consumer with such accuracy that the disturbances are negligible. To this end, a new control scheme is presented, where suppliers and customers take advantage of new technologies (ICT) in order to trade an agreed upon amount of energy with no impact on the power. The effect of the control algorithm on the power grid is evaluated through simulations conducted in a microgrid benchmark network, comparing performance with and without energy transactions. Furthermore, network protocol aspects are analyzed. The simulation results show improvements in grid performance such as reductions in both joule losses and voltage deviation. In conclusion, this improvement results in a reduction of both the utility company control effort, and the reserve power for balancing. Furthermore the avoidance of the need for a central organization, opens up scalability and facilitates a more open and competitive market.

The large-scale deployment of distributed photovoltaic (PV) systems on the low voltage distribution network (LVDN) poses significant challenges to network operators related to the dynamic interactions of the PV systems and the network. To address these challenges and implement grid support services (GSS’s), accurate and efficient PV system models are required that allow large networks with integrated PV to be simulated in an economical time frame. For this purpose, an accurate, computationally inexpensive, linearised, state-space model of a two-stage PV system in the dq0 rotating reference frame is presented in this paper. The model includes both the DC/DC and DC/AC converters, all system controllers, parasitic components, system losses, and an efficient PV array model. The performance of the model is validated with measured experimental data from a power hardware in the loop (PHIL) testbed at various simulated step changes in irradiance. The developed model is applied to a modified radial European LVDN benchmark with multiple distributed PV systems to demonstrate some of the functions, applications and advantages. A combined active and reactive power voltage-dependent droop control characteristic for GSS’s is demonstrated with solar irradiation step changes and measured solar irradiation data applied to each PV system. A full electromagnetic transient (EMT) PV system model developed in MATLAB is presented and compared to the linear state-space (LSS) model. The results demonstrate a computational burden reduction of 116:1 without loss of accuracy providing significant benefits and functionality for the study of large-scale grid integration of PV systems.

An LCL filter is commonly used in grid-connected inverter to attenuate the switching harmonics; nevertheless, the stability problems will arise in the grid current control if the resonance of LCL filter is not properly damped. High pass filter-based grid current feedback active damping is an effective solution to solve the aforesaid problem. However, for systems with digital control, the system may exhibit non-minimum phase system characteristics due to the control delay effect, which will affect the system stability. Moreover, the frequency responses of current controller parameters and active damping parameters are coupled. Therefore, to ensure the system stability and good dynamic performance, the current controller parameters and active damping parameters should be designed together, considering the control delay effect. For this issue, a systematic controller design method is proposed for the digitally controlled LCL-type grid-connected inverter with grid-current-feedback active damping. With the proposed method, the satisfactory regions of the control parameters for satisfying the system specifications can be obtained, from which the proper control parameters can be easily and quickly picked out, without the trial and error. Finally, the proposed design method is verified by the experiment.

This paper investigates the optimal grid reconfiguration (OGR) strategy in the smart grids with the random behavior of the many electric vehicle mobility (EVM) fleets and wind energy uncertainty. The increased utilization of EVMs in the power system with stochastic volatile behavior along with the high penetration of wind energy sources (WESs) can create new challenges in the system that will affect the system flexibility greatly. Here, the electric vehicle is mobile and there are distributed devices with deferrable options to supply energy at various times and locations. Accordingly, in this paper, the OGR is used as the remedial action to enhance the system flexibility to handle uncertainties. The main aim of this paper is to increase system flexibility and reduce expected operating costs by the coordination between EVM fleets, OGR and WESs’ uncertainty. Beside, this paper provides a novel method to evaluate the system flexibility while explicitly considering thermal unit generation and the EVM fleets. Numerical tests demonstrate the effectiveness of the proposed approach for analyzing the impact of EVM fleets on the system flexibility and hourly wind energy dispatch.

The increasing penetration of renewable energy resources (RERs) is challenging power grid planning and operation in maintaining grid reliability. Potential power grid reliability and stability issues may arise when large-scale RERs are connected to a weak power grid. These issues may become more significant due to the mutual interactions among RERs that are interconnected electrically close through a power network. Weakness analysis based on grid strength assessment is useful for identifying the potential weak grid issues. However, when taking into account the impact of the interactions among RERs, the weakness analysis becomes computationally challenging. Different combinations of points of interconnections (POIs) of RERs may have different impacts on grid strength at each POI. Due to the combination nature, such weakness analysis may be time-consuming when identifying the weakest combination of POIs from a large number of potential candidates in realistic power grids. To address this concern, the impact of the power network structure on grid strength is analyzed in this paper. It is found that the impact mainly depends on the impedance ratios at POIs. The findings can be summarized as two criteria to develop a recursive method for fast identification of the weakest combination in this paper. The efficacy of the proposed method is demonstrated through case studies on the IEEE 39-bus system and a realistic power grid.

© 2019 Elsevier Ltd In this paper, the importance of the matrix converter stabilization in bidirectional power flow control is investigated. A stabilization technique for matrix converters based on a combination of the damping resistor and the input digital filter is proposed. The suggested technique is applied to a direct matrix converter employed as an interface between two power sources as the main grid and a microgrid to realize a stable four-quadrant power flow control process. The control method is based on the voltage oriented control strategy using anti-windup proportional-integral controllers. The stability analysis using the small-signal model of the converter is presented and simulated numerically. The proposed stabilization and bidirectional power flow control methods are validated by experimental tests on a prototype.

As the development of plug-in-electric vehicles (PEVs) accelerates, the effective integration of large-scale PEVs with power grid becomes an urgent problem for utilities and PEV users. Mainly considering grid side preference, this paper proposes a distributed control method with a consensus algorithm to deal with large-scale PEV charging coordination. The objectives of the proposed coordination strategy are: minimizing the charging power loss and maximizing the available PEV power for vehicle-to-grid (V2G) services. The incremental cost functions are formulated for these objectives. The graph theory is applied to specify the communication network for PEVs. An interaction rule, the consensus algorithm is applied to realize the local information updating and external information exchanging among neighboring PEVs. A variable-size stochastic matrix is defined to specify the communication topology among PEVs, as well as guarantee the convergence of the consensus targets. The simulation results show that, with limited communication, the large-scale PEV charging/discharging can be efficiently coordinated to reduce total charging power loss or provide V2G service with maximum available PEV power. Meanwhile the PEV charging requirements specified by drivers can be satisfied. In addition, the convergence of the proposed distributed consensus algorithm can always be guaranteed upon random PEV departures.

Coordinating the operation of neighboring microgrids is a promising solution for the problem of growing penetration of renewable-based microgrids into the power system. In this paper, a hierarchical stochastic energy management system is proposed for operation management of interconnected microgrids. At the upper-level, a central entity is responsible for coordinating the operation of microgrids. Based on the energy scheduling made at this level, the power reference values to be exchanged within the microgrids network and between the microgrids and the main grid are calculated and communicated with the local energy management systems. At the lower-level, a decision making approach based on chance-constrained model predictive control is adopted for local operation management of each microgrid taking into account different sources of uncertainties. The results show that the proposed strategy provides the microgrids with the opportunity of exploiting maximum available capacity in the network. Consequently, the microgrids dependency on the main grid will be reduced and some important performance indices such as multi-microgrid system cost and real-time power deviations will be improved.

In view of the instability phenomenon of power electronics dominated power systems, an analytical method suitable for revealing the instability mechanism of power electronics dominated power systems is proposed. The proposed analytical method divides power electronics dominated power systems into two subsystems: electrical subsystem and control subsystem. First, the weak links of the system are screened out by eigenvalue analytical method, then the linearized relation of state variables in the weak links is derived from the perspective of the electrical subsystem. Through the study of the interactions between the weak links of the electrical subsystem and the related control subsystem, the mechanism of the system instability can be explained by “positive feedback effect” formed by the interactions between the electrical subsystem and the control subsystem. The proposed analytical method can reveal the dynamic interactive process of state variables compared to impedance analytical method and eigenvalue analytical method when the system is unstable. Meanwhile, a linearized model of weak links in the electrical subsystem can be set up specially, helping to reduce the workload. Finally, the analytical method is verified by three study cases when VSC-HVDC is connected to the weak AC power grid under two different operation conditions and when direct-drive permanent magnet synchronous generator system is connected to VSC-HVDC system.

At the time of contingency like converter outage in multi-terminal DC grid, it is critical that the working converter stations share the power imbalance/load according to their respective capacity. In this study, several concepts of designing variable droop constant are proposed. These variants are formulated out of conventional fixed droop scheme considering operational parameters of converters and desired voltage and frequency regulation. The adoption of variable droop allows converters to share the imbalance power proportional to their rating and available headroom. A droop design method to reduce the voltage deviations at converter terminals is also proposed. Further, a variable droop control scheme using voltage deviation, frequency deviation of the non-synchronous AC area connected to DC terminal and available headroom of the converters is also discussed. This scheme modifies the DC power flow in such a way that the converter terminal with frequency decrease in AC system, allocates to supply more power to the AC system and vice-versa. A five terminal MTDC system is modelled and simulated to show the effectiveness of proposed droop control schemes. The droop scheme for proportional power sharing according to available headroom adjusts the converter power cooperatively to respond to the needs of frequency regulation.

Under the current grid operation mode, reasonable integration of wind power is conducive to the exertion of its value. In this paper, the line flow transmission margin value considering wind power integration is assimilated into the locational marginal price (LMP). Accordingly, the LMP includes four components: energy consumption, network loss, congestion and line flow transmission margin. Based on the LMP difference of load nodes before and after wind power integration and the idea of power flow tracing, the specific values of different grid-connected wind farms at each node are evaluated, namely, the energy value and the network value of wind power. The load nodes that have a critical impact on wind power accommodation for each wind farm are identified. Moreover, the reserve cost caused by the uncertainty of wind power is considered, in which the maximum total value of all wind farms is set as the optimal objective. Finally, this paper analyses the LMP, value and accommodation of a single wind farm in detail through a microgrid system and an IEEE 118-bus system with multiple wind farms to verify the proposed method.

The interest in off-grid solar PV system has grown significantly in recent years. The price of suitable batteries started to decline following the price trajectory of solar PV, the curtailment of solar feed-in-tariff in many countries and the increasing electricity price. These are some important factors for grid defection trends. In this paper, we analyse the reliability and levelised cost of electricity (LCOE) of residential off-grid customers’ PV-battery systems in order to carry out a techno-economic feasibility study of grid-defection. In more detail, this study demonstrates how off-grid customers can trade-off reliability for LCOE of their PV-battery systems, taking into consideration the priority/user-preference of different load types in a household. Consequently, we propose a novel decision making tool to improve the performance of a dynamic home energy management system (HEMS). The HEMS is set up as a mixed-integer linear optimization (MILP) problem which is solved using a rolling-horizon approach for weekly and yearly simulations. Weekly simulations were first performed in order to investigate the optimal range of PV and battery size combinations based on reliability and LCOE, using a week with the lowest solar PV output and the highest demand. Given the optimal PV-battery size combinations, yearly simulations were performed to assess the reliability and LCOE of PV-battery systems of randomly selected residential households in the Ausgrid Solar Home Electricity Data. Simulation results over the critical time period of the year indicate that an off-grid PV-battery system is relatively feasible for customers who are willing to compromize lower reliability in exchange for a lower cost. The result however indicates that the cost is still higher compared with a grid-connected system.

Power system planning for modern distribution networks is undergoing a change because of distributed power generation and grid ancillary services. The vast electricity retail utility industry with many distribution network operators plans generation and transmission expansion planning for determining optimal investment decisions. This paper addresses this planning problem in a decentralized and distributed context. This paper introduces a coordinated decision making approach for optimal investments in generation and transmission expansion planning problems for distribution networks. The distribution networks are further classified into microgrids. Considering an agent as the functional information exchanging entity just like an energy meter with the objective to coordinate the expansion decisions of participants; a novel math-heuristic optimization model Coordinated Microgrid is presented. To simulate the coordination of information a multi-agent-system based coordinated decision making method is adopted and the value of coordination is investigated. The evolutionary vertical sequencing protocol, a heuristic method, is developed and implemented to simulate the coordination process among agents on the top level. The proposed protocol produces smart permutations of microgrids for coordination. On the bottom level, a two-stage chance-constrained stochastic MILP formulation for investment decisions with operational uncertainties is modeled. For market clearing a nodal-pricing scheme is adopted that maintains the Nash equilibrium among and across the microgrids for energy transactions. The proposed model is tested with consumption, network configuration data from three islands in west-coast of Norway. The models are solved to optimality and results lead to the observations that the value of coordination lies in profit increment of individual microgrid. The novel protocol proposed demonstrates an advantage of retrieving smart permutations from combinations of microgrids. In summary, CoMG is a novel expansion planning model for optimal investments in modern power distribution networks.

The renewable power systems have become more susceptible to the system insecure than traditional power systems due to reducing of the total inertia and damping properties that result from replacing the conventional generators with Renewable Energy Sources (RESs) as well as decoupling of the RESs from the AC grid using power converters. Therefore, maintaining the dynamic security of renewable power systems is the key challenge for integrating more RESs. This paper addresses a new strategy of frequency control including virtual inertia control based on Virtual Synchronous Generator (VSG), which emulates the behavior of conventional synchronous generators in large power systems, thus adding some inertia to the system control loop virtually and accordingly stabilizing the system frequency during high penetration of RESs. Moreover, the proposed virtual inertia control system-based VSG is coordinated with digital frequency protection for improvement the frequency stability and preservation the power system dynamic security because of the high integration level of the RESs. The effectiveness of the proposed coordination scheme is tested and verified through small and large scales of power systems, Microgrid (µG) and real hybrid power system in Egypt, respectively. System modelling and simulation results are carried out using Matlab/Simulink® software. The simulation results validated that the proposed coordination scheme can effectively regulate the system frequency and ensure robust performance to maintain the dynamic system security with high share of RESs for different contingencies.

Previous researches suggested that the direct-drive permanent magnetic synchronous generator (PMSG)-based wind farms are immune from sub-synchronous control interaction (SSCI). However, since the occurrence of emerging sub-synchronous oscillation (SSO) caused by PMSG-based wind farm connected to a weak AC network, it is of great significant to re-investigate this SSCI problem. To address it, a small-signal model of target system is established first, then modal analysis is conducted to delve into the dynamic interaction between PMSG and compensated network, and the time domain simulation is performed to verify modal analysis results. The results of the paper reveal that PMSG connected to compensated grid could excite an emerging SSCI, which is caused by the dynamic interaction of converters and series compensated line, and the oscillation frequency is strongly related to the electrical resonance frequency. The major contributions of the paper include: (1) re-discussion of the SSCI immunity of PMSG-based system and re-identification of the turbine types which are susceptible to SSCI, (2) analysis on frequency characters of the emerging SSCI, (3) investigation of decoupling effect between machine and grid.

This paper presents a real-time simulation and hardware-based approach for systematic integration of Distributed Energy Resources (DERs) in advanced distribution grids with a special focus on resilience. Advanced distribution grids are considered to be functionally more sophisticated than traditional ones. The desirable advanced functionalities include – reconfiguration, real-time sensing, DERs, self-healing, etc. Some of these functionalities are currently being realized by microgrids as well. However, it is not feasible to convert each section of a distribution grid into a microgrid, but can be instituted with functionalities by design and controls at relatively lower costs. Interconnection of DERs, including energy storage to improve reliability and resilience is presented in details. Resilience of distribution grids is gaining greater importance and research towards enhancing it utilizing DERs is a key area. A real-time resilience framework with Analytical Hierarchical Processes (AHP) is developed that adapts to changing configurations, DERs, switching operations, grid conditions, etc. to provide an accurate and adoptable composite resilience metric. This framework and the composite resilience metric can play a unique role in operational and design decisions for operating future distribution grids. Advanced functionalities such as scenario-based reconfiguration in distribution grids are considered, with resilience metrics as performance criteria for choosing a preferred combination. Simulations are performed using Digital Real-Time Simulator (DRTS) and characterized response of flow battery validated against actual flow battery hardware is imposed to provide realistic results. Reconfiguration program is interfaced with DRTS for bi-directional real-time communication. Key contributions include enhancement of resilience of distribution grids using energy storage system under dynamic operating conditions.

This paper, from the perspective of hourly dispatch, proposes an approach of sizing Energy Storage System (ESS) in an isolated grid. The objective is to minimize the total cost by optimizing the size of ESS, thermal units generation power, wind curtailment and load demand response. While transforming the chance constraints, such as the network constraints, into the deterministic constraints, the model takes into account the correlations of the forecast errors among wind farms, and load at different buses. In addition, two types of transmission line overloading probability (TLOP) constraints are considered in the ESS sizing models. In particular, an approach of linearizing the scenario generation network constraints is proposed, so that the commercial software can solve the optimization problem. Meanwhile, the performance of the proposed sizing method is validated on a 4-Bus system and a modified IEEE RTS-79 system.

When there are enormous number of systems, such as microgrids (MGs), in power systems, the study faces two challenges: nonlinearity and multiplicity. Therefore, in this paper, a new linear equivalent model (LEM) is proposed for synchronous generator (SG)-based MGs to reduce computation burden and complexity. The proposed LEM is based on a third-order linear model of SG. However, it includes equivalent models of vital controllers of SG-based MG; excitation and turbine-governor (EXS and GOV) systems. The ultimate aim of this study is to estimate parameters of LEM such that it behaves as a nonlinear detailed model (NDM). Measurements at point of common coupling (PCC) and genetic algorithm are used to reach this goal. The identified LEM is investigated at different operating points and the results are compared with NDM outputs to show accuracy of the proposed solution.

In this paper, a novel plug-in electric vehicle (PEV) modeling approach is proposed for residential charging stations. This methodology can be used in the design of autonomous energy management systems (EMS) with the purpose of providing the charging schedules using minimum input measured data. The proposed method is composed of two main steps. In the first step, unlike other similar works, online PEV recognition is performed by means of an artificial neural network as a supervised classification method. The required feature space for classification is provided using the power spectral density estimation and the statistical analysis of individual PEVs charging current. The second step deals with the statistical modeling of the charging habits to facilitate the scheduling by predicting the charging demand using the current measurements on the grid side. In this respect, each PEV charging habit is modeled based on the correlation among the plug-in time, departure time, required energy, and weekdays using kernel density estimation. The performance of the suggested method is validated using real data collected from a charging station. The final results confirm the applicability of the proposed methodology with a satisfactory precision. The effectiveness of the method is demonstrated using a comparative analysis in terms of the recognition performance.

A power system is continuously exposed to changes in load and operating conditions. This results in voltage variation which may lead to instability at times. Therefore, it is required to assess the voltage stability continuously for which a stability index is used. This paper uses phasor measurement data from selected buses to estimate the states of the system. Thevenin equivalent of the system is calculated and a voltage stability index obtained using ratio of change in load power to change in voltage magnitude. The index provides how close the system is towards instability, following load variation and/or change in topology. When the proposed index is equal to 1, the system reaches voltage collapse point. For any lower value of the index, the system is in stable region and when it approaches 1, it is vulnerable to collapse. Load margin assessment is performed when the system is voltage stressed and obtained for selected stressed buses using a least square technique. Load margins of buses around the stressed buses are also calculated which is useful in situational awareness of a system. Several case studies are performed on 39 bus New England test system and 233 bus North Eastern Indian grid by varying load and topology of the system. Different types of loads are also considered in the testing. The methods for stability index calculation and load margin assessment are found to be accurate. Comparative performance of the proposed technique with available method is also presented.

In this paper, a novel PLL technique based on Multi-Resonant disturbance Observer (MRO) is investigated. The proposed technique can achieve grid synchronization under distorted voltages and simultaneously quantify grid unbalances, including voltage sags and higher harmonics. Real-time quantification of grid condition is very important in estimating the overall power quality, which in turn has a drastic effect on power regulation. The proposed technique is easily applicable and expandable to any desired number of higher harmonics. In addition, we provide an in-depth analysis of the connection between original grid unbalances in the stationary reference frame and its image under dq transform. Finally, we propose a methodology capable of real-time estimation of positive and negative harmonic sequences based on the observed properties of fundamental and higher harmonics.

This paper presents a practical approach for the real-power economic dispatch of AC/DC power transmission systems formed by VSC-HVDC equipment. It uses the Lagrange multipliers method combined with a comprehensive representation of the AC/DC power system. The power losses of the AC systems, DC grid and power converters are considered in this novel formulation by using incremental transmission loss factors. For realistic solutions, the different control strategies of the power converters forming any VSC-based power grid are considered. Interestingly, this approach permits to conclude that the AC grids coupled to converters charged with DC voltage control define the nodal marginal prices in the DC network, and in turn, the energy prices in the VSC-connected passive grids are inherited from the DC network. Overall, this modelling approach yields great flexibility to model any arbitrary VSC-based HVDC power grid interconnecting various AC systems. The developed method has been validated using a two-terminal VSC-HVDC network interconnecting two otherwise independent AC grids. Its results are compared against those obtained by the sequential quadratic programming method available in the optimisation toolbox of Matlab©, with both solutions exhibiting differences inferior to 0.30% in the total generation costs, therefore concurring very well between each other. The practicality of this approach is also demonstrated by carrying out the real-power economic dispatch of an AC/DC transmission system comprising seven VSC units which give rise to a thirteen-node DC grid.

This paper proposes a framework to address day-ahead scheduling of a microgrid (MG) with wind, solar and micro-turbine distributed generators as well as batteries, considering the associated uncertainties and AC power flow constraints. The problem uncertainties are wind and solar generations, demand, and grid electricity price. The uncertainties are modelled using bounded intervals within adaptive robust optimization method. Unlike previous robust models presented for MG scheduling, our proposed adaptive robust model optimizes both wait-and-see and here-and-now decisions simultaneously which leads to obtaining a better operating point. In order to make wait-and-see and here-and-now decisions and immunize the model against worst case realizations, the proposed MG scheduling model has been formulated as a tri-level optimization framework. In the first level, here-and-now commitment decisions are made (these are decisions made before realization of uncertainties). In the second stage, the worst case realization of the uncertain parameters is determined. In the third level, the wait-and-see recourse decisions are made (these are decisions made after realization of uncertainties). Since there are before uncertainty-realization decisions, worst uncertainty-realization determination, and after uncertainty-realization decisions, the proposed model becomes a tri-level optimization framework. The proposed adaptive robust tri-level MG scheduling model, the proposed solution approach including AdptRob and ConvAC problems, and the proposed out-of-sample analysis are the main contributions of this paper. A convexified AC power flow model is used in the proposed framework for modeling the distribution network. The 69-bus distribution test system is used to test the proposed adaptive robust model as well as the proposed solution approach which converges very fast. Moreover, the results of the out-of-sample analysis shows that the proposed adaptive robust model results in lower expected cost and lower cost variance.