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An autonomous dc-bus dual-level control (DDLC) strategy is proposed for the two-stage three-phase photovoltaic power system. During the grid-fault situation, the second-stage inverter may lose the ability to regulate the dc-bus voltage and the first-stage boost converter has to change its mode from maximum power point tracking mode to dc-bus voltage control (DCVC) mode. However, the communication between the two-stage circuits must be established. The circuit complexity and cost will increase while the system's scalability and flexibility will be reduced. With the proposed DDLC strategy, the dc-bus voltage is controlled into different levels for different operation modes, without the need of communication mechanism. No extra sensors or circuits are required. Two important design parameters for the proposed DDLC are derived thoroughly. The computer simulations and hardware experimental results of a 4 kVA prototype circuit are presented to validate the performance of the proposed DDLC strategy.

This paper discusses the power variation of photovoltaic power plant (PVPP) impact on the frequency response of an isolated island microgrid. An island microgrid with PVPPs and diesel generators is selected for study. The power system network, diesel generation units, load and PVPP data are collected in detail. And the one-line diagram of the study system with regarding peak and off-peak loading is set up in the simulation software for the steady state load flow analysis. After that, the transient stability analysis is executed with considering the tripping and power variation of various PVPP ramp rates with and without considering the over frequency compensation of photovoltaic (PV) inverters. The dynamic response of diesel generators and system frequency are examined carefully. It is found that the over frequency phenomenon can be controlled effectively by the regulation of PV inverters to achieve better reliability of the microgrid.

Dynamic voltage restorers (DVRs) are one of the effective solutions to regulate the voltage of power systems and protect sensitive loads against voltage disturbances, such as voltage sags, voltage fluctuations, et cetera. The performance of voltage compensation with DVRs relies on the robustness to the power quality disturbances and rapid detection of voltage disturbances. In this paper, the recurrent wavelet fuzzy neural network (RWFNN)-based controller for the DVR is developed. With positive-sequence voltage analysis, the reference signal for the DVR compensation can be accurately obtained. In order to enhance the response time for the DVR controller, the RWFNN is introduced due to the merits of rapid convergence and superior dynamic modeling behavior. From the experimental results with the OPAL-RT real-time simulator (OP4510, OPAL-RT Technologies Inc., Montreal, Quebec, Canada), the effectiveness of proposed controller can be verified.

When a microgrid is grid-tied to a distribution system, it can provide surplus power generation to the distribution system, if any abnormality or interruption occurs in the distribution system, the microgrid can operate in standalone mode to isolate the impact of the abnormality or interruption. However, if the microgrid can not collect enough information from the distribution system, it may cause the failure of generation transferring of distribution feeders, or even further influence the stability of the distribution system. In this paper, a strategy for the resilient control of a microgrid is proposed. It can solve the above-mentioned problem, reduce the duration of the outage of loads. This strategy is experimented in the microgrid in the Institute of Nuclear Energy Research (INER), the reliability is also analyzed to evaluate the unavailability of the microgrid in INER, and it is verified that the proposed strategy can reduce the duration of the outage of loads, and hence the reliability of a microgrid can be upgraded.

To perform the fault protection for the microgrid in grid-connected mode, the wavelet energy fuzzy neural network-based technique (WEFNNBT) is proposed in this paper. Through the accurate activation of protective relay, the microgrid can be effectively isolated from the utility power system to prevent serious voltage fluctuation when the power quality of power system is disturbed. The proposed WEFNNBT can be divided into three stages—feature extraction (FE), feature condensation (FC), and disturbance identification (DI). In the FE stage, the feature of power signal at the point of common coupling (PCC) between microgrid and utility power system would be extracted with discrete wavelet transform (DWT). Then, the wavelet energy and variation of singular power signal can be obtained according to Parseval Theorem. To determine the dominant wavelet energy and enhance the robustness to the noise, the feature information is integrated in the FC stage. The feature information then would be processed in the DI stage to perform the fault identification and activate the protective relay if necessary. From the experimental results, it is realized that the proposed WEFNNBT can effectively perform the fault protection of microgrid.

An integrated microgrid with a novel shunt active power filter (APF) using Elman neural network (ENN) is proposed in this study. The microgrid consists of a storage system, a photovoltaic (PV) syst...

This article presents the electrical power planning, tests and analysis for a micro-grid (MG) in the distribution system. The MG of the Institute of Nuclear Energy Research has been selected for study. To enhance the MG reliability, two power sources are used for connecting to the utility power grid. The two power sources are currently interlocked, one for the regular and the other for the standby. Firstly, the phase sequence tests of the two power sources were performed to avoid the failure and damage of the equipment during power transfer. After that, the control logic planning between the two power sources is done to maintain the power supply of the MG. Finally, the reliability analysis for the load in the MG is performed to examine the effectiveness of the two power sources configuration.

The installation of renewable energy generation resources (such as photovoltaic arrays and wind-turbine generators) in a microgrid is important because a microgrid can increase the penetration of renewable energies in a smart grid. A community may be a grid-tied microgrid in which an energy management system may dispatch elastic loads (such as air conditioning systems). This paper investigates the optimal sizing of renewable energy generation resources in a community microgrid. The cost of renewables and community welfare are optimized while the comfort zone of indoor temperature in all homes is maintained using air conditioning systems. Community welfare is ensured by minimizing the purchased power from and maximizing the sold power to the utility grid with different time-of-use electricity tariffs. Since the problem of interest involves a large number of variables and chronological constraints, Markov models of photovoltaic power generation, wind generation, load and temperature are utilized to reduce the numbers of variables and constraints. The Markov-based optimization problem is then solved using the interior-point algorithm. The simulation results, based on a smart community of 50 homes, reveal the applicability of the proposed method.

In a general microgrid (MG), a step-up distribution transformer is used to facilitate integration of the low-voltage (LV) AC microgrid into a medium-voltage distribution system. On the other hand, isolation transformers are placed between distributed energy resources (DERs) (e.g. non-renewable/renewable energy resources and energy storage devices) and common AC buses/lines to eliminate DC-current components and to configure 3-phase & 4-wire, 3-phase & 3-wire, 1-phase & 2-wire, or 1-phase & 3-wire AC microgrids. When all neutral points of isolation transformers are grounded through a unique grounding system of the step-up distribution transformer, a uni-grounded AC microgrid structure is configured. This paper not only mentions advantages and shortcomings of the uni-grounded LVAC microgrid operation, but also investigates its transient operation characteristics. Transient simulation results of the uni-grounded LVAC MG are surveyed through various fault situations and operation transition tests between the grid-connected mode and the islanded mode of the microgrid. Available fault protection methods of a uni-grounded LVAC microgrid are considered. Transient simulation results from PSCAD software are used to validate the fault protection solutions developed for the uni-grounded LVAC microgrid. Last, a generalised fault protection system of uni-grounded LVAC microgrids is proposed in the paper.

The objective of this paper is to propose a bidirectional single-stage grid-connected inverter (BSG-inverter) for the battery energy storage system. The proposed BSG-inverter is composed of multiple bidirectional buck–boost type dc–dc converters (BBCs) and a dc–ac unfolder. Advantages of the proposed BSG-inverter include: single-stage power conversion, low battery and dc-bus voltages, pulsating charging/discharging currents, and individual power control for each battery module. Therefore, the equalization, lifetime extension, and capacity flexibility of the battery energy storage system can be achieved. Based on the developed equations, the power flow of the battery system can be controlled without the need of input current sensor. Also, with the interleaved operation between BBCs, the current ripple of the output inductor can be reduced too. The computer simulations and hardware experimental results are shown to verify the performance of the proposed BSG-inverter.

The main feature of the three-phase back-to-back active power conditioner (APC) is to improve the power quality of the microgrid. During the large power variation transient, the severe voltage surge/sag on the dc-link of the APC may cause its malfunction. Therefore, the dynamic optimal ac line current regulation (DOCR) with flexible dc-link voltage slope (FDVS) is proposed in this paper. The proposed DOCR can determine the accurate input current reference value to regulate the dc-link voltage under the large power variation condition. On the other hand, the proposed FDVS can further mitigate the dc-link voltage variation during the large power variation transient. The mathematical equations of the proposed control strategy are derived thoroughly. Furthermore, procedures to determine the dc-link capacitance with the proposed DOCR are developed. Finally, the experimental results obtained from a 5-kVA back-to-back APC verify the feasibility and the performance of the proposed line current regulation strategies.

This paper presents an improved dynamic voltage-current model of an ac electric arc furnace (EAF) for multiple operation stages and for the study of propagations of voltage fluctuations in a power network associated with the EAF in operating stages. The EAF model is developed based on wavelet-transform and neural-network-based methods by training actual measured EAF current and voltage data. The proposed EAF model is then implemented in an actual 161-kV power system for simulations. The voltage fluctuations at other buses due to the EAF in operation are then assessed. Simulation and measured results show that the improved hybrid EAF model is accurate and is suitable for voltage fluctuation assessment when the actual measurements in the power network are limited or not available while the EAF is in operation or before the similar types of EAFs are to be installed in the system.

An intelligent load-shedding strategy was designed and embedded in the special protection system (SPS) to enhance the system stability for an offshore island with high penetration of photovoltaic (PV) systems. To prepare the training data set for the artificial neural network (ANN), the transient stability analysis of the isolated power system was executed to determine the minimum amount of load to be interrupted to prevent the tripping of diesel generators for the emergency shutdown of PV systems. By selecting various combinations of PV penetration levels, total system load demand and the frequency decay rate at the instant of PV system tripping as the input neurons of the ANN, the proper load shedding scheme is derived and stored in the decision knowledge base of the SPS. When the intelligent energy management system (iEMS) detects the tripping of PV system, the SPS will be triggered to determine the amount of loss to be disconnected and executes the corresponding load interruption. By applying the proposed ANN based load shedding scheme in SPS, the amount of customer loading to be interrupted has been reduced dramatically for the restoration of system stability after the emergency shutdown of high penetration PV system.

An intelligent wind power smoothing control using recurrent fuzzy neural network (RFNN) is proposed in this study. First, the modeling of wind power generator and the designed battery energy storage system (BESS) are introduced. The BESS is consisted of a bidirectional interleaved DC/DC converter and a 3-arm 3-level inverter. Then, the network structure of the RFNN and its online learning algorithms are described in detail. Moreover, actual wind data is adopted as the input to the designed wind power generator model. Furthermore, the three-phase output currents of the wind power generator are converted to dq-axis current components. The resulted q-axis current is the input of the RFNN power smoothing control and the output is a gentle wind power curve to achieve the effect of wind power smoothing. The difference of the actual wind power and smoothed power is supplied by the BESS. The minimum energy capacity of the BESS with a small fluctuation of the grid power can be achieved by the RFNN power smoothing control. A digital signal processor (DSP) based BESS is built using two TMS320F28335. From the experimental results of various wind variation sceneries, the effectiveness of the proposed intelligent wind power smoothing control is verified.

To mitigate the impact of distribution system service quality due to high penetration of PV systems, a Distribution Renewable Energy Advanced Management System (DREAMS) is developed and installed at Feng Shan District of Taiwan Power Company (Taipower). The PV gateways and the public 4G communication system are applied to monitor the power generation and the voltage of 24 PV systems and to report the operation data to the master station. The power factor for the PV smart inverter is adjusted automatically to absorb the reactive power when the overvoltage problem occurs. When the distribution automation system (DAS) performs the functions of noninterruptible load transfer and service restoration after fault contingency, the DREAMS executes the power factor control for the PV smart inverters before the line switches are operated. The coordination control of DAS and DREAMS can prevent the overvoltage problem for a distribution system during the process of load transfer between distribution feeders with high PV penetration.

An intelligent controlled distributed generator (DG) system is proposed for the tracking control and islanding detection in this study. First, a DC power supply with a DC/AC power inverter is adopted to emulate a DG system for the tracking control of active power and reactive power outputs. Moreover, a novel active islanding detection method is proposed for the DG system to meet stringent standard requirements for interconnection with the power grid. The proposed active islanding detection method is based on injecting a disturbance signal into the DG system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the power grid is disconnected. The feasibility of the proposed active islanding detection method is evaluated under the UL1741 anti-islanding test configuration. Furthermore, in order to improve the tracking control of the active power and reactive power outputs of the inverter-based DG system, and to further improve the performance of the active islanding detection method, two probabilistic fuzzy neural network (PFNN) controllers are adopted to replace the conventional proportional-integral (PI) controllers. In addition, the network structure and the online learning algorithm of the adopted PFNN are introduced in detail. Finally, the effectiveness and feasibility of the tracking control and the proposed active islanding detection method using PFNN controllers are verified with experimental results.

This paper presents the effectiveness of the particle swarm optimization (PSO) to minimize the total active power loss of an island scale micro grid distribution network. In the adopted method, the co-simulation of the PSO algorithm and the Mat-power software on an island scale electrical network was proposed. The power system in Kiribati is selected as the study case. Two diesel power generation stations, one voltage regulator unit and one switching shunt capacitor bank are used to regulate the system voltage. The 24-h load flow is executed with the proposed PSO algorithm to minimize the active power loss and the annual power loss savings can be estimated. It is concluded that the proposed PSO algorithm can work well and give a satisfactory result.

This paper develops a novel fault protection system for AC microgrids having a multiple grounding system. Communication-supported digital relays which have different protection modules are used for this novel microgrid protection system. The protection modules in a digital relay have various functionalities to protect AC microgrids from various fault types, such as: low/high-impedance ground faults and short-circuits. To effectively use the developed novel microgrid protection system, the first step is to reconfigure different microgrid structures into a standard microgrid configuration having a multiple-grounding system through using delta/wye-grounded or wye-grounded/wye-grounded transformers. Then, a fast–dependable–adaptable (FDA) fault protection algorithm is developed to protect AC microgrids from faults occurring at trunk lines, common buses or branch lines. At an islanded operation mode of AC microgrids, by using digital relays, a new protection module is designed to detect, locate, and classify the faults occurring at trunk lines and common AC buses, while other protection modules can use the existing protection methodologies (e.g. directional/non-directional overcurrent protection principles, etc.) to detect and clear the faults at source branches or load branches of the microgrids. At a grid-connected operation mode, standard overcurrent protection modules are applied for the FDA fault protection system. Simulation and experiment results obtained from various fault cases at a real low-voltage AC microgrid have validated the effective operation of the FDA fault protection system.

This paper presents a shunt active power filter (APF) with division–summation (D– $\Sigma )$ digital control and based on a three-phase three-wire inverter configuration. The APF shapes source current by introducing one degree of freedom to compensate load harmonic currents. The adopted D– $\Sigma $ digital control approach can accommodate filter-inductance variation, reducing core size significantly, and it can derive control laws directly. An average power method is adopted in this paper for determining the fundamental current at the source side, which can readily be implemented without complex calculation, frame transformation, and extra filter. In the design and implementation, the inductances corresponding to various inductor currents were estimated at the startup and stored in the microcontroller for scheduling loop gain cycle by cycle, which can ensure the system stability. Measured results from a 5-kVA three-phase APF have confirmed the analysis and discussion of the APF.

This paper evaluates fault protection methods of ungrounded low-voltage (LV) AC microgrids (MGs) based on transient simulation results of a typical ungrounded LVAC microgrid. By considering operation characteristics of ungrounded MGs and a literature review on existing MG fault protection solutions in recent years, possible fault protection methods are proposed for an ungrounded AC MG. Transient simulation results of an ungrounded AC MG are obtained by line-to-line (LL) and line-to-ground (LG) faults, and operation transition tests of the microgrid between autonomous and grid-connected operation modes. Based on the simulation results, advantages and disadvantages of each ungrounded microgrid protection solution are highlighted. In order to get the optimal fault protection, combinations among some or all of possible fault protection solutions of an ungrounded LVAC microgrid are found out. As a result, main contributions of the paper contain: (i) proposing and analysing available fault protection solutions of ungrounded LVAC MGs, (ii) doing the transient simulations of a typical ungrounded microgrid under different disturbance cases, and (iii) suggesting the necessary combinations among proposed fault protection solutions of ungrounded MGs.

Under-frequency load shedding (UFLS) strategy provides a special protection scheme while severe events occur in the power system. This paper presents an UFLS strategy for an offshore standalone power system near Taiwan. The proposed UFLS strategy defines a fixed percentage, which will be allocated to 4 stages, of total system load. Compared to the current UFLS of the studied power system, the proposed UFLS strategy can improve power quality by restoring system frequency with a smaller amount of shed load.

The operation of diesel generators can be categorized into two modes: isochronous speed control and droop control. The isochronous mode provides an open loop control to restore system frequency back to the nominal value while the droop mode is a closed loop control to settle transients to steady states. This paper investigates these two modes of diesel generators in a standalone power system, operated by Taipower. The scenarios with peak and off-peak loads in the summer and winter were explored by considering the N-1 contingency. The optimal operation modes for multiple diesel generators in this standalone power system will be presented.

A distribution static compensator (DSTATCOM) is proposed in this study to improve the power quality, which includes the total harmonic distortion (THD) of the grid current and power factor (PF), of a mini grid with nonlinear and linear inductive loads. Moreover, the DC-link voltage regulation control of the DSTATCOM is essential especially under load variation conditions. Therefore, to improve the power quality and keep the DC-link voltage of the DSTATCOM constant under the variation of nonlinear and linear loads effectively, the traditional proportional-integral (PI) controller is substituted with a new online trained compensatory fuzzy neural network with an asymmetric membership function (CFNN-AMF) controller. In the proposed CFNN-AMF, the compensatory parameter to integrate pessimistic and optimistic operations of fuzzy systems is embedded in the CFNN. Furthermore, the dimensions of the Gaussian membership functions are directly extended to AMFs for the optimization of the fuzzy rules and the upgrade of learning ability of the networks. In addition, the network structure and online learning algorithm of the proposed CFNN-AMF are introduced in detail. Finally, the effectiveness and feasibility of the DSTATCOM using the proposed CFNN-AMF controller to improve the power quality and maintain the constant DC-link voltage under the change of nonlinear and linear inductive loads have been demonstrated by some experimental results.

The paper presents an economic evaluation, including a cost-benefit analysis and a sensitivity analysis, of smart photovoltaic (PV) inverters with a novel Watt-Var control scheme for enhancing PV penetration in distribution systems in Taiwan. The novel Watt-Var control scheme with three operation phases is utilized to avoid the voltage violation problem during peak solar irradiation period and increase the PV real power injection, and thus can get higher PV penetration in distribution systems. To evaluate the benefit and cost of the PV investment project, the annual revenue of PV power sales, the initial capital investment cost for a PV project with or without a smart inverter, and the operating and maintenance (O&amp, M) cost are taken into account. The paper demonstrates the analyses of net present value (NPV) and benefit-cost ratio (BCR) for the PV project. In addition, the paper also presents a sensitivity analysis to deal with the project uncertainty with respect to some affecting parameters. The analyzing results show that, under the feed-in tariffs (FITs) policy, with proper selection of PV and smart inverter capacities, the investment can be profitable, and the smart PV inverter can greatly enhance the PV penetration in distribution systems in Taiwan. These results can provide some useful information for making policy to encourage investment in solar PV industry.

A per-phase control strategy of the three-phase four-wire inverter is proposed in this paper. The proposed control method is simple and does not require any complex transformation. The equivalent single-phase half-bridge inverter of the three-phase four-wire inverter is presented and used to derive the equations of the reference sinusoidal control signal of each phase. The active power and reactive power of each phase can be controlled, respectively. Computer simulation and experimental results for different operating cases are presented to verify the performance of the proposed per-phase control method.