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Due to the higher proportion of non-synchronous power resources in microgrids, adequate frequency regulation supports are required to maintain acceptable system frequency stability. As one of the sources for frequency regulation support in microgrid operation, via proper droop controller operations, wind energy conversion systems (WECS) could deliver kinetic energy stored in their turbines to the grid when needed. However, as the system inertia becomes smaller, the droop controller's response to system disturbances could cause the WECS to resonate with the grid and lead to torsional stress and fatigue damage in the WECS drivetrain. To protect the WECS against such damage, a resonance damper based on pole-zero cancellation technique is proposed in this paper. Simulation results depict the possible resonance phenomenon, and the reduction of undesired fatigue damage by the proposed damper retrofitted to the droop controller while improving the overall frequency regulation. Sensitivity analysis results are also provided to verify its robustness for practical applications. [ABSTRACT FROM AUTHOR]

Due to delays in network reinforcement, many utilities adopt System Integrity Protection Scheme (SIPS) as the short-term last defense to prevent system instability after critical disturbances. One of the challenges in the design of a SIPS is to handle the effects of intermittent renewable generation. Penetration level, geographic distribution, forecast errors, inverters control modes, and synchronous generation displacement are among the sources of effects of renewables that affect the reliable operation of an SIPS. To adapt to variations in system conditions, a new proposition of Adaptable System Integrity Protection Scheme (ASIPS) utilizing offline, online, and edge computing resources is proposed in this article. It aims to maintain reliable operation and reduce control costs under the presence of output variations of renewables. Possible impacts of renewables to the SIPS operations are demonstrated. Based on continuous system state monitoring using Phasor Measurement Units, the proposed response-based ASIPS would trigger optimal controls determined online by using a linearized formulation, or due to time criticality, activate quasi-optimal controls periodically updated and stored in look-up tables using offline computing power. Simulation results demonstrate the effectiveness of the proposed ASIPS in preventing system instability by using reduced control efforts and costs according to real-time operation conditions. [ABSTRACT FROM AUTHOR]

A sustainable power grid involves variable and uncertain generation, load and equipment availability. In order to ensure the frequency quality, power system needs to maintain sufficient reserve capacity to meet the demand and generation variations, and to withstand contingency events. To limit the operation risk to an acceptable level, an operation practice driven and control performance based reserve allocation method is proposed in this paper to determine adequate frequency regulation reserve in an island power system with increasing renewable integrations. Analyses of on-line available frequency regulation reserves and control performance data recorded in Energy Management System are conducted to appraise and manage the risk of non-compliance of frequency control standard. The proposed method is based on the conditional probabilities of reaching certain Control Performance Standard 1 (CPS1) score under the availability of Automatic Generation Control ramping and droop response capability. Comparisons of estimated reserve requirements and expected performance of four dynamic reserve allocation schemes to comply with CPS1 are presented. [ABSTRACT FROM AUTHOR]

Microgrids are designed to ensure reliability and quality of power supply. Reliable islanding transition is key to maintain uninterrupted supply of power to critical loads. Current islanding transition schemes assume fast response from local energy resources to establish secure islanding; however, such fast response systems are often expensive. Analysis of historical events shows that the islanding event, at most instances, can be predicted; by exploiting this feature, this paper proposes an adaptive optimal defense mechanism to establish secure islanding, without acquiring fast response energy resources. The dynamics involved in the islanding transition are incorporated into the search for optimal defense measures by using “simulation optimization” technique. A comparison between no defense approach and with defensive approach for the scenario when the islanding occurs demonstrates the effectiveness of the proposed adaptive defensive approach. The application of the adaptive defensive approach can help improve system performance. Sensitivity analyses are conducted to suggest improvements to reduce the operation cost of proposed defense plan. [ABSTRACT FROM AUTHOR]

Transition to a sustainable energy environment results in aggregated generator and load dynamics in the distribution network. State estimation is a key function in building adequate network models for online monitoring and analyzes. The requirements of distribution system state estimation (DSSE) is becoming stringent because of the needs of new system modeling and operation practices associated with integration of distributed energy resources and the adoption of advanced technologies in distribution network. This paper summarizes the state-of-the-art technology, major hurdles, and challenges in DSSE development. The opportunities, paradigm shift, and future research directions that could facilitate the need of DSSE are discussed. [ABSTRACT FROM PUBLISHER]

An analytical method that can be used to study the optimal topology and maximum capacity of the existing distribution network to accommodate electric vehicle (EV) charging demands is presented in this paper. In order to facilitate a large number of EV integrations, the feeder reconfiguration problem is formulated as a discrete nonlinear optimization problem that finds optimal feeders' tie switch locations and their on/off schedule to minimize operation costs and comply with the system operation constraints. A novel stochastic dynamic programming technique is adopted to solve the problem that includes various uncertainties associated with feeder baseline and EV charging loads. Simulation results obtained from an 84-bus feeder test system have indicated that for a case with 20% EV penetration to a 70% capacity utilization feeder area, a 10.78% reduction of operation cost and a 14.4% decrease in maximum feeder utilization can be obtained by distribution feeder reconfiguration. [ABSTRACT FROM PUBLISHER]

Distribution system states have become more dynamic due to the integration of intermittent distributed generation/load and bi-directional power flows. The availability of close to real-time distribution system models will help the controls and customer participations in the active distribution networks. A framework using on-line and off-line computing power and data in existing distribution management system to work together and build distribution feeder models for operation purposes is proposed. Simulations and evaluation results of the synergy of big heterogeneous topological and measurement data from systems that have different data formats, polling cycles, and accuracy to establish immediate past and future feeder models are presented. Archived customer meter interval and supervisory control and data acquisition (SCADA) data with the same time stamp are used to build quasi dynamic models off-line, and to forecast the states and measurements at the feeder buses. The results are then used in the on-line quasi dynamic state estimations (DySEs). The state tracking capability of two DySE techniques in conjunction with a static state estimator under various data accuracy assumptions is evaluated. Numerical results demonstrate the benefit of data synergy in the improvement of system operation models and network efficiency. [ABSTRACT FROM PUBLISHER]

A stochastic modeling and simulation technique for analyzing impacts of electric vehicles charging demands on distribution network is proposed in this paper. Different from the previous deterministic approaches, the feeder daily load models, electric vehicle start charging time, and battery state of charge used in the impact study are derived from actual measurements and survey data. Distribution operation security risk information, such as over-current and under-voltage, is obtained from three-phase distribution load flow studies that use stochastic parameters drawn from Roulette wheel selection. Voltage and congestion impact indicators are defined and a comparison of the deterministic and stochastic analytical approaches in providing information required in distribution network reinforcement planning is presented. Numerical results illustrate the capability of the proposed stochastic models in reflecting system losses and security impacts due to electric vehicle integrations. The effectiveness of a controlled charging algorithm aimed at relieving the system operation problem is also presented. [ABSTRACT FROM PUBLISHER]

Distribution network designers use a transformer load-management system to estimate and examine the historical and current loads occurring on transformers and test proposed load situations. Due to a lack of measurements at the feeders and distribution transformers, the confidence on the transformer load-management reports was low in the past. Intelligent equipment and advanced information and communication technology are now being integrated into distribution networks at an unprecedented speed. The technology advancement provides an opportunity to enhance transformer load modeling and management. In this paper, a framework using synchronized measurements obtained from different information systems via a utility's enterprise service bus is proposed to calculate the actual load profiles of distribution transformers and reflect changing system conditions. Network analyses resulting from using improved system models based on distribution state estimation allow the system operators and designers to make informed decisions concerning where new loads can be added and when new transformer capacity must be included. [ABSTRACT FROM PUBLISHER]

Illegal use of electric energy is a widespread practice in many parts of the world. Smart metering enables the improvement of customer load model, theft and stressed asset detections. In this paper, a state estimation based approach for distribution transformer load estimation is exploited to detect meter malfunction/tampering and provide quantitative evidences of non-technical loss (NTL). A measure of overall fit of the estimated values to the pseudo feeder bus injection measurements based on customer metering data aggregated at the distribution transformers is used to localize the electricity usage irregularity. Following the state estimation results, an analysis of variance (ANOVA) is used to create a suspect list of customers with metering problems and estimate the actual usage. Typical Taiwan Power Company (TPC) distribution feeder data are used in the tests. Results of NTL detection under meter defect and energy theft scenarios are presented. Experiences indicate that the proposed scheme can give a good trace of the actual usage at feeder buses and supplement the current meter data validation estimation and editing (VEE) process to improve meter data quality. [ABSTRACT FROM PUBLISHER]

Electric arc furnaces (EAF) used in the steel manufacturing industry are one of the most disturbing loads that cause voltage flicker problems in the electric power network. Means for reduction of voltage flickers by conducting furnace controls, such as electrode controls, or by adding compensation equipment, such as power factor corrector and static var compensator, are widely used in the industry. In order to achieve the best result, an accurate model for flicker analysis and prediction is essential. In this paper, a new technique for EAF voltage flicker analysis is presented. In the proposed method, short-term flicker severity indices, Pst are analyzed by a nonlinear chaotic technique, in which a phase (state) space approach is used. Under the reconstructed phase spaces, Lyapunov exponent patterns in the chaotic trajectory are observed, and three short-term flicker predictions methods are developed and tested. The performance of the proposed method is compared with those of two other time series analysis methods. Test results indicate that with sufficient flicker measurement data, a short-term prediction of the flicker severity is achievable. The information would be useful for remedial controls to reduce displeasing flicker level caused by an EAF. [ABSTRACT FROM PUBLISHER]

There is increasing requests for noncontrollable distribution generation (DG) interconnections in the medium and low voltage networks. Many studies have suggested that with proper system planning, DG could provide benefits such as reliability enhancement, investment deferment, and reduced losses. However, without network reinforcements, the allowable interconnection capacity in a network is often restricted due to fault current level, voltage variation, and power flow constraints. This paper aims to address the issue of optimizing network operation and use for accommodating DG integrations. A new DG interconnection planning study framework that includes a coordinated feeder reconfiguration and voltage control to calculate the maximum allowable DG capacity at a given node in the distribution network is presented. A binary particle swarm optimization (BPSO) technique is employed to solve the discrete nonlinear optimization problem and possible uncertainties associated with volatile renewable DG resource and loads are incorporated through a stochastic simulation approach. Comprehensive case studies are conducted to illustrate the applicability of the proposed method. Numerical examples suggest that the method and procedure used in the current DG interconnection impact study should be modified in order to optimize the existing grid operation and usage to facilitate customer participation in system operation and planning. [ABSTRACT FROM PUBLISHER]

Due to the growth of electricity demands and transactions in power markets, existing power networks need to be enhanced in order to increase their loadability. The problem of determining the best locations for network reinforcement can be formulated as a mixed discrete-continuous nonlinear optimization problem (MDCP). The complexity of the problem makes extensive simulations necessary and the computational requirement is high. An ordinal optimization (OO) technique is proposed in this paper to solve the MDCP involving two types of flexible ac transmission systems (FACTS) devices, namely static var compensator (SVC) and thyristor controlled series compensator (TCSC), for system loadability enhancement. In this approach, crude models are proposed to cope with the complexity of the problem and speed up the simulations with high alignment confidence. Test results based on a practical power system confirm that the proposed models permit the use of OO-based approach for finding good enough solutions with less computational efforts. [ABSTRACT FROM AUTHOR]

Adoption of the IEC flicker standard by IEEE would encourage countries currently using \DeltaV10 flicker standard to consider either updating the \DeltaV10 calculation to make it more suitable for modern day applications, or switching to the IEC standard. In the process of revising the flicker standard, the design of flicker planning level is important. For this purpose, this letter presents comparative statistical analyses of flicker measurements based on present Pst and \DeltaV10 standards. Besides the comparison of synchronous flicker severity indices in 10-min intervals, analyses are also conducted using daily flicker statistical reference values measured at the point of common coupling (PCC) of ac and dc electric arc furnace facilities. [ABSTRACT FROM AUTHOR]

Presents an implementation of a stochastic Extended Kalman Filter algorithm, which provides optimal estimates of interconnected network states for power systems in which some or all measurements are delayed. Problem statement and formulation; Test results and discussion; Conclusion.