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Dielectric testing techniques, in both time and frequency domains, are currently widely used by power utilities for assessment of the condition of transformer oil-paper insulation systems. However, it has been reported that results of these tests are highly influenced by the operating temperature during measurements. The distribution, migration and equilibrium of moisture between oil and paper in a complicated insulation system is highly temperature dependent. It requires adequate experience and proper understanding to interpret the dielectric response results in the presence of temperature variations and thermal instability. Proper analysis of the dielectric test result is only possible with an understanding of the physical behavior of the insulation system in response to temperature. A circuit model, which describes the dielectric behavior of the transformers main insulation system, has been investigated in this paper. The values of the parameters of the model have been identified from the dielectric tests. A correlation has been observed between the operating temperature and the equivalent model parameters that can be used as additional information for better interpretation of the dielectric test results. This paper thus reports a detailed study on the effects of temperature on dielectric measurements of a transformer under controlled laboratory conditions. Some results of practical on-site testing are also presented to demonstrate the possibility of errors that may be introduced in dielectric test results analysis unless temperature effects are taken into consideration. [ABSTRACT FROM AUTHOR]

In interconnected power systems, operated by several system operators, the participating areas are strongly dependent on their neighbors. In order to identify the economically efficient generation dispatch in each area, a distributed multi-area optimal power flow (OPF) must be solved. Additionally, installation of an increasing number of HVDC lines to deal with increased power flows from renewable generation is expected to change the power system operation paradigm. The controllability introduced by the HVDC lines should be considered and incorporated in the OPF algorithm. In this paper we introduce a formulation for the distributed solution of the OPF problem in multi-area systems consisting of both HVAC and HVDC lines. We show the applicability of this formulation on two different operating schemes for HVDC grids and we compare their performance with a central solution for the mixed HVAC/HVDC grid. The proposed formulations are based on a linearized solution of the OPF problem. The only data to be exchanged between the areas pertains to the border nodes. [ABSTRACT FROM AUTHOR]

Load profile classification is very important in load forecast, planning and management. Although customers are generally grouped by utilities into residential, commercial classes and respective subclasses, there is a lack of systematic framework that can be used to characterize different classes with signatures that are both human-readable and machine-readable. The work presented in this paper attempts to formulate the theoretical framework for customer classification using the annual load profiles. This paper demonstrates how to extract characteristic attributes in frequency domain (CAFD) and use these CAFDs to formulate a hierarchy of load profiles that can be used as the systematic framework for customer load classification. As signatures for customer classes and subclasses, the CAFDs are obtained by using a data mining method called CART (classification and regression tree). The paper presents a load profile classification test to establish the efficacy of the proposed approach which is significant improvement over current practices that provide mostly qualitative labeling. [ABSTRACT FROM AUTHOR]

Presents a series of classified lists of power system relaying references from 1927 to 1999. References to the subjects of service; Publication of Electrical and Electronics Abstracts; Presentation of relaying algorithms.

This paper proposes a control-oriented energy function (COEF) based on passivity for transient stability control (TSC) of power systems and investigates the feasibility of an iterative process using the COEF for determining generation shedding (GS) requirements for real-time TSC, in particular, for severe cases when autoreclosing fails due to permanent faults. The COEF for TSC set up in this paper gives directly the GS requirement without calculations of stability region and Critical Clearing Time, and exempts all modeling assumptions except for nonnegative damping the generator models. The simulation with the full planning model of Western Electricity Coordinating Council system shows that the passivity-based COEF for TSC offers a concise, practical, and effective index for GS determination for transient stability control of power systems, which is particularly suitable for the Remedial Action Schemes that BC Hydro has been using. [ABSTRACT FROM AUTHOR]

This paper will describe the influence of mesh geometry on the homogeneity of discharges, power, and efficiency of ozone generation. Homogeneous discharges increase the efficiency of the generation of ozone. Geometry of mesh electrodes affects the power and type of discharges, concentration, and efficiency of the ozone generation. The analysis of selected results indicates the need for the use of mesh electrodes with a small cross section at least $0.1\times0.1$ mm2 mesh to obtain a homogeneous discharge. The mechanism by which the geometry of mesh electrodes on the homogeneity of discharge is illustrated in this paper. Homogeneous discharges increase the efficiency of the generation of ozone that reduces the cost of ozone production. The results of the experimental studies show an increase in the average efficiency of 60% of the ozone generation and a 20% reduction in the demand for power with the constant concentration of ozone, justifies the problem. [ABSTRACT FROM AUTHOR]

Within power generation, aging assets and an emphasis on more efficient operation of power systems and improved maintenance decision methods has led to a growing focus on asset prognostics. The main challenge facing the implementation of successful asset prognostics in power generation is the lack of available run-to-failure data. This paper proposes to overcome this issue by use of full-scope high-fidelity simulators to generate the run-to-failure data required. From this simulated failure data a similarity-based prognostic approach is developed for estimating the remaining useful life of a valve asset. Case study data is generated by initializing prebuilt industrial failure models within a 970 MW pressurized water reactor simulation. Such full-scope high-fidelity simulators are mainly operated for training purposes, allowing personnel to gain experience of standard operation as well as failures within a safe, simulated operating environment. This paper repurposes such a high-fidelity simulator to generate the type of data and affects that would be produced in the event of a fault. The fault scenario is then run multiple times to generate a library of failure events. This library of events was then split into training and test batches for building the prognostic model. Results are presented and conclusions drawn about the success of the technique and the use of high-fidelity simulators in this manner. [ABSTRACT FROM AUTHOR]

Because of the predicted shortage of fossil fuels in the future, public interest in utilizing solar energy for photovoltaic (PV) electricity has exponentially increased in recent years. In particular, interest in the building integration of PVs is growing worldwide, and the use of building-integrated PVs (BIPVs) is one of the fastest growing segments of the PV industry. Luminescent solar concentrators (LSCs) are one of the possible approaches for BIPVs. However, the high cost and poor stability of the dyes or quantum dots used in conventional LSCs prevent the widespread adoption of electricity generation through the LSC-based solar energy. Therefore, inorganic phosphors with long lifetime and photostability under ultraviolet (UV) excitation and moisture are favorable luminescent materials for LSCs. In this paper, thin-film LSCs using commercial inorganic phosphors are proposed. The thin-film LSCs with different inorganic phosphors were examined. The phosphor concentration and relative position of the thin phosphor layer were investigated to determine the suitable structure of a thin-film LSC. This paper aimed to achieve an understanding of thin-film LSCs by using inorganic phosphors and to provide useful guidelines for future commercialization. [ABSTRACT FROM AUTHOR]

The paper addresses the problem of determining the maximum distributed energy resource (DER) capacity that can be connected to low-voltage (LV) networks without creating voltage-rise problems. That maximum capacity depends on the network characteristics and on the candidate sites for DER connection. When sites are multiple and LV networks are poorly characterized, such maximum capacity cannot be determined with power-flow or other admittance-matrix-based approaches. This paper proposes an approach to estimate voltage rise caused by DER under reduced network characterization. Such approach is built upon customary voltage and impedance measurements to be made at the sites of DER injection and gives sufficiently accurate results under most practical situations. The paper validates the accuracy of the proposed approach against exact power-flow results for well-characterized networks and load situations and provides guidelines for DER connection based on maximum capacity nodal allocation. [ABSTRACT FROM PUBLISHER]

This paper presents a new security-constrained multiobjective optimal dispatch (SC-MOOD) framework for an economic and reliable operation of microgrids. The framework is developed based on a computationally effective multiobjective optimization technique, Pareto concavity elimination transformation (PaCcET). The new method considers grid steady-state and dynamic constraints while solving the optimal dispatch in both grid-connected and islanded modes. The constraints consist of power balance, voltage magnitude, line flows, power generation, frequency, and voltage transients. The proposed framework finds the most economic operating solutions to not only minimize the generation cost but also minimize the reliability cost. In this paper, the PaCcET is utilized to solve the SC-MOOD. The PaCcET uses an extraordinary transformation to first transfer all the points from a multiobjective space to a transformed objective space. It then solves a linear combination of transformed objectives using a single-objective optimizer to find all the nondominated points of the original multiobjective space. The performance of the new framework is verified using the simulation results in a microgrid with several distributed energy resources in both grid-connected and islanded modes. The results are then compared with two multiobjective optimization techniques, nondominated sorting genetic algorithm II and multiobjective particle swarm optimization, as two well-known benchmarks. [ABSTRACT FROM AUTHOR]

Renewable energy production is constantly growing worldwide, and some countries produce a relevant percentage of their daily electricity consumption through wind energy. Therefore, decision support systems that can make accurate predictions of wind-based power production are of paramount importance for the traders operating in the energy market and for the managers in charge of planning the nonrenewable energy production. In this paper, we present a decision support system that can predict electric power production, estimate a variability index for the prediction, and analyze the wind farm (WF) production characteristics. The main contribution of this paper is a novel system for long-term electric power prediction based solely on the weather forecasts; thus, it is suitable for the WFs that cannot collect or manage the real-time data acquired by the sensors. Our system is based on neural networks and on novel techniques for calibrating and thresholding the weather forecasts based on the distinctive characteristics of the WF orography. We tuned and evaluated the proposed system using the data collected from two WFs over a two-year period and achieved satisfactory results. We studied different feature sets, training strategies, and system configurations before implementing this system for a player in the energy market. This company evaluated the power production prediction performance and the impact of our system at ten different WFs under real-world conditions and achieved a significant improvement with respect to their previous approach. [ABSTRACT FROM AUTHOR]

Recurrence quantification analysis (RQA) is a nonlinear data analysis technique that can quantify the number and duration of a dynamical system of being in nearly the same area in phase space trajectory. This paper proposes three applications of RQA to analyse power system dynamics. These are denoising of PMU data, localization of power system events, and transient stability contingency ranking of power system. All three applications have been demonstrated using a multimachine test system. [ABSTRACT FROM AUTHOR]

This paper presents theoretical and experimental discussions on low-voltage-ride-through operation of a modular multilevel single-delta bridge-cell (SDBC) inverter intended for utility-scale photovoltaic (PV) systems. Modern grid codes require grid-tied inverters to provide dynamic grid support during grid-fault events by injecting reactive current. This paper discusses decoupled positive- and negative-sequence reactive-current control, focusing on asymmetric voltage sags with imbalanced magnitude and phase relationships. The main objective is to present a feedforward control method based on calculation of the zero-sequence current required for achieving power balance during normal and grid-fault conditions. Moreover, this paper demonstrates a practical method that minimizes overcurrent stress in the three inverter clusters by adjusting active power drawn from PV arrays. Experimental results on a three-phase 12.6-kVA system prove that the SDBC inverter is capable of seamlessly operating through asymmetric voltage sags. [ABSTRACT FROM AUTHOR]

In this paper, dynamic performance of automatic generation control (AGC) of two area thermal–thermal power system is determined through the steam chest and reheater constant trajectories. In earlier AGC studies, steam chest and reheater time constants denoted as T\text{SC} and T\text{RH} are considered to be constant, irrespective of plant generation schedules. However, it is discovered that T\text{SC} and T\text{RH} follow the specific trajectories with the plant generation schedules. These time constant trajectories are determined by the power output control strategies being employed to change the plant generation schedules. These control strategies are the different combinations of steam pressure versus flow rate curves used to operate the plant at different generation schedules. In this paper, time constant versus generation schedule trajectories of T\text{SC} and T\text{RH} have been derived for different power output control strategies. Furthermore, these time constant trajectories have been utilized to investigate the dynamic performance of two area reheat thermal power system. [ABSTRACT FROM AUTHOR]

This paper demonstrates that machine learning can be used to create effective algorithm selectors that select between power system control algorithms depending on the state of a network, achieving better performance than always using the same algorithm for every state. Also presented is a novel method for creating algorithm selectors that consider two objectives. The method is used to develop algorithm selectors for power flow management algorithms on versions of the IEEE 14- and 57-bus networks, and a network derived from a real distribution network. The selectors choose from within a diverse set of power flow management algorithms, including those based on constraint satisfaction, optimal power flow, power flow sensitivity factors, and linear programming. The network state-based algorithm selectors offer performance benefits over always using the same power flow management algorithm for every state, in terms of minimizing the number of overloads while also minimizing the curtailment applied to generators. [ABSTRACT FROM AUTHOR]

Power generators contain control systems that are able to regulate system frequency, but the frequency setpoint values are rarely modified from nominal values. This paper describes design considerations for a communication system from generators to frequency-sensitive distributed energy resources (FS-DER) using changes to frequency setpoint values of generators. Signaling discrete system states by generating off-nominal system frequency values can be used as a novel narrowband unidirectional broadcast communications channel. This paper describes two protocols for utilizing off-nominal frequencies to carry information: First, a protocol for dispatching blocks of FS-DER that is suitable for systems restricted to relatively slow rates of change of frequency (ROCOF). Second, for systems that allow higher ROCOF values, the feasibility of using power generation resources as a power-line communication transmitter is shown. Data from an operating islanded power system with diesel generators are analyzed to demonstrate the feasibility of the proposed communication system in systems fed by rotating machines. The feasibility of the proposed communication system in systems fed by voltage-source inverters is shown with laboratory tests of a 20-kVA inverter. The inverter was found to have a maximum ROCOF of 2.2 Hz/s, sufficient to enable its use as a power-line communication transmitter. [ABSTRACT FROM AUTHOR]

In this paper, the class-J mode of operation is investigated when sinusoidal, half-sinusoidal (HS), triangle, pulse, and reduced conduction angle voltage waveforms are shaped at the gate node of the transistor. Output power, maximum power-added efficiency (PAE), large signal gain (LSG), and load–pull contours are presented and compared for each input signal. It is shown that PAE of a class-J power amplifier (PA) is improved when an HS voltage is realized at the gate node of the transistor. This enhancement can also be observed for a pulse input with 20% duty cycle, however, at the expense of reduced output power and LSG. A proof-of-concept, two-stage class-J PA is designed and fabricated in a 0.25- \mu \textm AlGaAs-InGaAs pHEMT technology. The prototype PA is based on an HS gate voltage for the second-stage transistor, which operates in class-J mode. The driver stage also works in class-J mode to provide an HS voltage at its drain node, and the interstage matching network is designed to convey this waveform to gate of the second-stage transistor. Chip dimensions are $1.99\times1.24$ mm2, and 26.6–27.2-dBm output power with ≥50% PAE is achieved over the 0.92–1.4-GHz bandwidth. [ABSTRACT FROM PUBLISHER]

Silicon photovoltaics are prospective candidates to power mm-scale implantable devices. These applications require excellent performance for small-area cells under low-flux illumination condition, which is not commonly achieved for silicon cells due to shunt leakage and recombination losses. Small area (1–10 mm ^2 ) silicon photovoltaic cells are studied in this paper, where performance improvements are demonstrated using a surface n-type doped emitter and Si3N4 passivation. A power conversion efficiency of more than 17% is achieved for 660-nW/mm2 illumination at 850 nm. The silicon cells demonstrate improved power conversion efficiency and reduced degradation under low illumination conditions in comparison with conventional crystalline silicon photovoltaic cells available commercially. [ABSTRACT FROM PUBLISHER]

Due to uncertainties in generation and load, optimal decision making in electrical energy markets is a complicated and challenging task. Participating agents in the market have to estimate optimal bidding strategies based on incomplete public information and private assessment of the future state of the market, to maximize their expected profit at different time scales. In this paper, we present an agent-based model to address the problem of short-term strategic bidding of conventional generation companies (GenCos) in a power pool. Based on the proposed model, each GenCo agent develops a private probabilistic model of the market (using dynamic Bayesian networks), employs an online learning algorithm to train the model (sparse Bayesian learning), and infers the future state of the market to estimate the optimal bidding function. We show that by using this multiagent framework, the agents will be able to predict and adapt to approximate Nash equilibrium of the market through time using local reasoning and incomplete publicly available data. The model is implemented in MATLAB and is tested on four test case systems: two generic systems with 5 and 15 GenCo agents, and two IEEE benchmarks (9-bus and 30-bus systems). Both the day-ahead (DA) and hour-ahead (HA) bidding schemes are implemented. The results show a drop in market power in the 15-agent system compared to 5-agent system, along with a Pareto superior equilibrium in the HA scheme compared to the DA scheme, which corroborates the validity of the proposed decision making model. Also, the simulations show that introduction of an HA decision making stage as an uncertainty containment tool, leads to a more stable and less volatile price signal in the market, which consequently results in flatter and improved profit curves for the GenCos. [ABSTRACT FROM PUBLISHER]

Currently, power system planning practices are undergoing various transformations in an attempt to integrate efficiently significant amounts of low-carbon power generation technologies. At the heart of this efficient integration lies the need to plan for and exploit the available flexibility in power systems. In the past, the emphasis was on planning the capacity (i.e., power) of operating reserve requirements, in the form of categorized reserve types. Such approach was suitable for traditional power systems exhibiting low variability and uncertainty. The concept of power system flexibility is emerging as a way to emphasize the need to also consider the ramping capability of operating reserve needed to accommodate high variability and uncertainty arising from renewable energy integration. Prior considerations of power system flexibility, however, are found to be inadequate to handle energy-limited power system resources like energy storage assets and demand response. Hence, this paper sets to consider systematically energy limitations of operating reserve by proposing energy-based operating reserve definitions. We demonstrate the benefits of the new reserve definitions, using a receding-horizon economic dispatch integrating energy storage. [ABSTRACT FROM PUBLISHER]

In this paper, the mathematical model of an electricity generator with four static magnets and four dynamic magnets is suggested for the electricity generation. The introduced electricity generator is based on the electricity generator with two static magnets and two dynamic magnets, but it has three main advantages: it has more interactions between the static and dynamic magnets, it generates more electricity, and it generates smoother signals. Electricity generators are compared for the electricity generation. [ABSTRACT FROM AUTHOR]

This paper presents a new approach for reliability evaluation of composite power systems by combining Monte Carlo simulation and multi label k-nearest neighbor (MLKNN) algorithm. MLKNN is a classification technique in which target vector of each instance is assigned into multiple classes. In this paper, MLKNN is used to classify states (failure or success at system or bus level) of a complete power system without requiring optimal power flow (OPF) analysis, except in the training phase. As a result, the computational burden to perform OPF is reduced dramatically. For illustration, the proposed method is applied to the IEEE 30 BUS Test System and IEEE Reliability Test System. The obtained results from various case studies demonstrate that MLKNN based reliability evaluation provides promising results in both classification accuracy and computation time in evaluating the composite power system reliability. [ABSTRACT FROM AUTHOR]

The co-optimization of security-constrained unit commitment and dispatchable transmission network is a large-scale and computationally complex optimization problem that brings big challenges for the traditional centralized and/or master–slave based decomposition approaches. This paper proposes a fully parallel approach to achieve an efficient and fast solution while considering post-contingency corrective actions. In this paper, the original co-optimization problem is decomposed into six major solution modules for unit commitment, optimal power flow, and transmission switching in base case and contingencies, respectively. Moreover, each major solution module is further decomposed by unit, period, dispatchable line, and/or contingency to make the proposed approach favorable in a fully parallel computing environment. The effectiveness and efficiency of the proposed fully parallel approach are justified using numerical cases on a high-performance computing (HPC) platform. [ABSTRACT FROM AUTHOR]

In this paper, a past-aware state estimation (PASE) method (for static state estimation) is proposed for power distribution systems, which takes previous estimates into account to improve the accuracy of the current one, using an Ensemble Kalman Filter (EnKF). Fewer phasor measurements units are needed to achieve the same estimation error target than snapshot-based methods. Furthermore, contrary to existing methods, the proposed approach does not embed power flow equations into the state estimator, thus making it a versatile technique. The theoretical formulation of the EnKF-based PASE presented in the paper has been validated considering a 33-bus distribution system and using power consumption traces from real households. [ABSTRACT FROM AUTHOR]

The development of medium-/long-term studies for power-system operation and planning under the uncertainty of renewable generation is a key challenge faced by power-system agents worldwide. There is a vast literature on stochastic optimization models devoted to addressing the relevant issues on both operation and planning applications. Notwithstanding, few papers focus on addressing the gaps within the subject of joint scenario generation despite the high sensibility of stochastic optimization models with regard to their input scenarios. Characterizing wind power generation (WPG) stochastic processes to devise time- and spatial-dependent scenarios, based on simulation procedures, for time horizons of one to a few years is a difficult task. Multiple regimes and non-Gaussian distributions are two of the main issues that significantly change the risk described through generated scenarios. In this paper, a new methodology to simulate long-term joint scenarios for multivariate WPG time series is presented. The proposed framework, known as generalized auto regressive score models, is derived based on a new class of time-series model with time-varying parameters and an arbitrary non-Gaussian distribution. Our case study shows, based on real data from the Brazilian power system, that the proposed methodology is capable of producing scenarios with coherent temporal and spatial dependence that are needed in power system studies. [ABSTRACT FROM AUTHOR]

To encourage and support innovation, synthetic electric grids are fictional, designed systems that mimic the complexity of actual electric grids but contain no confidential information. Synthetic grid design is driven by the requirement to match wide variety of metrics derived from statistics of actual grids. In order to scale these systems to 10,000 buses or more, robust reactive power planning is needed, accounting for power flow convergence issues. This paper addresses reactive power planning and power flow convergence in the context of large synthetic power grids. The iterative algorithm presented by this paper supplements a synthetic transmission network that has been validated by a dc power flow with a realistic set of voltage control devices to meet a specified voltage profile, even with the constraints of difficult power flow convergence for large systems. The algorithm is illustrated with an example new synthetic 10,000 bus system, geographically situated in the western United States, which is publicly available and useful for a variety of research studies. An analysis is shown validating the synthetic system with actual grid characteristics. [ABSTRACT FROM AUTHOR]

This paper proposes a fast dc short-circuit fault detection method for HVdc grids, which relies on the voltage across the dc fault-current-limiting reactor. In the proposed approach, primary detection uses only the single-terminal dc reactor voltage information and is shown to be able to identify the faulted line as well as the faulted pole within 1 ms. The backup detection is primarily required for high resistance faults and uses communication between the two sides of the line. Its speed is dependent on the travel time of signals between the two ends, but will operate, as shown in the paper, typically in 2 ms or less. The approach is justified using analytical calculations and exhaustively validated via electromagnetic transient simulation for pole-to-pole and pole-to-ground faults, different fault resistance, fault locations, and dc reactor values. The validation shows that the method is able to identify all genuine dc line faults, but is not prone to misoperation with ac line faults, different loading levels, and so on. [ABSTRACT FROM AUTHOR]

This paper presents an algorithm for the economical design of a utility-scale photovoltaic (PV) power plant via compromising between the cost of energy and the availability of the plant. The algorithm inputs are the plant peak power and the price of inverters with respect to their power ratings. The outputs are the optimum inverter ratings and the interconnection topology of PV panels. This paper introduces the effective levelized cost of energy (LCOE) (ELCOE) index as the core of the proposed design algorithm. ELCOE is an improved index based on the conventional LCOE that includes the availability of a power plant in economical assessments. The conventional LCOE index determines centralized topology (e.g., 1-MW inverter for a 1-MW PV power plant) for minimizing the energy generation cost, whereas based on ELCOE, a multistring topology (e.g., a 1-MW PV plant consists of fifty 20-kW inverters) despite of higher investment cost becomes the economically winning topology. Given the price of commercially available PV inverters at present, the case studies in this paper show that, for 0.1–100-MW PV power plants, the economical ratings of inverters range from 8 to 100 kW. The recently installed PV power plants confirm the feasibility of the calculations based on the suggested algorithm. [ABSTRACT FROM PUBLISHER]

Slotless permanent magnet machines are attractive in some modern drive and power generation fields, where the cogging torque and additional losses need to be minimized or removed. The stator slotless design can be combined with different surface permanent magnet (SPM) rotor topologies. In this paper, explicit analytical expressions are derived to analytically compute the slotless machine torque and no-load back Electro-Motive Force in the case of segmented SPM rotor with parallel, radial, or Halbach-array magnetization patterns. The expressions are found by solving the magnetic field due to the slotless stator winding and to the permanent magnet blocks; the latter modeled through equivalent surface current densities. The accuracy of the method is successfully assessed by comparison with the finite-element analysis (FEA). The proposed formulas are an effective alternative to the FEA to quickly compare different design solutions as well as to optimize them. Application examples are provided in which the presented method is adopted to define the machine cross section that maximizes the torque density. [ABSTRACT FROM PUBLISHER]

This paper focuses on the zero-voltage ride-through (ZVRT) capability of a transformerless back-to-back (BTB) system intended for installation on a power distribution system with many distributed power generators. The BTB system consists of two modular multilevel cascade converters based on double-star chopper cells (MMCC-DSCC) and their ac sides are connected to a common ac mains via ac-link inductors. This paper provides an experimental discussion on the DSCC-based BTB system under voltage sags by using a three-phase 200-V 10-kW downscaled system. Experimental results show that the BTB system is equipped with ZVRT capability without causing any overvoltage and/or overcurrent even under the most severe voltage sags. [ABSTRACT FROM PUBLISHER]

This paper provides a theoretical discussion and comparison in energy balancing between a modular multilevel cascade inverter based on single-star bridge cells (SSBC) and that on single-delta bridge cells (SDBC). Attention is paid to applications involving asymmetric active-power generation in utility-scale grid-tied photovoltaic systems. Both qualitative and quantitative evaluation metrics to assess the energy-balancing capability are introduced and applied to both SSBC and SDBC inverters. As for the SSBC inverter, six zero-sequence voltage waveforms with different harmonic content enabling enhanced energy-balancing capability are analyzed and compared regarding their effectiveness. This paper also emphasizes on the SDBC as an alternative to the SSBC and highlights its superior operating characteristics under asymmetric active-power generation. [ABSTRACT FROM PUBLISHER]

Large power consumers often have on-site generation. If the utility tie opens, it is essential to isolate the on-site generators to prevent generator equipment damage before the utility attempts to reclose in a possible out-of-synchronism condition. Typically, islanding detection schemes are used to detect this condition and disconnect on-site generation quickly, thereby allowing successful utility reclose. This paper introduces a reliable islanding detection solution that was proposed, implemented, and tested at a refinery in Texas. The facility houses two on-site generators and is interconnected to the utility via a looped system. A topology-based islanding detection scheme was originally installed at this facility but was later decommissioned because of difficulties in adapting to evolving topology changes. Following an undesirable event in the utility system that could have resulted in damage to the refinery on-site generator equipment, the refinery decided to implement an islanding detection scheme that is independent of system topology changes and only relies on local-area measurements. However, the dependability of a traditional local measurement-based scheme is vulnerable to the dynamic generation–load mismatch, making it possibly unreliable. This paper describes a solution using a redundant high-speed multiprinciple islanding detection scheme that incorporates a unique voting supervision logic to achieve security. [ABSTRACT FROM AUTHOR]

Recent years have witnessed significant interest in convex relaxations of the power flows, with several papers showing that the second-order cone relaxation is tight for tree networks under various conditions on loads or voltages. This paper shows that ac-feasibility, i.e., to find whether some generator dispatch can satisfy a given demand, is NP-hard for tree networks. [ABSTRACT FROM AUTHOR]

This paper proposes an efficient solution approach based on Benders’ decomposition to solve a network-constrained ac unit commitment problem under uncertainty. The wind power production is the only source of uncertainty considered in this paper, which is modeled through a suitable set of scenarios. The proposed model is formulated as a two-stage stochastic programming problem, whose first-stage refers to the day-ahead market, and whose second-stage represents real-time operation. The proposed Benders’ approach allows decomposing the original problem, which is mixed-integer nonlinear and generally intractable, into a mixed-integer linear master problem and a set of nonlinear, but continuous subproblems, one per scenario. In addition, to temporally decompose the proposed ac unit commitment problem, a heuristic technique is used to relax the inter-temporal ramping constraints of the generating units. Numerical results from a case study based on the IEEE one-area reliability test system (RTS) demonstrate the usefulness of the proposed approach. [ABSTRACT FROM AUTHOR]

Emerging smart-grid-enabling technologies will allow an unprecedented degree of observability and control at all levels in a power system. Combined with flexible demand and storage, they could allow procuring energy at minimum cost and environmental impact. That however presupposes real-time coordination of demand of individual households and industries down at the distribution level, with generation at the transmission level. This is closely related with the balancing market economic dispatch (ED) problem, which currently does not take into account distribution network constraints and flexible demand characteristics. Still, assuming a suitably modified form of that problem was available, due to both computational and communications requirements, its centralized solution in its full detail would not be tractable. While there is currently a wealth of literature dealing with distributed optimization applications in power systems, it typically focuses on smaller parts of the overall energy management problem (e.g., transmission area synchronization or electric vehicles management) often without considering its full scale or establishing any association with energy market mechanisms. The target of this paper is twofold: 1) identify a flexible demand and distribution network inclusive formulation for ED and 2) propose a solution method. [ABSTRACT FROM AUTHOR]

This paper presents a method that in real-time determines remedial actions, which restore stable operation with respect to aperiodic small signal rotor angle stability (ASSRAS) when insecure or unstable operation has been detected. An ASSRAS assessment method is used to monitor the stability boundary for each generator in real-time. The ASSRAS boundary represents the condition when a generator reaches the maximum steady state active power injection. The proposed control method exploits analytically derived expressions for the ASSRAS boundary and other characteristic curves in the injection impedance plane to determine an active power redispatch among selected generators to restore stable and secure operation. Since the method is purely based on analytically derived expression, the computation of the remedial actions is fast and well suited for real-time operation. The method was tested on the IEEE 14-bus and the Nordic32 test systems where results show that the method can efficiently determine the required active power redispatch to avoid an imminent instability. [ABSTRACT FROM AUTHOR]

This paper proposes a novel comprehensive operation and self-healing strategy for a distribution system with both dispatchable and nondispatchable distributed generators (DGs). In the normal operation mode, the control objective of the system is to minimize the operation costs and maximize the revenues. A rolling-horizon optimization method is used to schedule the outputs of dispatchable DGs based on forecasts. In the self-healing mode, the on-outage portion of the distribution system will be optimally sectionalized into networked self-supplied microgrids (MGs) so as to provide reliable power supply to the maximum loads continuously. The outputs of the dispatchable DGs will be rescheduled accordingly too. In order to take into account the uncertainties of DG outputs and load consumptions, we formulate the problems as a stochastic program. A scenario reduction method is applied to achieve a tradeoff between the accuracy of the solution and the computational burden. A modified IEEE 123-node distribution system is used as a test system. The results of case studies demonstrate the effectiveness of the proposed methodology. [ABSTRACT FROM PUBLISHER]

HVDC technologies are widely acknowledged as one of solutions for the interconnection of renewable energy resources with the main electric power grid. The application of the latest modular multi-level converter (MMC) makes power conversion much more efficient. Due to the relatively low impedance in a DC system, DC fault currents may rise to an extremely high level in a short period of time, which can be very dangerous for HVDC converters. To improve the sustainability and security of electricity transmission, protection solutions for HVDC systems are being developed. Nevertheless, they have various drawbacks on fault signal detection and timely clearance. This paper proposes a protection method that provides a fast and reliable solution addressing those drawbacks. A protection algorithm based on travelling wave simulation and analysis is proposed to detect abrupt transient signals. The algorithm shows high efficiency, reliability, selectivity and has low sampling frequency requirements. The proposed protection method has been validated through a cyber-physical simulation platform, developed using a real-time digital simulator (RTDS) and IEC 61850 communication links. The obtained results show that the proposed method has good potential for practical applications. [ABSTRACT FROM AUTHOR]

This paper is to evaluate the presented model in part I for bidding strategy of virtual power plant (VPP) with centralized control in a joint market of energy and spinning reserve service. Two test VPPs are introduced and different scenarios are considered for markets prices. At first, the participation of VPP in only energy market is studied. Then, the spinning reserve market is taken into consideration and the bids of VPP in a joint market of energy and spinning reserve service is studied under different scenarios of markets prices and the results are analyzed. In all cases, the results show the effectiveness and the quality of the procedure and validate the proposed model. [ABSTRACT FROM PUBLISHER]

In this paper, the control of a grid-connected wind energy conversion system (WECS), based on an induction machine fed by a matrix converter (MC), is presented. The MC is controlled using a space vector modulation algorithm with zero displacement factor at the input. Stability issues related to the operation of the WECS for the whole power and speed range are fully analyzed in this paper, using a simplified small-signal model. The implementation of a model reference adaptive system (MRAS) observer, for sensorless control of the proposed WECS, is also presented in this paper. The MRAS observer is implemented using the output voltage demand, avoiding the use of voltage transducers to measure the machine voltage. From the speed estimated by the MRAS observer, the electrical torque of the induction generator is regulated in order to drive the WECS to the operating point where the aerodynamic efficiency is maximized. Experimental results obtained with a 2.5-kW prototype are presented and fully discussed in this paper. [ABSTRACT FROM PUBLISHER]

This paper analyzes the feasibility of optimally utilizing Ontario's grid potential for charging plug-in hybrid electric vehicles (PHEVs) during off-peak periods. Based an a simplified zonal model of Ontario's electricity-transmission network and a zonal pattern of base-load generation capacity from 2009 to 2025, an optimization model is developed to find the optimal, as well as maximum, penetrations of PHEVs into Ontario's transport sector. The results of this paper demonstrate that the present and projected electricity grid in Ontario can be optimally exploited for charging almost 6% of the total vehicles in Ontario or 12.5% of the vehicles in Toronto's transport sector by 2025; this corresponds to approximately 500 000 PHEVs that can be charged from the grid without any additional transmission or power-generation investments beyond those currently planned. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of a multiyear security constrained hybrid generation-transmission expansion planning. It is assumed that the overall generation requirements of a network are known along the planning horizon, but their allocations are unknown. Moreover the fuel cost throughout the net- work is not uniform. By allocating the overall generation capacity among the grid nodes, and determining the new transmission element additions along the planning horizon, the overall cost of the system is minimized. The problem is formulated as a mixed integer nonlinear programming problem, which for a large-scale system is very difficult to solve. In this paper a new constructive heuristic approach is proposed, so that the problem can be readily solved. To assess the capabilities of the proposed approach, two networks are studied: the Garver test grid as a small grid and the Iranian power grid as a large-scale grid. [ABSTRACT FROM AUTHOR]

Intentional islanding operation of distributed generation (DG) can increase system reliability and reduce customer outage costs. Guidelines for the impact study and operation of DG for islanding operation should be implemented. The Provincial Electricity Authority (PEA) plays more attention to intentional islanding operation. To perform islanding operation, PEA has established islanding operation and impact study guidelines for DG. This paper presents the development of these guidelines. A case study was conducted to demonstrate the results of both steady-state and dynamic analyses. Operational issues are also taken into account in this paper. [ABSTRACT FROM AUTHOR]

This paper proposes a new filter design method that can smooth the wind power generation output while keeping the energy capacity and power rating of the energy storage system (ESS) small. Wind power generation causes frequency fluctuations in power systems. Therefore, in many cases, the ESS is needed for smoothing the fluctuations of wind generator output. In order to improve the performance of the ESS controlled with the conventional low-pass filter (LPF), this paper investigates other types of filters. First, the relations between filter and energy capacity/power rating of the ESS are disclosed through the worst-case study. Then, the frequency fluctuation analysis of the power system with respect to the wind power generation is carried out in order to realize a pin-point smoothing. Finally, a metaheuristic optimization method is proposed for the multiobjective design of the filter based on these relations so as to achieve an optimal tradeoff between the output smoothing and energy capacity/power rating of the ESS. It is shown via simulation analysis with real wind data that the proposed method can suppress the frequency fluctuation of the power system effectively with the ESS having smaller energy capacity and power rating. [ABSTRACT FROM PUBLISHER]

In hydroelectric power plants, which are characterized by particularly high short-circuit current levels and high time constants, conventional current transformer specifications can result in increased equipment dimensions, thus complicating their installation, especially during refurbishment projects. This paper presents a study to assess the potential of various low-power instrument transformers (LPITs) for generator protection applications. Two types of LPITs were evaluated: the optical current transformer (OCT) and the stand alone merging unit (SAMU). To test the OCT, a 65-kA-peak test source was developed using a real-time simulator. This source was used to inject symmetrical and asymmetrical currents into LPITs for the assessment of protection accuracy class. Low-current tests were also performed to assess their metering classes. This paper presents the design of a high-current test bench, measurement uncertainty analysis, and analysis algorithms used for device evaluation. Analysis results are then presented and discussed in terms of their applicability to generator differential protection using SAMUs and OCTs. [ABSTRACT FROM AUTHOR]

This paper analyzes the benefits of dynamic line rating (DLR) in the system with high penetration of wind generation. A probabilistic forecasting model for the line ratings is incorporated into a two-stage stochastic optimization model. The scheduling model, for the first time, considers the uncertainty associated with wind generation, line ratings, and line outages to co-optimize the energy production and reserve holding levels in the scheduling stage as well as the redispatch actions in the real-time operation stage. Therefore, the benefits of higher utilization of line capacity can be explicitly balanced against the costs of increased holding and utilization of reserve services due to the forecasting error. The computational burden driven by the modeling of multiple sources of uncertainty is tackled by applying an efficient filtering approach. The case studies demonstrate the benefits of the DLR in supporting cost-effective integration of high penetration of wind generation into the existing network. We also highlight the importance of simultaneously considering the multiple sources of uncertainty in understanding the benefits of DLR. Furthermore, this paper analyzes the impact of different operational strategies, the coordination among multiple flexible technologies, and the installed capacity of wind generation on the benefits of DLR. [ABSTRACT FROM PUBLISHER]

This paper aims at providing a novel techno-economic flexibility index to quantify the relative flexibility of different conventional generation technologies. The proposed measure takes into account a comprehensive set of technical flexibility characteristics of generation units including minimum stable generation level, operating range, minimum up/down times, and ramp up/down capability. The impact of various technical parameters on the flexibility restriction is determined based on the additional costs imposed to the system operator in order to satisfy that constraint. Afterward, the calculated flexibility index is incorporated into day-ahead market clearing procedure as a new objective function beside operation cost using a multiobjective decision-making approach. Simulation results show that the need of different flexibility levels changes the optimal generation dispatch and results in different operation costs. Furthermore, the impact of two emerging flexible options, i.e., bulk energy storages and a typical demand response program in the flexibility contribution of other generation technologies is also investigated. The results reveal that the integration of emerging flexible options frequently changes the flexibility share of conventional units and can provide the required flexibility level at a lower cost. [ABSTRACT FROM AUTHOR]

A basic principle of electricity market design is that cost allocation should follow cost causation as closely as possible. As renewable resources play a larger role in electricity generation, system operators have become increasingly concerned about costs related to variability in net load. While variable generation resources have attracted a great deal of attention along these lines, load is a larger source of variability in most systems. This paper introduces a Shapley value framework to assess the total system cost attributable to electricity market participants that either exacerbate or alleviate net load variability. Furthermore, this paper investigates the extent to which these costs are adequately reflected in wholesale market prices. Numerical tests indicate that the cost of variability on the hourly time scale is in most cases internalized by market-integrated generators and buyers, mitigating concerns that variability imposes a socialized cost from ramping or cycling of thermal generators. [ABSTRACT FROM PUBLISHER]

As electric power system operators shift from conventional energy to renewable energy sources, power distribution systems will experience increasing fluctuations in supply. These fluctuations present the need to not only design online decentralized power allocation algorithms, but also characterize how effective they are given fast-changing consumer demand and generation. In this paper, we present an online decentralized dual descent (OD3) power allocation algorithm and determine (in the worst case) how much of observed social welfare can be explained by fluctuations in generation capacity and consumer demand. Convergence properties and performance guarantees of the OD3 algorithm are analyzed by characterizing the difference between the online decision and the optimal decision. We demonstrate validity and accuracy of the theoretical results in the paper through numerical experiments using real power generation data. [ABSTRACT FROM PUBLISHER]