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This paper presents a new method, called multicycle Q-modulation, which can be used in wireless power transmission (WPT) to modulate the quality factor (Q) of the receiver (Rx) coil and dynamically optimize the load impedance to maximize the power transfer efficiency (PTE) in two-coil links. A key advantage of the proposed method is that it can be easily implemented using off-the-shelf components without requiring fast switching at or above the carrier frequency, which is more suitable for integrated circuit design. Moreover, the proposed technique does not need any sophisticated synchronization between the power carrier and Q-modulation switching pulses. The multicycle Q-modulation is analyzed theoretically by a lumped circuit model, and verified in simulation and measurement using an off-the-shelf prototype. Automatic resonance tuning in the Rx, combined with multicycle Q-modulation helped maximizing PTE of the inductive link dynamically in the presence of environmental and loading variations, which can otherwise significantly degrade the PTE in multicoil settings. In the prototype conventional two-coil link, the proposed method increased the power amplifier plus inductive-link efficiency from 4.8% to 16.5% at ( RL = 1\, kW, d23 = 3\,cm), and from 23% to 28.2% at (RL = 100\,{\Omega}, d23 = 3\,cm) after 11% change in the resonance capacitance, while delivering 168.1 mW to the load (PDL). [ABSTRACT FROM PUBLISHER]

There is increasing evidence of shortage of ramping resources in the real-time operation of power systems. To explain and remedy this problem systematically, in this paper we take a novel look at the way the day-ahead unit commitment (UC) problem represents the information about load, generation and ramping constraints. We specifically investigate the approximation error made in mapping of the original problem, that would decide the continuous-time generation and ramping trajectories of the committed generating units, onto the discrete-time problem that is solved in practice. We first show that current practice amounts to approximating the trajectories with linear splines. We then offer a different representation through cubic splines that provides physically feasible schedules and increases the accuracy of the continuous-time generation and ramping trajectories by capturing sub-hourly variations and ramping of load in the day-ahead power system operation. The corresponding day-ahead UC model is formulated as an instance of mixed-integer linear programming (MILP), with the same number of binary variables as the traditional UC formulation. Numerical simulation over real load data from the California ISO demonstrate that the proposed UC model reduces the total day-ahead and real-time operation cost, and the number of events of ramping scarcity in the real-time operations. [ABSTRACT FROM PUBLISHER]

In this paper, we introduce an approach for a fast assessment of the dynamic characteristics of system frequency during the period of cold load pickup following a large-scale blackout. The approach is developed based on a load model and a model of generation control system: the load model considers the unique time-dependent characteristic of inrush power surges during the period of cold load pickup, while the model of generation control system mimics the characteristics of various governors that are crucial to the determination of the key variables including initial rate of frequency change, frequency nadir and settling frequency. With the proposed linearization and estimation methods, the model of generation control system can be quickly constructed to offer a great amount of flexibility and simplicity for the study of the impact of cold load on frequency response. The proposed approach allows system operators to quickly evaluate many different options for system restoration. The application of the proposed approach is demonstrated in a case study based on the IEEE 39-bus system. The differences between the results obtained using the proposed approach and those obtained from complete PSS/E simulation are very small, which suggests that the linearized model of generation control system is fast, and accurate enough to address the major concerns of cold load pickup in system restoration. [ABSTRACT FROM PUBLISHER]

This paper proposes a quasi-steady-state modeling approach for an approximation of long-term frequency dynamics in power systems. A specific phenomenon of concern is an onset of frequency swings during load/generation imbalance scenarios. The effects of system voltage characteristics, system inertia, and, more importantly, damping controllers are explained and quantified using the described quasi-steady-state models. Application of the methodology to a 14-generator benchmark system demonstrates that described models are suitable for simulation of different disturbance scenarios that can trigger frequency instability. Moreover, linearization of the proposed models can provide convenient means for impact assessment and coordinated design of damping controllers. To demonstrate this, coordinated tuning of multiband power system stabilizers to improve frequency dynamics has been performed and validated through nonlinear simulations using a commercial transient stability software. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a new methodology to formulate storage behavior in medium- and long-term power system models that use a load duration curve. Traditionally in such models, the chronological information among individual hours is lost; information that is necessary to adequately model the operation of a storage facility. Therefore, these models are not fully capable of optimizing the actual operation of storage units, and often use pre-determined data or some sort of peak-shaving algorithm. In a rapidly changing power system, the proper characterization of storage behavior and its optimization becomes an increasingly important issue. This paper proposes a methodology to tackle the shortcomings of existing models. In particular, we employ the so-called system states framework to recover some of the chronological information within the load duration curve. This allows us to introduce a novel formulation for storage in a system states model. In a case study, we show that our method can lead to computational time reductions of over 90% while accurately replicating hourly behavior of storage levels. [ABSTRACT FROM PUBLISHER]

This paper presents a wide-area control approach to improve the transient stability of the power systems while also damping the post-fault inter-area oscillations. The proposed approach employs a nonlinear Kalman filter to estimate the inter-area modes using phasor measurement units (PMUs). The wide-area control system then uses the estimated inter-area dynamics through the developed control algorithms to improve the first swing and damping stability of the system. The performance of the proposed approach is evaluated on the simplified Australian test system with different load models including induction motors and the results show significant improvement in the stability of the system by simply adding the wide-area control signals to the available controllers in the system. The application of the proposed wide-area control system is shown to be feasible on realistic systems by improving the system stability and efficiency. [ABSTRACT FROM PUBLISHER]

Aluminum production relies on the smelting process which consumes huge amounts of electrical energy. One possible solution to reduce the fossil fuel consumption by aluminum production is the integration of wind power. Based on this background, this paper studies an isolated power system for aluminum smelting production with a high penetration of wind power. A dynamic model of the aluminum smelter load (ASL) is introduced in this paper using the field experiment data. Based on this model, the dynamic model of the isolated system considering demand side participation is proposed. The MPC-based frequency controller is proposed to keep the frequency deviation within a proper range (\pm0.1 Hz) under wind power fluctuation as well as to recover the system frequency after a large disturbance (such as one generator trip). Finally, simulation results demonstrate the effectiveness of the proposed MPC based frequency controller. [ABSTRACT FROM PUBLISHER]

This paper presents a multiphase continuation power flow (MCPF) methodology to perform voltage security analyses on unbalanced multiphase distribution systems. The proposed tool includes comprehensive models of most network components, and allows for explicit representation of neutral cables and grounding connections. The methodology has been validated through comparisons with a commercial software and with results available in the literature. Additional analyses are presented using the IEEE 4-bus, the Neutral-to-Earth (NEV) and the IEEE 8500 Test Systems. These systems have been developed to present several challenges to distribution systems analytical tools. In particular, the influence of the 3-phase transformer connections on the PV curves have been demonstrated and has been useful to stress the importance of a complete system representation. [ABSTRACT FROM PUBLISHER]

Optimization models have been widely used in the power industry to aid the decision-making process of scheduling and dispatching electric power generation resources, a process known as unit commitment (UC). Since UC’s birth, there have been two major waves of revolution on UC research and real life practice. The first wave has made mixed integer programming stand out from the early solution and modeling approaches for deterministic UC, such as priority list, dynamic programming, and Lagrangian relaxation. With the high penetration of renewable energy, increasing deregulation of the electricity industry, and growing demands on system reliability, the next wave is focused on transitioning from traditional deterministic approaches to stochastic optimization for unit commitment. Since the literature has grown rapidly in the past several years, this paper is to review the works that have contributed to the modeling and computational aspects of stochastic optimization (SO) based UC. Relevant lines of future research are also discussed to help transform research advances into real-world applications. [ABSTRACT FROM PUBLISHER]

We report on the extension of a general stochastic simulation approach for power systems with integrated renewable resources to also incorporate the representation of utility-scale storage resources. The extended approach deploys models of the energy storage resources to emulate their scheduling and operations in the transmission-constrained hourly day-ahead markets. To this end, we formulate a scheduling optimization problem to determine the operational schedule of the controllable storage resources in coordination with the demands and the various supply resources, including the conventional and renewable resources. The incorporation of the scheduling optimization problem into the Monte Carlo simulation framework takes full advantage of the structural characteristics in the construction of the so-called sample paths for the stochastic simulation approach and to ensure its numerical tractability. The extended methodology has the capability to quantify the power system economics, emissions and reliability variable effects over longer-term periods for power systems with the storage resources. Applications of the approach include planning and investment studies and the formulation and analysis of policy. We illustrate the capabilities and effectiveness of the simulation approach on representative study cases on modified IEEE 118 and WECC 240-bus systems. These results provide valuable insights into the impacts of energy storage resources on the performance of power systems with integrated wind resources. [ABSTRACT FROM PUBLISHER]

This paper proposes an efficient method for evaluating composite system reliability via subset simulation. The central idea is that a small failure probability can be expressed as a product of larger conditional probabilities, thereby turning the problem of simulating a rare failure event into several conditional simulations of more frequent intermediate failure events. In existing methods, system states are simply assessed in a binary secure/failure manner. To fit into the context of subset simulation, the adequacy of system states is parametrized with a metric based on linear programming, thus allowing for an adaptive choice of intermediate failure events. Samples conditional on these events are generated by Markov chain Monte Carlo simulation. The proposed method requires no prior information before imulation. Different models for renewable energy sources can also be accommodated. Numerical tests show that this method is significantly more efficient than standard Monte Carlo simulation, especially for simulating rare failure events. [ABSTRACT FROM PUBLISHER]

This paper presents an application of multiple linear regression (MLR) to extract significant correlations between damping of electromechanical modes and system operating conditions and to forecast future damping values, based on existing day-ahead market forecasts for power flows and generation. The presented analysis uses measurements from the Nordic power system. First, a static MLR model is developed to explain the variability of the damping of the 0.35-Hz inter-area mode in the Nordic system. Together with the static model, a dynamic MLR model is used for forecasting the damping 24 hours ahead, using day-ahead market forecasts. Test results indicate the proposed methods are able to correctly predict about 90% of the low damped operating conditions observed during a year, if day-ahead market forecasts are accurate. These results suggest that the methods could be used to issue early warnings about future operating conditions with low damping. [ABSTRACT FROM PUBLISHER]

Interconnection wide electric transmission system has been envisioned to facilitate the growth of renewable energy, enhance reliability, improve system operating efficiency, and reduce emissions. In this paper, we propose an explicit planning approach for transmission design at the national level. It has been applied to the U.S. system to design transmission overlays for multiple future generation scenarios. Associated simulation results suggest that a national transmission overlay provides economic, environmental, and system performance benefits. [ABSTRACT FROM PUBLISHER]

A novel model predictive control (MPC) scheme is developed for mitigating the effects of severe line-overload disturbances in electrical power systems. A piece-wise linear convex approximation of line losses is employed to model the effect of transmission line power flow on conductor temperatures. Control is achieved through a receding-horizon model predictive control (MPC) strategy which alleviates line temperature overloads and thereby prevents the propagation of outages. The MPC strategy adjusts line flows by rescheduling generation, energy storage and controllable load, while taking into account ramp-rate limits and network limitations. In Part II of this paper, the MPC strategy is illustrated through simulation of the IEEE RTS-96 network, augmented to incorporate energy storage and renewable generation. [ABSTRACT FROM PUBLISHER]

In market operations, distributed generators (DGs) and price-sensitive loads participate in a microgrid energy market implemented in JADE. Each DG and each price-sensitive load is represented by the respective agents which perform various functions such as scheduling, coordination and market clearing subject to system, DG and load constraints. Each agent is assigned to one of the several agent objectives which maximizes either DG or load surpluses or both. In simulated operation of a microgrid, hourly power reference signals and load control signals from JADE are passed to DG and load models developed in MATLAB/Simulink using MACSimJX. Simulated operation of DGs and loads are studied by performing simulations under different agent objectives. Results from simulation studies demonstrate the effectiveness of implementing multi-agent system (MAS) in the distributed management of microgrids. [ABSTRACT FROM PUBLISHER]

In development studies carried out on large power systems, a need may arise for a reduction in which whole regions are seen as the nodes of a simplified graph whose edges replace the inter-regional links. The property required from this kind of backbone representation may be that reduced load flows stay close to their physical counterpart on the full grid. In the dc approximation, such a model can consist of a set of impedances attached to each edge, along with a flow characterizing a particular state of the system. The identification of the model accommodating best a large sample of flows, representative of all of their possible diversity, is a nonconvex problem for which two partially convex reformulations are proposed. Simple ad hoc algorithms are introduced as a way to find approximate solutions satisfying first-order optimality conditions. [ABSTRACT FROM PUBLISHER]

An interconnected electrical network that has electrical sources and loads makes a small-scale power system (SSPS). These systems have low inertia, which makes the modeling and controlling of them dissimilar to that of traditional large-scale power systems. A differential game-theoretic framework allows for the design of the distributed control structures for SSPS with player dynamics under simultaneous player movement. Under this approach, both loads and sources are defined as players in the system to form a game of energy between them. Game-theory-based modeling is necessary in this case since it optimizes the multiobjective optimization problem based on local control without the need for a communication channel. In this paper, a differential game-theoretic approach is used for path optimization of load players during a cold start that minimizes losses and achieves a desired steady-state operating point. Example simulation cases are obtained for a dc power system that has nine buses and dynamic load players. This power system is used to show the applicability, effectiveness, and performances of the proposed concepts. However, this method can be easily applied to other types of larger dc or ac networks. Finally, experimental results are yielded to validate the theoretical results and show that the proposed controller has higher performance compared with the traditional proportional–integral controller during transients. [ABSTRACT FROM PUBLISHER]

In restructured power systems, the transmission and distribution grids are autonomously utilized by independent system operator (ISO) and distribution companies (DISCOs), respectively. As the operating condition of one grid influences the decisions made by operators of other grids, the ISO and DISCOs should collaborate and cooperate with each other in order to operate the entire power system in a secure and economic manner. According to the concept of system of systems (SoS) engineering, this paper presents a decentralized decision-making framework to determine a secure and economical hourly generation schedule for a transmission system encompassing numbers of active distribution grids. Taking into consideration the physical connections and shared information between ISO and DISCOs, an SoS-based SCUC framework is designed and a hierarchical optimization algorithm is presented to find optimal operating points of all independent systems in the SoS-based power system architecture. The numerical results show the effectiveness of the proposed SoS framework and solution methodology. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a flexible mixed-integer linear programming formulation of the AC OPF problem for distribution systems, using convexification and linearization techniques. The proposed formulation allows the representation of discrete decisions via integer decision variables, captures the nonlinear behavior of the electrical network via approximations of controllable accuracy, and can be solved to global optimality with commercial optimization solvers. The formulation is based on conventional variables that describe network behavior, which ensures its flexibility and the possibility of application to various distribution system problems, as we indicate with case studies. [ABSTRACT FROM PUBLISHER]

Real-Time Thermal Rating (RTTR) is a smart-grid technology that allows electrical conductors to operate at an enhanced rating based on local weather conditions. RTTR also provides thermal visibility of the network, making system operators aware if the actual rating drops below the static seasonal rating. This paper investigates how using these enhanced variable ratings affects power network reliability. A methodology has been developed to assess network reliability with variable conductor ratings. The effect of failures and uncertainties in the RTTR system are also considered, and the effect of the correlation between conductor ratings due to common weather conditions is built into the model. State sampling and sequential Monte Carlo simulations are used to estimate the reliability of the RBTS 6-bus test network. At low loading levels, the RTTR appears to reduce network reliability but actually illustrates occasions when the existing ratings are being unknowingly infringed. For higher loading, the network reliability is significantly improved by the use of RTTR, with reductions in loss of load expectation of up to 67%. [ABSTRACT FROM PUBLISHER]

This paper presents a time-varying stochastic technique to assess conservation voltage reduction (CVR) effects based on load modeling. A time-varying exponential load model is developed to represent voltage dependences of loads. The recursive least square (RLS) method is applied to identify model parameters in a recursive way. CVR factors can be calculated using the identified model parameters. The time-varying stochastic model for CVR effects can then be constructed by the Kolmogorov-Smirnov (K-S) test. The proposed CVR assessment method is applied to one-year measurement data from a utility company. The calculated CVR factors are verified by a Euclidian distance-based comparison method. Stochastic models of CVR effects in each time window are constructed. Compared with previous efforts on assessing CVR effects, the proposed method does not require control groups or assumptions of linear relationships between the load and its impact factors. The probabilistic nature of CVR effects is also fully considered. [ABSTRACT FROM PUBLISHER]

In medium- and long-term power system models, it is a common approach to approximate the demand curve by load levels in order to make the models computationally tractable. However, in such an approach, the chronological information between individual hours is lost. In this paper, we propose a novel approach to power system models which constitutes an alternative to the traditional load levels. In particular, we introduce the concept of system states as opposed to load levels, which allows us to better incorporate chronological information in power system models, thereby resulting in a more accurate representation of system outcomes such as electricity prices and total cost. Moreover, the system states can be defined taking into account various important system features at once, as opposed to load levels which are defined using just one specific feature, i.e., demand or net demand. Therefore the system states approach better captures other results such as reserve prices, which are not driven by the usual feature used to define load levels. In a case study, we compare the newly proposed methodology to a standard load level approach, which validates that the system states approach better captures power system outcomes. [ABSTRACT FROM PUBLISHER]

Power systems training and education faces serious challenges due to the rising complexity of energy systems. This paper presents a simulation-based training platform for educating students and power systems professionals in complex Smart Grid applications. The system is split into parts like electrical grid or controls and specialized, domain-specific tools are then coupled to be able to simulate the overall behavior. Experiences with the developed education and training material and the corresponding modeling and simulation environment are discussed. The usage of advanced modeling and simulation approaches, especially when providing new functionality via coupling of simulation, is an accessible way to train and educate students efficiently in the complex and interdisciplinary area of power systems. [ABSTRACT FROM PUBLISHER]

Demand response (DR) has proved to be an inevitable part of the future grid. Much research works have been reported in the literature on the benefits and implementation of DR. However, little works have been reported on the impacts of DR on dynamic performance of power systems, specifically on the load frequency control (LFC) problem. This paper makes an attempt to fill this gap by introducing a DR control loop in the traditional LFC model (called LFC-DR) for a single-area power system. The model has the feature of optimal operation through optimal power sharing between DR and supplementary control. The effect of DR communication delay in the controller design is also considered. It is shown that the addition of the DR control loop increases the stability margin of the system and DR effectively improves the system dynamic performance. Simulation studies are carried out for single-area power systems to verify the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

This paper presents a particle swarm optimization (PSO)-based multi-objective planning algorithm for reactive power compensation of radial distribution networks with unified power quality conditioner (UPQC) allocation. A UPQC consists of a series and a shunt inverter. The UPQC model based on phase angle control (UPQC-PAC) is used. In UPQC-PAC, the series inverter injects a voltage with controllable phase angle in such a way that the voltage magnitude at load end remains unchanged. Due to the phase angle shift, the series inverter participates in load reactive power compensation along with the shunt inverter during healthy operating condition. In the proposed approach, the optimal location, the optimal reactive power compensation required at the location, and the optimal design parameters of UPQC are determined by minimizing three objective functions: 1) the rating of UPQC, 2) network power loss, and 3) percentage of nodes with undervoltage problem. These objectives are simultaneously minimized to obtain a set of non-dominated solutions using multi-objective PSO (MOPSO). The performances of two MOPSO variants are compared and the better one is used in all subsequent studies. A load flow algorithm including the UPQC-PAC model is devised. The performance of the proposed algorithm is validated with different case studies. [ABSTRACT FROM PUBLISHER]

Rapidly increasing the penetration level of renewable energies has imposed new challenges to the operation of power systems. Inability or inadequacy of these resources in providing inertial and primary frequency responses is one of the important challenges. In this paper, this issue is addressed within the framework of security-constrained unit commitment (SCUC) by adding new constraints representing the system frequency response. A modified system frequency response model is first derived and used to find analytical representation of system minimum frequency in thermal-dominant multi-machine systems. Then, an effective piecewise linearization (PWL) technique is employed to linearize the nonlinear function representing the minimum system frequency, facilitating its integration in the SCUC problem. The problem is formulated as a mixed-integer linear programming (MILP) problem which is solved efficiently by available commercial solvers. The results indicate that the proposed method can be utilized to integrate renewable resources into power systems without violating system frequency limits. [ABSTRACT FROM PUBLISHER]

This paper applies optimal power flow (OPF) to evaluate and maximize network benefits of demand-side management (DSM). The benefits are quantified in terms of the ability of demand-responsive loads to relieve upstream network constraints and provide ancillary services, such as operating reserve. The study incorporates detailed information on the load structure and composition, and allows the potential network benefits, which could be obtained through management of different load types, to be quantified and compared. It is demonstrated that the actual network location of demand-manageable load has an important influence on the effectiveness of the applied DSM scheme, since the characteristics of the loads and their interconnecting networks vary from one location to another. Consequently, some network locations are more favorable for implementation of DSM, and OPF can be applied to determine the optimal allocation of demand-side resources. The effectiveness of the presented approach is assessed using a time-sequential OPF applied to typical radial and meshed U.K. distribution networks. The results of the analysis suggest that network operators could not just participate in, but also encourage and add value to the implementation of specific DSM schemes at the optimum network locations in order to maximize the total benefit from DSM. [ABSTRACT FROM PUBLISHER]

A scalable and analytically tractable probabilistic model for the cascading failure dynamics in power grids is constructed while retaining key physical attributes and operating characteristics of the power grid. The approach is based upon extracting a reduced abstraction of large-scale power grids using a small number of aggregate state variables while modeling the system dynamics using a continuous-time Markov chain. The aggregate state variables represent critical power-grid attributes, which have been shown, from prior simulation-based and historical-data-based analysis, to strongly influence the cascading behavior. The transition rates among states are formulated in terms of certain parameters that capture grid's operating characteristics comprising loading level, error in transmission-capacity estimation, and constraints in performing load shedding. The model allows the prediction of the evolution of blackout probability in time. Moreover, the asymptotic analysis of the blackout probability enables the calculation of the probability mass function of the blackout size. A key benefit of the model is that it enables the characterization of the severity of cascading failures in terms of the operating characteristics of the power grid. [ABSTRACT FROM PUBLISHER]

This paper proposes improvements in the sequential Monte Carlo (MC) simulation based approaches for reliability evaluation of composite generation and transmission systems. The main idea is to compute a threshold load level to facilitate the process of state evaluation, which is very time-consuming mainly due to optimal power flow computations. Two main sampling techniques namely random sampling (RS) and Latin Hypercube sampling (LHS) are applied to the proposed sequential MC simulation technique. Their performances in terms of simulation time as well as solution accuracy are compared. Case studies using the IEEE Reliability Test System (IEEE RTS) are utilized to demonstrate the performance of the proposed approach. Reliability indices including loss of load probability, expected unserved energy, loss of load frequency and duration are estimated. It is shown that the proposed approach considerably reduces the computational requirements during state evaluation, and that the application of LHS can further decrease the simulation time and required sample size to reach convergence. [ABSTRACT FROM PUBLISHER]

Existing mode meter algorithms were derived with the assumption that load variations are accurately represented by white noise or an integral of white noise, which may not be satisfied in actual power systems. This paper proposes a mode meter algorithm which relaxes this assumption by explicitly taking into account spectral load characteristics. These characteristics can be either measured or estimated using the inverse of the existing power system model. The method is developed assuming an autoregressive moving average (ARMA) model of the system and incorporating estimated correlations between loads as inputs and synchrophasor measurements as outputs. Performances of the proposed method are compared with the Yule-Walker and N4SID methods using simulated synchrophasor data obtained from the KTH Nordic 32 test system. Finally, the effects of measurement noise on the proposed method are analyzed, as well as the effects of model uncertainty when the power system model is used to determine spectral load characteristics. It is shown that the proposed algorithm increases accuracy in mode estimates when the loads are described with nonwhite noise. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a method to compute linear sensitivity distribution factors (DFs) in near real-time. The method does not rely on the system power flow model. Instead, it uses only high-frequency synchronized data collected from phasor measurement units to estimate the injection shift factors through linear least-squares estimation, after which other DFs can be easily computed. Such a measurement-based approach is desirable since it is adaptive to changes in system operating point and topology. We further improve the adaptability of the proposed approach to such changes by using weighted and recursive least-squares estimation. Through numerical examples, we illustrate the advantages of our proposed DF estimation approach over the conventional model-based one in the context of contingency analysis and generation re-dispatch. [ABSTRACT FROM PUBLISHER]

This paper presents three new contributions to power flow analysis of unbalanced three-phase distribution systems. First, a complex vector based model in \alpha \beta 0\; stationary reference frame is developed to state the power flow equations using a compact matrix formulation. The proposed model is based on Kirchhoff's current law (KCL) and Kirchhoff's voltage law (KVL). Then, a general and exact power transformer model in the \alpha \beta 0\; reference frame is proposed. Finally, this transformer model is incorporated into the power flow problem. It will be shown that the use of an orthogonal reference frame simplifies the modeling of the distribution network components. In this work, both the network and the power transformer, as well as PQ type loads, PQ and PV type generators and a slack bus are modeled. By using the node incidence matrix instead of the admittance matrix, the information about the grid topology and the grid parameters (including power transformers) is separately organized. As it will be demonstrated, the proposed formulation is ready to incorporate other complex models of loads, generators or storage devices. The model is tested by using the IEEE 4-Node and the IEEE 123-Node Test Feeders with different transformer connections and balanced and unbalanced lines and loads. [ABSTRACT FROM PUBLISHER]

Integration of renewable energy sources and demand response poses new challenges to system operators as they increase the uncertainty of the power supply and demand. Recently, robust optimization techniques are applied to the unit commitment problem with uncertainty as an alternative to the stochastic programming approaches. However, it remains challenging to solve the robust unit commitment model with full transmission line constraints. In this paper, we propose novel acceleration techniques for solving two-stage robust unit commitment problem with consideration of full transmission line constraints. We use 1) the cutting-plane algorithm for the master problem, which dynamically includes critical transmission line constraints, and 2) column-generation methods, including the branch-and-price-and-cut algorithm and heuristic approaches, for the subproblems, which add only necessary transmission line dual variables on the fly. Computational results for the modified IEEE 118-bus system show that the combination of the cutting-plane algorithm and the heuristic column-generation approach greatly reduces the total solution time of the two-stage robust unit commitment problem. [ABSTRACT FROM PUBLISHER]

Local controllers are essential in distribution networks; they are employed in classical devices such as load tap-changing (LTC) transformers and switchable shunt capacitors, and more recently in distributed generation (DG). The effective use of distribution management system (DMS) applications requires an accurate model of the interaction between the local controllers through the distribution system. This paper presents a new sensitivity matrix approach for modeling such interactions, and demonstrates its application in the implicit ZBus Gauss method for power flow computation. The sensitivity method models both PV buses (for the connection of DG) and tap position adjustments through current source injections, and consequently avoids re-factorization of the network bus admittance matrix. Numerical results on distribution networks with up to 3145 buses show that the sensitivity-based power flow method for simulating the operation of local controllers is superior to a sequential control action adjustment approach previously proposed in the literature, and that its computing time is commensurate with the performance requirements in real-time DMS applications. [ABSTRACT FROM PUBLISHER]

The widespread use of distributed generations (DGs) in utility distribution feeders is a trend, and it brings about several challenges to the operation, planning, and design of general distribution networks. In this paper, a comprehensive tool, Continuation Distribution Power Flow (CDFLOW), is presented and evaluated. CDFLOW can be used for tracing steady-state stationary behaviors of general unbalanced distribution systems due to various types of power injection variations, including high penetration of DGs. The major computation engine behind CDFLOW is the continuation method. Major components, either balanced or unbalanced, grounded or ungrounded, are well modeled in CDFLOW. A detailed description of CDFLOW and its implementation regarding the predictor, corrector, adaptive step-size control and parameterizations are presented. For illustrative purposes, CDFLOW was applied to the IEEE 8500-node test system and a practical 1103-node distribution networks with promising results. [ABSTRACT FROM PUBLISHER]

Demand response programs incentivize loads to actively moderate their energy consumption to aid the power system. Uncertainty is an intrinsic aspect of demand response because a load's capability is often unknown until the load has been deployed. Algorithms must therefore balance utilizing well-characterized, good loads and learning about poorly characterized but potentially good loads; this is a manifestation of the classical tradeoff between exploration and exploitation. We address this tradeoff in a restless bandit framework, a generalization of the well-known multi-armed bandit problem. The formulation yields index policies in which loads are ranked by a scalar index, and those with the highest are deployed. The policy is particularly appropriate for demand response because the indices have explicit analytical expressions that may be evaluated separately for each load, making them both simple and scalable. This formulation serves as a heuristic basis for when only the aggregate effect of demand response is observed, from which the state of each individual load must be inferred. We formulate a tractable, analytical approximation for individual state inference based on observations of aggregate load curtailments. In numerical examples, the restless bandit policy outperforms the greedy policy by 5%–10% of the total cost. When the states of deployed loads are inferred from aggregate measurements, the resulting performance degradation is on the order of a few percent for the (now heuristic) restless bandit policy. [ABSTRACT FROM PUBLISHER]

Restoring a large-scale power system has always been a complicated and important issue. A lot of research work has been done on different aspects of the whole power system restoration procedure. However, more time will be required to complete the power system restoration process in an actual situation if accurate and real-time system data cannot be obtained. With the development of the wide area monitoring system (WAMS), power system operators are capable of accessing to more accurate data in the restoration stage after a major outage. The ultimate goal of the system restoration is to restore as much load as possible while in the shortest period of time after a blackout, and the restorable load can be estimated by employing WAMS. Moreover, discrete restorable loads are employed considering the limited number of circuit-breaker operations and the practical topology of distribution systems. In this work, a restorable load estimation method is proposed employing WAMS data after the network frame has been reenergized, and WAMS is also employed to monitor the system parameters in case the newly recovered system becomes unstable again. The proposed method has been validated with the New England 39-Bus system and an actual power system in Guangzhou, China. [ABSTRACT FROM PUBLISHER]

This paper presents a novel probabilistic distribution load flow (PDLF) algorithm to study the effect of connecting a wind turbine (WT) to a distribution system. This probabilistic approach is used to capture the stochastic behavior of the generation of WTs. Three different models of WTs are developed to be embedded in the PDLF. Consequently, a probabilistic approach to evaluate the impact of wind penetration into distribution systems is developed. Futhermore, the effect of WT penetration on feeder losses, voltage profile and substation powers is presented. [ABSTRACT FROM PUBLISHER]

This paper presents the principles of a centralized underfrequency load-shedding (UFLS) scheme based on a frequency stability boundary curve suitable for small isolated power systems. The centralized UFLS scheme is illustrated in case of two small isolated Spanish power systems. [ABSTRACT FROM PUBLISHER]

A method is proposed to reconstruct and track network state from a limited number of phasor measurement unit (PMU) data. To deal with the resulting unobservability, the state with bus powers and generator voltages closest to previously estimated values is computed. Those values, treated as pseudo-measurements, are obtained from the last reconstructed state, in a recursive manner. The method involves solving an optimization problem with linear constraints. It is scalable insofar as it accommodates from a few PMUs up to configurations ensuring full network observability. Reconstruction of only a region is possible. These and other features are demonstrated on the Nordic32 test system, with synchronized phasors obtained from detailed time simulation of a situation evolving towards instability. Suitable choices of PMU location and pseudo-measurements are also discussed. [ABSTRACT FROM PUBLISHER]

This paper investigates a secondary voltage control based on a graph partitioning method. The method divides the power system into regions to eventually prevent the propagation of disturbances and to minimize the interaction between these regions. The optimized number of regions is found based on the bus voltage sensitivity to disturbances being applied to loads in each region. Then, a number of representative buses are labelled as pilot buses displaying the critical point for voltage control in each region. The control uses decentralized controllers to eliminate voltage violations resulting from load variations and disturbances in the system. The decentralized controllers are implemented by fuzzy logic which is trained via offline simulations; they inject required reactive power into the regions to correct voltage violations. The methodology is applied to the IEEE 118-bus network. The results show the performance and ability of graph partitioning and fuzzy secondary voltage control to regulate the voltage and to avoid propagation of disturbances between regions. [ABSTRACT FROM PUBLISHER]

Present renewable portfolio standards are changing power systems by replacing conventional generation with alternate energy resources such as photovoltaic (PV) systems. With the increase in penetration of PV resources, power systems are expected to experience a change in dynamic and operational characteristics. This paper studies the impact of increased penetration of PV systems on static performance as well as transient stability of a large power system, in particular the transmission system. Utility scale and residential rooftop PVs are added to the aforementioned system to replace a portion of conventional generation resources. While steady state voltages are observed under various PV penetration levels, the impact of reduced inertia on transient stability performance is also examined. The studied system is a large test system representing a portion of the Western U.S. interconnection. The simulation results obtained effectively identify both detrimental and beneficial impacts of increased PV penetration both for steady state stability and transient stability performance. [ABSTRACT FROM PUBLISHER]

A high impedance fault (HIF) is characterized by a small, nonlinear, random, unstable, and widely varying fault current in a power distribution system. HIFs draw very low fault currents, and hence are not always effectively cleared by conventional overcurrent relays. Various schemes are proposed to detect such faults. This paper presents a method to detect HIFs using a tool based on mathematical morphology (MM). The method is implemented alongside the conventional overcurrent relay at the substation to improve the performance of this relay in detecting HIFs. It is rigorously tested on standard test systems using PSCAD/EMTDC® to generate test waveforms, and Matlab® to implement the method. Simulation results show that the proposed method is fast, secure, and dependable. [ABSTRACT FROM PUBLISHER]

Existing power system planning software is not capable of simulating large numbers of contingencies that involve bus mergers and bus splits without cumbersome modifications to planning models either manually or through scripting. This means that some of the events that can occur in a bulk power system are not studied in detail prior to real-time operation. This paper proposes the use of a unified network applications framework for planning contingency analysis capable of incorporating contingencies that involve arbitrary configurations of switching devices. The method handles any type of bus split or bus merger events automatically without requiring case conversion or modification. This drastically simplifies the tabulation of results of complex contingencies and makes potential unsecure system conditions visible during the planning stage. The efficiency of the algorithm is demonstrated in large-scale ISO models that incorporate full-topology switching modeling, and it is shown to be at least ten times faster than scripting. The proposed method hence supports direct comparison of planning and real-time grid security assessment evaluation, providing full temporal interoperability between offline contingency analysis and real-time security assessment. [ABSTRACT FROM PUBLISHER]

Society's increased concern over green house gas emission and the reduced cost of electric vehicle technologies has increased the number of electric vehicles (EV) and plug-in hybrid vehicles on the road. Previous studies into the effects of electric vehicles on the electric system have focused on transmission, generation, and the loss of life of distribution transformers. This paper focuses specifically on identifying distribution transformers that are most susceptible to excessive loading due to the implementation of electric vehicles. The authors use a binomial probability model to calculate the probability that a specific distribution transformer will experience excessive loading. Variables to the function include the existing peak transformer demand, number of customers connected to the transformer, and the most common EV charger demand. Also included in the paper is an optimization approach that utilizes the results from the binomial function to determine the optimal replacement strategy to minimize replacement costs. An extension of the approach is also utilized to explore the effectiveness of EV targeted demand side management programs. The authors apply the described algorithms to 75 000 distributions transformers within a distribution system located in Denver, Colorado, USA. [ABSTRACT FROM PUBLISHER]

An evolutionary programming (EP) based technique has been presented for the optimal placement of distributed generation (DG) units energized by renewable energy resources (wind and solar) in a radial distribution system. The correlation between load and renewable resources has been nullified by dividing the study period into several segments and treating each segment independently. To handle the uncertainties associated with load and renewable resources, probabilistic techniques have been used. Two operation strategies, namely “turning off wind turbine generator” and “clipping wind turbine generator output”, have also been adopted to restrict the wind power dispatch to a specified fraction of system load for system stability consideration. To reduce the search space and thereby to minimize the computational burden, a sensitivity analysis technique has been employed which gives a set of locations suitable for DG placement. For the proposed EP based approach, an index based scheme has also been developed to generate the population ensuring the feasibility of each individual and thus considerably reducing the computational time. The developed technique has been applied to a 12.66-kV, 69-bus distribution test system. The solutions result in significant loss reduction and voltage profile improvement. [ABSTRACT FROM PUBLISHER]

In order to support the growing interest in demand response (DR) modeling and analysis, there is a need for physical-based residential load models. The objective of this paper is to present the development of such load models at the appliance level. These include conventional controllable loads, i.e., space cooling/space heating, water heater, clothes dryer and electric vehicle. Validation of the appliance-level load models is carried out by comparing the models' output with the real electricity consumption data for the associated appliances. The appliance-level load models are aggregated to generate load profiles for a distribution circuit, which are validated against the load profiles of an actual distribution circuit. The DR-sensitive load models can be used to study changes in electricity consumption both at the household and the distribution circuit levels, given a set of customer behaviors and/or signals from a utility. [ABSTRACT FROM PUBLISHER]

Demand for electricity varies throughout the day, increasing the average cost of power supply. Time-of-use (TOU) pricing has been proposed as a demand-side management (DSM) method to influence user demands. In this paper, we describe a game-theoretic approach to optimize TOU pricing strategies (GT-TOU). We propose models of costs to utility companies arising from user demand fluctuations, and models of user satisfaction with the difference between the nominal demand and the actual consumption. We design utility functions for the company and the users, and obtain a Nash equilibrium using backward induction. In addition to a single-user-type scenario, we also consider a scenario with multiple types of users, each of whom responds differently to time-dependent prices. Numerical examples show that our method is effective in leveling the user demand by setting optimal TOU prices, potentially decreasing costs for the utility companies, and increasing user benefits. An increase in social welfare measure indicates improved market efficiency through TOU pricing. [ABSTRACT FROM PUBLISHER]

Matpower is an open-source Matlab-based power system simulation package that provides a high-level set of power flow, optimal power flow (OPF), and other tools targeted toward researchers, educators, and students. The OPF architecture is designed to be extensible, making it easy to add user-defined variables, costs, and constraints to the standard OPF problem. This paper presents the details of the network modeling and problem formulations used by Matpower, including its extensible OPF architecture. This structure is used internally to implement several extensions to the standard OPF problem, including piece-wise linear cost functions, dispatchable loads, generator capability curves, and branch angle difference limits. Simulation results are presented for a number of test cases comparing the performance of several available OPF solvers and demonstrating Matpower's ability to solve large-scale AC and DC OPF problems. [ABSTRACT FROM AUTHOR]