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Showing papers in "IEEE Transactions on Smart Grid in 2010"


Journal ArticleDOI
TL;DR: This paper presents an autonomous and distributed demand-side energy management system among users that takes advantage of a two-way digital communication infrastructure which is envisioned in the future smart grid.
Abstract: Most of the existing demand-side management programs focus primarily on the interactions between a utility company and its customers/users. In this paper, we present an autonomous and distributed demand-side energy management system among users that takes advantage of a two-way digital communication infrastructure which is envisioned in the future smart grid. We use game theory and formulate an energy consumption scheduling game, where the players are the users and their strategies are the daily schedules of their household appliances and loads. It is assumed that the utility company can adopt adequate pricing tariffs that differentiate the energy usage in time and level. We show that for a common scenario, with a single utility company serving multiple customers, the global optimal performance in terms of minimizing the energy costs is achieved at the Nash equilibrium of the formulated energy consumption scheduling game. The proposed distributed demand-side energy management strategy requires each user to simply apply its best response strategy to the current total load and tariffs in the power distribution system. The users can maintain privacy and do not need to reveal the details on their energy consumption schedules to other users. We also show that users will have the incentives to participate in the energy consumption scheduling game and subscribing to such services. Simulation results confirm that the proposed approach can reduce the peak-to-average ratio of the total energy demand, the total energy costs, as well as each user's individual daily electricity charges.

2,715 citations


Journal ArticleDOI
TL;DR: Simulation results show that the combination of the proposed energy consumption scheduling design and the price predictor filter leads to significant reduction not only in users' payments but also in the resulting peak-to-average ratio in load demand for various load scenarios.
Abstract: Real-time electricity pricing models can potentially lead to economic and environmental advantages compared to the current common flat rates. In particular, they can provide end users with the opportunity to reduce their electricity expenditures by responding to pricing that varies with different times of the day. However, recent studies have revealed that the lack of knowledge among users about how to respond to time-varying prices as well as the lack of effective building automation systems are two major barriers for fully utilizing the potential benefits of real-time pricing tariffs. We tackle these problems by proposing an optimal and automatic residential energy consumption scheduling framework which attempts to achieve a desired trade-off between minimizing the electricity payment and minimizing the waiting time for the operation of each appliance in household in presence of a real-time pricing tariff combined with inclining block rates. Our design requires minimum effort from the users and is based on simple linear programming computations. Moreover, we argue that any residential load control strategy in real-time electricity pricing environments requires price prediction capabilities. This is particularly true if the utility companies provide price information only one or two hours ahead of time. By applying a simple and efficient weighted average price prediction filter to the actual hourly-based price values used by the Illinois Power Company from January 2007 to December 2009, we obtain the optimal choices of the coefficients for each day of the week to be used by the price predictor filter. Simulation results show that the combination of the proposed energy consumption scheduling design and the price predictor filter leads to significant reduction not only in users' payments but also in the resulting peak-to-average ratio in load demand for various load scenarios. Therefore, the deployment of the proposed optimal energy consumption scheduling schemes is beneficial for both end users and utility companies.

1,782 citations


Journal ArticleDOI
TL;DR: This work proposes an aggregator that makes efficient use of the distributed power of electric vehicles to produce the desired grid-scale power and applies the dynamic programming algorithm to compute the optimal charging control for each vehicle.
Abstract: For vehicle-to-grid (V2G) frequency regulation services, we propose an aggregator that makes efficient use of the distributed power of electric vehicles to produce the desired grid-scale power. The cost arising from the battery charging and the revenue obtained by providing the regulation are investigated and represented mathematically. Some design considerations of the aggregator are also discussed together with practical constraints such as the energy restriction of the batteries. The cost function with constraints enables us to construct an optimization problem. Based on the developed optimization problem, we apply the dynamic programming algorithm to compute the optimal charging control for each vehicle. Finally, simulations are provided to illustrate the optimality of the proposed charging control strategy with variations of parameters.

1,045 citations


Journal ArticleDOI
TL;DR: A brief introduction to the PMU and wide-area measurement system (WAMS) technology is provided and the uses of these measurements for improved monitoring, protection, and control of power networks are discussed.
Abstract: Synchronized phasor measurements have become a mature technology with several international manufacturers offering commercial phasor measurement units (PMUs) which meet the prevailing industry standard for synchrophasors. With the occurrence of major blackouts in many power systems around the world, the value of data provided by PMUs has been recognized, and installation of PMUs on power transmission networks of most major power systems has become an important current activity. This paper provides a brief introduction to the PMU and wide-area measurement system (WAMS) technology and discusses the uses of these measurements for improved monitoring, protection, and control of power networks.

1,000 citations


Journal ArticleDOI
TL;DR: An optimization model to adjust the hourly load level of a given consumer in response to hourly electricity prices is described, which materializes into a simple linear programming algorithm that can be easily integrated in the Energy Management System of a household or a small business.
Abstract: This paper describes an optimization model to adjust the hourly load level of a given consumer in response to hourly electricity prices. The objective of the model is to maximize the utility of the consumer subject to a minimum daily energy-consumption level, maximum and minimum hourly load levels, and ramping limits on such load levels. Price uncertainty is modeled through robust optimization techniques. The model materializes into a simple linear programming algorithm that can be easily integrated in the Energy Management System of a household or a small business. A simple bidirectional communication device between the power supplier and the consumer enables the implementation of the proposed model. Numerical simulations illustrating the interest of the proposed model are provided.

946 citations


Journal ArticleDOI
TL;DR: This paper critically reviews the reliability impacts of major smart grid resources such as renewables, demand response, and storage and observes that an ideal mix of these resources leads to a flatter net demand that eventually accentuates reliability challenges further.
Abstract: Increasing complexity of power grids, growing demand, and requirement for greater reliability, security and efficiency as well as environmental and energy sustainability concerns continue to highlight the need for a quantum leap in harnessing communication and information technologies. This leap toward a ?smarter? grid is widely referred to as ?smart grid.? A framework for cohesive integration of these technologies facilitates convergence of acutely needed standards, and implementation of necessary analytical capabilities. This paper critically reviews the reliability impacts of major smart grid resources such as renewables, demand response, and storage. We observe that an ideal mix of these resources leads to a flatter net demand that eventually accentuates reliability challenges further. A gridwide IT architectural framework is presented to meet these challenges while facilitating modern cybersecurity measures. This architecture supports a multitude of geographically and temporally coordinated hierarchical monitoring and control actions over time scales from milliseconds and up.

907 citations


Journal ArticleDOI
TL;DR: A unique vision for the future of smart transmission grids is presented in which their major features are identified and each smart transmission grid is regarded as an integrated system that functionally consists of three interactive, smart components.
Abstract: A modern power grid needs to become smarter in order to provide an affordable, reliable, and sustainable supply of electricity. For these reasons, considerable activity has been carried out in the United States and Europe to formulate and promote a vision for the development of future smart power grids. However, the majority of these activities emphasized only the distribution grid and demand side leaving the big picture of the transmission grid in the context of smart grids unclear. This paper presents a unique vision for the future of smart transmission grids in which their major features are identified. In this vision, each smart transmission grid is regarded as an integrated system that functionally consists of three interactive, smart components, i.e., smart control centers, smart transmission networks, and smart substations. The features and functions of each of the three functional components, as well as the enabling technologies to achieve these features and functions, are discussed in detail in the paper.

894 citations


Journal ArticleDOI
TL;DR: The main industry drivers of smart grid and the different facets of DER under the smart grid paradigm are explored and the existing and evolving programs at different ISOs/RTOs and the product markets they can participate in are summarized.
Abstract: Demand response (DR), distributed generation (DG), and distributed energy storage (DES) are important ingredients of the emerging smart grid paradigm. For ease of reference we refer to these resources collectively as distributed energy resources (DER). Although much of the DER emerging under smart grid are targeted at the distribution level, DER, and more specifically DR resources, are considered important elements for reliable and economic operation of the transmission system and the wholesale markets. In fact, viewed from transmission and wholesale operations, sometimes the term ?virtual power plant? is used to refer to these resources. In the context of energy and ancillary service markets facilitated by the independent system operators (ISOs)/regional transmission organizations (RTOs), the market products DER/DR can offer may include energy, ancillary services, and/or capacity, depending on the ISO/RTO market design and applicable operational standards. In this paper we first explore the main industry drivers of smart grid and the different facets of DER under the smart grid paradigm. We then concentrate on DR and summarize the existing and evolving programs at different ISOs/RTOs and the product markets they can participate in. We conclude by addressing some of the challenges and potential solutions for implementation of DR under smart grid and market paradigms.

846 citations


Journal ArticleDOI
TL;DR: This work improves the basic formulation of cooperative PSO by introducing stochastic repulsion among the particles and simultaneously scheduling all DER schedules, to investigate the potential consumer value added by coordinated DER scheduling.
Abstract: We describe algorithmic enhancements to a decision-support tool that residential consumers can utilize to optimize their acquisition of electrical energy services. The decision-support tool optimizes energy services provision by enabling end users to first assign values to desired energy services, and then scheduling their available distributed energy resources (DER) to maximize net benefits. We chose particle swarm optimization (PSO) to solve the corresponding optimization problem because of its straightforward implementation and demonstrated ability to generate near-optimal schedules within manageable computation times. We improve the basic formulation of cooperative PSO by introducing stochastic repulsion among the particles. The improved DER schedules are then used to investigate the potential consumer value added by coordinated DER scheduling. This is computed by comparing the end-user costs obtained with the enhanced algorithm simultaneously scheduling all DER, against the costs when each DER schedule is solved separately. This comparison enables the end users to determine whether their mix of energy service needs, available DER and electricity tariff arrangements might warrant solving the more complex coordinated scheduling problem, or instead, decomposing the problem into multiple simpler optimizations.

824 citations


Journal ArticleDOI
Anthony R. Metke1, Randy L. Ekl1
TL;DR: This paper discusses key security technologies for a smart grid system, including public key infrastructures and trusted computing, which will require significant dependence on distributed intelligence and broadband communication capabilities.
Abstract: There is virtually universal agreement that it is necessary to upgrade the electric grid to increase overall system efficiency and reliability. Much of the technology currently in use by the grid is outdated and in many cases unreliable. There have been three major blackouts in the past ten years. The reliance on old technology leads to inefficient systems, costing unnecessary money to the utilities, consumers, and taxpayers. To upgrade the grid, and to operate an improved grid, will require significant dependence on distributed intelligence and broadband communication capabilities. The access and communications capabilities require the latest in proven security technology for extremely large, wide-area communications networks. This paper discusses key security technologies for a smart grid system, including public key infrastructures and trusted computing.

614 citations


Journal ArticleDOI
TL;DR: Using good predictions, in advance planning and real-time control of domestic appliances, a better matching of demand and supply can be achieved and a more energy-efficient electricity supply chain can be achieve.
Abstract: Emerging new technologies like distributed generation, distributed storage, and demand-side load management will change the way we consume and produce energy. These techniques enable the possibility to reduce the greenhouse effect and improve grid stability by optimizing energy streams. By smartly applying future energy production, consumption, and storage techniques, a more energy-efficient electricity supply chain can be achieved. In this paper a three-step control methodology is proposed to manage the cooperation between these technologies, focused on domestic energy streams. In this approach, (global) objectives like peak shaving or forming a virtual power plant can be achieved without harming the comfort of residents. As shown in this work, using good predictions, in advance planning and real-time control of domestic appliances, a better matching of demand and supply can be achieved.

Journal ArticleDOI
TL;DR: The scheduling problem of building energy supplies is considered with the practical background of a low energy building and testing results show that significant energy cost savings can be achieved through integrated scheduling and control of various building energy supply sources.
Abstract: Recent research shows that 20%-30% of building energy consumption can be saved through optimized operation and management without changing the building structure and the hardware configuration of the energy supply system. Therefore, there is a huge potential for building energy savings through efficient operation. Microgrid technology provides an opportunity and a desirable infrastructure for improving the efficiency of energy consumption in buildings. The key to improve building energy efficiency in operation is to coordinate and optimize the operation of various energy sources and loads. In this paper, the scheduling problem of building energy supplies is considered with the practical background of a low energy building. The objective function is to minimize the overall cost of electricity and natural gas for a building operation over a time horizon while satisfying the energy balance and complicated operating constraints of individual energy supply equipment and devices. The uncertainties are captured and their impact is analyzed by the scenario tree method. Numerical testing is performed with the data of the pilot low energy building. The testing results show that significant energy cost savings can be achieved through integrated scheduling and control of various building energy supply sources. It is very important to fully utilize solar energy and optimize the operation of electrical storage. It is also shown that precooling is a simple way to achieve energy savings.

Journal ArticleDOI
TL;DR: It is assumed that time synchronized measurements will be ubiquitously available at all high-voltage substations at very high rates and how this information can be utilized more effectively for real-time operation as well as for subsequent decision making is examined.
Abstract: In this paper we assume that time synchronized measurements will be ubiquitously available at all high-voltage substations at very high rates. We examine how this information can be utilized more effectively for real-time operation as well as for subsequent decision making. This new information available in real time is different, both in quality and in quantity, than the real-time measurements available today. The promise of new and improved applications to operate the power system more reliably and efficiently has been recognized but is still in conceptual stages. Also, the present system to handle this real-time data has been recognized to be inadequate but even conceptual designs of such infrastructure needed to store and communicate the data are in their infancy. In this paper, we first suggest the requirements for an information infrastructure to handle ubiquitous phasor measurements recognizing that the quantity and rate of data would make it impossible to store all the data centrally as done today. Then we discuss the new and improved applications, classified into two categories: one is the set of automatic wide-area controls and the other is the set of control center (EMS) functions with special attention to the state estimator. Finally, given that the availability of phasor measurements will grow over time, the path for smooth transition from present-day systems and applications to those discussed here is delineated.

Journal ArticleDOI
TL;DR: A stochastic model to schedule reserves provided by DR in the wholesale electricity markets and determine commitment states of generating units and their scheduled energy and spinning reserves in the scheduling horizon is presented.
Abstract: Considerable developments in the real-time telemetry of demand-side systems allow independent system operators (ISOs) to use reserves provided by demand response (DR) in ancillary service markets. Currently, many ISOs have designed programs to utilize the reserve provided by DR in electricity markets. This paper presents a stochastic model to schedule reserves provided by DR in the wholesale electricity markets. Demand-side reserve is supplied by demand response providers (DRPs), which have the responsibility of aggregating and managing customer responses. A mixed-integer representation of reserve provided by DRPs and its associated cost function are used in the proposed stochastic model. The proposed stochastic model is formulated as a two-stage stochastic mixed-integer programming (SMIP) problem. The first-stage involves network-constrained unit commitment in the base case and the second-stage investigates security assurance in system scenarios. The proposed model would schedule reserves provided by DRPs and determine commitment states of generating units and their scheduled energy and spinning reserves in the scheduling horizon. The proposed approach is applied to two test systems to illustrate the benefits of implementing demand-side reserve in electricity markets.

Journal ArticleDOI
TL;DR: This paper summarizes diverse concepts for the next generation of power distribution system, and two transmission engineering techniques are modified for use in distribution engineering: state estimation, and locational marginal pricing.
Abstract: This paper summarizes diverse concepts for the next generation of power distribution system. The objective is to bring distribution engineering more closely aligned to smart grid philosophy. Issues of design, operation, and control are discussed with regard to new system theoretic as well as component/materials advances. In particular, two transmission engineering techniques are modified for use in distribution engineering: state estimation, and locational marginal pricing. The impact of electronic control in distribution systems is discussed. Because education and training have a great impact on distribution engineering, these topics are discussed as well.

Journal ArticleDOI
TL;DR: This paper proposes changing the business process of DR scheduling and implementation by integrating DR with distribution grid topology.
Abstract: Demand response (DR) is becoming an integral part of power system and market operations. Smart grid technologies will further increase the use of DR in everyday operations. Once the volume of the DR reaches a certain threshold, the effect of the DR events on the distribution and transmission system operations will be hard to ignore. This paper proposes changing the business process of DR scheduling and implementation by integrating DR with distribution grid topology. Study cases using OATI webDistribute show the potential DR effect on distribution grid operations and the distribution grid changing the effectiveness of the DR. These examples illustrate the need of integrating demand response with the distribution grid.

Journal ArticleDOI
TL;DR: This paper proposes a vision of next-generation monitoring, analysis, and control functions for tomorrow's smart power system control centers and identifies the technology and infrastructure gaps that must be filled, and develops a roadmap to realize the proposed vision.
Abstract: This paper proposes a vision of next-generation monitoring, analysis, and control functions for tomorrow's smart power system control centers. The paper first reviews the present control center technology and then presents the vision of the next-generation monitoring, analysis, and control functions. The paper also identifies the technology and infrastructure gaps that must be filled, and develops a roadmap to realize the proposed vision. This smart control center vision is expected to be a critical part of the future smart transmission grid.

Journal ArticleDOI
TL;DR: This paper presents some of the latest implementations of FNET's applications, which add significant capacities to this system for observing power system problems.
Abstract: Recent developments in smart grid technology have spawned interest in the use of phasor measurement units to help create a reliable power system transmission and distribution infrastructure. Wide-area monitoring systems (WAMSs) utilizing synchrophasor measurements can help with understanding, forecasting, or even controlling the status of power grid stability in real-time. A power system frequency monitoring network (FNET) was first proposed in 2001 and was established in 2004. As a pioneering WAMS, it serves the entire North American power grid through advanced situational awareness techniques, such as real-time event alerts, accurate event location estimation, animated event visualization, and post event analysis. Several papers published in the past several years discussed the FNET structure and its functionality. This paper presents some of the latest implementations of FNET's applications, which add significant capacities to this system for observing power system problems.

Journal ArticleDOI
TL;DR: An algorithm is proposed that generates random topology power grids featuring the same topology and electrical characteristics found from the real data.
Abstract: In order to design an efficient communication scheme and examine the efficiency of any networked control architecture in smart grid applications, we need to characterize statistically its information source, namely the power grid itself. Investigating the statistical properties of power grids has the immediate benefit of providing a natural simulation platform, producing a large number of power grid test cases with realistic topologies, with scalable network size, and with realistic electrical parameter settings. The second benefit is that one can start analyzing the performance of decentralized control algorithms over information networks whose topology matches that of the underlying power network and use network scientific approaches to determine analytically if these architectures would scale well. With these motivations, in this paper we study both the topological and electrical characteristics of power grid networks based on a number of synthetic and real-world power systems. The most interesting discoveries include: the power grid is sparsely connected with obvious small-world properties; its nodal degree distribution can be well fitted by a mixture distribution coming from the sum of a truncated geometric random variable and an irregular discrete random variable; the power grid has very distinctive graph spectral density and its algebraic connectivity scales as a power function of the network size; the line impedance has a heavy-tailed distribution, which can be captured quite accurately by a clipped double Pareto lognormal distribution. Based on the discoveries mentioned above, we propose an algorithm that generates random topology power grids featuring the same topology and electrical characteristics found from the real data.

Journal ArticleDOI
TL;DR: In this article, a new bilevel prediction strategy is proposed for short-term loaf forecast (STLF) of micro-grids, which is composed of a feature selection technique and a forecast engine (including neural network and evolutionary algorithm) in the lower level as the forecaster and an enhanced differential evolution algorithm in the upper level for optimizing the performance of the forecasters.
Abstract: Microgrids are a rapidly growing sector of smart grids, which will be an essential component in the trend toward distributed electricity generation. In the operation of a microgrid, forecasting the short-term load is an important task. With a more accurate short-term loaf forecast (STLF), the microgrid can enhance the management of its renewable and conventional resources and improve the economics of energy trade with electricity markets. However, STLF for microgrids is a complex forecast process, mainly because of the highly nonsmooth and nonlinear behavior of the load time series. In this paper, characteristics of the load time series of a typical microgrid are discussed and the differences with the load time series of traditional power systems are described. In addition, a new bilevel prediction strategy is proposed for STLF of microgrids. The proposed strategy is composed of a feature selection technique and a forecast engine (including neural network and evolutionary algorithm) in the lower level as the forecaster and an enhanced differential evolution algorithm in the upper level for optimizing the performance of the forecaster. The effectiveness of the proposed prediction strategy is evaluated by the real-life data of a university campus in Canada.

Journal ArticleDOI
TL;DR: The goal is to present how the smart grid can enable the utilization of available end-user devices as a resource to mitigate power system problems such as voltage collapse.
Abstract: Existing and forthcoming devices at the residential level have the ability to provide reactive power support. Inverters which connect distributed generation such as solar panels and pluggable hybrid electric vehicles (PHEVs) to the grid are an example. Such devices are not currently utilized by the power system. We investigate the integration of these end-user reactive-power-capable devices to provide voltage support to the grid via a secure communications infrastructure. We determine effective locations in the transmission system and show how reactive power resources connected at those buses can be controlled. Buses belong to reactive support groups which parallel the regions of the secure communications architecture that is presented. Ultimately, our goal is to present how the smart grid can enable the utilization of available end-user devices as a resource to mitigate power system problems such as voltage collapse.

Journal ArticleDOI
Jin Ma, Pu Zhang, Hong-jun Fu, Bo Bo, Zhao Yang Dong 
TL;DR: A novel method is developed in this paper to locate the disturbance source for the low-frequency oscillation that has happened several times in the interconnected big power grids in China recently with the help of PMUs.
Abstract: A smart power grid is an integration of the advanced measurement, communication, computer, and control techniques. Among all the state-of-the-art technologies in building a smart power grid, the phasor measurement unit (PMU) is an important and promising one. Nowadays in China, most ultrahigh- and high-voltage buses are all equipped with PMUs. This paper reports an application of PMU data on locating the disturbance source for the low-frequency oscillation that has happened several times in the interconnected big power grids in China recently. The posterior analysis by the Electric Power System Research Institute of China (CEPRI) has confirmed that these low-frequency oscillations are caused by the resonance phenomena. It is urgent to find the disturbance source in case it happens again. However, there have been no systematic and effective methods to locate the disturbance in a very large power system. The trial and error method has been implemented via the digital simulations, but in vain. To overcome this problem, a novel method is developed in this paper to locate the disturbance source with the help of PMUs. The method takes advantage of the PMU measurements to reduce the searching area for locating the disturbance source. Case studies show the efficiency of the proposed method.

Journal ArticleDOI
TL;DR: This paper presents an ac/dc hybrid smart power system that has advantages of both dc and ac grids and is verified by numerical simulation results.
Abstract: Recently, smart grids are attracting attention. Already, a smart grid based on an AC grid is proposed. However, no study on research is presented or published on a smart grid based on a dc grid. This paper presents an ac/dc hybrid smart power system. The proposed system has advantages of both dc and ac grids. The proposed power system consists of a wind generator and several controllable loads. The controllable loads have different capacities. Therefore, by applying power consumption control with the droop characteristic, the dc bus voltage is maintained within the acceptable range. As controllable loads, electric water heater and electric vehicle are assumed. Effectiveness of the proposed method is verified by numerical simulation results.

Journal ArticleDOI
TL;DR: It is shown that, under certain conditions, the presented model has a set of closed-form solutions, and the effects of random wind speed on the generated power can be readily assessed.
Abstract: In this paper a load dispatch model for the system consisting of both thermal generators and wind turbines is developed. The stochastic wind power is included in the model as a constraint. It is shown that, under certain conditions, the presented model has a set of closed-form solutions. The availability of closed-form solutions is helpful to gain more fundamental insights, such as the impact of a particular parameter on the optimal solution. Moreover, the feasible ranges of optimal solutions are given in the case that the output power of thermal turbines is restricted. Furthermore, the probability distribution and the average of solutions are derived. This is called the wait-and-see approach in the discipline of stochastic programming. The present work shows that the effects of random wind speed on the generated power can be readily assessed.

Journal ArticleDOI
TL;DR: The results indicate that the proposed algorithm improves the voltage profile of an island after the system reconfiguration compared with the algorithm that only considers real power balance.
Abstract: In response to disturbances, a self-healing system reconfiguration that splits a power network into self-sufficient islands can stop the propagation of disturbances and avoid cascading events This paper proposes an area partitioning algorithm that minimizes both real and reactive power imbalance between generation and load within islands The proposed algorithm is a smart grid technology that applies a highly efficient multilevel multi-objective graph partitioning technique Thus, it is applicable to very large power grids The proposed algorithm has been simulated on a 200- and a 22,000-bus test systems The results indicate that the proposed algorithm improves the voltage profile of an island after the system reconfiguration compared with the algorithm that only considers real power balance In doing so, the algorithm maintains the computational efficiency

Journal ArticleDOI
TL;DR: A new strategy to accommodate pulsed-power loads in microgrid power systems is presented, based on identifying the optimal charging profile and it is shown the proposed strategy is highly effective in reducing the adverse impact of pulsing power loads.
Abstract: Microgrid power systems are becoming increasingly common in a host of applications. In this work, the mitigation of the adverse affects of pulsed-power loads on these systems is considered. In microgrid power systems, pulsed loads are particularly problematic since the total system inertia is finite. Examples include ships and aircraft with high-power radars, pulsed weapons, and electromagnetic launch and recovery systems. In these systems, energy is collected from the system over a finite time period, locally stored, and then rapidly utilized. Herein, a new strategy to accommodate these loads is presented. This strategy is based on identifying the optimal charging profile. Using simulation and experiment, it is shown the proposed strategy is highly effective in reducing the adverse impact of pulsed-power loads.

Journal ArticleDOI
TL;DR: This paper provides selected examples of failures that have been predicted by intelligent distribution fault anticipation (DFA) algorithms and the data requirements and processing analysis to detect these failures are discussed.
Abstract: Certain smart grid technologies can reduce the number of customers affected by prolonged outages, and thereby increase reliability through automated switching to restore service. Such technologies are useful, but reactive in nature, performing their function only after a fault occurs and an outage has been detected. They must presume that nonfaulted feeder sections and alternative feeders are healthy and capable of carrying increased power flow. Research at Texas A&M University has demonstrated that sophisticated, automated real-time analysis of feeder electrical waveforms can be used to predict failures and assess the health of distribution lines and line apparatus. Reliability can be substantially improved by detecting, locating, and repairing incipient failures before catastrophic failure, often before an outage occurs. Requirements for data and computation are substantially greater than for devices like digital relays and power-quality meters, but feasible with modern electronics. This paper provides selected examples of failures that have been predicted by intelligent distribution fault anticipation (DFA) algorithms. The data requirements and processing analysis to detect these failures are discussed. The problems related to full-scale deployment of the proposed system in a utility-wide application are presented. The authors use experience gained from their long-term research to propose concepts for overcoming these impediments.

Journal ArticleDOI
TL;DR: The status of current smart grid related efforts are summarized, the direction of research and development activities supported by the DOE are described, and smart grid priorities are explained.
Abstract: In September 2001, the U.S. Department of Energy (DOE) sponsored a workshop to develop a roadmap on communication and control technologies for distributed energy resources. From this and subsequent activities with industry, academia, and other research institutions, the concepts and vision of an interactive and adaptable electricity system emerged; a vision that is now commonly referred to as smart grid. Supported by significant federal investment announced in 2009, the DOE, its national laboratories, and industry partners are now making significant strides in smart grid deployments, demonstrations, and research. An imperative underlying these activities is that they contribute to ensuring the steps taken in transitioning toward a smart grid retain a system with dependable performance to the economy and society it services. This paper summarizes the status of current smart grid related efforts, explains smart grid priorities, and describes the direction of research and development activities supported by the DOE.

Journal ArticleDOI
Jiyi Chen1, Wenyuan Li, Adriel Lau, Jiguo Cao1, Ke Wang1 
TL;DR: The B-Spline smoothing and Kernel smoothing based techniques to automatically cleanse corrupted and missing data are presented and a man-machine dialogue procedure is proposed to enhance the performance.
Abstract: Load curve data refers to the electric energy consumption recorded by meters at certain time intervals at delivery points or end user points, and contains vital information for day-to-day operations, system analysis, system visualization, system reliability performance, energy saving and adequacy in system planning. Unfortunately, it is unavoidable that load curves contain corrupted data and missing data due to various random failure factors in meters and transfer processes. This paper presents the B-Spline smoothing and Kernel smoothing based techniques to automatically cleanse corrupted and missing data. In implementation, a man-machine dialogue procedure is proposed to enhance the performance. The experiment results on the real British Columbia Transmission Corporation (BCTC) load curve data demonstrated the effectiveness of the presented solution.

Journal ArticleDOI
TL;DR: It is recommended that up to 50% of load be controlled with minimal inconvenience to customers to potentially enhance angle, voltage, frequency, and thermal stability in smart grid control systems.
Abstract: The implementation of highly realistic real-time, massive, online, multi-time frame simulations is proposed as a means for building a common vision of smart grid functions among politicians, regulators, managers, operators, engineers, and technicians. These massive simulations will include hundreds of participants that play roles of reliability coordinators, transmission operators, distribution operators, power plant operators, and substation operators. These highly visible drills can demonstrate how the new smart grid systems, people, and processes can all work together economically and reliably. The industry, especially smart grid system designers, can get feedback from low cost, safe, and easily configurable simulations instead of waiting for expensive and hardwired deployments. Direct load control of millions of customer appliances is identified as a silver bullet to build self-healing and maximal flow smart grids that can accommodate large penetrations of intermittent wind and solar generation and rapid load growth due to plug-in electric vehicles. The paper recommends that up to 50% of load be controlled with minimal inconvenience to customers to potentially enhance angle, voltage, frequency, and thermal stability. An expert operator decision model is described with a view to helping system developers build operator-centered and friendly smart grid control systems.