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Smart Grid, IEEE Transactions on

Issue 4 • Date Dec. 2013

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Displaying Results 1 - 25 of 76
  • Table of Contents

    Page(s): C1 - 1742
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  • IEEE Transactions on Smart Grid publication information

    Page(s): C2
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  • A Real-Time Constraint Management Approach Through Constraint Similarity and Pattern Recognition in Power System

    Page(s): 1743 - 1750
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    In real-time energy market, Regional Transmission Organization (RTO) dispatchers meet the energy demand while respecting transmission security constraints using the least-cost security constrained economic dispatch program, called Unit Dispatch System (UDS). If the transmission violation detected by the Energy Management System (EMS) requires redispatch, system operator will transfer the transmission constraint information to UDS for resolution through a manual process. Dispatchers need to make an educated guess on constraint trends to support their manual redispatch process. However, as the number of constraints increases during peak hours, this process is more and more complicated and the system becomes less manageable. This paper intends to challenge this operational difficulty through a similarity model to reveal the constraint relations and a heuristic pattern recognition method to categorize constraints into controllable constraint groups (CCG). System operators only take care of a dominant constraint in each CCG using controllable units instead of them all. This will make system much more manageable during peak hours, therefore, will increase effectiveness and efficiency of system operations. View full abstract»

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  • S^{3}A : A Secure Data Sharing Mechanism for Situational Awareness in The Power Grid

    Page(s): 1751 - 1759
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    Power grids are complex systems whose security and reliability depend on the collaboration among all the concerning entities, including peer operators, government authorities, etc. Data sharing in the manner of centralizing the data of peer operators in a common data center is highly desirable and even necessary to the collaboration and, in particular, applications such as global situational awareness in response to critical events. However, due to the concerns about privacy and security of data, the operators are reluctant to outsource their data. Hence, we propose S3A, a mechanism that enables secure and efficient data sharing. The proposed scheme is demonstrated to achieve secure and unlinkable storage as well as fine-grained access control. View full abstract»

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  • A Bayesian-Based Approach for a Short-Term Steady-State Forecast of a Smart Grid

    Page(s): 1760 - 1771
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    Future distribution networks are undergoing radical changes, due to the high level of penetration of dispersed generation and information/communication technologies, evolving into the new concept of the Smart Grid. Dispersed generation systems, such as wind farms and photovoltaic power plants, require particular attention due to their incorporation of uncertain energy sources. Further and significant well-known uncertainties are introduced by the load demands. In this case, many new technical considerations must be addressed to take into account the impacts of these uncertainties on the planning and operation of distribution networks. This paper proposes novel Bayesian-based approaches to forecast the power production of wind and photovoltaic generators and phase load demands. These approaches are used in a probabilistic short-term steady-state analysis of a Smart Grid obtained by means of a probabilistic load flow performed using the Point Estimate Method. Numerical applications on a 30-busbar, low-voltage distribution test system with wind farms and photovoltaic power plants connected at different busbars are presented and discussed. View full abstract»

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  • A Dynamic Algorithm for Facilitated Charging of Plug-In Electric Vehicles

    Page(s): 1772 - 1779
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    Plug-in electric vehicles (PEVs) are a rapidly developing technology that can reduce greenhouse gas emissions and change the way vehicles obtain power. PEV charging stations will most likely be available at home and at work, offering flexible charging options. Ideally, each vehicle will charge when electricity prices are relatively low, to minimize the cost to the consumer and maximize societal benefits. A demand response (DR) service for a fleet of PEVs could yield such charging schedules by regulating consumer electricity use during certain time periods, in order to meet an obligation to the market. We construct an automated DR mechanism for a fleet of PEVs that facilitates vehicle charging to meet the needs of the vehicles and satisfy a load scheduling obligation. Our dynamic algorithm depends only on the knowledge of driving behaviors from a previous similar day, and uses a simple adjusted pricing scheme to instantly assign feasible and satisfactory charging schedules to thousands of vehicles in a fleet as they plug-in. The charging schedules generated using our adjusted pricing scheme can ensure that a new demand peak is not created and can reduce the consumer cost by over 30% when compared to standard charging, which may also increase peak demand by 3.5%. In this paper, we present our formulation, algorithm, and results. View full abstract»

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  • A Unified Single- and Three-Phase Control for Grid Connected Electric Vehicles

    Page(s): 1780 - 1790
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    In order to reduce cost, size, weight, and volume of on board chargers in electric vehicles, it has been proposed to pursue integration for the dual usage of converters for both charging and propulsion. The solution here goes further in that it also supports the control of slow single-phase and fast three-phase charging through one and the same power electronic converter. A unified control methodology for the on-board chargers in electric vehicles is proposed. The control is distinguished in that it can perform four-quadrant operation while connected in single-phase or three-phase mode. The operation and network synchronization are automatically adjusted based on given terminal voltage and current measurements without the need for supplementary status signals. An analysis illustrates how the various measurements are processed for obtaining single- and three-phase flexibility while retaining compatibility with well-established methods of converter current mode control. The proposed control is validated via detailed simulation and demonstrated in a smart grid laboratory. The hardware implementation in the laboratory substantiates the claims of flexible single- and three-phase control. View full abstract»

    Open Access
  • Optimum Sizing of Distributed Generation and Storage Capacity in Smart Households

    Page(s): 1791 - 1801
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    In the near future, a smart grid will accommodate customers who are prepared to invest in generation-battery systems and employ energy management systems in order to cut down on their electricity bills. The main objective of this paper is to determine the optimum capacity of a customer's distributed-generation system (such as a wind turbine) and battery within the framework of a smart grid. The proposed approach involves developing an electricity management system based on stochastic variables, such as wind speed, electricity rates, and load. Then, a hybrid stochastic method based on Monte Carlo simulation and particle swarm optimization is proposed to determine the optimum size of the wind generation-battery system. Several sensitivity analyses demonstrate the proper performance of the proposed method in different conditions. View full abstract»

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  • Coordination of the Charging of Electric Vehicles Using a Multi-Agent System

    Page(s): 1802 - 1809
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    An agent-based control system that coordinates the battery charging of electric vehicles in distribution networks is presented. The objective of the control system is to charge the electric vehicles at times of low electricity prices within distribution network technical constraints. Search techniques and neural networks are used for the decision making of the agents. The ability of the control system to work successfully when the distribution network is operated within its loading limits and when the loading limits are violated is demonstrated through experimental validation . View full abstract»

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  • Privacy-Preserving Energy Scheduling in Microgrid Systems

    Page(s): 1810 - 1820
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    We propose privacy-preserving energy management strategies for a microgrid system that consists of several cells and a central control center, with each cell composed of a local controller, a distributed renewable energy generator, and some energy consuming customers. It is assumed that the cells can cooperate by exchanging their locally generated energy and they can obtain external energy, both through the control center. The goal of energy management is to distribute the energy flow within the microgrid system to meet the energy demands of the customers and to minimize the cost of the external energy imported to the system. The problem is formulated as a linear optimization problem with privacy constraints. However, the privacy constraint, i.e., the constraint that the information related to the customers' behaviors in a cell cannot be disclosed to other cells and/or the control center, makes the standard linear programming tools not directly applicable. This motivates us to develop privacy-preserving schemes for effective energy management in such systems. To this end, we develop a dual decomposition-based algorithm and a fast suboptimal algorithm to solve the energy management problem with privacy constraints in a distributed fashion. Simulation results are provided to demonstrate the superior performance of the proposed techniques over the traditional methods. View full abstract»

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  • IEC 61850 Enabled Automatic Bus Transfer Scheme for Primary Distribution Substations

    Page(s): 1821 - 1828
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    Automatic bus transfer scheme (ABTS) is the practice of transferring a load bus to an alternate source when the normal power supply fails or is tripped thus ensuring continuity of supply. This paper comprehensively reviews existing schemes and implementations of ABTS especially for motor bus. To limit the fault levels, during certain situations, the transformers supplying a primary distribution substation can be run in split instead of parallel operation. This is because during outages if one transformer is lost, overloading of remaining transformers, if it occurs, can be managed. This paper proposes an ABTS for a primary distribution substation for a utility facing such a situation and present details of its implementation. In the proposed scheme which is enabled by digital communications, if a transformer is lost, the bus section circuit breaker (CB) will be closed automatically after the incomer CB trips. The proposed ABTS has been implemented in the bus section relay for a new 11 kV switchboard where inter-relay communication is based on the IEC 61850 suites of standard. The contribution of this paper is that it shows how to use a standard automation scheme smartly to defer network reinforcements and manage fault levels in primary distribution substation. View full abstract»

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  • Smart Overhead Lines Autoreclosure Algorithm Based on Detailed Fault Analysis

    Page(s): 1829 - 1838
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1242 KB) |  | HTML iconHTML  

    This paper presents a novel numerical algorithm implemented in a unique methodology for the control of smart single-phase autoreclosure and comprehensive fault analysis for overhead lines using synchronized measurement technology. The algorithm improves on existing methodologies for adaptive single-phase autoreclosure, fault location, detailed disturbance records analysis, and fault data management. It is based on line current and voltage data sampled at both line terminals and synchronized sampling of all analogue input variables is assumed in this paper. The proposed algorithm is derived in the spectral domain and based on the application of the Discrete Fourier Transform. The electrical arc as a source of higher harmonics is included in the complete fault model and represents the starting point for the development of the new algorithm. The algorithm's distinctive feature is that it can determine both the fault arc and the fault resistance. The presence or absence of an arc resistance is used to determine the nature of the fault. The algorithm can be applied to both short and long lines. The algorithm is thoroughly tested using electromagnetic transient simulations of an overhead line connected between two active networks, as well as with field data. View full abstract»

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  • Special section on real-time demand response [Section ToC]

    Page(s): 1839 - 1840
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  • Guest Editorial: Introduction to the special section on real-time demand response

    Page(s): 1841
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  • Reporting Available Demand Response

    Page(s): 1842 - 1851
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1307 KB) |  | HTML iconHTML  

    Demand response is increasingly important in many power systems but Transmission System Operators (TSO) require confirmation that the response is available if it is to be used effectively. Demand response may be used to minimise the amount of spinning reserve obtained from partially loaded generators. The ability of the proposed smart metering communication system in the U.K. to report the available demand response from domestic appliances was examined. This communication system expects to send all data traffic at an average rate of about 190 Mbytes per minute through a central Data Communication Company (DCC) to any actor operating in the power system. It is unlikely that this communication system will, in addition, support reporting demand response in near real-time. Using load profiles of fridges, cooking appliances and washers and dryers, the load profiles of 40 000 houses were constructed. These load profiles were used to calculate the average number of load changes in a typical house, a 11/0.4 kV transformer and a high voltage substation. Using these average numbers of load changes and the number of transformers and substations in the U.K. power system, the number of messages sent by all smart meters in the U.K. was calculated. It is shown that the wide area network proposed for the U.K. need to send an additional 162 Mbytes per minute to report demand response in near real-time. Then, a hierarchically arranged communication system that follows the hierarchy of electrical network was examined. It was assumed that aggregating units are installed at distribution transformers and substations. It is shown that by aggregating and sending only measurement changes, the number of bytes sent through the U.K. smart metering communication system per minute could be reduced from 162 M to 30 k. This has important implications as the U.K. is now finalizing the specifications for smart metering communications for about 27 million smart electricity meters that will be instal- ed in the period 2014-2020. View full abstract»

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  • Relative kW Response to Residential Time-Varying Pricing in British Columbia

    Page(s): 1852 - 1860
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    We apply graphical exploration and regression analysis to estimate 1717 participants' relative kW responses in BC Hydro's residential TOU/CPP pilot study. We define a customer's relative kW response as the percentage change in the customer's hourly kW demand due to exposure to time-varying pricing. Compared to the control group of customers facing non-TOU rates, we find that TOU pricing yields a statistically-significant evening peak kW decrease of 4-11%, after controlling for the effects of day of the week, month of the year, weather, customer location, and customer size. CPP produces an additional peak kW reduction of about 9%, which can be further increased to about 33% through remotely-activated load control of space and water heaters. Hence, a scheme of TOU pricing augmented with CPP and load control on system peak days can be a highly effective demand-response strategy for winter-peaking utilities. View full abstract»

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  • Residential Appliance DR Energy Management With Electric Privacy Protection by Online Stochastic Optimization

    Page(s): 1861 - 1869
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    This paper explores electric privacy issues that may occur along with the residential appliance demand response (DR) energy management in smart meters. Three metrics are introduced to quantitatively measure the spatial and/or temporal similarity of metered power profiles. The online stochastic optimization adopts the scenario-based approach via Monte Carlo (MC) simulation for minimizing the sum of the expected electricity payment and the weighted difference among metered power profiles for the entire day, which are measured by the three similarity metrics, in order to balance the tradeoff between the electricity payment and the electric privacy protection. In addition, batteries are employed to disguise the actual appliance power profile along with the scheduling horizon and enhance the electric privacy protection. Numerical case studies illustrate the effectiveness of the proposed approach for protecting the electric privacy in residential appliance DR energy management. View full abstract»

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  • Incorporating Non-Intrusive Load Monitoring Into Building Level Demand Response

    Page(s): 1870 - 1877
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    This paper brings the application of non-intrusive load monitoring (NILM) into demand response (DR). NILM is usually applied to identify the major loads in buildings, which is very promising in meeting the load monitoring requirements of demand response. Unlike the traditional approach of NILM in energy auditing, a new NILM system for DR is established based on a comprehensive analysis on the requirement of demand response. The new system is designed from both hardware and software aspects with a more practical load space and a more explicit measuring criteria. The ultimate goal of this paper is to pave the road for the future researchers to work in NILM for demand response. View full abstract»

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  • Hardware Design of Smart Home Energy Management System With Dynamic Price Response

    Page(s): 1878 - 1887
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    The smart grid initiative and electricity market operation drive the development known as demand-side management or controllable load. Home energy management has received increasing interest due to the significant amount of loads in the residential sector. This paper presents a hardware design of smart home energy management system (SHEMS) with the applications of communication, sensing technology, and machine learning algorithm. With the proposed design, consumers can easily achieve a real-time, price-responsive control strategy for residential home loads such as electrical water heater (EWH), heating, ventilation, and air conditioning (HVAC), electrical vehicle (EV), dishwasher, washing machine, and dryer. Also, consumers may interact with suppliers or load serving entities (LSEs) to facilitate the load management at the supplier side. Further, SHEMS is designed with sensors to detect human activities and then a machine learning algorithm is applied to intelligently help consumers reduce total payment on electricity without or with little consumer involvement. Finally, simulation and experiment results are presented based on an actual SHEMS prototype to verify the hardware system. View full abstract»

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  • Active Demand Response Using Shared Energy Storage for Household Energy Management

    Page(s): 1888 - 1897
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    In a deregulated market, wholesale energy costs and distribution investment costs contribute significantly to consumers' electricity bills. However, in a low carbon electrical power system, the two cost pressure points may not be synchronous in time and space with each other. This paper develops a novel methodology for home area energy management as a key vehicle for demand response, using electricity storage devices. The aim is to enable energy storage at consumer premises to not only take advantage of lower wholesale energy prices, but also to support low voltage (LV) distribution networks for reducing network investment. New operation strategies for domestic energy storage to facilitate demand response (DR) are developed in the paper. They have the capability to maximize the overall savings in energy costs and investment costs. In the proposed approach, the operation of home-area energy storage devices is jointly conducted by end customers and network operators. The purpose is to fight for an optimal balance between DRs to energy price and to network congestion, and thus to maximize benefits for both consumers and network operators. An intensive study is carried out to investigate the impacts of different dispatch strategies on wholesale energy costs and network investment costs. Benefit quantification methods are introduced as well to evaluate the total benefits in terms of savings in energy costs and investment costs that can be brought along by the proposed operation approach. The demonstration is carried out on two practical distribution networks with varying utilization levels for one typical calendar day and a whole year. View full abstract»

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  • Coordinating Storage and Demand Response for Microgrid Emergency Operation

    Page(s): 1898 - 1908
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    Microgrids are assumed to be established at the low voltage distribution level, where distributed energy sources, storage devices, controllable loads and electric vehicles are integrated in the system and need to be properly managed. The microgrid system is a flexible cell that can be operated connected to the main power network or autonomously, in a controlled and coordinated way. The use of storage devices in microgrids is related to the provision of some form of energy buffering during autonomous operating conditions, in order to balance load and generation. However, frequency variations and limited storage capacity might compromise microgrid autonomous operation. In order to improve microgrid resilience in the moments subsequent to islanding, this paper presents innovative functionalities to run online, which are able to manage microgrid storage considering the integration of electric vehicles and load responsiveness. The effectiveness of the proposed algorithms is validated through extensive numerical simulations. View full abstract»

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  • Leader-Follower Strategies for Energy Management of Multi-Microgrids

    Page(s): 1909 - 1916
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    This paper presents the application of bilevel programming for analyzing competitive situations of hierarchical decision making between an Energy Services Provider representing several microgrids (MGs)-each one comprising controllable loads and dispatchable distributed generation units-and a large central production unit. The rules of the interaction between the two entities are determined in a bilateral contract. This operation is compared to the vertically integrated operation of this system, i.e., only one entity manages both the central production unit and the distributed resources of the MG. This comparison highlights the benefits of applying a two level structure in the simulated interaction. View full abstract»

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  • Electrical Load Tracking Analysis for Demand Response in Energy Intensive Enterprise

    Page(s): 1917 - 1927
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    It is important for both energy intensive enterprises (EIEs) and the utilities to analyze the electrical load tracking capacity of EIEs, so as to utilize resources in EIEs, and promote the participation of EIEs in Demand Response (DR) programs. An electrical load tracking problem integrating power generations self-scheduling (PGSS) and flexible load adjustment (FLA) is introduced. The relationships among PGSS, FLA, and electrical load tracking capacity are discussed. A method to decide whether a load curve can be well-tracked is presented, and reference ideas for adjusting load curve are given too. Mathematical programming models are also presented for discussing and testing the effect of electrical load tracking. The proposed methods and models are tested in numerical simulations. View full abstract»

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  • Real-Time Demand Response From Energy Shifting in Distributed Multi-Generation

    Page(s): 1928 - 1938
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    In this paper, a comprehensive dedicated framework is set up to analyze distributed multi-generation (DMG) systems for the purpose of identifying and quantifying their potential to participate in real-time demand response (DR) programmes. At first, flexibility of DMG systems with multiple interconnected plant components is exploited to identify the optimal operational strategy in the presence of half-hourly pricing. Then, the costs and benefits of providing further real-time DR are assessed by taking into account different energy shifting strategies. The novel concept of electricity shifting potential is introduced to establish the upper limit to the possible reduction of the electricity flowing from the electrical grid to the DMG system. The maximum profitable energy shifting that can be activated in the presence of given DR incentives is established on the basis of a DR profitability map. The key point is that energy shifting can be deployed inside the local DMG system to respond to given DR signals without reducing the users' energy demand and thus without affecting their comfort level. Examples of real-time DR for a trigeneration system referring to half-hourly periods during selected Summer and Winter days are illustrated and discussed. View full abstract»

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  • Modeling Intelligent Energy Systems: Co-Simulation Platform for Validating Flexible-Demand EV Charging Management

    Page(s): 1939 - 1947
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    Energy systems experience a rise in complexity: new technologies, topologies and components, tighter links to other systems like markets and the increased usage of information technology. This leads to challenging questions that can not be answered via traditional methods. The goal of including renewable energy and clean technologies in the grid, however, requires solutions for the resulting complex problems. This paper investigates dynamic demand response for intelligent electric vehicle charging as a use-case for detailed hybrid models that cannot be properly handled by traditional tools alone. Universal modeling languages and specialized domain-specific modeling solutions are brought together via standardized co-simulation interfaces to achieve maximal flexibility and minimal implementation efforts. This combination of previously numerically incompatible modeling paradigms enables a detailed look into the dynamics of hybrid component models while keeping the comfort and the strength of established tools. This coupling of a Modelica-based physical simulation engine, a commercial power system simulation tool and an agent-based discrete event simulator for energy grids results in a novel co-simulation platform. This visionary concept provides the high level of detail, scope, flexibility, scalability and accuracy in simulations needed to analyze and optimize energy systems of the future. View full abstract»

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Aims & Scope

The IEEE Transactions on Smart Grid is a cross disciplinary and internationally archival journal aimed at disseminating results of research on smart grid that relates to, arises from, or deliberately influences energy generation, transmission, distribution and delivery. The journal publishes original research on theories and development on principles of smart grid technologies and systems. The Transactions also welcomes manuscripts on design, implementation and evaluation of power systems that are affected by smart grid. Surveys of existing work on smart grid may also be considered for publication when they propose a new viewpoint on history and a challenging perspective on the future of smart grid.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Mohammad Shahidehpour
Illinois Institute of Technology