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Journal ArticleDOI

Demand response and smart grids—A survey

01 Feb 2014-Renewable & Sustainable Energy Reviews (Pergamon)-Vol. 30, pp 461-478
TL;DR: In this article, a survey of demand response potentials and benefits in smart grids is presented, with reference to real industrial case studies and research projects, such as smart meters, energy controllers, communication systems, etc.
Abstract: The smart grid is conceived of as an electric grid that can deliver electricity in a controlled, smart way from points of generation to active consumers. Demand response (DR), by promoting the interaction and responsiveness of the customers, may offer a broad range of potential benefits on system operation and expansion and on market efficiency. Moreover, by improving the reliability of the power system and, in the long term, lowering peak demand, DR reduces overall plant and capital cost investments and postpones the need for network upgrades. In this paper a survey of DR potentials and benefits in smart grids is presented. Innovative enabling technologies and systems, such as smart meters, energy controllers, communication systems, decisive to facilitate the coordination of efficiency and DR in a smart grid, are described and discussed with reference to real industrial case studies and research projects.
Citations
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Journal ArticleDOI
TL;DR: In this paper, the impact of three major strategies for peak load shaving, namely demand side management (DSM), integration of energy storage system (ESS), and integration of electric vehicle (EV) to the grid has been discussed in detail.
Abstract: In this study, a significant literature review on peak load shaving strategies has been presented. The impact of three major strategies for peak load shaving, namely demand side management (DSM), integration of energy storage system (ESS), and integration of electric vehicle (EV) to the grid has been discussed in detail. Discussion on possible challenges and future research directions for each type of the strategy has also been included in this review. For the energy storage system, different technologies used for peak load shaving purpose, which include their methods of operation and control have been elaborated further. Finally, the sizing of the ESS storage system is discussed. For the demand side management system, various management methods and challenges associated with DSM implementation have been thoroughly explained. A detailed discussion on the electric vehicle strategy has also been included in the review, which considers the integration, control and operation techniques for implementing the peak load shaving.

303 citations

Journal ArticleDOI
TL;DR: This review covers the recent works done in the area of scheduling algorithms for charging EVs in smart grid and reviews the key results in this field following the classification proposed.
Abstract: Electric vehicles (EVs) are being introduced by different manufacturers as an environment-friendly alternative to vehicles with internal combustion engines, with several benefits. The number of EVs is expected to grow rapidly in the coming years. However, uncoordinated charging of these vehicles can put a severe stress on the power grid. The problem of charge scheduling of EVs is an important and challenging problem and has seen significant research activity in the last few years. This review covers the recent works done in the area of scheduling algorithms for charging EVs in smart grid. The works are first classified into two broad classes of unidirectional versus bidirectional charging, and then, each class is further classified based on whether the scheduling is centralized or distributed and whether any mobility aspects are considered or not. It then reviews the key results in this field following the classification proposed. Some interesting research challenges that can be addressed are also identified.

298 citations


Cites background from "Demand response and smart grids—A s..."

  • ...At the same time, this protects the grid from overloading at peak hours and allows the ISO to better manage the power system [9], [10]....

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  • ...It also enables users to update their energy consumption profiles based on real-time power market information and demand-side management, allowing for better balance between supply and demand [8], [9]....

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  • ...balance supply/demand potential of the grid [9]....

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Journal ArticleDOI
TL;DR: In this article, a multi-objective operational scheduling method for charging/discharging of EVs in a smart distribution system is proposed, which aims at minimizing the total operational costs and emissions.

296 citations


Cites methods from "Demand response and smart grids—A s..."

  • ...First, the distribution system should be equipped with AMI system to measure the charge/discharge amount of each EV [28]....

    [...]

Journal ArticleDOI
TL;DR: In this paper, the authors defined, classified and discussed the latest flexibility treatments in power system based on a comprehensive literature study, and specifically considered the abilities, barriers, and inherent attributes of power systems' potential to deal with high integration of Variable Generations (VGs) in future flexible power systems.
Abstract: Renewables are going to make our planet a better place to live. These clean resources of energy can bring a handful of advantages to the future electricity industries. Nevertheless, the large percentage of renewables integration can cause some operational issues, in power systems, which are needed to be identified and coped with. This paper defines, classifies and discusses the latest flexibility treatments in power system based on a comprehensive literature study. The current work specifically considers the abilities, barriers, and inherent attributes of power systems’ potential to deal with high integration of Variable Generations (VGs) in future flexible power systems.

290 citations

Journal ArticleDOI
TL;DR: The concept of Proof of Energy is proposed as a novel consensus protocol for P2P energy exchanges managed by DLT and an application of the proposed infrastructure considering a Virtual Power Plant aggregator and residential prosumers endowed with a new transactive controller to manage the electrical storage system is discussed.
Abstract: The unpredictability and intermittency introduced by Renewable Energy Sources (RESs) in power systems may lead to unforeseen peaks of energy production, which might differ from energy demand. To manage these mismatches, a proper communication between prosumers (i.e., users with RESs that can either inject or absorb energy) and active users (i.e., users that agree to have their loads changed according to the system needs) is required. To achieve this goal, the centralized approach used in traditional power systems is no longer possible because both prosumers and active users would like to take part in energy transactions, and a decentralized approach based on transactive energy systems (TESs) and Peer-to-Peer (P2P) energy transactions should be adopted. In this context, the Distributed Ledger Technology (DLT), based on the blockchain concept arises as the most promising solution to enable smart contracts between prosumers and active users, which are safely guarded in blocks with cryptographic hashes. The aim of this paper is to provide a review about the deployment of decentralized TESs and to propose and discuss a transactive management infrastructure. In this context, the concept of Proof of Energy is proposed as a novel consensus protocol for P2P energy exchanges managed by DLT. An application of the proposed infrastructure considering a Virtual Power Plant (VPP) aggregator and residential prosumers endowed with a new transactive controller to manage the electrical storage system is discussed.

285 citations


Cites background from "Demand response and smart grids—A s..."

  • ...In recent years, the concepts of Demand-Side Management (DSM) and DR have arisen in order to balance energy generation with energy consumption [5] and help preventing the congestion problems [6]....

    [...]

References
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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: An overview and a taxonomy for DSM is given, the various types of DSM are analyzed, and an outlook on the latest demonstration projects in this domain is given.
Abstract: Energy management means to optimize one of the most complex and important technical creations that we know: the energy system. While there is plenty of experience in optimizing energy generation and distribution, it is the demand side that receives increasing attention by research and industry. Demand Side Management (DSM) is a portfolio of measures to improve the energy system at the side of consumption. It ranges from improving energy efficiency by using better materials, over smart energy tariffs with incentives for certain consumption patterns, up to sophisticated real-time control of distributed energy resources. This paper gives an overview and a taxonomy for DSM, analyzes the various types of DSM, and gives an outlook on the latest demonstration projects in this domain.

2,647 citations

Journal ArticleDOI
TL;DR: The main objective of this paper is to provide a contemporary look at the current state of the art in smart grid communications as well as to discuss the still-open research issues in this field.
Abstract: For 100 years, there has been no change in the basic structure of the electrical power grid. Experiences have shown that the hierarchical, centrally controlled grid of the 20th Century is ill-suited to the needs of the 21st Century. To address the challenges of the existing power grid, the new concept of smart grid has emerged. The smart grid can be considered as a modern electric power grid infrastructure for enhanced efficiency and reliability through automated control, high-power converters, modern communications infrastructure, sensing and metering technologies, and modern energy management techniques based on the optimization of demand, energy and network availability, and so on. While current power systems are based on a solid information and communication infrastructure, the new smart grid needs a different and much more complex one, as its dimension is much larger. This paper addresses critical issues on smart grid technologies primarily in terms of information and communication technology (ICT) issues and opportunities. The main objective of this paper is to provide a contemporary look at the current state of the art in smart grid communications as well as to discuss the still-open research issues in this field. It is expected that this paper will provide a better understanding of the technologies, potential advantages and research challenges of the smart grid and provoke interest among the research community to further explore this promising research area.

2,331 citations

Book
01 Jan 2004
TL;DR: In this article, the authors present an overview of the early history of the electric power industry, including the early pioneers of the electrical power industry and the development of the modern electric power system.
Abstract: Preface.1 Basic Electric and Magnetic Circuits.1.1 Introduction to Electric Circuits.1.2 Definitions of Key Electrical Quantities.1.3 Idealized Voltage and Current Sources.1.4 Electrical Resistance.1.5 Capacitance.1.6 Magnetic Circuits.1.7 Inductance.1.8 Transformers.2 Fundamentals of Electric Power.2.1 Effective Values of Voltage and Current.2.2 Idealized Components Subjected to Sinusoidal Voltages.2.3 Power Factor.2.4 The Power Triangle and Power Factor Correction.2.5 Three-Wire, Single-Phase Residential Wiring.2.6 Three-Phase Systems.2.7 Power Supplies.2.8 Power Quality.3 The Electric Power Industry.3.1 The Early Pioneers: Edison, Westinghouse, and Insull.3.2 The Electric Utility Industry Today.3.3 Polyphase Synchronous Generators.3.4 Carnot Efficiency for Heat Engines.3.5 Steam-Cycle Power Plants.3.6 Combustion Gas Turbines.3.7 Combined-Cycle Power Plants.3.8 Gas Turbines and Combined-Cycle Cogeneration.3.9 Baseload, Intermediate and Peaking Power Plants.3.10 Transmission and Distribution.3.11 The Regulatory Side of Electric Power.3.12 The Emergence of Competitive Markets.4 Distributed Generation.4.1 Electricity Generation in Transition.4.2 Distributed Generation with Fossil Fuels.4.3 Concentrating Solar Power (CSP) Technologies.4.4 Biomass for Electricity.4.5 Micro-Hydropower Systems.4.6 Fuel Cells.4.6.7 Electrical Characteristics of Real Fuel Cells.4.6.8 Types of Fuel Cells.4.6.9 Hydrogen Production.5 Economics of Distributed Resources.5.1 Distributed Resources (DR).5.2 Electric Utility Rate Structures.5.3 Energy Economics.5.4 Energy Conservation Supply Curves.5.5 Combined Heat and Power (CHP).5.6 Cooling, Heating, and Cogeneration.5.7 Distributed Benefits.5.8 Integrated Resource Planning (IRP) and Demand-Side Management (DSM).6 Wind Power Systems.6.1 Historical Development of Wind Power.6.2 Types of Wind Turbines.6.3 Power in the Wind.6.4 Impact of Tower Height.6.5 Maximum Rotor Efficiency.6.6 Wind Turbine Generators.6.7 Speed Control for Maximum Power.6.8 Average Power in the Wind.6.9 Simple Estimates of Wind Turbine Energy.6.10 Specific Wind Turbine Performance Calculations.6.11 Wind Turbine Economics.7 The Solar Resource.7.1 The Solar Spectrum.7.2 The Earth's Orbit.7.3 Altitude Angle of the Sun at Solar Noon.7.4 Solar Position at any Time of Day.7.5 Sun Path Diagrams for Shading Analysis.7.6 Solar Time and Civil (Clock) Time.7.7 Sunrise and Sunset.7.8 Clear Sky Direct-Beam Radiation.7.9 Total Clear Sky Insolation on a Collecting Surface.7.10 Monthly Clear-Sky Insolation.7.11 Solar Radiation Measurements.7.12 Average Monthly Insolation.8 Photovoltaic Materials and Electrical Characteristics.8.1 Introduction.8.2 Basic Semiconductor Physics.8.3 A Generic Photovoltaic Cell.8.4 From Cells to Modules to Arrays.8.5 The PV I -V Curve Under Standard Test Conditions (STC).8.6 Impacts of Temperature and Insolation on I -V Curves.8.7 Shading impacts on I-V curves.8.8 Crystalline Silicon Technologies.8.9 Thin-Film Photovoltaics.9 Photovoltaic Systems.9.1 Introduction to the Major Photovoltaic System Types.9.2 Current-Voltage Curves for Loads.9.3 Grid-Connected Systems.9.4 Grid-Connected PV System Economics.9.5 Stand-Alone PV Systems.9.6 PV-Powered Water Pumping.APPENDIX A: Useful Conversion Factors.APPENDIX B: Sun-Path Diagrams.APPENDIX C: Hourly Clear-Sky Insolation Tables.APPENDIX D: Monthly Clear-Sky Insolation Tables.APPENDIX E: Solar Insolation Tables byCity.APPENDIX F: Maps of Solar Insolation.Index.

1,884 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