Demand response and smart grids—A survey
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.
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TL;DR: In this paper, the forecast errors of wind speed and solar irradiance are modeled by related probability distribution functions and then, by using the Latin hypercube sampling (LHS), the plausible scenarios of renewable generation for day-head energy and reserve scheduling are generated.
343 citations
Cites background from "Demand response and smart grids—A s..."
...However, over the past decade, alternative resources like demand response have become increasingly capable of providing a greater number and quantity of such electric grid services [3,4]....
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TL;DR: In this paper, the authors present a detailed technical overview of microgrid and smart grid in light of present development and future trend, including existing technical challenges, communication features, policies and regulation, etc.
Abstract: The modern electric power systems are going through a revolutionary change because of increasing demand of electric power worldwide, developing political pressure and public awareness of reducing carbon emission, incorporating large scale renewable power penetration, and blending information and communication technologies with power system operation. These issues initiated in establishing microgrid concept which has gone through major development and changes in last decade, and recently got a boost in its growth after being blessed by smart grid technologies. The objective of this paper is to presents a detailed technical overview of microgrid and smart grid in light of present development and future trend. First, it discusses microgrid architecture and functions. Then, smart features are added to the microgrid to demonstrate the recent architecture of smart grid. Finally, existing technical challenges, communication features, policies and regulation, etc. are discussed from where the future smart grid architecture can be visualized.
343 citations
Cites background from "Demand response and smart grids—A s..."
...Home (local) area network (HAN/LAN): Home (local) area network (HAN or LAN) implement to in-home smart devices and appliances such as plug-in electric vehicles (PEVs), programmable communicating thermostats, in-home displays (IHD) and distributed energy generation facilities [82,83]....
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...Thus, data transfer realizes not only from smart meter to meter data management system (MDMS) but also from MDMS to smart meter [82,83]....
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TL;DR: A comprehensive survey on the IoT-aided smart grid systems is presented in this article, which includes the existing architectures, applications, and prototypes of the IoTaided SG systems.
Abstract: Traditional power grids are being transformed into smart grids (SGs) to address the issues in the existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability, and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution, and utilization systems. SGs employ various devices for the monitoring, analysis, and control of the grid, deployed at power plants, distribution centers, and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation, and the tracking of such devices. This is achieved with the help of the Internet of Things (IoT). The IoT helps SG systems to support various network functions throughout the generation, transmission, distribution, and consumption of energy by incorporating the IoT devices (such as sensors, actuators, and smart meters), as well as by providing the connectivity, automation, and tracking for such devices. In this paper, we provide a comprehensive survey on the IoT-aided SG systems, which includes the existing architectures, applications, and prototypes of the IoT-aided SG systems. This survey also highlights the open issues, challenges, and future research directions for the IoT-aided SG systems.
313 citations
TL;DR: Simulation results show that this proposed DR algorithm, can promote SP profitability, reduce energy costs for CUs, balance energy supply and demand in the electricity market, and improve the reliability of electric power systems, which can be regarded as a win-win strategy for both SP and CUs.
312 citations
TL;DR: In this paper, the authors investigated heat pump systems in smart grids, focussing on fields of application and control approaches that have emerged in academic literature, based on a review of published literatu...
Abstract: This paper investigates heat pump systems in smart grids, focussing on fields of application and control approaches that have emerged in academic literature. Based on a review of published literatu ...
310 citations
Cites background from "Demand response and smart grids—A s..."
...Time scales and the need for flexibility in the power system The need for flexibility in the power system is frequently motivated by an increase in renewable energy [12,43] and the resulting need for an ability to react or plan ahead [18] for safe and efficient power system operation....
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...Those are with decreasing dynamics: Real time pricing, day ahead pricing and time of use tariffs [18]....
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...The mechanisms used to enable flexibility change with the service in the power system that is to be provided [12,18,44]....
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...A wider perspective is taken in reference [18] where the vision of a smart grid is defined as: “....
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...Although operation of small responsive loads [112,113] like heat pumps on the reserve markets is heavily discussed in review articles on demand side management, flexibility and smart grid [12,18,24], the examples concerning heat pumps on that field are limited [70,100,101,105,114–121]....
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References
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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
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
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 2004TL;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
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