Smart grid

About: Smart grid is a research topic. Over the lifetime, 37536 publications have been published within this topic receiving 627844 citations. The topic is also known as: intelligent grid.

Design and Demonstration of a 3.6-kV–120-V/10-kVA Solid-State Transformer for Smart Grid Application

Abstract: Solid-state transformer (SST) has been regarded as one of the most important emerging technologies for traction system and smart grid application. This paper presents the system design and performance demonstration of a high-voltage SST lab prototype that works as the active grid interface in smart grid architecture. Specifically, the designs of the key components of the system, including both power stage and controller platform, are presented. In addition, the advanced control system is developed to achieve high-performance operation. Furthermore, integration issues of SST with dc microgrid are presented. Lastly, tests under different scenarios are conducted to verify the following advanced features of the presented SST technology: 1) VAR compensation; 2) voltage regulation; 3) source voltage sag operation; and 4) microgrid integration.

Generating Statistically Correct Random Topologies for Testing Smart Grid Communication and Control Networks

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.

Connection locator in a power aggregation system for distributed electric resources

Abstract: Systems and methods are described for a power aggregation system. In one implementation, a service establishes individual Internet connections to numerous electric resources intermittently connected to the power grid, such as electric vehicles. The Internet connection may be made over the same wire that connects the resource to the power grid. The service optimizes power flows to suit the needs of each resource and each resource owner, while aggregating flows across numerous resources to suit the needs of the power grid. The service can bring vast numbers of electric vehicle batteries online as a new, dynamically aggregated power resource for the power grid. Electric vehicle owners can participate in an electricity trading economy regardless of where they plug into the power grid.

Smart grid design for efficient and flexible power networks operation and control

Abstract: The modernization of the US electric power infrastructure, especially in lieu of its aging, overstressed networks; shifts in social, energy and environmental policies, and also new vulnerabilities, is a national concern. Our system are required to be more adaptive and secure more than every before. Consumers are also demanding increased power quality and reliability of supply and delivery. As such, power industries, government and national laboratories and consortia have developed increased interest in what is now called the Smart Grid of the future. The paper outlines Smart Grid intelligent functions that advance interactions of agents such as telecommunication, control, and optimization to achieve adaptability, self-healing, efficiency and reliability of power systems. The author also presents a special case for the development of Dynamic Stochastic Optimal Power Flow (DSOPF) technology as a tool needed in Smart Grid design. The integration of DSOPF to achieve the design goals with advanced DMS capabilities are discussed herein. This reference paper also outlines research focus for developing next generation of advance tools for efficient and flexible power systems operation and control.

A review of demand side management business models in the electricity market

Abstract: Demand side management (DSM) can be defined as modifications in the demand side energy consumption pattern to foster better efficiency and operations in electrical energy systems. DSM activities, which are classified into “energy efficiency (EE)” and “demand response (DR)” are becoming more popular due to technological advances in smart grids and electricity market deregulation. However, it can be argued that ensuring DSM sustainability requires creating suitable business models. Business models are influenced by different factors such as electricity market regulation, mechanisms, power system characteristics and infrastructure. The proliferation of smart grid infrastructure, distributed generation, intermittent renewable energy resources and energy storage devices has affected DSM business models considerably. Therefore, in this paper, possible business models for EE and DR providers in different electricity market segments are analyzed and reviewed. The analysis covers three types of characteristics: DSM transaction characteristics, renewable energy correlation and DSM load control characteristics. In DSM transaction characteristics, the value proposition of DSM such as added value offered to the DSM purchaser and transaction triggers are discussed. In renewable energy correlation, the effect of increased renewable energy penetration on the business model is evaluated. In DSM load control characteristics, load control and aggregation aspects such as response speed, duration, advance notice, location sensitivity and actual usage frequency are analyzed.