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.

Smart Grid Data Cloud: A Model for Utilizing Cloud Computing in the Smart Grid Domain

Abstract: This paper presents a model for smart grid data management based on specific characteristics of cloud computing, such as distributed data management for real-time data gathering, parallel processing for real-time information retrieval, and ubiquitous access. The appliance of the cloud computing model meets the requirements of data and computing intensive smart grid applications. We gathered these requirements by analyzing the set of well-known smart grid use cases, most of which demand flexible collaboration across organizational boundaries of network operators and energy service providers as well as the active participation of the end user. Hence, preserving confidentiality and privacy, whilst processing the massive amounts of smart grid data, is of paramount importance in the design of the proposed Smart Grid Data Cloud.

Sequential Service Restoration for Unbalanced Distribution Systems and Microgrids

Abstract: The resilience and reliability of modern power systems are threatened by increasingly severe weather events and cyber-physical security events. An effective restoration methodology is desired to optimally integrate emerging smart grid technologies and pave the way for developing self-healing smart grids. In this paper, a sequential service restoration (SSR) framework is proposed to generate restoration solutions for distribution systems and microgrids in the event of large-scale power outages. The restoration solution contains a sequence of control actions that properly coordinate switches, distributed generators, and switchable loads to form multiple isolated microgrids. The SSR can be applied for three-phase unbalanced distribution systems and microgrids and can adapt to various operation conditions. Mathematical models are introduced for three-phase unbalanced power flow, voltage regulators, transformers, and loads. The SSR problem is formulated as a mixed-integer linear programming model, and its effectiveness is evaluated via the modified IEEE 123 node test feeder.

A review on electric vehicles interacting with renewable energy in smart grid

Abstract: Electric vehicles (EVs) represent one of the most promising technologies to green the transportation systems. An important issue is that high penetration of EVs brings heavy electricity demand to the power grid. One effective way to alleviate the impact is to integrate local power generation such as renewable energy sources (RESs) into charging infrastructure. Because of the intermittent and indispatchable nature of RESs, it becomes very challenging to coordinate EVs charging with other grid load and renewable generation. In this paper, EVs charging problem in the presence of smart grid technologies is investigated, and the interaction with renewable energy is reviewed. An overview about EVs and RESs is first presented, which mainly introduces major types of EVs and renewable energy estimation methods. Then, according to the objectives, the existing research works are divided into three categories: cost-aware, efficiency-aware, and emissions-aware interactions between EVs and RESs. Each category׳s discussion includes the description of core ideas, summarization of solutions, and comparison between different works. Finally, some key open issues about EVs interacting with RESs are given and some possible solutions are also discussed.

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

Abstract: 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.

GECO: Global Event-Driven Co-Simulation Framework for Interconnected Power System and Communication Network

Abstract: The vision of a smart grid is predicated upon pervasive use of modern digital communication techniques to today's power system. As wide area measurements and control techniques are being developed and deployed for a more resilient power system, the role of communication network is becoming prominent. Power system dynamics gets influenced by the communication delays in the network. Therefore, extensive integration of power system and communication infrastructure mandates that the two systems be studied as a single distributed cyber-physical system. This paper proposes a power system and communication network co-simulation framework (GECO) using a global event-driven mechanism. The accuracy is tunable based on the time-scale requirements of the phenomena being studied. This co-simulation can improve the practical investigation of smart grid and evaluate wide area measurement and control schemes. As a case study, a communication-based backup distance relay protection scheme is co-simulated and validated on this co-simulation framework.