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.

Electric vehicle fleet management in smart grids: A review of services, optimization and control aspects

Abstract: Electric vehicles can become integral parts of a smart grid, since they are capable of providing valuable services to power systems other than just consuming power. On the transmission system level, electric vehicles are regarded as an important means of balancing the intermittent renewable energy resources such as wind power. This is because electric vehicles can be used to absorb the energy during the period of high electricity penetration and feed the electricity back into the grid when the demand is high or in situations of insufficient electricity generation. However, on the distribution system level, the extra loads created by the increasing number of electric vehicles may have adverse impacts on grid. These factors bring new challenges to the power system operators. To coordinate the interests and solve the conflicts, electric vehicle fleet operators are proposed both by academics and industries. This paper presents a review and classification of methods for smart charging (including power to vehicle and vehicle-to-grid) of electric vehicles for fleet operators. The study firstly presents service relationships between fleet operators and other four actors in smart grids; then, modeling of battery dynamics and driving patterns of electric vehicles, charging and communications standards are introduced; after that, three control strategies and their commonly used algorithms are described; finally, conclusion and recommendations are made.

Dynamic Demand Response Controller Based on Real-Time Retail Price for Residential Buildings

Abstract: Demand response and dynamic retail pricing of electricity are key factors in a smart grid to reduce peak loads and to increase the efficiency of the power grid. Air-conditioning and heating loads in residential buildings are major contributors to total electricity consumption. In hot climates, such as Austin, Texas, the electricity cooling load of buildings results in critical peak load during the on-peak period. Demand response (DR) is valuable to reduce both electricity loads and energy costs for end users in a residential building. This paper focuses on developing a control strategy for the HVACs to respond to real-time prices for peak load reduction. A proposed dynamic demand response controller (DDRC) changes the set-point temperature to control HVAC loads depending on electricity retail price published each 15 minutes and partially shifts some of this load away from the peak. The advantages of the proposed control strategy are that DDRC has a detailed scheduling function and compares the real-time retail price of electricity with a threshold price that customers set by their preference in order to control HVAC loads considering energy cost. In addition, a detailed single family house model is developed using OpenStudio and Energyplus considering the geometry of a residential building and geographical environment. This HVAC modeling provides simulation of a house. Comfort level is, moreover, reflected into the DDRC to minimize discomfort when DDRC changes the set-point temperature. Our proposed DDRC is implemented in MATLAB/SIMULINK and connected to the EnergyPlus model via building controls virtual test bed (BCVTB). The real-time retail price is based on the real-time wholesale price in the ERCOT market in Texas. The study shows that DDRC applied in residential HVAC systems could significantly reduce peak loads and electricity bills with a modest variation in thermal comfort.

Developing ZigBee Deployment Guideline Under WiFi Interference for Smart Grid Applications

Abstract: Smart grid is an intelligent power generation, distribution, and control system. ZigBee, as a wireless mesh networking scheme low in cost, power, data rate, and complexity, is ideal for smart grid applications, e.g., real-time system monitoring, load control, and building automation. Unfortunately, almost all ZigBee channels overlap with wireless local area network (WLAN) channels, resulting in severe performance degradation due to interference. In this paper, we aim to develop practical ZigBee deployment guideline under the interference of WLAN. We identify the “Safe Distance” and “Safe Offset Frequency” using a comprehensive approach including theoretical analysis, software simulation, and empirical measurement. In addition, we propose a frequency agility-based interference avoidance algorithm. The proposed algorithm can detect interference and adaptively switch nodes to “safe” channel to dynamically avoid WLAN interference with small latency and small energy consumption. Our proposed scheme is implemented with a Meshnetics ZigBit Development Kit and its performance is empirically evaluated in terms of the packet error rate (PER) using a ZigBee and Wi-Fi coexistence test bed. It is shown that the empirical results agree with our analytical results. The measurements demonstrate that our design guideline can efficiently mitigate the effect of WiFi interference and enhance the performance of ZigBee networks.

A Software Defined Networking architecture for the Internet-of-Things

Abstract: The growing interest in the Internet of Things (IoT) has resulted in a number of wide-area deployments of IoT subnetworks, where multiple heterogeneous wireless communication solutions coexist: from multiple access technologies such as cellular, WiFi, ZigBee, and Bluetooth, to multi-hop ad-hoc and MANET routing protocols, they all must be effectively integrated to create a seamless communication platform. Managing these open, geographically distributed, and heterogeneous networking infrastructures, especially in dynamic environments, is a key technical challenge. In order to take full advantage of the many opportunities they provide, techniques to concurrently provision the different classes of IoT traffic across a common set of sensors and networking resources must be designed. In this paper, we will design a software-defined approach for the IoT environment to dynamically achieve differentiated quality levels to different IoT tasks in very heterogeneous wireless networking scenarios. For this, we extend the Multinetwork INformation Architecture (MINA), a reflective (self-observing and adapting via an embodied Observe-Analyze-Adapt loop) middleware with a layered IoT SDN controller. The developed IoT SDN controller originally i) incorporates and supports commands to differentiate flow scheduling over task-level, multi-hop, and heterogeneous ad-hoc paths and ii) exploits Network Calculus and Genetic Algorithms to optimize the usage of currently available IoT network opportunities. We have applied the extended MINA SDN prototype in the challenging IoT scenario of wide-scale integration of electric vehicles, electric charging sites, smart grid infrastructures, and a wide set of pilot users, as targeted by the Artemis Internet of Energy and Arrowhead projects. Preliminary simulation performance results indicate that our approach and the extended MINA system can support efficient exploitation of the IoT multinetwork capabilities.

Emergence of energy storage technologies as the solution for reliable operation of smart power systems: A review

Abstract: The ever increasing penetration of renewable energy systems (RESs) in today deregulated intelligent power grids, necessitates the use of electrical storage systems. Energy storage systems (ESSs) are helpful to make balance between generation and demand improving the performance of whole power grid. In collaboration with RESs, energy storage devices can be integrated into the power networks to bring ancillary service for the power system and hence enable an increased penetration of distributed generation (DG) units. This paper presents different applications of electrical energy storage technologies in power systems emphasizing on the collaboration of such entities with RESs. The role of ESSs in intelligent micropower grids is also discussed where the stochastic nature of renewable energy sources may affect the power quality. Particular attention is paid to flywheel storage, electrochemical storage, pumped hydroelectric storage, and compressed air storage and their operating principle are discussed as well. The application of each type in the area of power system is investigated and compared to others.