A review on energy efficiency optimization in Smart Grid

Rafiei, Sepide; Bakhshai, Alireza

doi:10.1109/iecon.2012.6389115

Cited by 10 publications

(3 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…6. Energy efficiency: Providing mechanisms for different kinds of customers to modify their energy usage during peak hours and optimizing the balance between power supply and demand [41]. 7.…”

Section: Smart Gridmentioning

confidence: 99%

Internet of Things in Smart Grid: Architecture, Applications, Services, Key Technologies, and Challenges

2019

View full text Add to dashboard Cite

Internet of Things (IoT) is a connection of people and things at any time, in any place, with anyone and anything, using any network and any service. Thus, IoT is a huge dynamic global network infrastructure of Internet-enabled entities with web services. One of the most important applications of IoT is the Smart Grid (SG). SG is a data communications network which is integrated with the power grid to collect and analyze data that are acquired from transmission lines, distribution substations, and consumers. In this paper, we talk about IoT and SG and their relationship. Some IoT architectures in SG, requirements for using IoT in SG, IoT applications and services in SG, and challenges and future work are discussed.

show abstract

Section: Smart Gridmentioning

confidence: 99%

Internet of Things in Smart Grid: Architecture, Applications, Services, Key Technologies, and Challenges

2019

View full text Add to dashboard Cite

show abstract

“…The PowerMatcher, a recognized technology, integrates demand and supply flexibility in the operation of the electricity system through the use of dynamic pricing and a hierarchical bidding coordination scheme, see e.g. [4,7,1,11,6]. This coordination scheme provides the Power-Matcher with attractive properties regarding scalability, stability and privacy [4,3] , which are prerequisites for practical usefulness.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Charging Strategies for Electric Vehicles in PowerMatcher-Driven Smart Energy Grids

Kempker

Dijk

Scheinhardt

et al. 2016

Proceedings of the 9th EAI International Conference on Performance Evaluation Methodologies and Tools

View full text Add to dashboard Cite

A crucial challenge in future smart energy grids is the largescale coordination of distributed energy demand and generation. The well-known PowerMatcher is a promising approach that integrates demand and supply flexibility in the operation of the electricity system through dynamic pricing and a hierarchical bidding coordination scheme. However, as the PowerMatcher focuses on short-term coordination of demand and supply, it cannot fully exploit the flexibility of e.g. electric vehicles over longer periods of time. In this paper, we propose an extension of the PowerMatcher comprising a planning module, which provides coordinated predictions of demand/price over longer times as input to the users for determining their short-term bids. The optimal short-term bidding strategy minimizing a user's costs is then formulated as a Stochastic Dynamic Programming (SDP) problem. We derive an analytic solution for this SDP problem leading to a simple short-term bidding strategy. Numerical results using real-world data show a substantial performance improvement compared to the standard PowerMatcher, without significant additional complexity. CCS Concepts Computing methodologies → Multi-agent planning; Mathematics of computing → Stochastic processes; Hardware → Smart grid;

show abstract

“…The urgent importance of 'greening' data centers has made itself known in the form of carbon footprints and exorbitant energy costs [1]. According to Vaid [2], energy consumption accounts for more than 35% of the current data center operational expenses, and this estimate is expected to rise to 50% in a few years.…”

Section: Introductionmentioning

confidence: 99%

Profiling: An application assignment approach for green data centers

Vasudevan

Tian

Tang

et al. 2014

IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society

View full text Add to dashboard Cite

Abstract-In the past few years, there has been a steady increase in the attention, importance and focus of green initiatives related to data centers. While various energy aware measures have been developed for data centers, the requirement of improving the performance efficiency of application assignment at the same time has yet to be fulfilled. For instance, many energy aware measures applied to data centers maintain a trade-off between energy consumption and Quality of Service (QoS). To address this problem, this paper presents a novel concept of profiling to facilitate offline optimization for a deterministic application assignment to virtual machines. Then, a profile-based model is established for obtaining near-optimal allocations of applications to virtual machines with consideration of three major objectives: energy cost, CPU utilization efficiency and application completion time. From this model, a profile-based and scalable matching algorithm is developed to solve the profile-based model. The assignment efficiency of our algorithm is then compared with that of the Hungarian algorithm, which does not scale well though giving the optimal solution.

show abstract

A review on energy efficiency optimization in Smart Grid

Cited by 10 publications

References 12 publications

Internet of Things in Smart Grid: Architecture, Applications, Services, Key Technologies, and Challenges

Internet of Things in Smart Grid: Architecture, Applications, Services, Key Technologies, and Challenges

Optimization of Charging Strategies for Electric Vehicles in PowerMatcher-Driven Smart Energy Grids

Profiling: An application assignment approach for green data centers

Contact Info

Product

Resources

About