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Data centers are high power consumers and the energy consumption of data centers keeps on rising in spite of all the efforts for increasing the energy efficiency. The need for energy-awareness in data centers makes the use of power modeling…
Parallel processing, the core of High Performance Computing (HPC), was and still the most effective way in improving the speed of computer systems. For the past few years, the substantial developments in the computing power of processors…
Cloud computing has become a critical infrastructure for modern society, like electric power grids and roads. As the backbone of the modern economy, it offers subscription-based computing services anytime, anywhere, on a pay-as-you-go…
In smart grid, the demand side management (DSM) techniques need to be designed to process a large number of controllable loads of several types. In this paper, we proposed a framework to study the demand side management in smart grid which…
Industries are considering the adoption of cloud and edge computing for real-time applications due to current improvements in network latencies and the advent of Fog and Edge computing. Current cloud paradigms are not designed for real-time…
To support the needs of ever-growing cloud-based services, the number of servers and network devices in data centers is increasing exponentially, which in turn results in high complexities and difficulties in network optimization. To…
The increasing penetration of inverter-based renewable generation has significantly reduced system inertia, making modern power grids more vulnerable to rapid frequency deviations following disturbances. While a wide range of flexible…
Recent communication, computation, and technology advances coupled with climate change concerns have transformed the near future prospects of electricity transmission, and, more notably, distribution systems and microgrids. Distributed…
Recent research shows large-scale AI-centric data centers could experience rapid fluctuations in power demand due to varying computation loads, such as sudden spikes from inference or interruption of training large language models (LLMs).…
Nowadays, more and more increasingly hard computations are performed in challenging fields like weather forecasting, oil and gas exploration, and cryptanalysis. Many of such computations can be implemented using a computer cluster with a…
To reduce negative environmental impacts, power stations and energy grids need to optimize the resources required for power production. Thus, predicting the energy consumption of clients is becoming an important part of every energy…
With the proliferation of the adoption of renewable energy in powering data centers, addressing the challenges of such energy sources has attracted researchers from academia and industry. One of the challenging characteristics of data…
With the growing complexity of big data workloads that require abundant data and computation, data centers consume a tremendous amount of power daily. In an effort to minimize data center power consumption, several studies developed power…
In this paper, we address a key issue of designing architectures and algorithms which generate optimal demand response in a decentralized manner for a smart-grid consisting of several stochastic renewables and dynamic loads. By optimal…
The accelerating technological landscape and drive towards net-zero emission made the power system grow in scale and complexity. Serial computational approaches for grid planning and operation struggle to execute necessary calculations…
This paper presents a capacity-constrained incentive-based demand response approach for residential smart grids. It aims to maintain electricity grid capacity limits and prevent congestion by financially incentivising end users to reduce or…
Operating a modern power grid reliably in case of SCADA/EMS failure or amid difficult times like COVID-19 pandemic is a challenging task for grid operators. In [11], a PMU-based emergency generation dispatch scheme has been proposed to help…
In the last decade, the Internet of Things paradigm has caused an exponential increase in the number of connected devices. This trend brings the Internet closer to everyday activities and enables data collection that can be used to create…
The energy consumption of computer and communication systems does not scale linearly with the workload. A system uses a significant amount of energy even when idle or lightly loaded. A widely reported solution to resource management in…
Diversification of digital applications and workloads has driven the development of diverse datacenter architectures on ever-larger scales. These datacenters consist of complex IT, power, and cooling systems with interdependencies that…