相关论文: Understanding Reduced-Voltage Operation in Modern …
Conservation voltage reduction(CVR) uses Volt-VAR optimization(VVO) methods to reduce customer power demand by controlling the feeders' voltage control devices. The objective of this paper is to present a VVO approach that controls the…
Under conditions of high penetration of renewables, the low-voltage (LV) distribution network needs to be carefully managed. In such a scenario, an accurate real-time low-voltage power network model is an important prerequisite, which opens…
Today, human operators primarily perform voltage control of the electric transmission system. As the complexity of the grid increases, so does its operation, suggesting additional automation could be beneficial. A subset of machine learning…
As SRAM-based caches are hitting a scaling wall, manufacturers are integrating DRAM-based caches into system designs to continue increasing cache sizes. While DRAM caches can improve the performance of memory systems, existing DRAM cache…
Processing-using-DRAM (PUD) is a paradigm where the analog operational properties of DRAM are used to perform bulk logic operations. While PUD promises high throughput at low energy and area cost, we uncover three limitations of existing…
A residual deep reinforcement learning (RDRL) approach is proposed by integrating DRL with model-based optimization for inverter-based volt-var control in active distribution networks when the accurate power flow model is unknown. RDRL…
The energy landscape for the Low-Voltage (LV) networks are beginning to change; changes resulted from the increase penetration of renewables and/or the predicted increase of electric vehicles charging at home. The previously passive…
In this paper, a new dual function fault current limiter-dynamic voltage restorer (FCL-DVR) topology is proposed. The proposed structure, in addition to performing routine FCL tasks, can be used to improve the voltage quality of point of…
Non-volatile memory (NVM) technologies such as spin-transfer torque magnetic random access memory (STT-MRAM) and spin-orbit torque magnetic random access memory (SOT-MRAM) have significant advantages compared to conventional SRAM due to…
Increasing the amount of electric power that is used on the demand side has brought more attention to the peak-load management of the distribution network (DN). The creation of infrastructures for smart grids, the efficient utilization of…
Accurate prediction of chip performance is critical for ensuring energy efficiency and reliability in semiconductor manufacturing. However, developing minimum operating voltage ($V_{min}$) prediction models at advanced technology nodes is…
In this paper, a design space exploration of power delivery networks is performed for multi-chip 2.5-D and 3-D IC technologies. The focus of the paper is the effective placement of the voltage regulator modules (VRMs) for power supply noise…
A voltage regulation method for slow voltage variations at distribution level is proposed, based on a view of the loads, generators and storage along a distribution line as point weights. The "centers of mass" of the absorbed and injected…
Battery-less technology evolved to replace battery technology. Non-volatile memory (NVM) based processors were explored to store the program state during a power failure. The energy stored in a capacitor is used for a backup during a power…
As neural networks (NN) are deployed across diverse sectors, their energy demand correspondingly grows. While several prior works have focused on reducing energy consumption during training, the continuous operation of ML-powered systems…
We explore how Demand Response (DR) can effectively provide electricity system services such as for the management of bi-directional power flows and the control of voltage deviations in active distribution networks, without compromising…
This paper presents a regression-based method for estimating voltages and voltage sensitivities for volt-var control on distribution circuits with limited data. The estimator uses power flow results for representative load and PV output…
Due to the increasing popularity of DC loads and the potential for higher efficiency, DC microgrids are gaining significant attention. DC microgrids utilize multiple parallel converters to deliver sufficient power to the load. However, a…
Enabling high energy efficiency is crucial for embedded implementations of deep learning. Several studies have shown that the DRAM-based off-chip memory accesses are one of the most energy-consuming operations in deep neural network (DNN)…
Reduction in power consumption has become a major criterion of design in modern ICs. One such scheme to reduce power consumption by an IC is the use of multiple power supplies for critical and non-critical paths. To maintain the impedance…