Energy resource scheduling considering reactive power management

The reactive power management is an important task in future power systems. The control of reactive power allows the increase of distributed energy resources penetration as well as the optimal operation of distribution networks. Currently, the control of reactive power is only controlled in large power units and in high and very high voltage substations. In this paper a reactive power control in smart grids paradigm is proposed, considering the management of distributed energy resources and of the distribution network by an aggregator namely Virtual Power Player (VPP).

Device power management for real-time embedded systems

A large part of power dissipation in a system is generated by I/O devices. Increasingly these devices provide power saving mechanisms to inter alia enhance battery life. While I/O device scheduling has been studied in the past for realtime systems, the use of energy resources by these scheduling algorithms may be improved. These approaches are crafted considering a huge overhead of device transition. The technology enhancement has allowed the hardware vendors to reduce the device transition overhead and energy consumption. We propose an intra-task device scheduling algorithm for real time systems that allows to shut-down devices while ensuring the system schedulability. Our results show an energy gain of up to 90% in the best case when compared to the state-of-the-art.

Reactive power management strategies in future smart grids

The reactive power management in distribution network with large penetration of distributed energy resources is an important task in future power systems. The control of reactive power allows the inclusion of more distributed recourses and a more efficient operation of distributed network. Currently, the reactive power is only controlled in large power plants and in high and very high voltage substations. In this paper, several reactive power control strategies considering a smart grids paradigm are proposed. In this context, the management of distributed energy resources and of the distribution network by an aggregator, namely Virtual Power Player (VPP), is proposed and implemented in a MAS simulation tool. The proposed methods have been computationally implemented and tested using a 32-bus distribution network with intensive use of distributed resources, mainly the distributed generation based on renewable resources. Results concerning the evaluation of the reactive power management algorithms are also presented and compared.

Exploring Cross-layer power management for PGAS applications on the SCC platform

Technological limitations and power constraints are resulting in high-performance parallel computing architectures that are based on large numbers of high-core-count processors. Commercially available processors are now at 8 and 16 cores and experimental platforms, such as the many-core Intel Single-chip Cloud Computer (SCC) platform, provide much higher core counts. These trends are presenting new sets of challenges to HPC applications including programming complexity and the need for extreme energy efficiency.In this work, we first investigate the power behavior of scientific PGAS application kernels on the SCC platform, and explore opportunities and challenges for power management within the PGAS framework. Results obtained via empirical evaluation of Unified Parallel C (UPC) applications on the SCC platform under different constraints, show that, for specific operations, the potential for energy savings in PGAS is large; and power/performance trade-offs can be effectively managed using a cross-layerapproach. We investigate cross-layer power management using PGAS language extensions and runtime mechanisms that manipulate power/performance tradeoffs. Specifically, we present the design, implementation and evaluation of such a middleware for application-aware cross-layer power management of UPC applications on the SCC platform. Finally, based on our observations, we provide a set of recommendations and insights that can be used to support similar power management for PGAS applications on other many-core platforms.

The Design and Implementation of a Power Management Feature to a Configuration Management System

Green IT is a term that covers various tasks and concepts that are related to reducing the environmental impact of IT. At enterprise level, Green IT has significant potential to generate sustainable cost savings: the total amount of devices is growing and electricity prices are rising. The lifecycle of a computer can be made more environmentally sustainable using Green IT, e.g. by using energy efficient components and by implementing device power management. The challenge using power management at enterprise level is how to measure and follow-up the impact of power management policies? During the thesis a power management feature was developed to a configuration management system. The feature can be used to automatically power down and power on PCs using a pre-defined schedule and to estimate the total power usage of devices. Measurements indicate that using the feature the device power consumption can be monitored quite precisely and the power consumption can be reduced, which generates electricity cost savings and reduces the environmental impact of IT.

Channel Adaptive MAC Protocol with Traffic-Aware Distributed Power Management in Wireless Sensor Networks-Some Performance Issues

In Wireless Sensor Networks (WSN), neglecting the effects of varying channel quality can lead to an unnecessary wastage of precious battery resources and in turn can result in the rapid depletion of sensor energy and the partitioning of the network. Fairness is a critical issue when accessing a shared wireless channel and fair scheduling must be employed to provide the proper flow of information in a WSN. In this paper, we develop a channel adaptive MAC protocol with a traffic-aware dynamic power management algorithm for efficient packet scheduling and queuing in a sensor network, with time varying characteristics of the wireless channel also taken into consideration. The proposed protocol calculates a combined weight value based on the channel state and link quality. Then transmission is allowed only for those nodes with weights greater than a minimum quality threshold and nodes attempting to access the wireless medium with a low weight will be allowed to transmit only when their weight becomes high. This results in many poor quality nodes being deprived of transmission for a considerable amount of time. To avoid the buffer overflow and to achieve fairness for the poor quality nodes, we design a Load prediction algorithm. We also design a traffic aware dynamic power management scheme to minimize the energy consumption by continuously turning off the radio interface of all the unnecessary nodes that are not included in the routing path. By Simulation results, we show that our proposed protocol achieves a higher throughput and fairness besides reducing the delay

A Reinforcement-Learning Approach to Power Management

We describe an adaptive, mid-level approach to the wireless device power management problem. Our approach is based on reinforcement learning, a machine learning framework for autonomous agents. We describe how our framework can be applied to the power management problem in both infrastructure and ad~hoc wireless networks. From this thesis we conclude that mid-level power management policies can outperform low-level policies and are more convenient to implement than high-level policies. We also conclude that power management policies need to adapt to the user and network, and that a mid-level power management framework based on reinforcement learning fulfills these requirements.

Optimal power management strategy for energy storage with stochastic loads

In this paper, a power management strategy (PMS) has been developed for the control of energy storage in a system subjected to loads of random duration. The PMS minimises the costs associated with the energy consumption of specific systems powered by a primary energy source and equipped with energy storage, under the assumption that the statistical distribution of load durations is known. By including the variability of the load in the cost function, it was possible to define the optimality criteria for the power flow of the storage. Numerical calculations have been performed obtaining the control strategies associated with the global minimum in energy costs, for a wide range of initial conditions of the system. The results of the calculations have been tested on a MATLAB/Simulink model of a rubber tyre gantry (RTG) crane equipped with a flywheel energy storage system (FESS) and subjected to a test cycle, which corresponds to the real operation of a crane in the Port of Felixstowe. The results of the model show increased energy savings and reduced peak power demand with respect to existing control strategies, indicating considerable potential savings for port operators in terms of energy and maintenance costs.

Power Management Controls

In an office building in the US the office equipment uses about 7% of the total electricity use. Eventhough this is a low number, there is still a reason to save more energy, especially since one third of theenergy savings are lost when power management is not enabled.The core in the project ”Power Management Controls” is to develop a voluntary standard, The UserInterface Standard, that manufacturers of office equipment can use as a reference when they developnew equipment and design new interfaces. The interface is an important part of the use of powermanagement and doing this should increase the use of power management and save more energy. Theinterfaces are ofter hidden or inconsistent and confusing, which makes it harder for the user tounderstand power management. A more consistent interface makes it easier for the user to understandthe meaning of an interface and power management itselfThe standard consists of six different parts, which describe what can be done to achieve a consistentinterface. The standard also describes the part of the project called Dynamic Behavior. This part isconcentrating on the interfaces and the behavior of the device over time, which is important for the userto understand.The purpose of this degree project is to study and participate in the project ”Power ManagementControls”, and to understand what is being done to save more energy.

Progettazione e Implementazione di un modulo di Power Management per Smart Environments

Progettazione ed implementazione di un modulo che gestisca il consumo di energia in uno Smart Environment, contestualizzato nell'ambito di un progetto europeo, SOFIA (Smart Object For Intelligent Applications), che ambisce ad accelerare l'integrazione di oggetti intelligenti nella vita quotidiana. Il consumo energetico da gestire e' quello di una rete di sensori; e' stato dimostrato che, riducendo le trasmissioni di dati tra sensori ed il resto della rete, le batterie durano quasi il doppio del tempo e, di conseguenza, la vita della rete e' raddoppiata, con vantaggi evidenti per l'ambiente.

Dynamic power management: from portable devices to high performance computing

Electronic applications are nowadays converging under the umbrella of the cloud computing vision. The future ecosystem of information and communication technology is going to integrate clouds of portable clients and embedded devices exchanging information, through the internet layer, with processing clusters of servers, data-centers and high performance computing systems. Even thus the whole society is waiting to embrace this revolution, there is a backside of the story. Portable devices require battery to work far from the power plugs and their storage capacity does not scale as the increasing power requirement does. At the other end processing clusters, such as data-centers and server farms, are build upon the integration of thousands multiprocessors. For each of them during the last decade the technology scaling has produced a dramatic increase in power density with significant spatial and temporal variability. This leads to power and temperature hot-spots, which may cause non-uniform ageing and accelerated chip failure. Nonetheless all the heat removed from the silicon translates in high cooling costs. Moreover trend in ICT carbon footprint shows that run-time power consumption of the all spectrum of devices accounts for a significant slice of entire world carbon emissions. This thesis work embrace the full ICT ecosystem and dynamic power consumption concerns by describing a set of new and promising system levels resource management techniques to reduce the power consumption and related issues for two corner cases: Mobile Devices and High Performance Computing.

Power management techniques in an FPGA-Based WSN node for high performance application

In this work, the power management techniques implemented in a high-performance node for Wireless Sensor Networks (WSN) based on a RAM-based FPGA are presented. This new node custom architecture is intended for high-end WSN applications that include complex sensor management like video cameras, high compute demanding tasks such as image encoding or robust encryption, and/or higher data bandwidth needs. In the case of these complex processing tasks, yet maintaining low power design requirements, it can be shown that the combination of different techniques such as extensive HW algorithm mapping, smart management of power islands to selectively switch on and off components, smart and low-energy partial reconfiguration, an adequate set of save energy modes and wake up options, all combined, may yield energy results that may compete and improve energy usage of typical low power microcontrollers used in many WSN node architectures. Actually, results show that higher complexity tasks are in favor of HW based platforms, while the flexibility achieved by dynamic and partial reconfiguration techniques could be comparable to SW based solutions.

Analysis and design of power management scheme for an on-board solar energy storage system

This paper investigates the power management issues in a mobile solar energy storage system. A multi-converter based energy storage system is proposed, in which solar power is the primary source while the grid or the diesel generator is selected as the secondary source. The existence of the secondary source facilitates the battery state of charge detection by providing a constant battery charging current. Converter modeling, multi-converter control system design, digital implementation and experimental verification are introduced and discussed in details. The prototype experiment indicates that the converter system can provide a constant charging current during solar converter maximum power tracking operation, especially during large solar power output variation, which proves the feasibility of the proposed design. © 2014 IEEE.

QoE-aware power management in vehicle-to-grid networks:a matching-theoretic approach

Frequency, time and places of charging and discharging have critical impact on the Quality of Experience (QoE) of using Electric Vehicles (EVs). EV charging and discharging scheduling schemes should consider both the QoE of using EV and the load capacity of the power grid. In this paper, we design a traveling plan-aware scheduling scheme for EV charging in driving pattern and a cooperative EV charging and discharging scheme in parking pattern to improve the QoE of using EV and enhance the reliability of the power grid. For traveling planaware scheduling, the assignment of EVs to Charging Stations (CSs) is modeled as a many-to-one matching game and the Stable Matching Algorithm (SMA) is proposed. For cooperative EV charging and discharging in parking pattern, the electricity exchange between charging EVs and discharging EVs in the same parking lot is formulated as a many-to-many matching model with ties, and we develop the Pareto Optimal Matching Algorithm (POMA). Simulation results indicates that the SMA can significantly improve the average system utility for EV charging in driving pattern, and the POMA can increase the amount of electricity offloaded from the grid which is helpful to enhance the reliability of the power grid.

Prototipazione FPGA di sottosistemi integrati per power management basati su ISA RISC-V

Fino a 15 anni fa, era possibile aumentare il numero di transistor su un singolo chip e contemporaneamente la sua frequenza di clock mantenendo la densità di potenza costante. Tuttavia dal 2004 non è più possibile mantenere invariata la potenza dissipata per unità d’area a causa di limitazioni fisiche. Al fine di aumentare le performance dei processori e di impedire una diminuzione delle frequenze di clock, i processori moderni integrano on-die dei Power Controller Subsystems (PCS) come risorsa hardware dedicata che implementa complesse strategie di gestione di temperatura e potenza. In questo progetto di tesi viene progettata l'architettura dell'interfaccia di comunicazione di ControlPULP, un PCS basato su ISA RISC-V, per la connessione verso un processore HPC. Tale interfaccia di comunicaione integra il supporto hardware per lo scambio di messaggi secondo la specifica SCMI. L'interfaccia sviluppata viene successivamente validata attraverso simulazione ed emulazione su supporto hardware FPGA. Tale supporto hardware viene inoltre utilizzato per la caratterizzazione dell'utilizzo di risorse dell'architettura progettata. Oltre allo sviluppo dell'interfaccia hardware viene sviluppato e caratterizzato un firmware per la decodifica dei messaggi SCMI conforme ai requisiti di esecuzione su un sistema real-time.