Read the abstract, see who wrote it and who cites it, and get the citation in APA, MLA, Chicago or Harvard.
About 10,000 papers for “Power optimization”
Mor Harchol‐Balter · Cambridge University Press eBooks · 2013
This chapter combines and applies many analytical techniques we have studied thus far (Renewal-Reward, general transform analysis, and M/G/1 response time analysis) toward analyzing the problem of power management of a single server. The goal is to understand when a server should be turned off to save on power (sometimes called “power napping”) and when it should be left on.
Cited by 0
Željko Bogdan, Mislav Čehil, Damir Kopjar · Energy · 2007
Cited by 129
Al Omar, Ehmedi · Zenodo (CERN European Organization for Nuclear Research) · 2024
Cited by 0Open access
Ventura Nadal, Ignasi · QRU Quaderns de Recerca en Urbanisme · 2021
Aquesta tesi consisteix en el desenvolupament d’un model per optimitzar l’operació d’un sistema elèctric de potència que integra tecnologies d’energies renovables, generadors de combustible i sistemes d’emmagatzematge d’energia. Desenvolupa un problema de flux de potència òptim no lineal, de programació mixta-entera i de diversos períodes, que determina com operar els generadors fotovoltaics, els generadors de combustible i l’estat de càrrega de les bateries cada hora per tal de minimitzar els costos de distribució. Totes aquestes variables s’adhereixen a restriccions que imposen les limitacions físiques del sistema. El problema formula la xarxa de distribució mitjançant el Branch Flow Model per a xarxes radials amb dues relaxacions. Eliminar els angles de tensió i corrent i introduir una relaxació de con de segon ordre perquè el problema sigui convex. A més, com que no es garanteix que la solució del flux de potència sigui factible per al problema no relaxat, es desenvolupa un algoritme per trobar la solució òptima que mantingui la relaxació. La implementació d’aquest model es farà mitjançant el programari GAMS, MATLAB i EXCEL i serà el més genèric possible per adaptar-se fàcilment a qualsevol sistema de distribució de mitja tensió. En aquest projecte, es desenvolupen tres casos pràctics diferents: un escenari base amb generació fotovoltaica i sense sistemes d’emmagatzematge d’energia, un escenari amb un alt nivell de penetració fotovoltaica i un tercer escenari que afegeix bateries al segon cas. Tots els models presenten una part tècnica i econòmica i l’objectiu d’optimització és minimitzar els costos operatius diaris
Cited by 0Open access
A. Debs · 1988
Cited by 0
Al Omar, Ehmedi · Zenodo (CERN European Organization for Nuclear Research) · 2024
Cited by 0Open access
José Monteiro · 2003
Power dissipation has recently emerged as one the most critical design constraints. A wide range of techniques has already been proposed for the optimization of logic circuits for low power. Power management methods are among the most effective techniques for power reduction. These methods detect periods of time during which parts of the circuit are not doing useful work and shut them down by either turning off the power supply or the clock signal. Several methods have been presented that perform shut-down on a clock-cycle base. Depending on the input conditions at the beginning of a clock-cycle, the clock driving some of the registers in the circuit can be inhibited, thus reducing the switching activity in the fanout of those registers. These techniques are referred to as data-dependent or dynamic power management techniques. In this tutorial we describe some of the most representative data-dependent power management techniques that have recently been proposed, namely: precomputation, guarded evaluation, gated-clock finite state machines (FSM)'s and FSM decomposition. Each of these techniques uses a different approach to identify the input conditions for which the circuit (or part of) can be disabled. These techniques are put into perspective and recent results are discussed.
Cited by 12
Dan Li, Liqun Gao, Shun Lu et al. · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · 2007
Aiming at the precocious convergence problem of particle swarm optimization algorithm, adaptive particle swarm optimization(APSO) algorithm was presented. In this algorithm, the notion of species was introduced into population diversity measure. The species technique is based on the concept of dividing the population into several species according to their similarity. The inertia weight was nonlinearly adjusted by using population diversity information at each iteration step. Velocity mutation operator and position crossover operator were both introduced and the global performance was clearly improved. The algorithm had been applied to reactive power optimization. The simulation results of the standard IEEE-30-bus power system had indicated that APSO was able to undertake global search with a fast convergence rate and a feature of robust computation. It was proved to be validity, fast convergence and computation efficiency during the reactive power optimization.
Cited by 10
P. R. Sujin, Tapan Prakash, M. Mary Linda · arXiv (Cornell University) · 2010
Reactive power plays an important role in supporting the real power transfer by maintaining voltage stability and system reliability. It is a critical element for a transmission operator to ensure the reliability of an electric system while minimizing the cost associated with it. The traditional objectives of reactive power dispatch are focused on the technical side of reactive support such as minimization of transmission losses. Reactive power cost compensation to a generator is based on the incurred cost of its reactive power contribution less the cost of its obligation to support the active power delivery. In this paper an efficient Particle Swarm Optimization (PSO) based reactive power optimization approach is presented. The optimal reactive power dispatch problem is a nonlinear optimization problem with several constraints. The objective of the proposed PSO is to minimize the total support cost from generators and reactive compensators. It is achieved by maintaining the whole system power loss as minimum thereby reducing cost allocation. The purpose of reactive power dispatch is to determine the proper amount and location of reactive support. Reactive Optimal Power Flow (ROPF) formulation is developed as an analysis tool and the validity of proposed method is examined using an IEEE-14 bus system.
Cited by 16Open access
Patrick Groeneveld · 2004
No abstract available.
Cited by 0
Liming Wei (2873834), Fengyang Zhang (21380334) · Figshare · 2025
<div> To accelerate energy efficiency improvement and green transition in industrial parks while addressing energy utilization and carbon reduction requirements, this study proposes a low-carbon economic dispatch model for integrated energy systems (IES) based on an enhanced multi-objective artificial hummingbird algorithm (MOAHA). The main contributions are threefold: First, we establish an optimized dispatch model incorporating combined cooling, heating and power (CCHP) systems, a refined two-stage power-to-gas (P2G) conversion process, and carbon capture technologies. Second, a stepwise carbon trading mechanism is introduced to further reduce carbon emissions from the IES. Third, a multi-strategy enhanced MOAHA is developed through three key improvements: 1) Logistic-sine fused chaotic mapping for population initialization to enhance distribution uniformity and solution quality; 2) Elite opposition-based learning and adaptive spiral migration foraging mechanisms to optimize individual positions and population diversity; 3) Simplex method integration to strengthen local search capabilities and optimization precision. Comprehensive case studies demonstrate the model’s effectiveness, achieving an 82.9% reduction in carbon emissions and 17.3% decrease in operational costs compared to conventional approaches. The proposed framework provides a technically viable solution for sustainable energy management in industrial parks, effectively balancing economic and environmental objectives. </div>
Cited by 0Open access
Sánchez Reinoso, Carlos Roberto, Buitrago, Roman Horacio, Milone, Diego Humberto · Conicet · 2015
The objective of this chapter is to optimize the photovoltaic power plant considering the effects of variable shading on time and weather. For that purpose, an optimization scheme based on the simulator from Sanchez Reinoso, Milone, and Buitrago (2013) and on evolutionary computation techniques is proposed. Regarding the latter, the representation used and the proposed initialization mechanism are explained. Afterwards, the proposed algorithms that allow carrying out crossover and mutation operations for the problem are detailed. In addition, the designed fitness function is presented. Lastly, experiments are conducted with the proposed optimization methodology and the results obtained are discussed.
Cited by 0Open access
Яськів, Володимир Іванович, Гурник, Олександр Петрович · 2011
Подано результати досліджень по оптимізації режимів коректорів коефіцієнта потужності на основі однотакного підвищуючого перетворювача
Cited by 0
Liming Wei (2873834), Fengyang Zhang (21380334) · Figshare · 2025
<div> To accelerate energy efficiency improvement and green transition in industrial parks while addressing energy utilization and carbon reduction requirements, this study proposes a low-carbon economic dispatch model for integrated energy systems (IES) based on an enhanced multi-objective artificial hummingbird algorithm (MOAHA). The main contributions are threefold: First, we establish an optimized dispatch model incorporating combined cooling, heating and power (CCHP) systems, a refined two-stage power-to-gas (P2G) conversion process, and carbon capture technologies. Second, a stepwise carbon trading mechanism is introduced to further reduce carbon emissions from the IES. Third, a multi-strategy enhanced MOAHA is developed through three key improvements: 1) Logistic-sine fused chaotic mapping for population initialization to enhance distribution uniformity and solution quality; 2) Elite opposition-based learning and adaptive spiral migration foraging mechanisms to optimize individual positions and population diversity; 3) Simplex method integration to strengthen local search capabilities and optimization precision. Comprehensive case studies demonstrate the model’s effectiveness, achieving an 82.9% reduction in carbon emissions and 17.3% decrease in operational costs compared to conventional approaches. The proposed framework provides a technically viable solution for sustainable energy management in industrial parks, effectively balancing economic and environmental objectives. </div>
Cited by 0Open access
Liming Wei (2873834), Fengyang Zhang (21380334) · Figshare · 2025
<div> To accelerate energy efficiency improvement and green transition in industrial parks while addressing energy utilization and carbon reduction requirements, this study proposes a low-carbon economic dispatch model for integrated energy systems (IES) based on an enhanced multi-objective artificial hummingbird algorithm (MOAHA). The main contributions are threefold: First, we establish an optimized dispatch model incorporating combined cooling, heating and power (CCHP) systems, a refined two-stage power-to-gas (P2G) conversion process, and carbon capture technologies. Second, a stepwise carbon trading mechanism is introduced to further reduce carbon emissions from the IES. Third, a multi-strategy enhanced MOAHA is developed through three key improvements: 1) Logistic-sine fused chaotic mapping for population initialization to enhance distribution uniformity and solution quality; 2) Elite opposition-based learning and adaptive spiral migration foraging mechanisms to optimize individual positions and population diversity; 3) Simplex method integration to strengthen local search capabilities and optimization precision. Comprehensive case studies demonstrate the model’s effectiveness, achieving an 82.9% reduction in carbon emissions and 17.3% decrease in operational costs compared to conventional approaches. The proposed framework provides a technically viable solution for sustainable energy management in industrial parks, effectively balancing economic and environmental objectives. </div>
Cited by 0Open access
Carlos Roberto Sánchez Reinoso, R.H. Buitrago, Diego H. Milone · IGI Global eBooks · 2016
The objective of this chapter is to optimize the photovoltaic power plant considering the effects of variable shading on time and weather. For that purpose, an optimization scheme based on the simulator from Sanchez Reinoso, Milone, and Buitrago (2013) and on evolutionary computation techniques is proposed. Regarding the latter, the representation used and the proposed initialization mechanism are explained. Afterwards, the proposed algorithms that allow carrying out crossover and mutation operations for the problem are detailed. In addition, the designed fitness function is presented. Lastly, experiments are conducted with the proposed optimization methodology and the results obtained are discussed.
Cited by 0
Chi Ting Ng · DR-NTU (Nanyang Technological University) · 2017
With increasing demands for power and increasing energy scarcity, it is essential that power generation should be as efficient as possible. The power dispatch problem is a real-world power system problem that aims to schedule a given set of generators to meet the power load demand while fulfilling a given set of constraints. With equality and inequality constraints, the power dispatch problem is a highly non-linear optimization problem that requires powerful evolutionary algorithms to solve. In this paper, a form of evolutionary algorithm known as differential evolution is used to minimize the transmission loss in a power system. Variations of the standard differential evolution, such as SHADE, L-SHADE and L-SHADE EpSin, are also applied.
Cited by 0
Jason Cong, Puneet Gupta, J. Jack Lee · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · 2010
In response to the increasing variations in integrated-circuit manufacturing, the current trend is to create designs that take these variations into account statistically. In this paper, we quantify the difference between the statistical and deterministic optima of leakage power while making no assumptions about the delay model. We develop a framework for deriving a theoretical upper bound on the suboptimality that is incurred by using the deterministic optimum as an approximation for the statistical optimum. We show that for the mean power measure, the deterministic optima is an excellent approximation, and for the mean plus standard deviation measures, the optimality gap increases as the amount of inter-die variation grows, for a suite of benchmark circuits in a 45 nm technology. For large variations, we show that there are excellent linear approximations that can be used to approximate the effects of variation. Therefore, the need to develop special statistical power optimization algorithms is questionable.
Cited by 7
Hari Sundararajan · Civil War Book Review · 2011
After many years of focusing on “faster” computers, people have started taking notice of the fact that the race for “speed” has had the unfortunate side effect of increasing the total power consumed, thereby increasing the total cost of ownership of these machines. The heat produced has required expensive cooling facilities. As a result, it is difficult to ignore the growing trend of “Green Computing,” which is defined by San Murugesan as “the study and practice of designing, manufacturing, using, and disposing of computers, servers, and associated subsystems – such as monitors, printers, storage devices, and networking and communication systems – efficiently and effectively with minimal or no impact on the environment”. There have been different approaches to green computing, some of which include data center power management, operating system support, power supply, storage hardware, video card and display hardware, resource allocation, virtualization, terminal servers and algorithmic efficiency. In this thesis, we particularly study the relation between algorithmic efficiency and power consumption, obtaining performance models in the process. The algorithms studied primarily include basic linear algebra routines, such as matrix and vector multiplications and iterative solvers. Our studies show that it if the source code is optimized and tuned to the particular hardware used, there is a possibility of reducing the total power consumed at only slight costs to the computation time. The data sets utilized in this thesis are not significantly large and consequently, the power savings are not large either. However, as these optimizations can be scaled to larger data sets, it presents a positive outlook for power savings in much larger research environments.
Cited by 0Open access
Liming Wei (2873834), Fengyang Zhang (21380334) · Figshare · 2025
<div> To accelerate energy efficiency improvement and green transition in industrial parks while addressing energy utilization and carbon reduction requirements, this study proposes a low-carbon economic dispatch model for integrated energy systems (IES) based on an enhanced multi-objective artificial hummingbird algorithm (MOAHA). The main contributions are threefold: First, we establish an optimized dispatch model incorporating combined cooling, heating and power (CCHP) systems, a refined two-stage power-to-gas (P2G) conversion process, and carbon capture technologies. Second, a stepwise carbon trading mechanism is introduced to further reduce carbon emissions from the IES. Third, a multi-strategy enhanced MOAHA is developed through three key improvements: 1) Logistic-sine fused chaotic mapping for population initialization to enhance distribution uniformity and solution quality; 2) Elite opposition-based learning and adaptive spiral migration foraging mechanisms to optimize individual positions and population diversity; 3) Simplex method integration to strengthen local search capabilities and optimization precision. Comprehensive case studies demonstrate the model’s effectiveness, achieving an 82.9% reduction in carbon emissions and 17.3% decrease in operational costs compared to conventional approaches. The proposed framework provides a technically viable solution for sustainable energy management in industrial parks, effectively balancing economic and environmental objectives. </div>
Cited by 0Open access