2,265 research outputs found
Interaction between intelligent agent strategies for real-time transportation planning
In this paper we study the real-time scheduling of time-sensitive full truckload pickup-and-delivery jobs. The problem involves the allocation of jobs to a fixed set of vehicles which might belong to dfferent collaborating transportation agencies. A recently proposed solution methodology for this problem is the use of a multi-agent system where shipper agents other jobs through sequential auctions and vehicle agents bid on these jobs. In this paper we consider such a multi-agent system where both the vehicle agents and the shipper agents are using profit maximizing look-ahead strategies. Our main contribution is that we study the interrelation of these strategies and their impact on the system-wide logistical costs. From our simulation results, we conclude that the system-wide logistical costs (i) are always reduced by using the look-ahead policies instead of a myopic policy (10-20%) and (ii) the joint effect of two look-ahead policies is larger than the effect of an individual policy. To provide an indication of the savings that might be realized with a central solution methodology, we benchmark our results against an integer programming approach
Economic regulation for multi tenant infrastructures
Large scale computing infrastructures need scalable and effi cient resource allocation mechanisms to ful l the requirements of its participants and applications while the whole system is regulated to work e ciently. Computational markets provide e fficient allocation mechanisms that aggregate information from multiple sources in large, dynamic and complex systems where there is not a single source with complete information. They have been proven to be successful in matching resource demand and resource supply in the presence of sel sh multi-objective and utility-optimizing users and sel sh pro t-optimizing providers. However, global infrastructure metrics which may not directly affect participants of the computational market still need to be addressed -a.k.a. economic externalities like load balancing or energy-efficiency.
In this thesis, we point out the need to address these economic externalities, and we design and evaluate appropriate regulation mechanisms from di erent perspectives on top of existing economic models, to incorporate a wider range of objective metrics not considered otherwise. Our main contributions in this thesis are threefold; fi rst, we propose a taxation mechanism that addresses the resource congestion problem e ffectively improving the balance of load among resources when correlated economic preferences are present; second,
we propose a game theoretic model with complete information to derive an algorithm to aid resource providers to scale up and down resource supply so energy-related costs can be reduced; and third, we relax our previous assumptions about complete information on the resource provider side and design an incentive-compatible mechanism to encourage users to truthfully report their resource requirements effectively assisting providers to make energy-eff cient allocations while providing a dynamic allocation mechanism to users.Les infraestructures computacionals de gran escala necessiten mecanismes d’assignació de recursos escalables i eficients per complir amb els requisits computacionals de tots els seus participants, assegurant-se de que el sistema és regulat apropiadament per a que funcioni de manera efectiva. Els mercats computacionals són mecanismes d’assignació de recursos eficients que incorporen informació de diferents fonts considerant sistemes de gran escala, complexos i dinà mics on no existeix una única font que proveeixi informació completa de l'estat del sistema. Aquests mercats computacionals han demostrat ser exitosos per acomodar la demanda de recursos computacionals amb la seva oferta quan els seus participants son considerats estratègics des del punt de vist de teoria de jocs. Tot i això existeixen mètriques a nivell global sobre la infraestructura que no tenen per que influenciar els usuaris a priori de manera directa. Aixà doncs, aquestes externalitats econòmiques com poden ser el balanceig de cà rrega o la eficiència energètica, conformen una lÃnia d’investigació que cal explorar. En aquesta tesi, presentem i descrivim la problemà tica derivada d'aquestes externalitats econòmiques. Un cop establert el marc d’actuació, dissenyem i avaluem mecanismes de regulació apropiats basats en models econòmics existents per resoldre aquesta problemà tica des de diferents punts de vista per incorporar un ventall més ampli de mètriques objectiu que no havien estat considerades fins al moment. Les nostres contribucions principals tenen tres vessants: en primer lloc, proposem un mecanisme de regulació de tipus impositiu que tracta de mitigar l’aparició de recursos sobre-explotats que, efectivament, millora el balanceig de la cà rrega de treball entre els recursos disponibles; en segon lloc, proposem un model teòric basat en teoria de jocs amb informació o completa que permet derivar un algorisme que facilita la tasca dels proveïdors de recursos per modi car a l'alça o a la baixa l'oferta de recursos per tal de reduir els costos relacionats amb el consum energètic; i en tercer lloc, relaxem la nostra assumpció prèvia sobre l’existència d’informació complerta per part del proveïdor de recursos i dissenyem un mecanisme basat en incentius per fomentar que els usuaris facin pública de manera verÃdica i explÃcita els seus requeriments computacionals, ajudant d'aquesta manera als proveïdors de recursos a fer assignacions eficients des del punt de vista energètic a la vegada que oferim un mecanisme l’assignació de recursos dinà mica als usuari
Dynamic tariffs-based demand response in retail electricity market under uncertainty
Demand response (DR) programs play a crucial role in improving system
reliability and mitigating price volatility by altering the core profile of
electricity consumption. This paper proposes a game-theoretical model that
captures the dynamic interplay between retailers (leaders) and consumers
(followers) in a tariffs-based electricity market under uncertainty. The
proposed procedure offers theoretical and economic insights by analyzing demand
flexibility within a hierarchical decision-making framework. In particular, two
main market configurations are examined under uncertainty: i) there exists a
retailer that exercises market power over consumers, and ii) the retailer and
the consumers participate in a perfect competitive game. The former case is
formulated as a mathematical program with equilibrium constraints (MPEC),
whereas the latter case is recast as a mixed-integer linear program (MILP).
These problems are solved by deriving equivalent tractable reformulations based
on the Karush-Kuhn-Tucker (KKT) optimality conditions of each agent's problem.
Numerical simulations based on real data from the European Energy Exchange
platform are used to illustrate the performance of the proposed methodology.
The results indicate that the proposed model effectively characterizes the
interactions between retailers and flexible consumers in both perfect and
imperfect market structures. Under perfect competition, the economic benefits
extend not only to consumers but also to overall social welfare. Conversely, in
an imperfect market, retailers leverage consumer flexibility to enhance their
expected profits, transferring the risk of uncertainty to end-users.
Additionally, the degree of consumer flexibility and their valuation of
electricity consumption play significant roles in shaping market outcomes.Comment: 3
Load Balancer using Whale-Earthworm Optimization for Efficient Resource Scheduling in the IoT-Fog-Cloud Framework
Cloud-Fog environment is useful in offering optimized services to customers in their daily routine tasks. With the exponential usage of IoT devices, a huge scale of data is generated. Different service providers use optimization scheduling approaches to optimally allocate the scarce resources in the Fog computing environment to meet job deadlines. This study introduces the Whale-EarthWorm Optimization method (WEOA), a powerful hybrid optimization method for improving resource management in the Cloud-Fog environment. Striking a balance between exploration and exploitation of these approaches is difficult, if only Earthworm or Whale optimization methods are used. Earthworm technique can result in inefficiency due to its investigations and additional overhead, whereas Whale algorithm, may leave scope for improvement in finding the optimal solutions using its exploitation. This research introduces an efficient task allocation method as a novel load balancer. It leverages an enhanced exploration phase inspired by the Earthworm algorithm and an improved exploitation phase inspired by the Whale algorithm to manage the optimization process. It shows a notable performance enhancement, with a 6% reduction in response time, a 2% decrease in cost, and a 2% improvement in makespan over EEOA. Furthermore, when compared to other approaches like h-DEWOA, CSDEO, CSPSO, and BLEMO, the proposed method achieves remarkable results, with response time reductions of up to 82%, cost reductions of up to 75%, and makespan improvements of up to 80%
Dynamic Multigrain Parallelization on the Cell Broadband Engine
This paper addresses the problem of orchestrating and scheduling
parallelism at multiple levels of granularity on heterogeneous
multicore processors. We present policies and mechanisms for adaptive
exploitation and scheduling of multiple layers of parallelism on the
Cell Broadband Engine. Our policies combine event-driven task
scheduling with malleable loop-level parallelism, which is exposed
from the runtime system whenever task-level parallelism leaves cores
idle. We present a runtime system for scheduling applications with
layered parallelism on Cell and investigate its potential with RAxML,
a computational biology application which infers large phylogenetic
trees, using the Maximum Likelihood (ML) method. Our experiments show
that the Cell benefits significantly from dynamic parallelization
methods, that selectively exploit the layers of parallelism in the
system, in response to workload characteristics. Our runtime
environment outperforms naive parallelization and scheduling based on
MPI and Linux by up to a factor of 2.6. We are able to execute RAxML
on one Cell four times faster than on a dual-processor system with
Hyperthreaded Xeon processors, and 5--10\% faster than on a
single-processor system with a dual-core, quad-thread IBM Power5
processor
Contributions on DC microgrid supervision and control strategies for efficiency optimization through battery modeling, management, and balancing techniques
Aquesta tesi presenta equips, models i estratègies de control que han estat desenvolupats amb l'objectiu final de millorar el funcionament d'una microxarxa CC.
Es proposen dues estratègies de control per a millorar l'eficiència dels convertidors CC-CC que interconnecten les unitats de potència de la microxarxa amb el bus CC. La primera estratègia, Control d'Optimització de Tensió de Bus centralitzat, administra la potència del Sistema d'Emmagatzematge d'Energia en Bateries de la microxarxa per aconseguir que la tensió del bus segueixi la referència dinà mica de tensió òptima que minimitza les pèrdues dels convertidors. La segona, Optimització en Temps Real de la Freqüència de Commutació, consisteix a operar localment cada convertidor a la seva freqüència de commutació òptima, minimitzant les seves pèrdues.
A més, es proposa una nova topologia d'equilibrador actiu de bateries mitjançant un únic convertidor CC-CC i s'ha dissenyat la seva estratègia de control. El convertidor CC-CC transfereix cà rrega cel·la a cel·la, emprant encaminament de potència a través d'un sistema d'interruptors controlats. L'estratègia de control de l'equalitzador aconsegueix un rà pid equilibrat del SOC evitant sobrecompensar el desequilibri.
Finalment, es proposa un model simple de degradació d'una cel·la NMC amb elèctrode negatiu de grafit. El model combina la simplicitat d'un model de circuit equivalent, que explica la dinà mica rà pida de la cel·la, amb un model fÃsic del creixement de la capa Interfase Sòlid-Electròlit (SEI), que prediu la pèrdua de capacitat i l'augment de la resistència interna a llarg termini. El model proposat quantifica la incorporació de liti al rang de liti ciclable necessà ria per a aconseguir els lÃmits de OCV després de la pèrdua de liti ciclable en la reacció secundà ria. El model de degradació SEI pot emprar-se per a realitzar un control predictiu de bateries orientat a estendre la seva vida útil.Aquesta tesi presenta equips, models i estratègies de control que han estat desenvolupats amb l'objectiu final de millorar el funcionament d'una microxarxa CC.
Es proposen dues estratègies de control per a millorar l'eficiència dels convertidors CC-CC que interconnecten les unitats de potència de la microxarxa amb el bus CC. La primera estratègia, Control d'Optimització de Tensió de Bus centralitzat, administra la potència del Sistema d'Emmagatzematge d'Energia en Bateries de la microxarxa per aconseguir que la tensió del bus segueixi la referència dinà mica de tensió òptima que minimitza les pèrdues dels convertidors. La segona, Optimització en Temps Real de la Freqüència de Commutació, consisteix a operar localment cada convertidor a la seva freqüència de commutació òptima, minimitzant les seves pèrdues.
A més, es proposa una nova topologia d'equilibrador actiu de bateries mitjançant un únic convertidor CC-CC i s'ha dissenyat la seva estratègia de control. El convertidor CC-CC transfereix cà rrega cel·la a cel·la, emprant encaminament de potència a través d'un sistema d'interruptors controlats. L'estratègia de control de l'equalitzador aconsegueix un rà pid equilibrat del SOC evitant sobrecompensar el desequilibri.
Finalment, es proposa un model simple de degradació d'una cel·la NMC amb elèctrode negatiu de grafit. El model combina la simplicitat d'un model de circuit equivalent, que explica la dinà mica rà pida de la cel·la, amb un model fÃsic del creixement de la capa Interfase Sòlid-Electròlit (SEI), que prediu la pèrdua de capacitat i l'augment de la resistència interna a llarg termini. El model proposat quantifica la incorporació de liti al rang de liti ciclable necessà ria per a aconseguir els lÃmits de OCV després de la pèrdua de liti ciclable en la reacció secundà ria. El model de degradació SEI pot emprar-se per a realitzar un control predictiu de bateries orientat a estendre la seva vida útil.This dissertation presents a set of equipment, models and control strategies, that have been developed with the final goal of improving the operation of a DC microgrid.
Two control strategies are proposed to improve the efficiency of the DC-DC converters that interface the microgrid’s power units with the DC bus. The first strategy is centralized Bus Voltage Optimization Control, which manages the power of the microgrid’s Battery Energy Storage System to make the bus voltage follow the optimum voltage dynamic reference that minimizes the converters’ losses. The second control strategy is Online Optimization of Switching Frequency, which consists in locally operating each converter at its optimum switching frequency, again minimizing power losses. The two proposed optimization strategies have been validated in simulations.
Moreover, a new converter-based active balancing topology has been proposed and its control strategy has been designed. This equalizer topology consists of a single DC-DC converter that performs cell-to-cell charge transfer employing power routing via controlled switches. The control strategy of the equalizer has been designed to achieve rapid SOC balancing while avoiding imbalance overcompensation. Its performance has been validated in simulation.
Finally, a simple degradation model of an NMC battery cell with graphite negative electrode is proposed. The model combines the simplicity of an equivalent circuit model, which explains the fast dynamics of the cell, with a physical model of the Solid-Electrolyte Interphase (SEI) layer growth process, which predicts the capacity loss and the internal resistance rise in the long term. The proposed model fine-tunes the capacity loss prediction by accounting for the incorporation of unused lithium reserves of both electrodes into the cyclable lithium range to reach the OCV limits after the side reaction has consumed cyclable lithium. The SEI degradation model can be used to perform predictive control of batteries oriented toward extending their lifetime
Connecting office buildings to the smart grid:harvesting flexibility
Traditionally, the electricity system is oriented top- down and buildings are just energy consumers. Since electricity is expensive to store, supply and demand have to be balanced at all times. In the nearby future, the electricity system must be able to cope with an increase in intermittent decentralized energy production. Also, ongoing electrification is expected to contribute to an increase in demand. Demand side management and control is needed to ensure reliability of supply at acceptable costs. Buildings can be a part of the solution as they can offer flexibility in energy consumption and/or production. By enabling flexible control of processes on the building premises, the building can provide balancing services and respond to congestion problems in the power system, while user comfort can be guaranteed. For the engineering company BAM Techniek, it is of importance to know how the integration of such smart grid technologies in buildings can contribute to (energy) service provision. This study focusses on the enabling of flexibility in energy consumption and generation, while comfort is guaranteed. The project aims to create a framework that enables flexible control of building processes, and analyses of the potential value of flexibility in office buildings. The proposed framework consists of a technical solution, and an analysis of the economical benefits. Priority based control is introduced to enable flexible control of building processes. The concept is capable of prioritizing the energy consumption of processes, and controlling the consumption depending on the needs of the electricity market. An empty office has for instance, a low priority to consume energy. User needs are integrated in the prioritization mechanisms. This mechanism ensures that processes stay within the allowed bandwidth, while providing flexibility to the power system. Since the priority based control connects the end user needs to the market needs, a bi-directional flow of information is required. The Eneco World Office is used to perform a building case study to test the technological framework. Three sources of flexibility are investigated: decentralized climate systems, electric vehicles, and a sensible heat buffer. Results show that the amount of available flexibility depends mainly on load profiles and comfort settings. Electric vehicles and the sensible heat buffer provide significant amounts of flexibility. The flexibility in decentralized climate systems is limited since the room air temperature responds relatively fast to changes in settings and comfort boundaries are quickly met. The long term effect of storage in the building inertia should however be investigated further. Economical benefits can be created by using the variation in costs on the wholesale market caused by market volatility. When flexibility is used to contribute to the balance in a portfolio of buildings, the imbalance can be reduced, which leads to a reduction in costs. Finally, flexibility can contribute to a reduction in peak demand of buildings, leading to cost savings in the network connection. The need for smart grids is growing, while energy services are becoming more important in the built environment. Considering the potential value of smart grid services in the built environment and the market size, it is evident that the developing smart grid market presents opportunities for BAM Techniek. The provision of flexibility services can be a valuable addition to the energy services portfolio
State-of-the-Art of the Flywheel/Li-ion Battery Hybrid Storage System for Stationary Applications
This thesis presents the State-of-the-Art of a flywheel/Li-ion battery Hybrid Energy Storage System for stationary applications. As Renewable Energy Sources increase in the grid so do the stability problems associated with their intermittency. Here the importance of Energy Storage Systems that aim to provide many grid services. The complementary features of the two devices in terms of power, energy and discharge time candidate this hybrid system as an optimal solution to support future grids
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