Model predictive control for deferrable loads scheduling

Real-time demand response is essential for handling the uncertainties of renewable generation. Traditionally, demand response has been focused on large industrial and commercial loads, however it is expected that a large number of small residential loads such as air conditioners, dish washers, and electric vehicles will also participate in the coming years. The electricity consumption of these smaller loads, which we call deferrable loads, can be shifted over time, and thus be used (in aggregate) to compensate for the random fluctuations in renewable generation.

In this thesis, we propose a real-time distributed deferrable load control algorithm to reduce the variance of aggregate load (load minus renewable generation) by shifting the power consumption of deferrable loads to periods with high renewable generation. The algorithm is model predictive in nature, i.e., at every time step, the algorithm minimizes the expected variance to go with updated predictions. We prove that suboptimality of this model predictive algorithm vanishes as time horizon expands in the average case analysis. Further, we prove strong concentration results on the distribution of the load variance obtained by model predictive deferrable load control. These concentration results highlight that the typical performance of model predictive deferrable load control is tightly concentrated around the average-case performance. Finally, we evaluate the algorithm via trace-based simulations.

Radio-aware service-level scheduling to minimize downlink traffic delay through Mobile Edge Computing

One of the most challenging problems in mobile broadband networks is how to assign the available radio resources among the different mobile users. Traditionally, research proposals are either speci c to some type of traffic or deal with computationally intensive algorithms aimed at optimizing the delivery of general purpose traffic. Consequently, commercial networks do not incorporate these mechanisms due to the limited hardware resources at the mobile edge. Emerging 5G architectures introduce cloud computing principles to add flexible computational resources to Radio Access Networks. This paper makes use of the Mobile Edge Computing concepts to introduce a new element, denoted as Mobile Edge Scheduler, aimed at minimizing the mean delay of general traffic flows in the LTE downlink. This element runs close to the eNodeB element and implements a novel flow-aware and channel-aware scheduling policy in order to accommodate the transmissions to the available channel quality of end users.

Proposição e análise de modelos híbridos para o problema de escalonamento de produção em oficina de máquinas

Nas últimas décadas, o problema de escalonamento da produção em oficina de máquinas, na literatura referido como JSSP (do inglês Job Shop Scheduling Problem), tem recebido grande destaque por parte de pesquisadores do mundo inteiro. Uma das razões que justificam tamanho interesse está em sua alta complexidade. O JSSP é um problema de análise combinatória classificado como NP-Difícil e, apesar de existir uma grande variedade de métodos e heurísticas que são capazes de resolvê-lo, ainda não existe hoje nenhum método ou heurística capaz de encontrar soluções ótimas para todos os problemas testes apresentados na literatura. A outra razão basea-se no fato de que esse problema encontra-se presente no diaa- dia das indústrias de transformação de vários segmento e, uma vez que a otimização do escalonamento pode gerar uma redução significativa no tempo de produção e, consequentemente, um melhor aproveitamento dos recursos de produção, ele pode gerar um forte impacto no lucro dessas indústrias, principalmente nos casos em que o setor de produção é responsável por grande parte dos seus custos totais. Entre as heurísticas que podem ser aplicadas à solução deste problema, o Busca Tabu e o Multidão de Partículas apresentam uma boa performance para a maioria dos problemas testes encontrados na literatura. Geralmente, a heurística Busca Tabu apresenta uma boa e rápida convergência para pontos ótimos ou subótimos, contudo esta convergência é frequentemente interrompida por processos cíclicos e a performance do método depende fortemente da solução inicial e do ajuste de seus parâmetros. A heurística Multidão de Partículas tende a convergir para pontos ótimos, ao custo de um grande esforço computacional, sendo que sua performance também apresenta uma grande sensibilidade ao ajuste de seus parâmetros. Como as diferentes heurísticas aplicadas ao problema apresentam pontos positivos e negativos, atualmente alguns pesquisadores começam a concentrar seus esforços na hibridização das heurísticas existentes no intuito de gerar novas heurísticas híbridas que reúnam as qualidades de suas heurísticas de base, buscando desta forma diminuir ou mesmo eliminar seus aspectos negativos. Neste trabalho, em um primeiro momento, são apresentados três modelos de hibridização baseados no esquema geral das Heurísticas de Busca Local, os quais são testados com as heurísticas Busca Tabu e Multidão de Partículas. Posteriormente é apresentada uma adaptação do método Colisão de Partículas, originalmente desenvolvido para problemas contínuos, onde o método Busca Tabu é utilizado como operador de exploração local e operadores de mutação são utilizados para perturbação da solução. Como resultado, este trabalho mostra que, no caso dos modelos híbridos, a natureza complementar e diferente dos métodos Busca Tabu e Multidão de Partículas, na forma como são aqui apresentados, da origem à algoritmos robustos capazes de gerar solução ótimas ou muito boas e muito menos sensíveis ao ajuste dos parâmetros de cada um dos métodos de origem. No caso do método Colisão de Partículas, o novo algorítimo é capaz de atenuar a sensibilidade ao ajuste dos parâmetros e de evitar os processos cíclicos do método Busca Tabu, produzindo assim melhores resultados.

Gain Scheduling Control of an Islanded Microgrid Voltage

The aim of this research study has been to design a gain scheduling (GS) digital controller in order to control the voltage of an islanded microgrid in the presence of fast varying loads (FVLs), and to compare it to a robust controller. The inverter which feeds the microgrid is connected to it through an inductance-capacitor-inductance (LCL) filter. The oscillatory and nonlinear behaviour of the plant is analyzed in the whole operating zone. Afterwards, the design of the controllers which contain two loops in cascade are described. The first loop concerns the current control, while the second is linked to the voltage regulation. Two controllers, one defined as Robust and another one as GS controller, are designed for the two loops, emphasizing in their robustness and their ability to damp the oscillatory plant behaviour. To finish, some simulations are carried out to study and compare the two kinds of controllers in different operating points. The results show that both controllers damp the oscillatory behaviour of the plant in closed loop (CL), and that the GS controller ensures a better rejection of current disturbances from FVLs.

A Novel Scheduling Index Rule Proposal for QoE Maximization in Wireless Networks

This paper deals with the resource allocation problem aimed at maximizing users' perception of quality in wireless channels with time-varying capacity. First of all, we model the subjective quality-aware scheduling problem in the framework of Markovian decision processes. Then, given that the obtaining of the optimal solution of this model is unachievable, we propose a simple scheduling index rule with closed-form expression by using a methodology based on Whittle approach. Finally, we analyze the performance of the achieved scheduling proposal in several relevant scenarios, concluding that it outperforms the most popular existing resource allocation strategies.

Comparison of different scheduling techniques for H-infinity controllers

Several approaches to designing schedule H-infinity control systems are compared. These include a controller switching approach and also parameter scheduling of an observer representation of the controller. They are illustrated by application to a Generic VSTOI. Aircraft Model (GVAM) supplied by The Royal Aerospace Establishment (RAE) at Bedford. The switched design has been tested on the simulator at RAE Bedford. The linear H-infinity designs make use of a loop-shaping followed by robust stabilisation to additive perturbations of a normalised coprime factorisation of the shaped plans. The different scheduling approaches are compared with respect to achieved robust stability levels. performance and complexity of implementation.

Solving problems in production scheduling

Traditionally, production scheduling has been viewed as a problem-solving task that involves a single problem - generation of a suitable schedule. This paper presents an alternative model in which individual difficulties are viewed as problems, and the task is to maintain a suitable schedule by resolving as many of these problems as possible. Decision support software is described that has facilities for defining policies to handle numerous minor problems and complete problem-solving strategies to deal with major problems. The paper then discusses the potential for this style of decision support to improve the performance of human schedulers. © 1995.

Product scheduling for thermal energy reduction in papermaking industries

Papermaking is considered as an energy-intensive industry partly due to the fact that the machinery and procedures have been designed at the time when energy was both cheap and plentiful. A typical paper machine manufactures a variety of different products (grades) which impose variable per-unit raw material and energy costs to the mill. It is known that during a grade change operation the products are not market-worthy. Therefore, two different production regimes, i.e. steady state and grade transition can be recognised in papermaking practice. Among the costs associated with paper manufacture, the energy cost is 'more variable' due to (usually) day-to-day variations of the energy prices. Moreover, the production of a grade is often constrained by customer delivery time requirements. Given the above constraints and production modes, the product scheduling technique proposed in this paper aims at optimising the sequence of orders in a single machine so that the cost of production (mainly determined by the energy) is minimised. Simulation results obtained from a commercial board machine in the UK confirm the effectiveness of the proposed method. © 2011 IFAC.