Wireless network for connecting the devices and sensors to communicate and sense is quite attractive nowadays for a wide range of applications. The scaling of the wireless network to millions of nodes currently is impractical if the process is supplied by battery energy. The batteries need to be periodically replaced or recharged due to the limited battery size. One solution is harvesting ambient energy to power the network. In this thesis, we consider a battery-limited energy harvesting communication system with online power control. Assuming independent and identically distributed (i.i.d.) energy arrivals and the harvest-store-use architecture, it is shown that the greedy policy achieves the maximum throughput if and only if the battery capacity is below a certain positive threshold that admits a precise characterization. Simple lower and upper bounds on this threshold are established. The asymptotic relationship between the threshold and the mean of the energy arrival process is analyzed for several examples. Furthermore, value iteration method is applied for solving the Bellman equation to obtain the optimal power allocation policy. The optimal policy is analyzed for several examples. / Thesis / Master of Applied Science (MASc)

Opportunistic spectrum access has become a high priority research area in the past few years. The motivation behind this actively researched area is the fact that the limited spectrum available is currently being utilized in an inefficient way. The complete wireless spectrum is assigned and reserved, but not necessarily being used. At the same time, the demand for innovation in wireless technology is growing. Since there is no room in the wireless spectrum to allocate significant frequency bands for future wireless technologies, the only recourse is to increase utilization of the spectrum. To achieve this, we must find a way to share the spectrum. Spectrum sharing techniques will require coordination between all the layers of the protocol stack. The network and the wireless medium are inextricably linked and, thus, both must be considered when optimizing wireless network performance. Unfortunately, interactions in the wireless medium can lead to non-convex problems which have been shown to be NP-hard. Techniques must be developed to tackle the optimization problems that arise from wireless network analysis. In this document we focus on analyzing the spectrum sharing problem from two perspectives: cooperative game theory and non-convex optimization. We develop a cooperative game theory model to analyze a scenario where nodes in a multi-hop wireless network need to agree on a fair allocation of spectrum. We show that in high interference environments, the utility space of the game is non-convex, which may make some optimal allocations unachievable with pure strategies. However, we show that as the number of channels available increases, the utility space becomes close to convex and thus optimal allocations become achievable with pure strategies. We propose the use of the NBS and show that it achieves a good compromise between fairness and efficiency, using a small number of channels. We also propose a distributed algorithm for spectrum sharing and show that it achieves allocations reasonably close to the NBS. In our game theory analysis, we studied the possible outcomes of the spectrum sharing problem and propose the NBS as a desirable outcome and propose an algorithm to achieve the NBS spectrum allocation. However, the expression used to compute the NBS is a non-convex optimization problem. We propose an optimization model to solve a class of problems that incorporate the non-convex dynamics of the wireless medium that occur when the objective is a function of SINR. We present two case studies to show the application of the model to discrete and continuous optimization problems. We propose a branch and bound heuristic, based on the RLT, for approximating the solution of continuous optimization problems. Finally, we present results for the continuous case study. We show simulation results for the heuristic compared to a time constrained mixed integer linear program (MILP) as well as a nonlinear optimization using random starting points. We show that for small networks the MILP achieves the optimal in reasonable time and the heuristic achieves a value close to the optimal. We also show that for large networks the heuristic outperforms the MILP as well as the nonlinear search. / Ph. D.

Doctor of Philosophy / Department of Electrical and Computer Engineering / Shelli K. Starrett / Monitoring and control of modern power systems have become very complex tasks due to the interconnection of power grids. These large-scale power grids confront system operators with a huge set of system inputs and control parameters. This work develops and compares intelligent systems-based algorithms which may be considered by power system operators or planners to help manage, process, and evaluate large amounts of data due to varying conditions within the system. The methods can be used to provide assistance in making operational control and planning decisions for the system in a timely manner. The effectiveness of the proposed algorithms is tested and validated on four different power systems. First, Artificial Neural Network (ANN) models are developed and compared for two different voltage collapse indices and utilizing two different-sized sets of inputs. The ANNs monitor and evaluate the voltage profile of a system and generate intelligent conclusions regarding the status of the system from a voltage stability perspective. A feature reduction technique, based on the analysis of generated data, is used to decrease the number of inputs fed to the ANN, decreasing the number of physical quantities that need to be measured. The major contribution of this work is the development of four different algorithms to control the VAR resources in a system. Four different objectives were also considered in this part of the work, namely: minimization of the number of control changes needed, minimization of the system power losses, minimization of the system's voltage deviations, and consideration of the computational time required. Each of the algorithms is iterative in nature and is designed to take advantage of a method of decoupling the load flow Jacobian matrix to decrease the time needed per iteration. The methods use sensitivity information derived from the load flow Jacobian and augmented with equations relating the desired control and dependent variables. The heuristic-sensitivity based method is compared to two GA-based methods using two different objective functions. In addition, a FL algorithm is added to the heuristic-sensitivity algorithm and compared to a PS-based algorithm. The last part of this dissertation presents the use of one of the GA-based algorithms to identify the size of shunt capacitor necessary to enhance the voltage profile of a system. A method is presented for utilizing contingency cases with this algorithm to determine required capacitor size.

A stall-regulated wind turbine with fixed-speed operation provides a configuration which is one of the cheapest and simplest forms of wind generation and configurations. This type of turbine, however, is non-optimal at low winds, stresses the component structure and gives rise to significant power peaks during early stall conditions at high wind speeds. These problems can be overcome by having a properly designed generator speed control. Therefore, to track the maximum power locus curve at low winds, suppress the power peaks at medium winds, limit the power at a rated level at high winds and obtain a satisfactory power-wind speed curve performance (that closely resembles the ideal power-wind speed curve) with minimum stress torque simultaneously over the whole range of the wind speed variations, the availability of active control is vital. The main purpose of this study is to develop an internal model control (IMC) design for the squirrel-cage induction generator (SCIG), coupled with a full-rated power converter of a small (25 kW), stall-regulated, variable-speed wind-turbine (SRVSWT) system, which is subject to variations in the generator speed, electromagnetic torque and rotor flux. The study was done using simulations only. The objective of the controller was to optimise the generator speed to maximise the active power generated during the partial load region and maintain or restrict the generator speed to reduce/control the torque stress and the power-peaking between the partial and full load regions, before power was limited at the rated value of 25 kW at the full load region. The considered investigation involved estimating the proportional-integral (PI) and integral-proportional (IP) controllers parameter values used to track the stator-current producing torque, the rotor flux and the angular mechanical generator speed, before being used in the indirect vector control (IVC) and the sensorless indirect vector control (SLIVC) model algorithms of the SCIG system. The design of the PI and IP controllers was based on the fourth-order model of the SCIG, which is directly coupled to the full-rated power converter through the machine stator, whereas the machine rotor is connected to the turbine rotor via a gearbox. Both step and realistic wind speed profiles were considered. The IMC-based PI and IP controllers (IMC-PI-IP) tuning rule was proven to have smoothened the power curve and shown to give better estimation results compared to the IMC-based PI controllers (IMC-PI), Ziegler-Nichols (ZN) and Tyreus-Luyben (ZN) tuning rules. The findings also showed that for the SRVSWT system that employed the IVC model algorithm with the IMC-PI-IP tuning rule, considering the application of a maintained/constant speed (CS) strategy at the intermediate load region is more profitable than utilizing SRVSWT with the modified power tracking (MoPT) strategy. Besides that, the finding also suggested that, for the IMC-PI-IP approach, the IVC does provide better power tracking performance than the SLIVC model algorithm.

Fuel cost represents a significant operating expense for owners and fleet managers of hydraulic off-highway vehicles. Further, the upcoming Tier IV compliance for off-highway applications will create further expense for after-treatment and cooling. Solutions that help address these factors motivate fleet operators to consider and pursue more fuelefficient hydraulic energy recovery systems. Electrical hybridization schemes are typically complex, expensive, and often do not satisfy customer payback expectations. This paper presents a hydraulic energy recovery architecture to realize energy recovery and utilization through a hydraulic hydro-mechanical transformer. The proposed system can significantly reduce hydraulic metering losses and recover energy from multiple services. The transformer enables recovered energy to be stored in a high-pressure accumulator, maximizing energy density. It can also provide system power management, potentially allowing for engine downsizing. A hydraulic test stand is used in the development of the transformer system. The test stand is easily adaptable to simulate transformer operations on an excavator by enabling selected mode valves. The transformer’s basic operations include shaft speed control, pressure transformation control, and output flow control. This paper presents the test results of the transformer’s basic operations on the test stand, which will enable a transformer’s full function on an excavator.

Rise of the global environmental awareness and climate change impacts caused by greenhouse gases emissions brings about a revolution in the power and energy industries to reduce fossil fuels and promote low-carbon and renewable distributed generation (DG). The new dimensions, mainly encouraged by the governments’ legislative targets and incentives, have allowed the development of DG worldwide. In the U.K., renewable DG especially wind is being connected on distribution networks and ranges widely in scales. Despite the growing number of potential DG sites, the surplus generation present on the passive networks can lead to some technical problems. In particular, rural networks where wind farms exist are prone to voltage rise and line thermal constraints. In order to accommodate new DG and ensure security of supply and network reliability, active management to mitigate these issues are required. In addition, the duties to provide cost-effective DG connections at avoided expensive investment incurred from conventional solutions, e.g., reinforcement and maintain robust network are a major challenge for Distribution Network Operators (DNOs). This thesis endeavours to develop an adaptive control scheme that provides local and real-time management against voltage variations and line capacity overload at the point of wind connections on rural distribution networks. Taking into account maximising power exports and providing an economically-viable control scheme, the wind turbine’s capability, comprising reactive power control and active power curtailment, is used. Whilst the thesis concentrates on the decentralised control applying several different algorithms, in addition, semi-coordinated and centralised approaches that adopt on-load tap changing transformers’ regulation and Optimal Power Flow tool are developed. Comparisons of these approaches based upon measures, i.e., economics, DG penetration and performance are determined. As an outcome, the developed scheme can enable growing integration of renewable DG on distribution networks and can be seen as an interim solution for the DNOs towards Smart Distribution Networks.

In wireless networks, there is an ever-increasing demand for higher system throughputs, along with growing expectation for all users to be available to multimedia and Internet services. This is especially difficult to maintain at the cell-edge. Therefore, a key challenge for future orthogonal frequency division multiple access (OFDMA)-based networks is inter-cell interference coordination (ICIC). With full frequency reuse, small inter-site distances (ISDs), and heterogeneous architectures, coping with co-channel interference (CCI) in such networks has become paramount. Further, the needs for more energy efficient, or “green,” technologies is growing. In this light, Uplink Interference Protection (ULIP), a technique to combat CCI via power reduction, is investigated. By reducing the transmit power on a subset of resource blocks (RBs), the uplink interference to neighbouring cells can be controlled. Utilisation of existing reference signals limits additional signalling. Furthermore, cell-edge performance can be significantly improved through a priority class scheduler, enhancing the throughput fairness of the system. Finally, analytic derivations reveal ULIP guarantees enhanced energy efficiency for all mobile stations (MSs), with the added benefit that overall system throughput gains are also achievable. Following this, a novel scheduler that enhances both network spectral and energy efficiency is proposed. In order to facilitate the application of Pareto optimal power control (POPC) in cellular networks, a simple feasibility condition based on path gains and signal-to-noise-plus- interference ratio (SINR) targets is derived. Power Control Scheduling (PCS) maximises the number of concurrently transmitting MSs and minimises their transmit powers. In addition, cell/link removal is extended to OFDMA operation. Subsequently, an SINR variation technique, Power SINR Scheduling (PSS), is employed in femto-cell networks where full bandwidth users prohibit orthogonal resource allocation. Extensive simulation results show substantial gains in system throughput and energy efficiency over conventional power control schemes. Finally, the evolution of future systems to heterogeneous networks (HetNets), and the consequently enhanced network management difficulties necessitate the need for a distributed and autonomous ICIC approach. Using a fuzzy logic system, locally available information is utilised to allocate time-frequency resources and transmit powers such that requested rates are satisfied. An empirical investigation indicates close-to-optimal system performance at significantly reduced complexity (and signalling). Additionally, base station (BS) reference signals are appropriated to provide autonomous cell association amongst multiple co-located BSs. Detailed analytical signal modelling of the femto-cell and macro/pico-cell layouts reveal high correlation to experimentally gathered statistics. Further, superior performance to benchmarks in terms of system throughput, energy efficiency, availability and fairness indicate enormous potential for future wireless networks.

In this thesis, our objective is to improve the energy efficiency and load balance for wireless networks. We first study the relationships between the base station (BS) on/off operation and traffic distribution. A cooperative power saving method called clustering BS-off (CBSO) scheme is proposed. Instead of adopting a unified and consistent BS-off scheme in the whole network, the proposed centralized and distributed CBSO schemes can adaptively group BSs in several clusters based on the traffic fluctuations with space and time. Second, to further improve the network load balance and energy efficiency in distributed manner, we propose a power efficient self-organized virtual small networking (VSN) protocol. A heuristic firefly algorithm is applied to arrange the BSs' operation in small groups based on the traffic level. By jointly considering the load balance, the effectiveness of the proposed algorithm is demonstrated based on the average and min-max traffic levels of BSs' groups. Finally, the importance of detailed BS operation between active and sleep modes is considered. The operating procedure of femtocell base station, i.e., HeNB, is modeled as an MAP/PH/1/k queueing system. Such queueing analysis particularly focuses on the HeNB vacation process with user priorities. The HeNB's power on/off scheme is modeled as alternative service and vacation periods. The hybrid access is regarded as high and low priority users in the queuing system. We further propose the adaptive service rate and vacation length (ASV) method, so that the HeNB can work in a more energy-efficient way while satisfying QoS requirements such as blocking probability and users waiting time. Simulation results show the effectiveness of the proposed strategies and the overall network energy efficiency can be improved significantly. / October 2016

In the CDMA cellular networking system, power control is a very important issue because it is an interference limited system. In order to reduce the near-far problem and improve the battery life of mobile station, the transmit power of mobile stations must be controlled to limit interference. In this paper, we study the effect of power control on system performance. Different power control rates may have influence on the performance. Meanwhile, we take the consideration of different call admission control algorithm. By introducing soft handoff waiting queue and guard channel into the soft handoff algorithm, we compare the power control influence on a base case (which is similar to IS95 algorithm, but with perfect power control) and proposed call admission control algorithm. The simulation shows that increasing power control rate and combination of power control and soft handoff prioritization can greatly reduce the blocking rates and refuse rates of new/soft handoff calls, thus the system performance is improved.

[pt] Neste trabalho será inicialmente discutida a recepção e o desempenho de sinais espalhados espectralmente em canais corrompidos por ruído aditivo gaussiano branco e por desvanecimento plano ou seletivo. A seguir será feita a análise de sistemas CDMA, abordando-se a estrutura de recepção, os códigos de espalhamento, a caracterização estatística da interferência multiusuário e a influência das fases das portadoras, dos filtros de transmissão, dos atrasos entre os sinais e da sincronização na potência interferente. Será também abordado o controle de potência em sistemas CDMA, avaliando-se a redução da capacidade causada por erros neste controle, obtendo-se sua implementação e propondo-se um algoritmo de minimização do erro médio quadrático caso a solução analítica não possa ser aplicada. Por fim, será feita a descrição da transmissão do sinal de tráfego da padronização do sistema CDMA IS-95 e avaliado o desempenho do esquema de recepção proposto. / [en] This work will initially discuss reception and performance issues of spread sprectrum signals considering additive white gaussian noise and flat or selective fading channels. Then it will analyze the CDMA system, considering the reception structure, spreading codes, multiuse interference statistical characteristics, and the influence of carrier phases, transmission filters, delays between signals abd synchronization on the interference power. It will also adress the power control in CDMA systems, evaluating the capacity reduction caused by power control errors, achieving an analytical soluction to the power allocation in the forward link, discussing its implementation and suggesting a least square error algorithm when the analytical soluction can not be used. Finally, it will describe the traffic channel transmission in the IS-95 CDMA standard, evaluating the performance of the reception model.