Cognitive strategies for reducing energy consumption in wireless sensor networks

El consumo energético de las Redes de Sensores Inalámbricas (WSNs por sus siglas en inglés) es un problema histórico que ha sido abordado desde diferentes niveles y visiones, ya que no solo afecta a la propia supervivencia de la red sino que el creciente uso de dispositivos inteligentes y el nuevo paradigma del Internet de las Cosas hace que las WSNs tengan cada vez una mayor influencia en la huella energética. Debido a la tendencia al alza en el uso de estas redes se añade un nuevo problema, la saturación espectral. Las WSNs operan habitualmente en bandas sin licencia como son las bandas Industrial, Científica y Médica (ISM por sus siglas en inglés). Estas bandas se comparten con otro tipo de redes como Wi-Fi o Bluetooth cuyo uso ha crecido exponencialmente en los últimos años. Para abordar este problema aparece el paradigma de la Radio Cognitiva (CR), una tecnología que permite el acceso oportunista al espectro. La introducción de capacidades cognitivas en las WSNs no solo permite optimizar su eficiencia espectral sino que también tiene un impacto positivo en parámetros como la calidad de servicio, la seguridad o el consumo energético. Sin embargo, por otra parte, este nuevo paradigma plantea algunos retos relacionados con el consumo energético. Concretamente, el sensado del espectro, la colaboración entre los nodos (que requiere comunicación adicional) y el cambio en los parámetros de transmisión aumentan el consumo respecto a las WSN clásicas. Teniendo en cuenta que la investigación en el campo del consumo energético ha sido ampliamente abordada puesto que se trata de una de sus principales limitaciones, asumimos que las nuevas estrategias deben surgir de las nuevas capacidades añadidas por las redes cognitivas. Por otro lado, a la hora de diseñar estrategias de optimización para CWSN hay que tener muy presentes las limitaciones de recursos de estas redes en cuanto a memoria, computación y consumo energético de los nodos. En esta tesis doctoral proponemos dos estrategias de reducción de consumo energético en CWSNs basadas en tres pilares fundamentales. El primero son las capacidades cognitivas añadidas a las WSNs que proporcionan la posibilidad de adaptar los parámetros de transmisión en función del espectro disponible. La segunda es la colaboración, como característica intrínseca de las CWSNs. Finalmente, el tercer pilar de este trabajo es teoría de juegos como algoritmo de soporte a la decisión, ampliamente utilizado en WSNs debido a su simplicidad. Como primer aporte de la tesis se presenta un análisis completo de las posibilidades introducidas por la radio cognitiva en materia de reducción de consumo para WSNs. Gracias a las conclusiones extraídas de este análisis, se han planteado las hipótesis de esta tesis relacionadas con la validez de usar capacidades cognitivas como herramienta para la reducción de consumo en CWSNs. Una vez presentada las hipótesis, pasamos a desarrollar las principales contribuciones de la tesis: las dos estrategias diseñadas para reducción de consumo basadas en teoría de juegos y CR. La primera de ellas hace uso de un juego no cooperativo que se juega mediante pares de jugadores. En la segunda estrategia, aunque el juego continúa siendo no cooperativo, se añade el concepto de colaboración. Para cada una de las estrategias se presenta el modelo del juego, el análisis formal de equilibrios y óptimos y la descripción de la estrategia completa donde se incluye la interacción entre nodos. Con el propósito de probar las estrategias mediante simulación e implementación en dispositivos reales hemos desarrollado un marco de pruebas compuesto por un simulador cognitivo y un banco de pruebas formado por nodos cognitivos capaces de comunicarse en tres bandas ISM desarrollados en el B105 Lab. Este marco de pruebas constituye otra de las aportaciones de la tesis que permitirá el avance en la investigación en el área de las CWSNs. Finalmente, se presentan y discuten los resultados derivados de la prueba de las estrategias desarrolladas. La primera estrategia proporciona ahorros de energía mayores al 65% comparados con una WSN sin capacidades cognitivas y alrededor del 25% si la comparamos con una estrategia cognitiva basada en el sensado periódico del espectro para el cambio de canal de acuerdo a un nivel de ruido fijado. Este algoritmo se comporta de forma similar independientemente del nivel de ruido siempre que éste sea espacialmente uniformemente. Esta estrategia, a pesar de su sencillez, nos asegura el comportamiento óptimo en cuanto a consumo energético debido a la utilización de teoría de juegos en la fase de diseño del comportamiento de los nodos. La estrategia colaborativa presenta mejoras respecto a la anterior en términos de protección frente al ruido en escenarios de ruido más complejos donde aporta una mejora del 50% comparada con la estrategia anterior. ABSTRACT Energy consumption in Wireless Sensor Networks (WSNs) is a known historical problem that has been addressed from different areas and on many levels. But this problem should not only be approached from the point of view of their own efficiency for survival. A major portion of communication traffic has migrated to mobile networks and systems. The increased use of smart devices and the introduction of the Internet of Things (IoT) give WSNs a great influence on the carbon footprint. Thus, optimizing the energy consumption of wireless networks could reduce their environmental impact considerably. In recent years, another problem has been added to the equation: spectrum saturation. Wireless Sensor Networks usually operate in unlicensed spectrum bands such as Industrial, Scientific, and Medical (ISM) bands shared with other networks (mainly Wi-Fi and Bluetooth). To address the efficient spectrum utilization problem, Cognitive Radio (CR) has emerged as the key technology that enables opportunistic access to the spectrum. Therefore, the introduction of cognitive capabilities to WSNs allows optimizing their spectral occupation. Cognitive Wireless Sensor Networks (CWSNs) do not only increase the reliability of communications, but they also have a positive impact on parameters such as the Quality of Service (QoS), network security, or energy consumption. These new opportunities introduced by CWSNs unveil a wide field in the energy consumption research area. However, this also implies some challenges. Specifically, the spectrum sensing stage, collaboration among devices (which requires extra communication), and changes in the transmission parameters increase the total energy consumption of the network. When designing CWSN optimization strategies, the fact that WSN nodes are very limited in terms of memory, computational power, or energy consumption has to be considered. Thus, light strategies that require a low computing capacity must be found. Since the field of energy conservation in WSNs has been widely explored, we assume that new strategies could emerge from the new opportunities presented by cognitive networks. In this PhD Thesis, we present two strategies for energy consumption reduction in CWSNs supported by three main pillars. The first pillar is that cognitive capabilities added to the WSN provide the ability to change the transmission parameters according to the spectrum. The second pillar is that the ability to collaborate is a basic characteristic of CWSNs. Finally, the third pillar for this work is the game theory as a decision-making algorithm, which has been widely used in WSNs due to its lightness and simplicity that make it valid to operate in CWSNs. For the development of these strategies, a complete analysis of the possibilities is first carried out by incorporating the cognitive abilities into the network. Once this analysis has been performed, we expose the hypotheses of this thesis related to the use of cognitive capabilities as a useful tool to reduce energy consumption in CWSNs. Once the analyses are exposed, we present the main contribution of this thesis: the two designed strategies for energy consumption reduction based on game theory and cognitive capabilities. The first one is based on a non-cooperative game played between two players in a simple and selfish way. In the second strategy, the concept of collaboration is introduced. Despite the fact that the game used is also a non-cooperative game, the decisions are taken through collaboration. For each strategy, we present the modeled game, the formal analysis of equilibrium and optimum, and the complete strategy describing the interaction between nodes. In order to test the strategies through simulation and implementation in real devices, we have developed a CWSN framework composed by a CWSN simulator based on Castalia and a testbed based on CWSN nodes able to communicate in three different ISM bands. We present and discuss the results derived by the energy optimization strategies. The first strategy brings energy improvement rates of over 65% compared to WSN without cognitive techniques. It also brings energy improvement rates of over 25% compared with sensing strategies for changing channels based on a decision threshold. We have also seen that the algorithm behaves similarly even with significant variations in the level of noise while working in a uniform noise scenario. The collaborative strategy presents improvements respecting the previous strategy in terms of noise protection when the noise scheme is more complex where this strategy shows improvement rates of over 50%.

Hybrid wind-diesel power plant valuation and optimization using real option theory and dynamic programming

El sistema de energía eólica-diesel híbrido tiene un gran potencial en la prestación de suministro de energía a comunidades remotas. En comparación con los sistemas tradicionales de diesel, las plantas de energía híbridas ofrecen grandes ventajas tales como el suministro de capacidad de energía extra para "microgrids", reducción de los contaminantes y emisiones de gases de efecto invernadero, y la cobertura del riesgo de aumento inesperado del precio del combustible. El principal objetivo de la presente tesis es proporcionar nuevos conocimientos para la evaluación y optimización de los sistemas de energía híbrido eólico-diesel considerando las incertidumbres. Dado que la energía eólica es una variable estocástica, ésta no puede ser controlada ni predecirse con exactitud. La naturaleza incierta del viento como fuente de energía produce serios problemas tanto para la operación como para la evaluación del valor del sistema de energía eólica-diesel híbrido. Por un lado, la regulación de la potencia inyectada desde las turbinas de viento es una difícil tarea cuando opera el sistema híbrido. Por otro lado, el bene.cio económico de un sistema eólico-diesel híbrido se logra directamente a través de la energía entregada a la red de alimentación de la energía eólica. Consecuentemente, la incertidumbre de los recursos eólicos incrementa la dificultad de estimar los beneficios globales en la etapa de planificación. La principal preocupación del modelo tradicional determinista es no tener en cuenta la incertidumbre futura a la hora de tomar la decisión de operación. Con lo cual, no se prevé las acciones operativas flexibles en respuesta a los escenarios futuros. El análisis del rendimiento y simulación por ordenador en el Proyecto Eólico San Cristóbal demuestra que la incertidumbre sobre la energía eólica, las estrategias de control, almacenamiento de energía, y la curva de potencia de aerogeneradores tienen un impacto significativo sobre el rendimiento del sistema. En la presente tesis, se analiza la relación entre la teoría de valoración de opciones y el proceso de toma de decisiones. La opción real se desarrolla con un modelo y se presenta a través de ejemplos prácticos para evaluar el valor de los sistemas de energía eólica-diesel híbridos. Los resultados muestran que las opciones operacionales pueden aportar un valor adicional para el sistema de energía híbrida, cuando esta flexibilidad operativa se utiliza correctamente. Este marco se puede aplicar en la optimización de la operación a corto plazo teniendo en cuenta la naturaleza dependiente de la trayectoria de la política óptima de despacho, dadas las plausibles futuras realizaciones de la producción de energía eólica. En comparación con los métodos de valoración y optimización existentes, el resultado del caso de estudio numérico muestra que la política de operación resultante del modelo de optimización propuesto presenta una notable actuación en la reducción del con- sumo total de combustible del sistema eólico-diesel. Con el .n de tomar decisiones óptimas, los operadores de plantas de energía y los gestores de éstas no deben centrarse sólo en el resultado directo de cada acción operativa, tampoco deberían tomar decisiones deterministas. La forma correcta es gestionar dinámicamente el sistema de energía teniendo en cuenta el valor futuro condicionado en cada opción frente a la incertidumbre. ABSTRACT Hybrid wind-diesel power systems have a great potential in providing energy supply to remote communities. Compared with the traditional diesel systems, hybrid power plants are providing many advantages such as providing extra energy capacity to the micro-grid, reducing pollution and greenhouse-gas emissions, and hedging the risk of unexpected fuel price increases. This dissertation aims at providing novel insights for assessing and optimizing hybrid wind-diesel power systems considering the related uncertainties. Since wind power can neither be controlled nor accurately predicted, the energy harvested from a wind turbine may be considered a stochastic variable. This uncertain nature of wind energy source results in serious problems for both the operation and value assessment of the hybrid wind-diesel power system. On the one hand, regulating the uncertain power injected from wind turbines is a difficult task when operating the hybrid system. On the other hand, the economic profit of a hybrid wind-diesel system is achieved directly through the energy delivered to the power grid from the wind energy. Therefore, the uncertainty of wind resources has increased the difficulty in estimating the total benefits in the planning stage. The main concern of the traditional deterministic model is that it does not consider the future uncertainty when making the dispatch decision. Thus, it does not provide flexible operational actions in response to the uncertain future scenarios. Performance analysis and computer simulation on the San Cristobal Wind Project demonstrate that the wind power uncertainty, control strategies, energy storage, and the wind turbine power curve have a significant impact on the performance of the system. In this dissertation, the relationship between option pricing theory and decision making process is discussed. A real option model is developed and presented through practical examples for assessing the value of hybrid wind-diesel power systems. Results show that operational options can provide additional value to the hybrid power system when this operational flexibility is correctly utilized. This framework can be applied in optimizing short term dispatch decisions considering the path-dependent nature of the optimal dispatch policy, given the plausible future realizations of the wind power production. Comparing with the existing valuation and optimization methods, result from numerical example shows that the dispatch policy resulting from the proposed optimization model exhibits a remarkable performance in minimizing the total fuel consumption of the wind-diesel system. In order to make optimal decisions, power plant operators and managers should not just focus on the direct outcome of each operational action; neither should they make deterministic decisions. The correct way is to dynamically manage the power system by taking into consideration the conditional future value in each option in response to the uncertainty.

Power line interference filtering on surface electromyography based on the stationary wavelet packet transform

Power line interference is one of the main problems in surface electromyogram signals (EMG) analysis. In this work, a new method based on the stationary wavelet packet transform is proposed to estimate and remove this kind of noise from EMG data records. The performance has been quantitatively evaluated with synthetic noisy signals, obtaining good results independently from the signal to noise ratio (SNR). For the analyzed cases, the obtained results show that the correlation coefficient is around 0.99, the energy respecting to the pure EMG signal is 98–104%, the SNR is between 16.64 and 20.40 dB and the mean absolute error (MAE) is in the range of −69.02 and −65.31 dB. It has been also applied on 18 real EMG signals, evaluating the percentage of energy respecting to the noisy signals. The proposed method adjusts the reduction level to the amplitude of each harmonic present in the analyzed noisy signals (synthetic and real), reducing the harmonics with no alteration of the desired signal.

The EU power sector needs long-term price signals. CEPS Special Report No. 135/April 2016

By 2030, half of the EU’s electricity demand will be covered by renewables and will need to be accompanied by flexible conventional back-up resources. Due to the high upfront costs inherent to renewables and the progressively lower running times associated with back-up capacity, the cost of capital will have a proportionately greater impact on total costs than today. This report examines how electricity markets can be designed to provide long-term price signals, thereby reducing the cost of capital for these technologies and allowing for a more efficient transition. It finds that current market arrangements are unable to provide long-term price signals. To address this issue, we argue that a system for long-term contracts with a regulated counterparty could be implemented. A centralised system where capacity or energy or a combination of both is contracted, could be introduced for conventional and renewable capacity, based on a regional adequacy assessment and with a competitive bidding system in place to ensure cost-effectiveness. Member states face a number of legislative barriers while implementing these types of systems, however, which could be reduced by merging legislation and setting EU framework rules for the design of these contractual agreements.

Staff report on measures for reducing energy consumption for homeowners and renters.

Prepared in cooperation with the Edison Electric Institute and marketing staff of various utilities throughout the country.

An endurance-strength training regime is effective in reducing myoelectric manifestations of cervical flexor muscle fatigue in females with chronic neck pain

Objective: The purpose of this study was to investigate whether an endurance-strength training program is effective in reducing myoelectric manifestations of sternocleidomastoid (SCM) and anterior scalene (AS) muscle fatigue which have been found to be greater in people with chronic neck pain. Methods: Fifty-eight female patients with chronic non-severe neck pain were randomized into one of two 6-week exercise intervention groups: an endurance-strength training regime for the cervical flexor muscles or a referent exercise intervention involving low load retraining of the cranio-cervical flexor muscles. The primary outcomes were a change in maximum voluntary contraction (MVC) force and change of the initial value and rate of change of the mean frequency, average rectified value and conduction velocity detected from the SCM and AS muscles during sub-maximal isometric cervical flexion contractions at 50, 25 and 10% MVC. Results: At the 7th week follow-up assessment, the endurance-strength training group revealed a significant increase in MVC force and a reduction in the estimates of the initial value and rate of change of the mean frequency for both the SCM and AS muscles (P < 0.05). Both exercise groups reported a reduced average intensity of neck pain and reduced neck disability index score (P < 0.05). Conclusions: An endurance-strength exercise regime for the cervical flexor muscles is effective in reducing myoelectric manifestations of superficial cervical flexor muscle fatigue as well as increasing cervical flexion strength in a group of patients with chronic non-severe neck pain. Significance: Provision of load to challenge the neck flexor muscles is required to reduce the fatigability of the SCM and AS muscles in people with neck pain. Improvements in cervical muscle strength and reduced fatigability may be responsible for the reported efficacy with this type of exercise program. (c) 2006 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All fights reserved.

A micro gas turbines for UK domestic combined heat and power

Various micro-radial compressor configurations were investigated using one-dimensional meanline and computational fluid dynamics (CFD) techniques for use in a micro gas turbine (MGT) domestic combined heat and power (DCHP) application. Blade backsweep, shaft speed, and blade height were varied at a constant pressure ratio. Shaft speeds were limited to 220 000 r/min, to enable the use of a turbocharger bearing platform. Off-design compressor performance was established and used to determine the MGT performance envelope; this in turn was used to assess potential cost and environmental savings in a heat-led DCHP operating scenario within the target market of a detached family home. A low target-stage pressure ratio provided an opportunity to reduce diffusion within the impeller. Critically for DCHP, this produced very regular flow, which improved impeller performance for a wider operating envelope. The best performing impeller was a low-speed, 170 000 r/min, low-backsweep, 15° configuration producing 71.76 per cent stage efficiency at a pressure ratio of 2.20. This produced an MGT design point system efficiency of 14.85 per cent at 993 W, matching prime movers in the latest commercial DCHP units. Cost and CO2 savings were 10.7 per cent and 6.3 per cent, respectively, for annual power demands of 17.4 MWht and 6.1 MWhe compared to a standard condensing boiler (with grid) installation. The maximum cost saving (on design point) was 14.2 per cent for annual power demands of 22.62 MWht and 6.1 MWhe corresponding to an 8.1 per cent CO2 saving. When sizing, maximum savings were found with larger heat demands. When sized, maximum savings could be made by encouraging more electricity export either by reducing household electricity consumption or by increasing machine efficiency.

Reductions of peak-to-average power ratio and optical beat interference in cost-effective OFDMA-PONs

The peak-to-average power ratio (PAPR) and optical beat interference (OBI) effects are examined thoroughly in orthogonal frequency-division multiplexing access (OFDMA)-passive optical networks (PONs) at a signal bit rate up to ∼ 20 Gb/s per channel using cost-effective intensity-modulation and direct-detection (IM/DD). Single-channel OOFDM and upstream multichannel OFDM-PONs are investigated for up to six users. A number of techniques for mitigating the PAPR and OBI effects are presented and evaluated including adaptive-loading algorithms such as bit/power-loading, clipping for PAPR reduction, and thermal detuning (TD) for the OBI suppression. It is shown that the bit-loading algorithm is a very efficient PAPR reduction technique by reducing it at about 1.2 dB over 100 Km of transmission. It is also revealed that the optimum method for suppressing the OBI is the TD + bit-loading. For a targeted BER of 1 × 10-3, the minimum allowed channel spacing is 11 GHz when employing six users. © 2013 Springer Science+Business Media New York.

The complements towards developing a new risk management framework and Its applicability to the Nigerian power sector

The availability of regular supply has been identified as one of the major stimulants for the growth and development of any nation and is thus important for the economic well-being of a nation. The problems of the Nigerian power sector stems from a lot of factors culminating in her slow developmental growth and inability to meet the power demands of her citizens regardless of the abundance of human and natural resources prevalent in the nation. The research therefore had the main aim of investigating the importance and contributions of risk management to the success of projects specific to the power sector. To achieve this aim it was pertinent to examine the efficacy of risk management process in practice and elucidate the various risks typically associated with projects (Construction, Contractual, Political, Financial, Design, Human resource and Environmental risk factors) in the power sector as well as determine the current situation of risk management practice in Nigeria. To address this factors inhibiting the proficiency of the overarching and prevailing issue which have only been subject to limited in-depth academic research, a rigorous mixed research method was adopted (quantitative and qualitative data analysis). A review of the Nigeria power sector was also carried out as a precursor to the data collection stage. Using purposive sampling technique, respondents were identified and a questionnaire survey was administered. The research hypotheses were tested using inferential statistics (Pearson correlation, Chi-square test, t-test and ANOVA technique) and the findings revealed the need for the development of a new risk management implementation Framework. The proposed Framework was tested within a company project, for interpreting the dynamism and essential benefits of risk management with the aim of improving the project performances (time), reducing the level of fragmentation (quality) and improving profitability (cost) within the Nigerian power sector in order to bridge a gap between theory and practice. It was concluded that Nigeria’s poor risk management practices have prevented it from experiencing strong growth and development. The study however, concludes that the successful implementation of the developed risk management framework may help it to attain this status by enabling it to become more prepared and flexible, to face challenges that previously led to project failures, and thus contributing to its prosperity. The research study provides an original contribution theoretically, methodologically and practically which adds to the project risk management body of knowledge and to the Nigerian power sector.

Permanent magnet synchronous generator based wind power generation system fault protection schemes

The PMSG-based wind power generation system protection is presented in this paper. For large-scale systems, a voltagesource converter rectifier is included. Protection circuits for this topology are studied with simulation results for cable permanent fault conditions. These electrical protection methods are all in terms of dumping redundant energy resulting from disrupted path of power delivery. Pitch control of large-scale wind turbines are considered for effectively reducing rotor shaft overspeed. Detailed analysis and calculation of damping power and resistances are presented. Simulation results including fault overcurrent, DC-link overvoltage and wind turbine overspeed are shown to illustrate the system responses under different protection schemes to compare their application and effectiveness.

DC-link voltage control strategy for reducing capacitance and total harmonic distortion in single-phase grid-connected photovoltaic inverters

High-volume capacitance is required to buffer the power difference between the input and output ports in single-phase grid-connected photovoltaic inverters, which become an obstacle to high system efficiency and long device lifetime. Furthermore, total harmonic distortion becomes serious when the system runs into low power level. In this study, a comprehensive analysis is introduced for two-stage topology with the consideration of active power, DC-link (DCL) voltage, ripple and capacitance. This study proposed a comprehensive DCL voltage control strategy to minimise the DCL capacitance while maintaining a normal system operation. Furthermore, the proposed control strategy is flexible to be integrated with the pulse-skipping control that significantly improves the power quality at light power conditions. Since the proposed control strategy needs to vary DCL voltage, an active protection scheme is also introduced to prevent any voltage violation across the DCL. The proposed control strategy is evaluated by both simulation and experiments, whose results confirm the system effectiveness.

Time series wind power forecasting based on variant Gaussian process and TLBO

Due to the variability and stochastic nature of wind power system, accurate wind power forecasting has an important role in developing reliable and economic power system operation and control strategies. As wind variability is stochastic, Gaussian Process regression has recently been introduced to capture the randomness of wind energy. However, the disadvantages of Gaussian Process regression include its computation complexity and incapability to adapt to time varying time-series systems. A variant Gaussian Process for time series forecasting is introduced in this study to address these issues. This new method is shown to be capable of reducing computational complexity and increasing prediction accuracy. It is further proved that the forecasting result converges as the number of available data approaches innite. Further, a teaching learning based optimization (TLBO) method is used to train the model and to accelerate
the learning rate. The proposed modelling and optimization method is applied to forecast both the wind power generation of Ireland and that from a single wind farm to show the eectiveness of the proposed method.

Optimal generation scheduling of interconnected wind-coal intensive power systems

Large scale wind power generation complicated with restrictions on the tie line plans may lead to significant wind power curtailment and deep cycling of coal units during the valley load periods. This study proposes a dispatch strategy for interconnected wind-coal intensive power systems (WCISs). Wind power curtailment and cycling of coal units are included in the economic dispatch analysis of regional systems. Based on the day-ahead dispatch results, a tie line power plan adjustment strategy is implemented in the event of wind power curtailment or deep cycling occurring in the economic dispatch model, with the objective of reducing such effects. The dispatch strategy is designed based on the distinctive operation characteristics of interconnected WCISs, and dispatch results for regional systems in China show that the proposed strategy is feasible and can improve the overall system operation performance.

A multi vector energy analysis for interconnected power and gas systems

This paper presents the first multi vector energy analysis for the interconnected energy systems of Great Britain (GB) and Ireland. Both systems share a common high penetration of wind power, but significantly different security of supply outlooks. Ireland is heavily dependent on gas imports from GB, giving significance to the interconnected aspect of the methodology in addition to the gas and power interactions analysed. A fully realistic unit commitment and economic dispatch model coupled to an energy flow model of the gas supply network is developed. Extreme weather events driving increased domestic gas demand and low wind power output were utilised to increase gas supply network stress. Decreased wind profiles had a larger impact on system security than high domestic gas demand. However, the GB energy system was resilient during high demand periods but gas network stress limited the ramping capability of localised generating units. Additionally, gas system entry node congestion in the Irish system was shown to deliver a 40% increase in short run costs for generators. Gas storage was shown to reduce the impact of high demand driven congestion delivering a reduction in total generation costs of 14% in the period studied and reducing electricity imports from GB, significantly contributing to security of supply.

Exergetic, energetic, economic and environmental evaluation of concentrated solar power plants in Libya

The PhD project addresses the potential of using concentrating solar power (CSP) plants as a viable alternative energy producing system in Libya. Exergetic, energetic, economic and environmental analyses are carried out for a particular type of CSP plants. The study, although it aims a particular type of CSP plant – 50 MW parabolic trough-CSP plant, it is sufficiently general to be applied to other configurations. The novelty of the study, in addition to modeling and analyzing the selected configuration, lies in the use of a state-of-the-art exergetic analysis combined with the Life Cycle Assessment (LCA). The modeling and simulation of the plant is carried out in chapter three and they are conducted into two parts, namely: power cycle and solar field. The computer model developed for the analysis of the plant is based on algebraic equations describing the power cycle and the solar field. The model was solved using the Engineering Equation Solver (EES) software; and is designed to define the properties at each state point of the plant and then, sequentially, to determine energy, efficiency and irreversibility for each component. The developed model has the potential of using in the preliminary design of CSPs and, in particular, for the configuration of the solar field based on existing commercial plants. Moreover, it has the ability of analyzing the energetic, economic and environmental feasibility of using CSPs in different regions of the world, which is illustrated for the Libyan region in this study. The overall feasibility scenario is completed through an hourly analysis on an annual basis in chapter Four. This analysis allows the comparison of different systems and, eventually, a particular selection, and it includes both the economic and energetic components using the “greenius” software. The analysis also examined the impact of project financing and incentives on the cost of energy. The main technological finding of this analysis is higher performance and lower levelized cost of electricity (LCE) for Libya as compared to Southern Europe (Spain). Therefore, Libya has the potential of becoming attractive for the establishment of CSPs in its territory and, in this way, to facilitate the target of several European initiatives that aim to import electricity generated by renewable sources from North African and Middle East countries. The analysis is presented a brief review of the current cost of energy and the potential of reducing the cost from parabolic trough- CSP plant. Exergetic and environmental life cycle assessment analyses are conducted for the selected plant in chapter Five; the objectives are 1) to assess the environmental impact and cost, in terms of exergy of the life cycle of the plant; 2) to find out the points of weakness in terms of irreversibility of the process; and 3) to verify whether solar power plants can reduce environmental impact and the cost of electricity generation by comparing them with fossil fuel plants, in particular, Natural Gas Combined Cycle (NGCC) plant and oil thermal power plant. The analysis also targets a thermoeconomic analysis using the specific exergy costing (SPECO) method to evaluate the level of the cost caused by exergy destruction. The main technological findings are that the most important contribution impact lies with the solar field, which reports a value of 79%; and the materials with the vi highest impact are: steel (47%), molten salt (25%) and synthetic oil (21%). The “Human Health” damage category presents the highest impact (69%) followed by the “Resource” damage category (24%). In addition, the highest exergy demand is linked to the steel (47%); and there is a considerable exergetic demand related to the molten salt and synthetic oil with values of 25% and 19%, respectively. Finally, in the comparison with fossil fuel power plants (NGCC and Oil), the CSP plant presents the lowest environmental impact, while the worst environmental performance is reported to the oil power plant followed by NGCC plant. The solar field presents the largest value of cost rate, where the boiler is a component with the highest cost rate among the power cycle components. The thermal storage allows the CSP plants to overcome solar irradiation transients, to respond to electricity demand independent of weather conditions, and to extend electricity production beyond the availability of daylight. Numerical analysis of the thermal transient response of a thermocline storage tank is carried out for the charging phase. The system of equations describing the numerical model is solved by using time-implicit and space-backward finite differences and which encoded within the Matlab environment. The analysis presented the following findings: the predictions agree well with the experiments for the time evolution of the thermocline region, particularly for the regions away from the top-inlet. The deviations observed in the near-region of the inlet are most likely due to the high-level of turbulence in this region due to the localized level of mixing resulting; a simple analytical model to take into consideration this increased turbulence level was developed and it leads to some improvement of the predictions; this approach requires practically no additional computational effort and it relates the effective thermal diffusivity to the mean effective velocity of the fluid at each particular height of the system. Altogether the study indicates that the selected parabolic trough-CSP plant has the edge over alternative competing technologies for locations where DNI is high and where land usage is not an issue, such as the shoreline of Libya.