The performance of photovoltaic (PV) modules in terms of their ability to convert incident photon to electrical energy (efficiency) depends mostly on the spectral distribution of incident radiation from the sun. The incident spectrum finally perceived by the module depends strongly on the composition of the medium in which it has traveled. The composition of the earth’s atmosphere, which includes, amongst others, water vapour, gases such as carbon dioxide and oxygen, absorbs or scatters some of the sunlight. The incident solar spectrum is also modified by the diffuse aspect of radiation from the sky which strongly depends on aerosol concentration, cloudiness and local reflection of the earth’s surface. Although it is well known that the changes in outdoor spectrum affect device performance, little work has been conducted to support this theory. This is probably due to lack of spectral data or in certain instances where data is available, little knowledge of interpreting that data. The outdoor spectral data that one obtains in the field does not come clearly for just simple interpretation. Different analytical interpretation procedures have been proposed, all trying to explain and quantify the spectral influence on PV devices. In this study an assessment methodology for evaluating the effects of outdoor spectra on device performance parameters during the course of the day, seasons and or cloudy cover has been developed. The methodology consists of developing a device dependant concept, Weighted Useful Fraction (WUF) using the outdoor measured spectral data. For measuring PV module’s performance parameters, a current-voltage (I-V) tester was developed in order to monitor the performance of six different module technologies. The Gaussian distribution was used to interpret the data. For hot-spot analysis, different techniques were used, which include Infrared thermographic technique for identifying the hot-spots in the solar cells, SEM and EDX techniques. The AES technique was also used in order to identify other elements at hot-spots sites that could not be detected by the EDX technique. iii Results obtained indicate that multicrystalline modules performance is affected by the changes in the outdoor spectrum during summer or winter seasons. The modules prefer a spectrum characterized by WUF = 0.809 during summer season. This spectrum corresponds to AM 2.19 which is different from AM 1.5 used for device ratings. In winter, the mc-Si module’s WUF (0.7125) peaks at 13h00 at a value corresponding to AM 1.83. Although these devices have a wider wavelength range, they respond differently in real outdoor environment. Results for mono – Si module showed that the device performs best at WUF = 0.6457 which corresponds to AM 1.83 during summer season, while it operates optimally under a winter spectrum indicated by WUF of 0.5691 (AM2.58). The seasonal changes resulted in the shift in WUF during day time corresponding to the “preferred” spectrum. This shift indicates that these devices should be rated using AM values that correspond to the WUF values under which the device operates optimally. For poly-Si, it was also observed the WUF values are lower than the other two crystalline-Si counterparts. The pc-Si was observed to prefer a lower AM value indicated by WUF = 0.5813 during winter season while for summer it prefers a spectrum characterized by WUF = 0.5541 at AM 3.36. The performance of the single junction a-Si module degraded by 67 percent after an initial outdoor exposure of 16 kWh/m² while the HIT module did not exhibit the initial degradation regardless of their similarities in material composition. It was established that the WUF before degradation peaks at 15h00 at a value of 0.7130 corresponding to AM 4.50 while the WUF after degradation “prefers” the spectrum (WUF = 0.6578) experienced at 15h30 corresponding to AM value of 5.57. Comparing the before and after degradation scenarios of a-Si:H, it was observed that the device spends less time under the red spectrum which implies that the device “prefers” a full spectrum to operate optimally. The degradation of a-Si:H device revealed that the device spectral response was also shifted by a 7.7 percent after degradation. A higher percentage difference (61.8 percent) for spectral range for the HIT module is observed, but with no effects on device parameters. Seasonal changes (summer/winter) resulted in the outdoor spectrum of CuInSe2 to vary by WUF = 1.5 percent, which resulted in the decrease in Isc. This was ascertained by iv analyzing the percentage change in WUF and evaluating the corresponding change in Isc. The analysis showed that there was a large percentage difference of the module’s Isc as the outdoor spectrum changed during the course of the day. This confirmed that the 17 percent decrease in Isc was due to a WUF of 1.5 percent. In mc-Si solar cells used in this study, it was found that elemental composition across the entire solar cell was not homogenously distributed resulting in high concentration of transition metals which were detected at hot spot areas. The presence of transition metals causes hot-spot formation in crystalline solar cells. Although several transition elements exist at hot-spot regions, the presence of oxygen, carbon, iron and platinum was detected in high concentrations. From this study, it is highly recommended that transition elements and oxygen must be minimized so as to increase the life expectancy of these devices and improve overall systems reliability

This study focuses on the institutional problems involved in planning for large-scale energy and resource projects in B.C. Fundamental to planning for these projects is the resolution of the tension between economic growth and environmental quality. Concern is expressed that, to date, planning has stressed economic values at the expense of environmental values held in society. A more equitable planning structure is needed whereby interested groups in society may present informed views to the planners and decision-makers to help them achieve solutions that more nearly represent the public interest. To reach a solution that reflects the public interest an advocacy approach to planning is suggested in Chapter Two. This approach stresses interest group participation in the "planning process" to conduct planning that meets public expectations. In order that environmental interests are incorporated into the planning and decision-making for major power and resource projects, an environmental review agency is proposed. This agency would have the power to conduct is own investigations into issues that might affect the environment and advocate its findings in the debate over the proposed Projects. To test the suitability in British Columbia of the advocacy approach a number of criteria are developed, The criteria reflect some basic democratic values held in our society and the problems associated with institutional design. The criteria include public participation and representation, information generation, efficiency, equality, professional humility, natural justice, liberty and political leadership. The characteristics of B.C.'s political milieu are examined in Chapter Three to see what problems the implementation of the advocacy approach for environmental and resource planning might face in the province. Three characteristics of the political milieu are seen as possible constraints on the effective implementation of a review agency - materialist values held in the province, lack of strong interest groups and the dependence on resource extraction for economic prosperity. A case study of the planning and decision-making for the Bennett Dam on the Peace River, presented in Chapter Four, outlines the inadequacy of the planning process. Even though there have been some changes in planning procedures since the initial planning for the Peace project, two principal deficiencies remain - there is virtually no scope for public involvement in the planning process and the information produced is too highly technical to make for effective public participation. As a consequence major energy and resource planning will likely produce results that favour energy and development interests. / Applied Science, Faculty of / Community and Regional Planning (SCARP), School of / Graduate

No description available.

Microbial fuel cell (MFC) has become one of the energy-sustainable technologies for wastewater treatment purpose in the recent years. It combines wastewater treatment and electricity generation together so as to achieve energy balance. By inoculating microorganism in the anode chamber and filling catholyte in the cathode chamber, and also with the help of a proton exchange membrane (PEM) between them, the MFC can transfer protons and produce power. Microbial desalination cells (MDC) are based on MFC’s structure and can fulfill desalination function by the addition of a middle chamber and anion exchange membrane (AEM). This study focuses on ammonium removal and electricity generation in MDC system. Mainly two types of liquid were tested, a solution of Hjorthorn Salt and filtrated supernatant. The experiments were performed at Hammarby Sjöstad research station and laboratory of Land and Water Resources department, Stockholm. It consists of a preparation stage, a MFC stage and a MDC stage. Until the end of MFC stage, biofilm in the anode chamber had been formed and matured. After that, solutions of different initial concentrations (1.5, 2.5, 5, 15 g/L) of Hjorthorn Salt and also filtrated supernatant have been tested. Ammonium removal degree can be obtained by measuring the initial concentration and cycle end concentration, while electricity generation ability can be calculated by voltage data which was continuously recorded by a multimeter. Results showed that this MDC system is suitable for ammonium removal in both of Hjorthorn Salt solutions and supernatant. The removal degrees in Hjorthorn Salt solution at desalination chamber were 53.1%, 52.7%, 60.34%, and 27.25% corresponding to initial NH4+ concentration of 340.7, 376, 376 and 2220 mg/L. The ammonium removal degrees in the supernatant were up to 53.4% and 43.7% under 21 and 71 hours operation, respectively. In power production aspect, MDC produced maximum voltage when potassium permanganate was used in the cathode chamber (217 mV). The power density in solutions of Hjorthorn Salt was relative low (46.73 - 86.61 mW/m3), but in the supernatant it showed a good performance, up to 227.7 and 190.8 mW/m3.

The energy resource planning process for electric utilities in the Northwestern United States is unique because the region relies upon a mix of hydro and thermal resources. Consequently, methods used to study predominantly thermal or predominantly hydro systems are not applicable. Methods are needed to determine if a particular configuration of resources will be adequate to meet future energy load, taking into account various sources of uncertainty. A literature survey of presently available methods is described, and one method is studied in some detail. A new method for analyzing systems that rely upon a mix of hydro and thermal resources is then described. The primary contributors to uncertainty in a hydro/thermal electricity supply system are: (1) uncertain rainfall and snowfall, which results in uncertain availability of hydro energy; (2) the uncertain arrival times of planned nuclear and coal plants; (3) uncertain capacity factors for thermal plants; and (4) the uncertain amount of energy that customers will require in future years. The new model, called CHANCE, characterizes each of these uncertain phenomena with a probability density function. Mathematical convolution and an algorithm developed by the author are then used to determine the probability density function for the energy margin--the difference between supply and demand. Measures of the "energy adequacy" of the supply system are then computed from the energy margin probability density function. A computer program was designed so that the conceptual model can be easily applied to any desired electrical supply system. Once an appropriate set of input assumptions h2ve been determined, they are easily entered into the computer via a question and answer sequence and stored for future use. The computer program then computes the energy adequacy of the system. The user can then change assumptions and/or resource schedules via a question and answer sequence, and recompute the energy adequacy. The computer then prepares a report showing how the alternative assumptions and/or schedules compare. CHANCE has been applied to Pacific Power and Light Company, Portland, Oregon. At the present time, about half of their energy is generated by hydro plants and the other half is generated by coal plants. Only a small fraction is generated by nuclear plants. All planned additional generation is either coal-fired or nuclear-fired. The results of applying CHANCE indicate that planned resources are not likely to be adequate to meet the needs in the early 1980's. Several evaluation exercises have also been carried out. First, CHANCE was calibrated against other electrical energy planning models used by Pacific Power and Light. Next, the sensitivity of the CHANCE model to changes in input assumptions was measured. As was anticipated, the model is highly sensitive to the assumed energy load forecast, to the assumed potential delays in the arrival of resources, and to the assumed thermal plant capacity factors. Thus, more research in these areas is warranted. Research that might lead to improvements in the CHANCE model is then outlined, and final conclusions are drawn. The final conclusions are that the CHANCE model: (1) is valid relative to the outlined scope, (2) is quite versatile and flexible, and (3) fulfills an important need in electrical energy planning.

The objective of this study is to determine a predicted energy capacity of disaster debris for the production of emergency power using a combined heat and power (CHP) unit. A prediction simulation using geographic information systems (GIS) will use data from past storms to calculate an estimated amount of debris along with an estimated energy potential of said debris. Rather than the expense and burden of transporting woody debris such as downed trees and wood framing materials offsite, they can be processed (sorting and chipping) to provide an onsite energy source to provide power to emergency management facilities such as shelters in schools and hospitals. A CHP unit can simultaneously produce heat, cooling effects and electrical power using various biomass sources.This study surveys the quantity and composition of debris produced for a given classification of disaster and location. A comparison of power efficiency estimates for various disasters is conducted.

No description available.

A thesis submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Doctor of Philosophy. University of the Witwatersrand, Johannesburg / Power system adequacy has been historically insufficient in the Southern African Power Pool (SAPP) region with resulting negative effects on economic growth and electrification efforts. Existing domestic regulatory frameworks and opaque longterm bilateral contracting for procuring capacity in the region have been shown to be insufficient in ensuring system adequacy. The concept of an adequacy product in the form of a Capacity Mechanism (CM) introduced into the SAPP region has not yet appeared in the literature. A Capacity Mechanism (CM) for the SAPP region has been proposed and designed as part of this research to address this. A framework has been developed to consider CMs via the combination of a screening assessment, quantitative (model-based) analysis of more favourable CM options and an identification and quantification of key design elements. The developed framework can also be generalised and applied to other jurisdictions where CMs are under consideration. A regional CM which transparently and explicitly values capacity is proposed in the form of a forward-looking annual Capacity Auction that is locationally disaggregated, supplied by all possible supply-side resources with all feasible SAPP market participants included. The CM should be technology agnostic and account for the dual requirement for firm capacity to meet peak demand and firm-energy to meet annual energy requirements considering the dominance of hydrobased capacity in the region when excluding South Africa. There should be a leadtime of 3-4 years with the possibility of long-term auctions for large hydro-based capacity. Strict market monitoring and adherence to performance incentives and penalties will need to be ensured to avoid exercising of market power considering the dominant size of the South African power system. Appropriately mandated institutions to run Capacity Auctions would include the SAPP Co-Ordination Centre as well as a sufficiently mandated regional regulatory body. A further contribution is made in the form of a public domain power system dataset of the SAPP region with sufficient detail to be used in power system operations and planning efforts by future researchers and practitioners. / E.K. 2020

År 2019 installerades 732 solpaneler på taket i ett hus i Örebro universitet. Energiproduktionenav anläggningen samlades i en databas i Akademiska Hus med ett antal parametrar från enväderstation i samma hus. Att kunna modellera den här produktionen som en funktion avväderparametrar och historiska värden med hjälp av maskininlärning, och jämföra olikamodeller är målet i detta projekt. Det finns gjorda arbeten med samma mål i olikalaborationsmiljöer och andra platser men inte för denna anläggning. Mätvärden under två årfrån 2019 till 2021 kommer från Akademiska Hus och resultaten blir två modeller: ett NarrowNeural Network samt en Support Vector Machine med 7 procent avvikelse och en NonlinearAutoregressive Neural Network för envariatmodellen. / In 2019, 732 solar panels were installed on the roof of a building at Örebro University. Thesolar power production of the facility has been collected in a database in Akademiska Hus,along with several parameters from a weather station in the same building. The goal of thisproject is to model solar power production as a function of weather parameters and historicalvalues using machine learning techniques. This study investigates various predictive models tofind a suitable model for predicting this production. There have been several studies in theliterature that have performed this goal in various laboratory environments and other places,but not for this facility. The measured data for this study is recorded by Akademiska Hus forover two years from 2019 to 2021. The results of this work lead to two suitable machine learningmodels while using weather parameters: 1) Narrow Neural Network and 2) Support VectorMachine with 7% errors in both models. Moreover, this study has investigated univariatemodels to predict the solar power production as a time series based on its historical data. Forthis aim, a Nonlinear Autoregressive Neural Network has been applied which results inconsiderably low errors in the evaluations.

The problem of unit commitment in an electric utility system is analyzed. The types of generating units considered include nuclear-steam, fossil-steam, thermalpeaking, conventional and pumped-storage hydro. The large problem of generating unit commitment, due to the inclusion of the nuclear unit, is decomposed into two stages. In the first stage, the relatively stable nuclear generation is optimized with respect to the generation from the large fossil-steam unit. Hourly generation levels for all the units in the system are determined in the second stage. AS a result of considering the startup-shutdown cost, the objective function has a fixed charge component in addition to first and second degree polynomials. Representation of the minimum turndown level and minimum Shutdown duration of the generator necessitates the use of O-1 variables along with continuous variables. The solution methodology presented here, applying an extension of the Lambda-Separable Programming, can handle these requirements efficiently. Application of the algorithm results in a minimum-cost generation schedule for all units in the system. Optimum generation levels of energy limited units are determined without using a preselected unit commitment order. The effect of startup-shutdown costs on the number of hours a Plant should operate is established. The cost and benefit of spent nuclear fuel reprocessing is analyzed and the effect of uranium prices on it (reprocessing) is shown. The model is tested using a sample system of six generating units. Hourly generation schedules, includig purchase and sale, are determined for two one-week periods while the nuclear generation is optimized for an entire year. / Ph. D.