Design and assessment of a large commercial Photovoltaic System in Barbados

One of the main aims of this thesis is to design an optimized commercial Photovoltaic (PV) system in Barbados from several variables such as racking type, module type and inverter type based on practicality, technical performance as well as financial returns to the client. Detailed simulations are done in PVSYST and financial models are used to compare different systems and their viability. Once the preeminent system is determined from a financial and performance perspective a detailed design is done using PVSYST and AutoCAD to design the most optimal PV system for the customer. In doing so, suitable engineering drawings are generated which are detailed enough for construction of the system. Detailed cost with quotes from relevant manufacturers, suppliers and estimators become instrumental in determining Balance of System Costs in addition to total project cost. The final simulated system is suggested with a PV capacity of 425kW and an inverter output of 300kW resulting in an array oversizing of 1.42. The PV system has a weighted Performance Ratio of 77 %, a specific yield of 1467 kWh/kWp and a projected annual production of 624 MWh/yr. This system is estimated to offset approximately 28 % of Carlton’s electrical load annually. Over the course of 20 years the PV system is projected to produce electricity at a cost of $0.201USD/kWh which is significantly lower than the $0.35 USD/kWh paid to the utility at the time of writing this thesis. Due to the high cost of electricity on the island, an attractive Feed-In-Tariff is not necessary to warrant the installation of a commercial System which over a lifetime which produces electricity at less than 60% of the cost to the user purchasing electricity from the utility. A simple payback period of 5.4 years, a return on investment of 17 % without incentives, in addition to an estimated diversion of 6840 barrels of oil or 2168 tonnes of CO2 further provides compelling justification for the installation of a commercial Photovoltaic System not only on Carlton A-1 Supermarket, but also island wide as well as regionally where most electricity supplies are from imported fossil fuels.

Electrical Evaluation of a Low Concentrating PVT Collector Based on Performance Ratio

Photovoltaic Thermal/Hybrid collectors are an emerging technology that combines PV and solar thermal collectors by producing heat and electricity simultaneously. In this paper, the electrical performance evaluation of a low concentrating PVT collector was done through two testing parts: power comparison and performance ratio testing. For the performance ratio testing, it is required to identify and measure the factors affecting the performance ratio on a low concentrating PVT collector. Factors such as PV cell configuration, collector acceptance angle, flow rate, tracking the sun, temperature dependence and diffuse to irradiance ratio. Solarus low concentrating PVT collector V12 was tested at Dalarna University in Sweden using the electrical equipment at the solar laboratory. The PV testing has showed differences between the two receivers. Back2 was producing 1.8 energy output more than Back1 throughout the day. Front1 and Front2 were almost the same output performance. Performance tests showed that the cell configuration for Receiver2 with cells grouping (6- 32-32-6) has proved to have a better performance ratio when to it comes to minimizing the shading effect leading to more output power throughout the day because of lowering the mismatch losses. Different factors were measured and presented in this thesis in chapter 5. With the current design, it has been obtained a peak power at STC of 107W per receiver. The solar cells have an electrical efficiency of approximately 19% while the maximum measured electrical efficiency for the collector was approximately 18 % per active cell area, in addition to a temperature coefficient of -0.53%/ ˚C. Finally a recommendation was done to help Solarus AB to know how much the electrical performance is affected during variable ambient condition and be able to use the results for analyzing and introducing new modification if needed.

Statistical bound of genetic solutions to quadratic assignment problems

Quadratic assignment problems (QAPs) are commonly solved by heuristic methods, where the optimum is sought iteratively. Heuristics are known to provide good solutions but the quality of the solutions, i.e., the confidence interval of the solution is unknown. This paper uses statistical optimum estimation techniques (SOETs) to assess the quality of Genetic algorithm solutions for QAPs. We examine the functioning of different SOETs regarding biasness, coverage rate and length of interval, and then we compare the SOET lower bound with deterministic ones. The commonly used deterministic bounds are confined to only a few algorithms. We show that, the Jackknife estimators have better performance than Weibull estimators, and when the number of heuristic solutions is as large as 100, higher order JK-estimators perform better than lower order ones. Compared with the deterministic bounds, the SOET lower bound performs significantly better than most deterministic lower bounds and is comparable with the best deterministic ones. 

On statistical bounds of heuristic solutions to location problems

Solutions to combinatorial optimization problems, such as problems of locating facilities, frequently rely on heuristics to minimize the objective function. The optimum is sought iteratively and a criterion is needed to decide when the procedure (almost) attains it. Pre-setting the number of iterations dominates in OR applications, which implies that the quality of the solution cannot be ascertained. A small, almost dormant, branch of the literature suggests using statistical principles to estimate the minimum and its bounds as a tool to decide upon stopping and evaluating the quality of the solution. In this paper we examine the functioning of statistical bounds obtained from four different estimators by using simulated annealing on p-median test problems taken from Beasley’s OR-library. We find the Weibull estimator and the 2nd order Jackknife estimator preferable and the requirement of sample size to be about 10 being much less than the current recommendation. However, reliable statistical bounds are found to depend critically on a sample of heuristic solutions of high quality and we give a simple statistic useful for checking the quality. We end the paper with an illustration on using statistical bounds in a problem of locating some 70 distribution centers of the Swedish Post in one Swedish region. 

Hushållsavfall i Borlänge kommun : analyser av material en och flerfamiljshus

In Borlänge, source separation has been the basis for management of household waste for over five years. This report reviews today?s system and gives a model for further follow-up through waste grouping. In the basic system waste is separated into three fractions: biodegradable, waste to energy and waste to landfill. All waste is packed in plastic bags, put in separate containers for each fraction, and collected from the property. Separate analyses were made of waste from single family houses and apartment buildings. The amount of waste per household and week, number of non-sorted bags, purity, recovery rate and density of each fraction was calculated. The amount of packaging collected together with the household waste is given. Material collected under the Swedish law of Producers? Responsibility is not covered in this report.

A finite sample improvement of the fixed effects estimator : applied to technical infficiency

The FE ('fixed effects') estimator of technical inefficiency performs poorly when N ('number of firms') is large and T ('number of time observations') is small. We propose estimators of both the firm effects and the inefficiencies, which have small sample gains compared to the traditional FE estimator. The estimators are based on nonparametric kernel regression of unordered variables, which includes the FE estimator as a special case. In terms of global conditional MSE ('mean square error') criterions, it is proved that there are kernel estimators which are efficient to the FE estimators of firm effects and inefficiencies, in finite samples. Monte Carlo simulations supports our theoretical findings and in an empirical example it is shown how the traditional FE estimator and the proposed kernel FE estimator lead to very different conclusions about inefficiency of Indonesian rice farmers.