Use of autoregressive models to generate a series of daily averaged point cloudiness values

Analysis of observed data for 10 years in two Romanian localities showed that the daily averaged point cloudiness in a given day mainly depends on the cloud cover amount from the past two days. Hence, first or second order autoregressive (AR) processes can be used to generate a point cloudiness time series. The second order models are slightly better than the first order models. The AR models generate data whose mean and standard deviation are close to those of the observed data. Good agreement between the skewness of the observed and synthetic data occurs during the warm season. No concordance was emphasized between the kurtosis of observed and generated daily averaged point cloudiness values.     

Modeling and maximum power point tracking (MPPT) method for PV array under partial shade conditions

Influenced by partial shade, PV module aging or fault, there are multiple peaks on PV array's output power–voltage (P–V) characteristic curve. Conventional maximum power point tracking (MPPT) methods are effective for single peak P–V characteristic under uniform solar irradiation, but they may fail in global MPP tracking under multi-peak P–V characteristics. Existing methods in literature for this problem are still unsatisfactory in terms of effectiveness, complexity and speed. In this paper, we first analyze the mathematical model of PV array that is suitable for simulation of complex partial shade situation. Then an adaptive MPPT (AMPPT) method is proposed, which can find real global maximum power point (MPP) for different partial shade conditions. When output characteristic of PV array varies, AMPPT will adjust tracking strategies to search for global peak area (GPA). Then it is easy for conventional MPPT to track the global MPP in GPA. Simulation and experimental results verify that the proposed AMPPT method is able to find real global MPP accurately, quickly and smoothly for complex multi-peak P–V characteristics. Comparison analysis results demonstrate that AMPPT is more effective for most shade types.     

Effect of blends of Palm-Jatropha-Pongamia biodiesels on cloud point and pour point

To minimize use of biodiesels synthesized from edible oils like Palm due to raising food versus fuel issue, Palm biodiesel (PBD) was blended with biodiesels derived from tree borne non-edible oil seeds Jatropha, and Pongamia to examine the effect on cloud point (CP) and pour point (PP) of PBD. Dependence of CP and PP on esters of fatty acid composition was also examined. Good correlations between CP and palmitic acid methyl ester (PAME) and between PP and PAME were obtained. A correlation between CP and total unsaturated fatty acid methyl ester (X) was also obtained and correlation between PP and X was also determined. Using these four correlations, cloud and pour points of different biodiesel blends can be determined.     

Evaluation of a cloud cover based model for estimation of hourly global solar radiation in Western Canada

Cloud cover based solar radiation models are relatively simple and convenient as the models require the input of cloud cover data which are mostly available from the meteorological stations. In this study, the performance of a cloud cover based solar radiation model (Kasten–Czeplak model) with original or locally fitted coefficients was evaluated for estimating the hourly global solar radiation for four different locations in Western Canada. The average value of R², mean bias error, and root mean square error are 0.69, ?61.6, and 157.9?W?m^?2, respectively, for the model with original coefficients, whereas 0.82, 4.4, 107.1?W?m^?2 with locally fitted coefficients. Results show that the Kasten–Czeplak model with locally fitted coefficients satisfactorily estimated the hourly solar radiation of four different locations in Western Canada. Also, the results indicate that the model with original coefficients has very limited accuracy under intermediate cloud cover conditions.     

Evaluation of a new maximum power point tracker (MPPT) applied to the photovoltaic stand-alone systems

In this paper a comparative study through experimental work between a new low-cost maximum power point tracker (MPPT) and the conventional configurations of the photovoltaic (PV) regulators under different atmospheric conditions is presented. The comparison is made by means of the energy production obtained by the PV generator of each system. From the results obtained it can be concluded that, depending on the charge state of the batteries, the MPPT can increase the overall efficiency of the system between 2.8% and 18.5% compared with the performance of a conventional system.     

The density and cloud point of diesel oil mixtures with the straight vegetable oils (SVO): Palm,cabbage palm,cotton, groundnut,copra and sunflower

The densities and cloud points of six vegetable oils mixed in variable proportions to diesel oils (commercial vehicle fuels) are measured. Simple correlations are reported between these properties and the fatty acids vegetable oil composition. A simple modelling summarises experimental data informations.     

Local wind-energy potential for the city of Guelph,Ontario (Canada)

Municipalities around the world are using community energy plans (CEPs) to drive progress towards a more sustainable energy future. Many recognize the supply of local and renewable energy as a crucial component of a resilient future including the potential use of wind power generation. The city of Guelph (Ontario, Canada) included wind energy as a component of its CEP. The goal of this work was to estimate the potential for wind power generation within the municipal boundaries of this city. This paper summarizes the methodology used and results obtained with site and meteorological data, wind maps, and turbine power curves. The methodology relies on the use of a geographically uniform array of turbines, spread throughout the community. An array of utility-scale turbines could potentially generate 29% of Guelph’s 2005 total electricity demand, whereas one consisting of small-scale turbines could achieve 10% of that demand.     

Methodology for the large-scale assessment of small hydroelectric potential: Application to the Province of New Brunswick (Canada)

The mapping of the small hydropower (SHP) resource over a given territory is indispensable to identify suitable sites for the development of SHP renewable energy projects. In this study, a straightforward method to map the SHP potential over a large territory is presented. The methodology uses a synthetic hydro network (SHN) created from digital elevation models (DEM) to ensure precise hydro head estimations. From the SHN, hydro heads are calculated by subtracting the minimum from the maximum elevation of synthetic stream segments. Subsequently, stream segments with low hydro heads over a specified maximum distance are removed. Finally, the method uses regional regression models to estimate the annual baseflow for all drainage areas in the study area. The technical SHP potential can then be estimated as a function of the hydro head and maximum penstock length. An application of the method is made to the province of New Brunswick, Canada, where SHP maps have been developed to promote the development of the SHP energy sector in the province. In terms of the SHP opportunity, it is shown that the province of New Brunswick (71,450 km²) has a good SHP resource. Using a representative hydro head (10 m) and penstock length (3000 m) for the region, 696 potential sites have been identified over the territory. Results show that the technical SHP potential for New Brunswick is 368 MW for the conventional hydroelectric reservoir SHP configuration, while for the run-of-river SHP configuration, the technical SHP potential is 58 MW.     

Evaluation of performance of photovoltaic system with maximum power point (MPP)

Performance of the photovoltaic system is highly influenced by the weather, especially the irradiation and the temperature. To simplify the design of solar generator power, a mathematical model and its validity of the solar cell are required. In this work, the value of the parameters in the mathematical model is obtained by the measurement of the I–V curve of the module. To get an I–V curve, one of the modules in the system was radiated and loaded by a load simulator. A photovoltaic pumping system with maximum power point tracker was built and tested. The results were analyzed and evaluated by using the parameters and the photovoltaic system was shown to be well optimized.     

Perturbative methods for maximum power point tracking (MPPT) of photovoltaic (PV) systems: a review

Over the past few decades, the world demand for energy has risen steadily, forcing the world communities to look for alternative sources. Photovoltaic (PV) is seen as the most promising solution for this demand. However, the PV system is popularly known to suffer from low‐energy harvesting due to the change of environment conditions. An inexpensive and practical solution to extract the energy from the PV is by improving the maximum power point tracking (MPPT) controller technique. An ideal MPPT should be able to track the true maximum power operating point accurately under all circumstances and overcome all nonlinearities in the characteristic I‐V curves. This paper presents an updated review of the techniques based on the perturbative MPPT methods, both using the conventional and soft computing methods. The working principles of the techniques, parameter effects, and their limitations are discussed. The focus of this review is to direct the readers to the new direction of MPPT using the artificial intelligence and evolutionary computation techniques. Besides serving as a comprehensive source of information, the paper also provides a critical review on the relative performance of the selected MPPT methods. This includes the module dependency, tracking performance, and the ability to handle the partial shading conditions. Copyright © 2015 John Wiley & Sons, Ltd.     

The cost impacts of a mandatory move to time-of-use pricing on residential customers: an Ontario (Canada) case-study

Using 2008 hourly electricity data from 1,020 households in Milton, Ontario (Canada), this article asks and answers two questions: ‘How do residential customers’ total costs change as the result of a mandatory move from a traditional, flat-rate pricing structure, to a time-of-use one?’; and ‘Are particular “kinds” of customers either “winners” or “losers” as a result of this move?’ In response to the first question, 45% of customers have lower bills under a time-of-use regime (as compared with what they would have paid, had the previous two-tier regime continued, with their ‘new’ consumption patterns), while 55% of customers have higher bills. For 98.2% of customers, the difference in total cost is less than 5% (either way), and the average relative change is a 0.233% increase. In response to the second question, customers that have a relatively high level of consumption in either peak periods or wintertime are, in the absence of other differences, more likely to have higher bills under a time-of-use regime. Those households that consume higher quantities of electricity are more likely to have lower bills under a time-of-use regime, as compared with the two-tier regime. The article concludes by highlighting the equity implications of this finding and by identifying areas for future research.     

Managing solar-PV variability with geographical dispersion: An Ontario (Canada) case-study

The purpose of this article is to determine whether the geographic dispersion of solar-photovoltaic panels reduces variability in energy production. Following this, three questions are posed: 1) If geographic dispersion reduces variability, how dispersed should the panels be?; 2) What happens during peak price periods?; and 3) How are these insights affected by consideration of system-wide demand? Using measured and modelled weather data on an hourly basis from 16 locations across Ontario (Canada), hourly energy production figures for 1000 kW of solar-photovoltaic panels are generated for 2003, 2004, and 2005. Geographical dispersion of panels across multiple locations (as compared to the deployment of all panels in one location, namely, Toronto, Ontario) leads to, in particular instances, energy production profiles that have lower variability, greater total energy production, and a higher correlation value with the Ontario-wide system. Further research is needed both to isolate particularly-advantageous combinations and to broaden the investigation to consider alternative performance metrics, additional analytical techniques and land-use implications.     

Optimal solar-PV tilt angle and azimuth: An Ontario (Canada) case-study

The purpose of this article is to determine the tilt angle and azimuth for a photovoltaic panel in Ontario (Canada) at which revenue is maximised. Measured and modelled solar radiation data, simulated photovoltaic panel performance, hourly electricity market data and details regarding pricing regimes from 2003 to 2008 are used to study two different locations. In all instances, the desired tilt angle is slightly less than latitude (depending upon the particular pricing regime, between 36° and 38° for Ottawa, which is at a latitude of 45°N, and between 32° and 35° for Toronto, which is at a latitude of 44°N), and the desired azimuth is close to due south (depending upon the particular pricing regime, between 4° west of due south and 6° east of due south for Ottawa, and between 1° west of due south and 2° east of due south for Toronto). In conclusion, the importance of solar electricity – particularly valuable because of when it is produced and where it can be produced – is highlighted, as are future priorities for research.     

Simulation of a wind farm in swift current region in Southern Saskatchewan (Canada)

An attempt is made to simulate the Centennial wind farm consisting of 83 wind turbines. The farm is located in the Coulee municipality region near Swift Current, Southern Saskatchewan (Canada). The Wind Atlas Analysis and Application Program and other mapping programs were used for generating the annual energy production (AEP). Based on the generated wind atlas and using both the meteorological data for a period of 10 years (2000–2009), and a vector map with height contour and surface roughness lines, the total AEP for the wind farm was calculated. In addition, AEPs of the wind farm were individually calculated for 2007, 2008 and 2009. The results of the simulated model were compared to the actual values for 3 years. The average absolute deviation between the predicted and actual mean AEP values was found to be less than 7%.     

Three-dimensional thermal and airflow (3D-TAF) model of a dome-covered house in Canada

A dome-covered house is an example of designing sustainable buildings by learning from the optimized biological forms from the nature. The paper presents a 3-D thermal and air flow (3D-TAF) model that estimates the energy needs of a dome-covered house. The model is verified with CFD simulations under the COMSOL Multiphysics environment, experimental measurements and simulation results from similar structures published by other researchers. The use of the dome is expected to reduce the annual heating load of the house by 62.6%, compared with that of an isolated house located in Montreal at 45N latitude.     

Thermal and hydraulic characteristics of a large-scaled parabolic trough solar field (PTSF) under cloud passages

To better understand the characteristics of a large-scaled parabolic trough solar field (PTSF) under cloud passages, a novel method which combines a closed-loop thermal hydraulic model (CLTHM) and cloud vector (CV) is developed. Besides, the CLTHM is established and validated based on a pilot plant. Moreover, some key parameters which are used to characterize a typical PTSF and CV are presented for further simulation. Furthermore, two sets of results simulated by the CLTHM are compared and discussed. One set deals with cloud passages by the CV, while the other by the traditionally distributed weather stations (DWSs). Because of considering the solar irradiance distribution in a more detailed and realistically way, compared with the distributed weather station (DWS) simulation, all essential parameters, such as the total flowrate, flow distribution, outlet temperature, thermal and exergetic efficiency, and exergetic destruction tend to be more precise and smoother in the CV simulation. For example, for the runner outlet temperature, which is the most crucial parameter for a running PTSF, the maximum relative error reaches −15% in the comparison. In addition, the mechanism of thermal and hydraulic unbalance caused by cloud passages are explained based on the simulation.     

Assessment and energy implications of street air temperature cooling by shade tress in Athens (Greece) under extremely hot weather conditions

Air temperature measurements under the vegetation canopy of trees in suburban streets and at reference points were carried out under mostly light wind conditions in five streets in the city of Athens (Greece) during a short exceptionally hot weather period in 2007. The average cooling effect at 1400 h (LST) was found to range from 0.5 to 1.6 °C and at 1700 h (LST) from 0.4 to 2.2 °C; the highest cooling effect of 2.2 °C was found to be reached in a street with high tree shaded area and minimal traffic load. These results imply the passive cooling potential of shade trees. The trees cooling effect values obtained for Athens, however, were found to be lower than the ones reported in similar studies in the Mediterranean region. In terms of residential energy implications, the elaboration of the results using simplified assumptions showed that the current level of tree cover in the examined streets may reduce summer time consumption for air conditioning during the day by 2.6–8.6% and during peak hours by 2.9–9.7%.     

Causal relationship between energy consumption (EC) and GDP: A Markov-switching (MS) causality

This paper re-examines the causal relationship between energy use and Gross Domestic Product (GDP) in the United States for the period 1960-2005. To that end, we use Markov-switching vector autoregressive (MS-VAR) models, rather than vector autoregressive (VAR) models, which allows for regime shifts. These models are capable of detecting changes in the relationship between variables; in addition, the coefficients of the model are time dependent and they depend on the states of the variables. Therefore, in contrast to VAR and vector error correction models (VECM), which assume a stable relationship, the relationship between the variables could be different in the separate regimes.Results from the estimation of MS models show changes in the pattern of causality relationship between GDP and energy use. That is, we found evidence of bidirectional Granger causality (GC) between the variables in the first regime, while there is no GC between the variables in the second regime. The first regime consists of 1971-1975, 1977-1982, 1989-1995, and from 2001 to the end of the sample. This regime includes the energy crises in 1970s, the recessions in the early 1980s, 1990s, and the recession in 2001.