scholarly journals An Improved Sunflower-Inspired Solar Tracking Strategy for Maximizing Photovoltaic Panel Power Generation

2019 ◽  
Vol 8 (2) ◽  
pp. 1756-1762
Keyword(s):  
Power Generation ◽  
Tracking Error ◽  
Fine Tuning ◽  
Tracking Performance ◽  
Stepper Motor ◽  
Motor Current ◽  
Solar Tracking ◽  
Current Consumption ◽  
The Impact ◽  
Tracking Strategy

A previous study proposed a nature-inspired tracking strategy that mimics the solar tracking behavior of sunflowers driven by the light stimulus and the circadian clock. The approach delivered a good tracking performance with an average tracking error of 0.727° under clear, partly cloudy, and cloudy conditions. However, it incurred high tracking errors caused by false detection brought about by the abrupt changes in the amount of solar radiation during realignment. In addition, the scheme also maintained high stepper motor current consumption due to the use of a fixed stepping resolution. To address these issues, the previous tracking routine was modified to direct the search for the sun’s position to a range of calculated altitude angles where a fine-tuning process will be performed using current measurements and the adoption of a variable stepping resolution during panel reorientation. Experiments were conducted to measure the performance of the modifications in terms of tracking error, power generation, and stepper motor current consumption. A comparison of the performances between the previous and the modified approaches was done to assess the impact of the proposed improvement. The result of the comparison showed that the modifications significantly improved the overall tracking performance of the strategy.

Food Safety Security: A new Concept for Enhancing Food Safety Measures

2012 ◽  
Vol 82 (3) ◽  
pp. 216-222 ◽  
Author(s):  
Venkatesh Iyengar ◽  
Ibrahim Elmadfa
Keyword(s):  
Food Safety ◽  
Hazard Analysis ◽  
Warning System ◽  
Shared Responsibility ◽  
Fine Tuning ◽  
Strategic Action ◽  
Surveillance Network ◽  
Measurement Systems ◽  
Critical Control Points ◽  
The Impact

The food safety security (FSS) concept is perceived as an early warning system for minimizing food safety (FS) breaches, and it functions in conjunction with existing FS measures. Essentially, the function of FS and FSS measures can be visualized in two parts: (i) the FS preventive measures as actions taken at the stem level, and (ii) the FSS interventions as actions taken at the root level, to enhance the impact of the implemented safety steps. In practice, along with FS, FSS also draws its support from (i) legislative directives and regulatory measures for enforcing verifiable, timely, and effective compliance; (ii) measurement systems in place for sustained quality assurance; and (iii) shared responsibility to ensure cohesion among all the stakeholders namely, policy makers, regulators, food producers, processors and distributors, and consumers. However, the functional framework of FSS differs from that of FS by way of: (i) retooling the vulnerable segments of the preventive features of existing FS measures; (ii) fine-tuning response systems to efficiently preempt the FS breaches; (iii) building a long-term nutrient and toxicant surveillance network based on validated measurement systems functioning in real time; (iv) focusing on crisp, clear, and correct communication that resonates among all the stakeholders; and (v) developing inter-disciplinary human resources to meet ever-increasing FS challenges. Important determinants of FSS include: (i) strengthening international dialogue for refining regulatory reforms and addressing emerging risks; (ii) developing innovative and strategic action points for intervention {in addition to Hazard Analysis and Critical Control Points (HACCP) procedures]; and (iii) introducing additional science-based tools such as metrology-based measurement systems.

scholarly journals Decarbonization of Residential Building Energy Supply: Impact of Cogeneration System Performance on Energy, Environment, and Economics

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2538
Author(s):  
Praveen K. Cheekatamarla
Keyword(s):  
Carbon Dioxide ◽  
Power Generation ◽  
Energy Consumption ◽  
Carbon Footprint ◽  
Residential Buildings ◽  
Building Energy ◽  
Primary Energy ◽  
Primary Energy Consumption ◽  
Cogeneration System ◽  
The Impact

Electrical and thermal loads of residential buildings present a unique opportunity for onsite power generation, and concomitant thermal energy generation, storage, and utilization, to decrease primary energy consumption and carbon dioxide intensity. This approach also improves resiliency and ability to address peak load burden effectively. Demand response programs and grid-interactive buildings are also essential to meet the energy needs of the 21st century while addressing climate impact. Given the significance of the scale of building energy consumption, this study investigates how cogeneration systems influence the primary energy consumption and carbon footprint in residential buildings. The impact of onsite power generation capacity, its electrical and thermal efficiency, and its cost, on total primary energy consumption, equivalent carbon dioxide emissions, operating expenditure, and, most importantly, thermal and electrical energy balance, is presented. The conditions at which a cogeneration approach loses its advantage as an energy efficient residential resource are identified as a function of electrical grid’s carbon footprint and primary energy efficiency. Compared to a heat pump heating system with a coefficient of performance (COP) of three, a 0.5 kW cogeneration system with 40% electrical efficiency is shown to lose its environmental benefit if the electrical grid’s carbon dioxide intensity falls below 0.4 kg CO2 per kWh electricity.

Expectations, Prefitting Counseling, and Hearing Aid Outcome

2009 ◽  
Vol 20 (05) ◽  
pp. 320-334 ◽  
Author(s):  
Gabrielle H. Saunders ◽  
M Samantha Lewis ◽  
Anna Forsline
Keyword(s):  
Hearing Aids ◽  
Hearing Aid ◽  
Well Being ◽  
Fine Tuning ◽  
Initial Contact ◽  
High Expectations ◽  
Digital Hearing Aids ◽  
The Impact ◽  
Unrealistic Expectations

Background: Data suggest that having high expectations about hearing aids results in better overall outcome. However, some have postulated that excessively high expectations will result in disappointment and thus poor outcome. It has been suggested that counseling patients with unrealistic expectations about hearing aids prior to fitting may be beneficial. Data, however, are mixed as to the effectiveness of such counseling, in terms of both changes in expectations and final outcome. Purpose: The primary purpose of this study was to determine whether supplementing prefitting counseling with demonstration of real-world listening can (1) alter expectations of new hearing aid users and (2) increase satisfaction over verbal-only counseling. Secondary goals of the study were to examine (1) the relationship between prefitting expectations and postfitting outcome, and (2) the effect of hearing aid fine-tuning on hearing aid outcome. Research Design: Sixty new hearing aid users were fitted binaurally with Beltone Oria behind-the-ear digital hearing aids. Forty participants received prefitting counseling and demonstration of listening situations with the Beltone AVE™ (Audio Verification Environment) system; 20 received prefitting counseling without a demonstration of listening situations. Hearing aid expectations were measured at initial contact and following prefitting counseling. Reported hearing aid outcome was measured after eight to ten weeks of hearing aid use. Study Sample: Sixty new hearing aid users aged between 55 and 81 years with symmetrical sensorineural hearing loss. Intervention: Participants were randomly assigned to one of three experimental groups, between which the prefitting counseling and follow-up differed: Group 1 received prefitting counseling in combination with demonstration of listening situations. Additionally, if the participant had complaints about sound quality at the follow-up visit, the hearing aids were fine-tuned using the Beltone AVE system. Group 2 received prefitting counseling in combination with demonstration of listening situations with the Beltone AVE system, but no fine-tuning was provided at follow-up. Group 3 received prefitting hearing aid counseling that did not include demonstration of listening, and the hearing aids were not fine-tuned at the follow-up appointment. Results: The results showed that prefitting hearing aid counseling had small but significant effects on expectations. The two forms of counseling did not differ in their effectiveness at changing expectations; however, anecdotally, we learned from many participants that that they enjoyed listening to the auditory demonstrations and that they found them to be an interesting listening exercise. The data also show that positive expectations result in more positive outcome and that hearing aid fine-tuning is beneficial to the user. Conclusions: We conclude that prefitting counseling can be advantageous to hearing aid outcome and recommend the addition of prefitting counseling to address expectations associated with quality of life and self-image. The data emphasize the need to address unrealistic expectations prior to fitting hearing aids cautiously, so as not to decrease expectations to the extent of discouraging and demotivating the patient. Data also show that positive expectations regarding the impact hearing aids will have on psychosocial well-being are important for successful hearing aid outcome.

A Comparative Study of Data and Physically Based Gas Turbine Modeling for Long-Term Monitoring Scenarios: Part II — Emission Prediction Utilizing Different Levels of Design Information

2018 ◽  
Author(s):  
Moritz Lipperheide ◽  
Thomas Bexten ◽  
Manfred Wirsum ◽  
Martin Gassner ◽  
Stefano Bernero
Keyword(s):  
Gas Turbine ◽  
A Priori ◽  
Model Development ◽  
Fine Tuning ◽  
Plant Operator ◽  
Engine Model ◽  
Physically Based ◽  
Design Type ◽  
The Impact

Reliable engine and emission models allow for an online monitoring of commercial gas turbine operation and help the plant operator and the original equipment manufacturer (OEM) to ensure emission compliance of the aging engine. However, model development and validation require fine-tuning on the particular engines, which may differ in a fleet of a single design type by production, assembly and aging status. For this purpose, Artificial Neural Networks (ANN) offer a good and fast alternative to traditional physically-based engine modeling, because the model creation and adaption is merely an automatized process in commercially available software environments. However, ANN performance depends strongly on the availability of suitable data and a-priori data processing. The present work investigates the impact of specific engine information from the OEM’s design tools on ANN performance. As an alternative to a strictly data-based benchmark approach, engine characteristics were incorporated into ANNs by a pre-processing of the raw measurements with a simplified engine model. The resulting ‘virtual’ measurements, i.e. hot gas temperatures, then served as inputs to ANN training and application during long-term gas turbine operation. When processed input parameters were used for ANNs, overall long-term NOx prediction improved by 55%, and CO prediction by 16% in terms of RMSE, yielding comparable overall RMSE values to the physically-based model.

scholarly journals A Statistical Modeling Methodology for Long-Term Wind Generation and Power Ramp Simulations in New Generation Locations

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2442 ◽  
Author(s):  
Jussi Ekström ◽  
Matti Koivisto ◽  
Ilkka Mellin ◽  
Robert Millar ◽  
Matti Lehtonen
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Statistical Modeling ◽  
Renewable Energy Sources ◽  
Measurement Data ◽  
Wind Power Generation ◽  
System Level ◽  
Wind Generation ◽  
The Impact

In future power systems, a large share of the energy will be generated with wind power plants (WPPs) and other renewable energy sources. With the increasing wind power penetration, the variability of the net generation in the system increases. Consequently, it is imperative to be able to assess and model the behavior of the WPP generation in detail. This paper presents an improved methodology for the detailed statistical modeling of wind power generation from multiple new WPPs without measurement data. A vector autoregressive based methodology, which can be applied to long-term Monte Carlo simulations of existing and new WPPs, is proposed. The proposed model improves the performance of the existing methodology and can more accurately analyze the temporal correlation structure of aggregated wind generation at the system level. This enables the model to assess the impact of new WPPs on the wind power ramp rates in a power system. To evaluate the performance of the proposed methodology, it is verified against hourly wind speed measurements from six locations in Finland and the aggregated wind power generation from Finland in 2015. Furthermore, a case study analyzing the impact of the geographical distribution of WPPs on wind power ramps is included.

Potential Impacts of Net-Zero Energy Buildings With Distributed Photovoltaic (PV) Power Generation on the Electrical Grid

2018 ◽  
Author(s):  
Dongsu Kim ◽  
Heejin Cho ◽  
Rogelio Luck
Keyword(s):  
Power Generation ◽  
Electricity Demand ◽  
Office Buildings ◽  
Office Building ◽  
Electrical Grid ◽  
Net Zero ◽  
Demand Profile ◽  
The Impact ◽  
Pv Power Generation ◽  
The U.S

This study evaluates potential aggregate effects of net-zero energy building (NZEB) implementations on the electrical grid in simulation-based analysis. Many studies have been conducted on how effective NZEB designs can be achieved, however the potential impact of NZEBs have not been explored sufficiently. As significant penetration of NZEBs occurs, the aggregated electricity demand profile of the buildings on the electrical grid would experience dramatic changes. To estimate the impact of NZEBs on the electrical grid, a simulation-based study of an office building with a grid-tied PV power generation system is conducted. This study assumes that net-metering is available for NZEBs such that the excess on-site PV generation can be fed to the electrical grid. The impact of electrical energy storage (EES) within NZEBs on the electrical grid is also considered in this study. Finally, construction weighting factors of the office building type in U.S. climate zones are used to estimate the number of national office buildings. In order to consider the adoption of NZEBs in the future, this study examines scenarios with 20%, 50%, and 100% of the U.S. office building stock are composed of NZEBs. Results show that annual electricity consumption of simulated office buildings in U.S. climate locations includes the range of around 85 kWh/m2-year to 118 kWh/m2-year. Each simulated office building employs around 242 kWp to 387 kWp of maximum power outputs in the installation of on-site PV power systems to enable NZEB balances. On a national scale, the daily on-site PV power generation within NZEBs can cover around 50% to 110% of total daily electricity used in office buildings depending on weather conditions. The peak difference of U.S. electricity demand typically occurs when solar radiation is at its highest. The peak differences from the actual U.S. electricity demand on the representative summer day show 9.8%, 4.9%, and 2.0% at 12 p.m. for 100%, 50%, and 20% of the U.S. NZEB stocks, respectively. Using EES within NZEBs, the peak differences are reduced and shifted from noon to the beginning of the day, including 7.7%, 3.9%, and 1.5% for each percentage U.S. NZEB stock. NZEBs tend to create the significant curtailment of the U.S. electricity demand profile, typically during the middle of the winter day. The percentage differences at a peak point (12 p.m.) are 8.3%, 4.2%, and 1.7% for 100%, 50%, and 20% of the U.S. NZEB stocks, respectively. However, using EES on the representative winter day can flatten curtailed electricity demand curves by shifting the peak difference point to the beginning and the late afternoon of the day. The shifted peak differences show 7.4%, 3.7%, and 1.5% at 9 a.m. for three U.S. NZEB stock scenarios, respectively.

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