Lilandra Dennis

Bioenergy I

This course’s assessment included a research assignment based on questions set in conjunction with the lecture topic for that week (excerpt in image) and a literature review based on a topic selected from a list provided by the lecturer. The topic chosen by my partner and I was “Agro-Pv Systems and The Role Of Bioenergy In A Circular Biomass Approach”.

Project Abstract:

Agrophotovoltaics (Agro-PV), also known as Agrivoltaics (Agri-PV), APV or solar sharing, is a method for the simultaneous use of agricultural land for food production and photovoltaic electricity production. This technology enables an efficient dual use of agricultural land: photovoltaics on open land can be substantially expanded without using valuable resources on fertile arable land. They can be built by placing PV panels on top of greenhouses or in open field systems by spacing them between or above crops. Studies have shown that crops, like tomatoes, peppers, berries and grape vines, are the most suitable for APV as they require shade to grow.  

APV can be utilized for cultivated plants through specialized support systems for the PV modules that are adapted to cultivation, while it can be utilized for grassland with conventional mounting structures for ground mount photovoltaic systems with minor adaptations. There have been commercial and research APV facilities developed more recently but more research is needed to maximise and fully understand the potential of APV. Most advances in APV currently occur in Europe and Asia with some use in Latin America. Although, there is greater need for such in Latin America and the Caribbean due to limited land in developed areas and funding for land use. Trinidad and Tobago has the potential and usable space available to develop and promote APV technology locally at the API and the Orange Grove and Brechin Castle solar plant sites. Future research involves the use of solar trackers to maximise PV yield, the application of wavelength-selective PV modules in horticulture and the potential synergistic effects of APV panels especially in arid regions.

Of all forms of energy utilized by humankind, Bioenergy has been one of the first ever utilized from its use as fuel for fire in the caveman era to the modern era where we are processing all available biomass through a variety of technological methods to extract high quality synthesized sources of energy, entirely from organic matter.

Within the use of Bioenergy, also comes the opportunity to utilize all possible organic matter that may have once been considered useless waste products. This leads to the design of the Circular Biomass approach, where there will be a continuous cycle of reuse and recycling of feedstocks throughout the agribusiness and energy sector to achieve a sustainable and efficient system for energy and food production.

Solar Energy Conversion

The assessment of this course consisted of three (3) exams, two (2) labs, and one (1) research project.

Lab 1:

The title of Lab 1 was “Comparison of The Efficiencies of The Flat Plate and Evacuated Tube Solar Collectors”. The objectives of the lab were to calculate the efficiencies of the flat plate and evacuated tube solar collectors using two different methods (Method I and Method II) and to compare the efficiencies of flat plate collector and evacuated tube solar collector. The efficiencies of the flat plate solar collector and evacuated tube solar collector were evaluated under similar conditions and time periods. To calculate the efficiency of the two different solar water heaters, the temperatures of the inlet and outlet were measured and recorded simultaneously at 10-minute intervals for both solar collectors for the time period of 9:00 am to 1:00 pm. The solar irradiance was also monitored and recorded under the same conditions.

The efficiencies were calculated over a time period using both Method I and Method II. Method I does not account for heat losses while Method II does account for heat losses in the equation. For Method I, it was found that the flat plate collector had a significantly higher efficiency when compared to the evacuated tube collector. Yet, for Method II, the efficiency of the evacuated tube collector was analogous and at times higher than the flat plate collector. It was seen that there was a vast difference in efficiency calculated across Method I and Method II for the evacuated tube collector which could be attributed to heat losses whilst the efficiency values for the flat plate collector were mostly similar across both methods.

Lab 2 (excerpt in image):

The title of Lab 2 was “RETScreen Modelling”. RETScreen was used to perform an energy model for Solar Thermal Power Plant in Alturas, California, USA to determine technical and financial feasibility of the proposed case and to examine if the project could have been classified under the Clean Development Mechanisms. This Solar Thermal Power Plant project was found to feasible but not CDM eligible since it resulted in reduction in GHG emissions to 0.552 tCO2/MWh annually, an overall profit of $36,792,000 over the project lifetime with IRR on equity of 23.7% and payback period on equity of 4.7 years but its host country USA is not classified as “developing status”.

Research Project:

The research project was based on discussion questions provided by the lecturer. These questions prompted exploration into the energy targets of Caribbean countries, Trinidad and Tobago’s implementation and plans for Renewable Energy implementation, its contribution to CARICOM’s Renewable Energy target, benefits of Renewable Energy in the country’s energy mix and recommendations for the country to reach its target.

In conclusion, T&T has made a commitment of 10% RE power generation by 2021 and the reduction in overall emissions from the power generation, transportation and industrial sectors by 15% by 2030. Projects such as the green hydrogen project with production capacity of 27,200 tonnes per year that is expected to start up in 2024 and the development of two utility scale solar PV power plants in Brechin Castle and Orange Grove which are expected to become operational by 2022 to produce 112 MW collectively. These projects will allow T&T to meet their 10% NDCs in 2021.

In addition, the incentives currently in place for RE expenditure in the industrial and transportation sector need to be re-examined to determine overall effectiveness in terms of CO2 equivalent reduction. Notwithstanding, stricter CO2 targets should be enforced throughout T&T sectors to encourage the energy transition. Although, companies have made public pledges to reduce GHG emissions locally, they have not made tangible steps to enact those pledges. As such, T&T’s focus should be aimed at decarbonizing these sectors and cascading learnings across industries.

Wind Energy I

This course’s assessment consisted of two (2) reports based on Simulations conducted individually after an Introductory Lab Session.

Report 1:

This report utilised the WindFarmer Demonstration Software Version 5.3.27.0 to complete Exercises 1 & 2 from their “Software Exercises” Manual. Exercise 1 familiarised the user with the basic functions of WindFarmer and the navigation of its user interface. Exercise 2 illustrated how to complete an energy calculation and optimise the wind farm layout for energy production using the software. The calculated net energy yield of the original and modified wind farm layout results were compared. It was found that the array efficiency decreased by 0.4% and the estimated annual net energy production increased by 14.49 GWh/yr.

Report 2 (excerpt in image):

This report utilised the WindFarmer Demonstration Software version 5.3.27.0 to complete Exercises 1 - 9 from their “Software Exercises” Manual and showed the theory involved in the completion of the exercises. The user was familiarised with the basic functionality of the WindFarmer software. The user was able to complete energy calculations and generate reports using the software. The user was equipped with knowledge of wind farm layout optimisation for energy production and the ability to compare the results of the WindFarmer Optimisation algorithm.

In the first energy yield report, the array efficiency was 96.7% and the estimated annual net energy production was 18.61 GWh/yr. With optimisation, in the second energy yield report, the array efficiency was 96.3% and the estimated annual net energy production was 33.1 GWh/yr. Energy report 3 showed that the array efficiency was 96.7% and the estimated annual net energy production was 33.9 GWh/yr. Energy report 4 showed that the array efficiency was 97.34% and the estimated annual net energy production was 32.3 GWh/yr. Electrical efficiency was 98% for energy reports 1 – 4. Energy report 5 showed that the array efficiency was 99.06%, the estimated annual net energy production was 10.39 GWh/yr and electrical efficiency was 97.69% due to electrical losses and load.

The noise was heaviest within the radius of each turbine, with each cluster propagating off of each other. Further away from the turbines, the noise dropped in levels leading to a noise level below 40db(A) outside of the belt. The dwellings in this simulation were affected by shadow flicker 1 – 20 hours per year with the most shadow flicker occurring within the immediate boundary of the wind farm such that theoretical planning permission would have been granted to this wind farm since the surrounding buildings were not adversely affected for a prolonged period of time. Viewpoint 1 showed the tips and hubs of 10 turbines with the horizontal subtended angle of 32 degrees, site visibility of 79% and the vertical subtended angle of 5.75 degrees. 

Thus, the theoretical wind farm in Scotland would have been near ideal in terms of theoretical planning permission.

Electrical Integration of Renewables

The assessment for this course entailed two (2) assignments and two (2) exams. They were based on scenarios for electrical wiring and calculation of renewable systems.

Energy Use and Energy Auditing

This course’s assessment involved two (2) reports – a Home Audit and a Commercial Audit. The Home Audit was conducted based on information I would’ve gathered on my home. The basic information for the Commercial Audit was provided by the lecturer where further research was required on the power consumption of the equipment used within the organisation.

Report 1:

Electrical (T&TEC) bills for an approximately 139 square meter single story home were obtained for a 12-month period. The lighting and appliances for the household were noted. The Home Energy Audit sheet was populated to complete a bill, lighting, and appliance analysis, as well as a summary sheet. An energy consumption distribution pie chart was developed based on this information.

From the electrical bills, it was seen that the average electrical energy used was 626 kWh, with the average cost being $195.00. From the summary data, the total average monthly energy was 638 kWh and total monthly cost was $160.00. When comparing the bills analysis with the summary values it was seen that there was a Variance of 12 kWh or 1.95%.

The energy consumption distribution pie chart showed the following:

• Air Conditioning was 0% as the household is not air conditioned

• Lighting was 2% as the household utilises LED bulbs

• Food Preservation was 37% as there one fridge in use

• Food Preparation was 1%* due to the miniscule use of a blender, microwave oven and hand mixer. Other forms of preparation was completed using gas as opposed to electricity.

• Laundry was 17% as the household utilises an iron, washing machine and tankless water heater regularly

• Comfort Conditioning was 25% due to the regular use of fans and an air purifier

• Hair and Beauty was 0% as the household utilises a heating pad and shaver sparsely

• Household was 5% due to the frequent use of laptops and rare use of a vacuum cleaner

• Home Entertainment was 14% was the household commonly uses multiple LED televisions

Report 2 (excerpt in image):

An Audit was conducted on an Insurance Company to determine various Energy Saving Opportunities that can be implemented. The energy consumption savings, cost savings and simple payback for the implementation of each opportunity were also established.

Records from 1st June 2020 to 1st February 2022 were compiled and analysed. The electricity consumption recorded from the bills and the estimated average electricity consumption (from the lighting, general equipment, and air conditioning usage) were compared and balanced. Air Conditioning was the major energy consumer at 75%, General Equipment was secondary at 13%, followed by Lighting at 11% and Refrigeration at 1%.

The Total Average Monthly Energy Consumption was 45,493 kWh at a Total Average Monthly Cost of $15,755.00 TTD. The Electrical Energy Usage Index (EUI) was 422.81 kWh/m2yr. Based on the building’s annual consumption of 546,276 kWh, the resultant annual carbon dioxide would be 386.22 tons/year. This is equivalent to 26,591 gallons of gasoline consumed.

The recommended Energy Management Opportunities (EMOs) were:

• Installing blinds and/or dark tint at windows

• Placing computers and laptops in sleep mode and switching off monitors when persons are on breaks, lunch, walking around the office or they are generally not in use

• Switching off lights, computers, laptops, monitors, and other general appliances/equipment that do not have too long of a start-up process

• Automating general appliances/equipment that do not have too long of a start-up process using Wi-Fi controlled plugs (SMART Plugs)

• Placing printers, scanners, shedders, and fax machines in energy saver mode after 5 minutes of inactivity

• Unplugging general equipment which are seldomly used

• Switching to digital signatures, correspondence with clients, receipts, and file keeping. Only printing the final policy document for the client’s proof of policy. Thus, reducing the amount of printing conducted by staff.

• Educating staff on Energy Conservation and Efficiency through workshops, training, memos, and signage

• Switching to LED lighting

• Installing VFDs (Variable Frequency Drives) on the Air Handler Units

• Installing double pane windows

• Insulating the walls and ceilings of the building

• Automating the lights on the 1st and 2nd Floors so that they switch on at 6am and off at 6 pm. Outside of those hours, they can operate on a motion sensor, in case of an intruder or for the security officers to patrol easily.

A Renewable Energy Option which the company can consider is installing solar panels to supplement 25% of its energy consumption.

An Energy Management Plan helps to identify various economical options and solutions for energy production and consumption. As the company is currently without an Energy Management Plan, provisions have been enclosed in the report for the implementation of one.

Wind Energy II

This course’s assessment consisted of two (2) reports based on Simulations conducted individually during or after Lab Sessions.

Report 1 (excerpt in image):

An energy prognosis for the wind energy turbine (ENERCON E-30) on the campus of the University of Applied Sciences Flensburg was created. WindPRO 3.4 was utilised to input and output data for calculation and wind park planning. The wind conditions were determined using WAsP and WindPRO. Ground roughness within a radius of up to 20 km, contour lines, obstacles and wind statistics were determined. The energy prognosis was utilised to state the expected annual energy output of the wind energy turbine on the campus of the University Flensburg.

The Enercon 30 wind turbine generator was inserted into the simulation. The roughness, wind statistics, contour lines, obstacles, and objects were defined and manipulated. The energy prognosis for the simulation was determined.

It was observed that the “Annual Energy Result” without the Campus Hall was 1.7 MWh/y more than that with the Campus Hall. Consequently, the “Annual Energy Result - 10%” without the Campus Hall was 1 MWh/y more than that with the Campus Hall. It was also noted that the free mean wind speed without the Campus Hall was 0.01 m/s than more than that with the Campus Hall and “Capacity factor” without the Campus Hall was 01% more than that with the Campus Hall. The “Total Resulting Energy” without the Campus Hall was 1.7 MWh more than that with the Campus Hall. The “Resulting Energy” without the Campus Hall was 1.2 MWh and 0.4 MWh greater than that with the Campus Hall in Sector 10 (WNW) and Sector 11 (NNW) respectively.

In “Wind profile overview” the diagrams reflected that there were lesser wind speeds at the various altitudes for the graphs with the Campus Hall. It can be seen that at a height of 30 m in Sector 10 without the Campus Hall there is a wind speed of 5.6 m/s whereas with the Campus Hall there is a wind speed of 5.3 m/s. It can be seen that at a height of 30 m in Sector 11 without the Campus Hall there is a wind speed of 5 m/s whereas with the Campus Hall there is a wind speed of 4.7 m/s. Thus, it can be deduced that the Campus Hall reduced the wind speed of the area as it proved to be a hinderance of air flow. The simulation was exported into Google Earth to view a 3D map of the University of Flensburg and its WTG.

Report 2:

Wind data was fed from the wind met tower into windPRO. Data was converted from the file into a “Meteo-Object”. Data (Weibull distributions of the wind rose) was interpreted. Data was utilised to calculate the energy yield of a WTG. It was found that the Annual Energy Result was 488.9 MWh/y, Annual Energy Free mean wind speed was 6.11 m/s and Capacity factor was 27.9%.

The wind statistic was generated from long term wind data at the site where the wind turbine is located.

A wind park (or farm) was created with the given turbine coordinates. The energy production of the wind park was calculated. It was calculated that the Result PARK was 3,137.9 MWh/y, Result – 10.0% was 2,824.1 MWh/y, GROSS Free WTGs was 3,425.4 MWh/y, Wake loss was 8.4%, and Capacity factor was 23.0%. The wind park area was defined, and the wind park was optimized. It was calculated that the Result PARK was 3,290.0 MWh/y, Result – 10.0% was 2,961.0 MWh/y, GROSS Free WTGs was 3,430.2 MWh/y, Wake loss was 4.1%, and Capacity factor was 24.1%. Thus, between the two layouts, the Result PARK was 152.1 MWh/y, Result – 10.0% was 136.9 MWh/y, GROSS Free WTGs was 4.8 MWh/y, and Capacity factor was 1.1% greater in Layout 2 than Layout 1. Wake loss was 4.3% less in Layout 2 than Layout 1.

Three noise sensitive areas were created. The noise level of the turbine and its resulting noise level as heard by its surroundings via those noise sensitive areas were determined. The noise demand was 45.0 dB(A). The sound level from WTGs at noise sensitive point A was 42.6 dB(A), noise sensitive point B was 37.8 dB(A), and noise sensitive point C was 55.2 dB(A). Noise sensitive points A and B fulfilled their noise demand. However, noise sensitive point C did not as it was over the limit by 10.2 dB(A). It can be deduced that since noise sensitive point C was the closest to the turbine it had the highest dB(A) value.

The shadow created by the turbine was calculated. At the shadow receptor, for the worse case, shadow hours per year was 9:28, shadow days per year was 46 and maximum shadow hours per day was 0:17. Thus, proving that the receptor was positioned such that it was below the threshold value of 30. A flicker map for the turbine was generated.

A PV field was created. The time varying production of the field was calculated. All production was 1,425,448 kWh/y and all/average hourly power was 162.6 kW AC. 

The ideal location on Trinidad out of 5 options to create a wind farm was determined to be Icacos. A wind farm with 2 GE General Electric GE 1.85 – 87 WTGs at that location was created. AEP with Park, Noise, Shadow, PV field AEP calculations were performed.