Review of Literature on Renewable Energy Power Generation
At present, the Philippines is experiencing power shortages, especially in the island of Mindanao, where the rotational blackout ranges from six (8) to eight (12) hours a day for rural areas and one hour for urban areas since March 2013. Residents of Mindanao will have to suffer and continue to experience rotating blackouts until 2015 due to shortage of power capacity (Flores, 2014). LiDAR technology, which is based based on laser ranging, which measures the distance between a sensor and target based on half the elapsed time between the emission of a pulse and the detection of a reflected return (Wulder, et al., 2012) can be used to identify and map renewable energy resources. Since the country is relying too much on fossil fuels that are becoming very expensive, it is about time to consider renewable energy sources to help the country’s sustainability. Renewable energy offers several benefits and it includes the technology to process these sources has less impact on the environment compared to the conventional technologies. It will not run out and have an unlimited supply such as solar energy, as long as the sun will shine, solar energy will never be depleted compared to fossil fuels that are about to be exhausted. Biomass offer several advantages compared to the existing conventional process that is using coal, oil and fossil fuels in their manufacturing processes (Naik, Goud, Rout, & Dalai, 2010).
Overview of Bio-Energy and Biomass Power Generation
Energy production is an interesting field that researchers, scientists, engineers, inventors and other enthusiast explores for the purpose of developing new technology as no one knows when the fossil fuels (gas, coal, and oil) will be completely depleted. Thus, it is important to search for alternative ways to produce energy as the sustainability of every nation depends on it. Renewable energy sources are a good alternative to fossil fuels energy, but most of the producing technologies such as Concentrated Solar Panel (CSP), Solar Photovoltaic, and wind turbines, are still relatively expensive. One of the few exceptions to this rule for renewable sources is biomass. Ever since the human exists, biomass has been used to produce heat by burning raw materials like wood or straw. Biomass is a flexible feedstock capable of conversion into solid, liquid and gaseous fuels by chemical and biological processes. Biomass categories are agricultural residues, forest residues, used wood, municipal solid waste, organic liquid wastes and manure. The main agricultural residue is straw and stalks from grains, rice, corn, beans, tubers, and cotton, sugarcane and oil crops. In China, it includes wheat and the annual available amount all over the country for the agricultural waste is equivalent to 150 million Tons of Standard Coal Equivalent (TCEs). The yearly available amount of forest residues and used wood is equivalent to 300 million TCEs, and the yearly available amount of municipal solid waste nationwide equal to 13 million TCEs. In addition, the annual available amount of organic liquid wastes and manure throughout the country is equivalent to 57 million TCEs (Zhen-yu Zhao, Hong Yan, 2012). However, in the Philippines, no concrete facts and results of studies on biomass converted to fuel energy were published as of writing this paper. Worldwide, several published studies and research were done for the renewable energy to help aid the increasing demand of petroleum as the principal source of energy (Dhuico, 2012). One that can substitute petroleum fuel is the biofuel, a renewable energy source produced from natural (plant) materials. Solid biomass fuels are classified into three types. These are wood pellets, wood chips and torrefied pellets which are the new products that result from combining the torrefaction and pelletization techniques (Wu, Schott, & Lodewijks, 2011).
On the other hand, most common liquid biofuels, such as ethanol from corn, wheat or sugar beet and biodiesel from oil seeds, are produced from classic food crops that require high-quality agricultural land for growth. The biofuels produced from the renewable resources could help to minimize the fossil fuel burning and carbon dioxide, CO2 production. Biofuels produced from biomass such as plants or organic waste could help to reduce both the world’s dependence on oil and CO2 production. Classifications of biofuels based on production technologies: First-generation biofuels; second generation biofuels; third generation biofuels; and fourth generation biofuels. The first-generation biofuels appear unsustainable because of the potential stress that their production places on food commodities. Second generation biofuels need to build on the need for sustainable liquid fuels through processing including pyrolysis and hydrothermal liquefaction. Advantages and disadvantages of the first and second generation biofuels and petroleum refinery are presented in Figure 1 (Naik, Goud, Rout, & Dalai, 2010).
Biomass to Energy Conversion
Conversion of biomass to a useful energy requires several processes. It can be categories in four as shown in figure 2. The four categories are physical, chemical, biological and thermo-chemical conversions (Naik, Goud, Rout, & Dalai, 2010). These can be produced in three main products. Two related to energy, power/heat generation and transportation fuels and one as a chemical feedstock. There are several factors to consider when choosing a conversion process. These include the type and quantity of biomass feedstock, the desired form of the energy, i.e. end-use requirements, project specific restrictions, environmental standards, and even the economic conditions. For producing a gaseous fuel for spark ignition gas engines, two main process technologies are involved. These are thermo-chemical and bio-chemical/biological. Mechanical extraction is the third technology for producing energy from biomass, e.g. rapeseed methyl ester (RME) bio-diesel. In thermo-chemical conversion four process options are available: combustion, pyrolysis, gasification and liquefaction. Similarly, bio-chemical conversion encompasses two process options: digestion, which is a production of biogas that is a mixture of mainly methane and carbon dioxide and fermentation, production of ethanol (McKendry, 2002).
Combustion of biomass produces hot gases at temperatures around 800–1000 “C. It is possible to burn any type of biomass but in practice combustion is feasible only for biomass with a moisture content <50%, unless the biomass is pre-dried. High moisture content biomass is better suited to biological conversion processes. The scale of combustion plant ranges from very small scale (e.g. for domestic heating) up to large-scale industrial plants in the range 100–3000 MW. Co-combustion of biomass in coal-fired power plants is an especially attractive option because of the high conversion efficiency of these plants (McKendry, 2002).
Biomass gasification research is focused on applications of low temperature atmospheric pressure fluid bed and entrained-flow reactor technologies using both steam and recycle gas as the fluidizing/ transport medium (Baldwin, et al., 2012). The work is carried out over a broad scale ranging from laboratory microreactors through bench scale systems up to NREL’s 20 kg/h thermochemical process development unit (TCPDU); a schematic of the TCPDU is shown in Figure 8.3.
Models of the biomass waste to energy conversion system
Biomass Estimation and Survey
As the importance of biofuels from biomass has been proven its worth to the sustainability of a country, scientists and other researchers find a way to estimate the biomass from the different areas to study and calculate the possible source of the renewable energy. Estimation may involve mathematical modeling (Ahmed, Siqueira, & Hensley, 2013), remote sensing data gathering (Song, Gong, Zhu, Shi, Li, & Cheng, 2012) (Zhao, Popescu, & Nelson, 2009) and use of LiDAR technology (Wulder, et al., 2012; Song, Gong, Zhu, Shi, Li, & Cheng, 2012). Critical to the adoption of lidar as a survey tool, however, is the capacity to simultaneously measure both vertical and horizontal vegetation structure and terrain morphology in detail and with high accuracy.
Laser vegetation imaging sensor (LVIS) which is an airborne scanning laser altimeter developed by the NASA Goddard Spaceflight Center (GSFC) was deployed to scan forest as shown in figure 3. Using different types of allometric equations to predict biomass from diameter data has a significant impact on LiDAR performance. The allometric equations used to estimate biomass and the accuracy of those estimates are all discussed in more detail in (Ahmed, Siqueira, & Hensley, 2013; Wulder, et al., 2012).
This document covers the survey of recent studies conducted, related to alternative source energy for the production of electricity. The focus is on the use of Light Detection and Ranging (LiDAR) data in extracting information, with regards to the possibility of using building and houses in urban areas, as the main infrastructure for harnessing solar energy.
Fossil Fuel and Environment
With the advent of the rapidly changing world, climate change has become a very big problem, which traces its roots in the use of fossil fuel for generating electricity. The process of producing electricity always involved burning of gas, oil or coal, resulting to the production of carbon dioxide. This contributes to the greenhouse effect, where outgoing radiative energy are trapped in the atmosphere, re-emitting some back into the earth’s surface, heating up its atmosphere. The use fossil fuel would also mean a reduction in the world’s fossil fuel reserve. (Energy Resources: Fossil Fuels, 2013) “Fossil fuels are not a renewable energy resource.” This triggered scientists and engineers all over the world to focus their interests in finding alternative sources of energy that are renewable and do not contribute to the destruction of environment. A good example to this is the solar energy. Here, solar energy is utilized in a sustainable manner through proper design of buildings and selecting the right location of windows. Another involves the use of photovoltaic (PV) devices for generating electricity.
As mentioned (Juice, 2011) in his article that “one third of the U.S. energy consumption is from buildings and houses”. A scenario suggesting the possibility of considering solar energy generation on top of these buildings. However, Juice emphasized that in order to plan the most efficient deployment of solar energy systems, it is important to know which buildings represent the best application for solar investment. This leads to a situation where solar mapping and its interpretation, in terms of calculating its solar energy potential comes into play. According to (Africani, Lambertinia, Bitellia, Minghettib, & Pas, 2013), “ the aim is not easy because a lot of consideration must be made such as insolation, orientation of the surface, size of the surface, shading due to topography, shading due to taller buildings next the surface, shading due to taller vegetation and other possible problems typical of urban areas”. With the advancement in technology, the quest for finding ways of calculating solar energy potential in urban areas, has led researchers to rely on the use of data coming from a Light Detection and Ranging (LiDAR) equipment.
LiDAR Technology for Renewable Energy Feature Extraction
LiDAR technology (Tooke, 2013; Kodysha, Omitaomua, Bhaduria, & Neisha, 2013) can be used to generate digital surface models (DSM) and digital elevation models (DEM) or digital terrain models (DTM). An example of a DSM useful for assessing the appropriate location of solar energy is shown in Figure 8.5 below.
Combining LiDAR and GIS tools offers a way to identify if a particular area is adequate for solar energy generation. Collins (Collins, 2014) in his article stated that the availability of LiDAR data is increasing for many industries, and it is useful for solar projects as it contains very accurate elevation data (DEM) that can be used to determine ideal places for solar panel placement. Since 2009 (Highman, 2011) LiDAR data has been used in generating DSM of rooftops, which can then be identified and separated using the building boundaries. In this scenario, suitable roof space for each building can be identified (Lanig, Klärle, & Ludwig, 2009). Calculation is possible over standard GIS functionalities, which compute the location factors roof pitch, roof exposition, shading, roof area size and global solar irradiation energy”. (Lukac & Zalik, 2013) As cited in their study, “Voegtle et al. (2005) extracted the roof planes from the LiDAR data, then the suitable areas for PV systems were detected using a GIS data base management system”. Also cited that in the study conducted by Kassner et al. (2008), “ the roof’s contours were masked, then a raster interpolation was performed, and the solar potential was estimated ”. The third citation was the work of Jochem et. al. (2009) “that introduced a more efficient buildings’ roof planes extraction, and performed solar potential estimation using the sun model to assess the PV potential in the urban areas”. Another method which is used by (Meik, Lanig, Wunderlich, & Stolzenburg, 2011) is based on the total insolation calculation. Insolation is the solar power available per m2 of the surface over one year. Here, the calculation takes into account the orientation of the interconnecting surface, the shadowing effect of all objects which get temporarily between the sun’s path and the rooftop. Then suitable areas of the 3D surface extracted from the LiDAR data which receive more than 880 kWh/m² were identified. The size of said areas and the total amount of energy received at this area are the relevant attributes which determine the suitability for a solar pv installation.
On June 3, 2014, USC-RE group visited the Department of Energy Regional Office 7 (DOE 7) and have a meeting with Engr. Eduardo Amante and Engr. Felix Timbal. The group was able to get some data on Solar, Hydropower, Biomass, Geothermal and Wind RE projects of DOE as of 2014 together with the existing Mini-Hydropower Plants in the Philippines. The group then identified that Cebu province has three existing Mini-Hydropower plants located at Kawasan, Badian with 750-kW capacity and Basak, Badian and Mantayupan, Barili, the latter two having 500-kW capacity.
Meeting with UP Phil-LIDAR 2 RE Group
On September 9, 2014, Engr. Isabelo A. Rabuya (USC REMap Study Leader) went for a meeting with the RE team of Phil-LIDAR 2 in UP Diliman. The meeting was with Prof. Rosario Ang, project leader for Renewable Energy Resource Assessment, and the five Science Research Specialists in the RE team. The purpose of the meeting was to clarify on the overall strategy for the RE Resource Assessment that UP leads. The following things were established during the meeting:
• The focus for the RE resource assessment are only the following: solar, wind, biomass and micro-hydropower.
• UP has budget to deploy ten meteorological stations to measure wind velocity and solar radiation intensity all over the country. Not all regions can have a station but only those identified to have high wind RE potential. USC group has to identify a site for possible deployment (northernmost tip of Cebu).
• UP will develop the resource assessment workflows for the four RE resources identified for mapping. Tentative workflows were presented during the meeting. USC asked for training in implementing the workflows.
• The RE group in each region has to coordinate with the agriculture group to get data for biomass RE resource potential, and with the hydrology group for micro-hydro resource raw data.
To acquire more knowledge regarding RE, the group attended an engineering graduate course every Saturday on Renewable Energy, with lectures on the technology behind the conversion of RE sources to a useable energy. The lectures are part of the RE course under Dr. Michael Abundo of Nanyang Technological University in Singapore, for both master and doctor of engineering programs of the College of Engineering.
The lectures included the following RE topics:
• Marine and Ocean RE
• RE Policy in the ASEAN Region
On October 22-24, 2014, the group attended the training and mentoring regarding Image processing using the ENVI tool with LandSat8 Data and LIDAR Data. With the training provided by the DOST and UP-Diliman LIDAR team, USC-RE group can now do some image processing with LIDAR data for the RE Resource map. The training includes image transformation, image enhancement and interpretation for feature extraction (Oct. 22, 2014); image transformation, accuracy assessment, image classification (Oct. 23, 2014); and feature classification using supervised classification SVM and accuracy assessment (Oct. 24, 2014. Feature extraction and classification using SVM may take several trials before a good classification can be made. The output from the classification using SVM can be further improved when the regions of interest (ROI) are accurate. So the layering of the bands is very important. Figure 8.6 and Figure 8.7 are the some outputs for variance and classification using SVM done during the training.
Figure 8.6 HLS and variance/illumination outputs
Field Visit (Bohol)
The REMap group was part of the USC Phil LiDAR Team that visited Bohol last October 12 and 13, 2014. During the two-day visit, the team met the local government officials of the municipalities of Tubigon, Calape, Clarin, etc. The Tubigon vice mayor was very pleased to know that the USC is doing such research since it could be very helpful for them as they are also trying to know and locate the hazardous area of their municipality after the tragic earthquake last Oct. 15, 2013. With their MPDC officer, Engr. Noel C. Mendaña, they are willing to give to the university any information that we need for the research with proper letter of request. According to the Department of Agriculture Region 7, the total area harvested in the province of Bohol (composed of three districts) is 43,514.91 HA for the 1st two quarters of the year (Jan-Mar 2014).
The team then went to Calape. While going to the town hall of Calape, the team did some geo-tagging using GPS on agricultural lands and some water ways (see Figure 8.8 to Figure 8.10).
On day two, the team went to other municipalities near Tubigon. The group checked the existing cooperative in Libertad, Bohol. On the way, the team passed by one of the sources of biomass which are charcoal from coconut (see Figure 8.11). This mini-charcoal making industry is one of the sources of income of a number of people. Vast plantation of coconut trees are also nearby so the supply of coconut husks to this place is not an issue.
The existing Libertad Multipurpose Cooperative has a rice mill (see Figure 8.12 to Figure 8.16). The milling machine is operating every day with an average capacity of 400kgs/day. The operation is also dependent on the harvest of the farmers. The coop also has a biomass-fueled dryer. The dryer uses the rice hulls, to generate heat and being blown by a blower to the dryer facility. So the bio-waste from the milling facility is technically being used as an alternative source of energy in their area. Although the blower still uses gasoline to operate, utilizing the rice hulls as the source of heat for the dryer significantly helps the community. The capacity of the dyer is around 120 sacks. The average time of drying is about 8 hours. The beneficiaries include the nearest towns according to the cooperative cashier, Evangeline Rebusa.