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Energy for Sustainable Development 16 (2012) 125–145

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Energy for Sustainable Development

Human power (HP) as a viable electricity portfolio option below 20 W/Capita Abigail R. Mechtenberg a,⁎, Kendra Borchers a, Emanuel Wokulira Miyingo b, Farhan Hormasji a, Amirtha Hariharan a, John Vianney Makanda c, Moses Kizza Musaazi b a b c

Departments of Mechanical Engineering, Applied Physics, and African Studies Center, University of Michigan, Ann Arbor, USA Department of Electrical Engineering, Makerere University, Kampala, Uganda Business Department, Mountains of the Moon University, Fort Portal, Uganda

a r t i c l e

i n f o

Article history: Received 31 December 2010 Revised 21 December 2011 Accepted 21 December 2011 Available online 10 March 2012 Keywords: Microgrids Human power PACE Reliable electricity Empowering local innovation Available electricity

a b s t r a c t Human development and electrical energy co-exist seamlessly in high Human Development Index (HDI) countries 1 where reliability and availability of electricity is greater than 95%. In numerous low HDI countries, 2 there is 5–50% electric grid availability. These electric grids can have reliability below 50% due to faults and extreme load shedding. Unavailable and unreliable electric grid events are situations disconnected from a centralized grid (if the grid fails then it is off-line). In Africa, renewable energy portfolios include solar, wind, biomass, biogas, small hydroelectric power and recently nuclear energy (MEMD, 2005, 2006, 2008, 2009) and are cited to meet the disconnected grid situations. However, Human Power (HP) is a missing portfolio option and, if implemented in countries with average electrical power consumed below 20 W/Capita, would impact human development directly. The technologies include merry-go-round generators in schools, hand crank lighting in hospitals and health clinics during electricity outages and bicycle generators for offgrid businesses. This result is derived from (1) a new energy concept defined as PACE (People-based Activities Caloric Energy), (2) estimations from children's play — energy harvesting as free energy (3) disconnected-grid fuel costs for petrol and diesel generators, and (4) policy empowerment which is based on designing and building microgrids. These designs result from an innovative Physics and Business of Energy (PBE) curriculum, in conjunction with University of Michigan (USA), taught in Uganda at Mountains of the Moon University, Makerere University and St. Joseph's Technical Institute with an association called Uganda Small Scale Industries Association (USSIA). The HP-module is part of a multi-module curriculum for Empowering Ugandans to Power Uganda. The overall educational and design policies create a key missing gateway to co-designed and locally built microgrids. These policies are applicable in many, if not all, low HDI countries. © 2012 Elsevier Ltd. All rights reserved.

Introduction A particular quote from Dr. Gro Brundtland resonated in this research, “Above all we must be uncompromising in our determination to eradicate poverty (Brundtland, 2004).” A large component of global poverty lies within the context of human development. The Human Development Index (HDI), of the United Nations Development Programme (UNDP), combines development into a single index of economics, education, and health (WEA, 2000). This paper seeks to elaborate on the relationship between human development and access to reliable electricity. For example, schools need access to effective and efficient systems for lighting and computers;

⁎ Corresponding author. 1 The United Nations Development Programme defines the human development index (HDI) with education, health, and economic indicators. “Co-exist seamlessly” means that it is almost assumed that a building will have access to electricity and that it is reliable. 2 Low HDI countries are defined with human development indexes at or below 0.50. 0973-0826/$ – see front matter © 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.esd.2011.12.006

health centers and hospitals need to run medical equipment reliably; and the economy's telecom communication systems all depend on electricity (Cabraal et al., 2005). We parse out the difference between access to electricity and reliable electricity within the application of locally maintained human powered (HP-ed) electricity generating systems. Previous researchers have created a graph similar to the one shown below in Fig. 1 (Sanchez, 2010; Mechtenberg, 2009; Martínez and Ebenhack, 2008; Goldemberg et al., 2004). They tend to focus on energy or electricity consumed in a year and not on average electrical power consumed for that year (see Appendix B). One methodology focuses on consumption patterns (kWh/day) while this methodology focuses on design possibilities (W). The average electrical power consumed is an annual estimated base power load for the country calculated from annual electrical energy consumed (the actual load usually peaks during the day and is lower at night). Recall the infamous or historical 60 Watt incandescent light bulb. People in countries below 20 W/Capita each have a 20 Watt base power load which is equivalent to 33% of an incandescent light bulb lit at all times throughout the year. In a given country, many people will have no access to the electric grid which is what drives this metric so low (Jacobson et al., 2005; Bereket and

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Fig. 1. The 20 W/Capita black line of average power (metric for estimated base power load) is the scale of human electrical power which includes 29 nations — primarily due to grid inaccessibility. Countries between black (20 W/Capita) and black dotted line (673 W/Capita) may benefit from HP during grid unreliability events. Above dotted black line there are exercise gyms implementing HP.

Dube, 2004). This Watts/Capita indicator is significant in thinking of local and/or small scale urban and rural electricity designs which can increase accessibility to electricity as well as increased reliability (see Appendix C). The unreliability of the electric grid can be as devastating as not having access to electricity. Thus, our research seeks to: 1) provide electricity to rural areas and 2) to create back-up systems for areas where the

grid is already in use in low HDI countries. Our motivation is based on increasing human development and thus decreasing poverty, but we are also motivated to decrease the crises that occur on a regular basis due to unavailable and unreliable electricity (Mechtenberg, 2009; Sanchez, 2010). A few examples of said crises include power outages during surgeries (Mechtenberg, 2009), schools using kerosene lanterns which cause air pollution and fires, (Ezzati et al., 2004), businesses

Fig. 2. Country-by-country total average electrical base power used per Capita in 2005: red countries are below 20 W/Capita and high levels of unavailable electricity also classified as low electrification rates (i.e. off-grid). Pink is between 20 and 347 W/Capita and some of these countries have unreliable electricity events which could benefit from HP for priority loads. Even in the green areas (above 1000 W/Capita) there are unreliable events (like the North American 2003 brownout) where people used HP-ed lights and radios.

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Fig. 3. Paper's logical progression is based on HP limitations, simple free energy situations, competiveness, and educational gateway to microgrids.

losing sales or decreasing margin when electricity is unreliable. These examples illustrate how even an extremely small amount of electricity in the countries below 20 W/Capita can bring about development and decrease crises events. HP is defined in this paper as electrical power generated from human muscles and will be discussed in detail. HP-ed is the abbreviation for human powered. Since HP-ed devices will be able to provide 20 W/Capita (threshold defined above and shown in Fig. 1) HP should be studied more closely as a backup system for on-grid sites and as an initial power supply in rural off-grid HP locations (or back-up system to solar panel systems for cloudy days). Furthermore, it will be shown that HP-ed electricity can actually increase the food Calorie efficiency of human activities and therefore decrease the food caloric intake (although this is difficult to imagine at first). Another alternative for supplying small amounts of electric power is solar photovoltaics (PV), which is invariably used with high efficiency lamps (compact fluorescent or LED) and other high efficiency devices at an extremely high cost and inability to maintain locally. The development benefits of providing electricity increase when the end-use devices are more efficient. The same applies to human power. There is as little sense to operate an incandescent lamp using HP as it is using a PV system. The scale of HP's impact on development As stated above, HP is a way to reach the first step of electricity needed for development. Before proceeding with technical aspects, it is important to ask, “What is the scale of HP compared to the needs of developing countries?” In Fig. 1, the correlation between average electrical power consumed and HDI is evident. Fig. 2, a map of the World, gives geographical context. Below the black line in Fig. 1 is placed at 20 W/capita, which is a power level that can be met by the HP-ed devices mentioned throughout the Human constraints on HP section and defined from Metabolic Equivalency of Task (MET) and NASA experimental data of sustained maximum mechanical power output. Countries that are below the black line in Fig. 1 are represented as red in Fig. 2. These are almost exclusively in sub-Saharan Africa with a few in Asia. These locations can be impacted with the introduction of HP-ed electricity generating devices. Countries that are between the Table 1 Comparison of three HP-ed devices presented in this paper. Device

Power range (W)

Total capital cost (US $)

Unitary capital cost ($/W)

Bicycle Hand-crank MGR

100–150 50–100 100–600

75–500 50–500 500–2400

0.25–2.00 1.00–3.00 2.00–4.00

black and black dotted line in Fig. 1 may or may not benefit from HP. These countries may benefit from HP in rural areas or in times of a crisis. The countries above the black dotted line are countries that would not benefit significantly from HP; however, some of these countries (including US and Hong Kong) have implanted HP in exercise gyms (AP, May 17, 2009; Freeplay Energy, Pvt Ltd, 2009; Newcomb, November 26, 2010) and other energy harvesting devices (EP, 2005, STEMiNC, 2011). We define these cases as “free energy” which is a subset of the research literature within energy harvesting (Donelan et al., 8 February 2008). Even though there are large differences to consider within each country, the countries above the black dotted line (Fig. 1) have above 95% availability and good reliability of their electric grid (EIA, 2009; UNDP/WHO, 2009; Bereket and Dube, 2004). On the other extreme, countries below the black line (Fig. 1) have 10–25% electrification rates (Jacobson et al., 2005; UNDP/WHO, 2009; Dasappa, 2011) and poor reliability. These electrification rates are closely related to the electric grid availability. In addition, the electrical demand outweighs the capacity such that there are regular electrical grid-power outages (rolling brownouts) and blackouts. In Fort Portal, Uganda, total electricity consumption is quite low despite its connection to a hydroelectric powered electric grid. The unreliability of the grid and limited rural electrification are two problems where HP can play a significant role; however, it is largely ignored. Many people in underdeveloped nations accept scheduled load shedding. They may only get electricity 4 to 12 h a day or every 2 days (Sven and Peters, 2011). That means the rest of the time they do not have access to electricity from the electric grid. This is a failure of the systems' electric power capacity and can be defined as unreliability.3 If one assumes that 50% of electricity consumers connected to the electric grid use diesel generators when the electric grid is not available this is a large amount of additional greenhouse gas emissions as a direct result of unreliable electric grids. These unreliability events should be investigated further. Back-up electricity is potentially as important as primary electricity generating devices in terms of diesel fuel consumed and the relation within the climate-povertydevelopment nexus (Casillas and Kammen, 2010). Now that the need for electricity has been discussed, and there is an understanding of which countries/types of countries can be impacted by HP, it is essential that an outline for the supporting ideas and topics be established. Working together as an international team from Fort Portal, Kampala (Uganda), and Michigan (United States), we present the following: Section 1: Research Ideology and specific human powered (HP-ed) devices Section 2: Human Constraints on human power (HP) 3 It is unreliability for a hospital and health center for example when nurses and doctors cannot provide health care services due to load shedding of the electric grid.

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Fig. 4. Spectrum of electrical devices according to power demand (lighting is implicitly high efficiency, most likely LEDs).

Section 3: Free electricity energy and the schools' merry-go-round generator Section 4: Bicycle generator economically compared to other electricity generating devices Section 5: Human power empowerment policy implications for education Fig. 3 illustrates that this research is not saying human power is a solution, but should be considered in a portfolio of options. Research Ideology and Specific HP-ed Devices All of the HP-ed electricity generating devices discussed in this paper are co-designed with local technicians, business students and owners, and engineers from St. Joseph's Technical Institute, Ugandan Small Scale Industries Association (USSIA), Mountains of the Moon University, and Makerere University (Uganda), respectively. We hold the world view that in order for implementation to be viable, sustainable, and effective we must work with local people to co-design devices so that 1) the devices are designed with an understanding of the cultural constraints and inputs, 2) the devices can be built locally and therefore maintained locally, thus creating a new type of locally sustainable product, 3) the economic revenue generated from the devices stays within the local economy, and 4) there is local expertise in the community that is needed to repair and maintain the devices (Kamkwamba and Mealer, 2010; Mechtenberg, 2009).4 This co-design is contrasted with aid-based programs. Aid in Africa is problematic at times (Moyo, 2009), but throughout the high HDI countries of the world, research and development (R&D) programs have fostered innovation and advances (a different type of aid where say 99% of projects may fail, but even if 1% succeed, it is considered worth the investment). Furthermore, grassroots efforts have led to innovative advances (Maathai, 2009) in and out of Africa. The philosophy on research, co-design, and entrepreneurial implementation builds a strong foundation for our Empowering Ugandans to Power Uganda energy and sustainable development policy program (discussed in Section 5). The HP-ed devices that have been explored by our research team include: the bicycle generator, the hand-crank surgical lamp, and the merry-go-round (MGR) generator. Each of these devices is designed to target the needs of a specific sector that impacts human development. The bicycle generator is intended to be used in domestic settings and in small businesses (although hospitals could also use it as part of a backup electricity system — Mechtenberg, 2009). The 4 Economists hold the world view of rational human beings interact/transact in a free market which we do not hold as true in a developing country due to continual crisis situations and unregulated markets. Although both extremes are not helpful, we are encouraging an open discussion of philosophies.

hand-crank surgical lamp is designed for hospitals and health centers in off-grid conditions. The MGR generator is designed to provide electricity in schools that cannot afford either grid electricity or off-grid rural electrification (and has been implemented in Ghana-www. empowerplayground.org). Table 1 shows the general range of power each device can generate, its total capital cost (including batteries), and unitary capital cost dollars/W . As can be seen from Table 1, a person can bike at 125 W of power capacity for 1 h and have 125 Wh of electricity generated, but it will need to be stored in a battery to be used later (all costs include a small battery within the system: 120–600 Wh). Assuming the round-trip battery efficiency is 90% and the bicycle generator efficiency is 80%, the total electricity available for consumption would be 90 Wh. So, for the day, the average base power for this amount of energy available (and ready to be consumed) would be 3.75 W for this person, assuming 1 h of generation per day. The question then becomes “what loads can be supported?” If the person uses a 5 Watt device (e.g. a radio), then it will be supplied electrical power for 18 h daily. If it is a load of 3.75 W (e.g. a small set of LED lights for surgery), then the use is for 24 h. If the device is used for a few hours a day (say 4 h at night) the radio and LED lights will be supported/powered for a number of days: i.e. 5 and 6 days respectively. Because of the low power availability, the efficiency of end-use devices is even more critical for HP-ed devices. HP is only useful for small loads in rural areas, or to act as a backup emergency system for critical loads. HP is not intended to be the only power source in places of high electricity consumption like hospitals. Many electrical devices and appliances have been produced to meet a particular need or make a particular activity more efficient. These technologies are important to the health and technological progress of a society. 5 Consider Fig. 4 and the spectrum of electrical devices and the range of power that can be provided by HP-ed devices. For example, a bicycle generator that can output 100 W could be used to charge a cell phone, provide lighting for a house, or run a radio, laptop, or printer or a combination (either on-demand or with a battery: Butcher, 2009). The smaller the total power demand, the less pedaling would be needed per day (less mechanical output) and the longer the device can run on a battery charge (see earlier discussion). Our current prototype bicycle generator has been used to charge motor cycle batteries that are later on used to run a radio. It has also been used to run through an inverter to power a color TV. FreePlay, a company that manufactures hand powered devices, has used HP to run radios since 1996 (Freeplay Energy, Pvt Ltd, 2009) but to our knowledge no one has considered it widely for human 5 We use progress in terms of traveling down a technological pathway — for example increase in cell phone networks.

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When looking at kinesiology research, in terms of HP, there are three important factors to consider: a) the maximum sustainable power of human muscles, b) the number of Calories a person burns for a particular activity, and c) how the efficiency of the activity is affected by adding the device (Reynolds, 1927). These scenarios will be addressed in this section. Maximum sustainable power output One of the constraints on HP-ed devices is how much power a human can output (Davies and Rennie, 1968). The following equation represents the relationship between HP and electrical power: P electrical ¼ ηdevice P Human mechanical output

Fig. 5. Reproduced from NASA experimental results on sustained maximum power for one person (Roth, 1966).

development (although it received journalistic attention). We believe this is due to the lack of understanding and potential misunderstanding of HP (discussed in the next section).

Human constraints on HP One concern that is often expressed when HP is suggested is that there would be an increase in manual labor for those who choose these HP-ed electricity generating devices. This is not necessarily accurate. We provide two concepts to address this concern: 1) PACE (People-based activities — Calorie efficiency) and kinesiology data discussed in this section; and 2) free energy also called energy harvesting discussed in section 3.

ð1Þ

where ηdevice is the efficiency of the device, PHuman mechanical output is the mechanical power output of human muscles, and Pelectrical is the electrical power output from the electricity generating devices. Thus, it is important to know how much power a person can produce on average. The maximum power output depends on the time over which it can be sustained. NASA's research on maximum sustained mechanical work (Fig. 5) shows that a 100 W mechanical energy output can be sustained for about 4 h. Of course, power output will vary from person to person and depends on the health and age of the individual, but knowing the general range of power outputs possible helps to design the system. It is reasonable to assume that most healthy people in developing countries should be able to sustain an output of 100 W for at least an hour a day (or average power capacity of 4.2 W/Capita which is 21% increase from 20 W/Capita). In fact, some people in developed countries are worried about overweight and obese health statistics and discuss exercising for 30 min at least three times a week which would be around 1 W/Capita average power. PACE: Person-based Activity Caloric Energy In this section we will compare HP to other sources of power in terms of (a) technology to technology efficiency — typical comparison or (b) human activity to human activity efficiency — cultural or site constrained comparisons. One example of a comparison is the following: should biomass be made into a fuel and then burned in a diesel engine/generator or

Fig. 6. A person's energy consumed from five human activities to charge a cell phone (PACE1 and PACE3 are walking (slow and fast) to and from a charging station; PACE2 and PACE4 are running (slow and fast) to and from a charging station; PACE5 is using a local bicycle generator).

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Fig. 7. Ragone Plot of four HP-ed electricity generating devices: piezoelectric, hand-crank generator, bicycle generator, merry-go-round generator. Each device can charge a cell phone (star) in a different amount of time.

should a person eat food (as their “fuel”) and then operate a bicycle generator? This is what we define as a technology to technology energy and energy efficiency comparison. If the devices are compared in this way, it can be seen that the methane biogas generator will be on average 27% efficient (Gupta et al., 2009 — ignoring biomass to methane conversion efficiency) whereas human bodies using a bicycle generator will be 20% efficient (25% human body Pietro, 2000; 80% mechanical bicycle Wilson, 2004). However, this comparison ignores the infrastructure that is assumed to accomplish the provision of biogas far away from roads (or other modern infrastructure like digesters) in Africa. Technology to technology comparisons are often not meaningful in comparing HP with alternatives. For instance, biodiesel is rarely used to generate electricity. Electricity is more likely to be generated using biomass waste (e.g. biogas) or cellulosic biomass (i.e. non edible), solar, wind, or hydro power or fossil fuels. None of these pathways imply an either–or selection of HP versus alternative technology starting from and competing with the same resource base (food). Instead of comparing the systems technology to technology, we are going to compare activity to activity based on cultural and sitebased constraints. Determining constraints is a critical step in any design process, and the constraints in developing countries are very different from those in the US. The main constraint in our particular case is how rural Africans

acquire electricity for cell phones or batteries for their homes. In rural Uganda people walk long distances to charge lead-acid batteries. They sometimes carry batteries on their heads, which means that they are at risk from battery acid leakage/burning. They typically pour out battery acid onto the ground, clean the electrodes, and pour new acid into the battery, which presents an environmental concern. This method of charging batteries presents a greater incentive to change than you would experience in the US where the constraints are much different. In the US, people charge their devices by plugging them into the nearest electrical socket/outlet (and there are many to choose from) and at a battery's end-of-life there are policies which promote recycling. Some of these various policy factors are not considered when comparing technology-to-technology; therefore a new energy concept for the nations below the 20 W/Capita line is defined to better account for the role of human activity as it relates to electricity consumption. In other words, this is a human activity-to-human activity comparison. The United States PACE to charge cell phones is around 5–10 food Calories, but the Ugandan PACE varies greatly and can be between 50 and 1000 food Calories. We describe this new energy concept called PACE as food Calories consumed (with PACE efficiency defines as the Calories' efficient use — as a percentage). PACE is a term that quantifies the amount of energy (in terms of food Calories) required in completing a particular activity.

Fig. 8. MGR generator built by St. Joseph's Technical Institute in Uganda (left and center) and MGR generator imported from Brigham Young University to Ghana and being used routinely (right).

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Fig. 9. MGRs can generate from 100 to 600 W dependent upon the design of the system and how much energy the children exert while playing.

In our discussion, we will use the term PACE in discussing different activities related to obtaining electricity. The PACE of every culture is vastly different from others, and thus it can be used to compare a given activity across multiple countries. PACE illustrates that there are certain electricity generating devices that make sense in one culture while not in another simply because of the specific electricity situation in that culture. Again, it is understood that human bodies have evolved into approximately 25% efficient organisms in terms of biological (chemical) food energy in and mechanical work. In the modern industrialized world, humans do less mechanical work because machines are available to do much of this work. People in these societies are so Calorie “efficient” with their activities that they need to exercise in gyms to burn additional chemical energy (Calories) or risk the body turning the unused Calories into fat (risk of becoming overweight and/or obese). However, for many people in developing countries machines rarely do their work. Consequently, an added benefit of electrical machines is that societal efficiencies of human activities increase. Thus they would require less total mechanical work (less manual labor). As counter-intuitive as this may seem, an average healthy person using a bicycle generator every day for 1 h could consume less energy producing electricity that would be used for a given activity than the energy consumed by an identical person doing the same activity without electricity. A key example is given below, but there are many more which can be generated in future research. Just as energy consumption and energy efficiency are important concepts to discuss, PACE and PACE efficiency is distinctive. PACE is the amount of food Calories consumed. PACE efficiency is defined as the efficient use of the food Calories. In Uganda, we will compare two possible ways to charge a cell phone: (1) walking to a distant charging station or (2) charging with local bicycle generator (at the village).

ηUganda PACE1−4 ¼

ηUganda PACE5 ¼

Ecellphone Ewalking=running

Ecellphone Ebike generator

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answer the questions “which pathway is more efficient?” as well or in addition to “which energy pathway consumes fewer food Calories?” The following results are based on kinesiology research using METs (Metabolic Equivalency of Tasks) charts (Ainsworth et al., 1993; Barnes and Floor, 1996).6 For a person who lives within 2 km of a charging station, it is more efficient to walk to the charging station than to charge the cell phone from a local bicycle generator. In other words, this person consumes fewer Calories walking to and from the charging station. However, for a person who lives farther than 6 km away from a charging station, it is more efficient to use a local bicycle generator. Between 2 and 4 km, the result varies depending on if the person walks or runs. Fig. 6 illustrates the energy input (Calories of food) needed for either walking or running to the nearest charging station in terms of the distance (km) traveled. The straight line (PACE5) shows the point where more energy is consumed walking or running to and from the charging station than using a local bicycle generator, which consumes 240 Cal to charge 10 cell phones (10 ∗ 3.7 V at 1.5 A = 55.5 Wh). 7 Finally, human-generated electricity needs to be compared to other forms of labor intensive employment: tea picking, coffee bean harvesting, transporting bananas via bikes, etc. 8 When we compare them in a METs table (see Appendix A), we see that bicycling on a stationary bike can consume fewer Calories than these current economic practices (see farming versus biking METs value). Furthermore, having access to electricity can make some of these manual labor jobs less strenuous. The next section will compare various high-tech HPed electricity generating devices which receive R&D funding versus appropriate technology solutions which are not included in energy portfolios for developing countries.

Different human powered (HP-ed) device efficiencies in terms of food Calories HP depends on food Calories as the initial form of potential chemical energy. Thus, one needs to consider the efficiency from food Calories in to electrical energy out. This is always related to the time sustained at this power output level. Fig. 7 is a Ragone Plot. A Ragone Plot allows us to easily compare technologies in terms of power output/capacity, energy storage and time. Fig. 7's storage technology capacity is the human body+ device and the energy storage is input of food. This HP-ed Ragone plot is based on the human activities required for human muscle power (the natural technology), human food Calories needed (storage), and time the human has to power the electrical device or charge another storage device. Using a high-tech piezoelectric backpack (STEMiNC, 2011) will have a different power output and food energy input requirement from say riding a bicycle electric generator. A typical Ragone plot technology comparison would be (1) a liquid fuel (gasoline) and engine with high power and energy density versus (2) a capacitor and electric powertrain with high power, but low energy density (Christen and Carlen, 2000). In Fig. 7, the plot shows energy storage input against power outputs of a given technology (with diagonal lines being time). This is the

ð2Þ

ð3Þ

PACE efficiency in our case is calculated in terms of the human food energy consumed (input) and the generated electrical energy (output). Comparing these two Ugandan human activities allows the discussion of increased manual labor to be addressed and to

6 For those who are unfamiliar with the MET scale a chart of some human activities is provided in Appendix A with sample calculation. 7 If the battery rating (in C's) is 2/3 C instead of 3/2 C, this will change the maximum current level from 1.5A to 0.75 A. 8 If people are reluctant to implement HP-ed devices in developing countries because of the increase in manual labor, it must be noted that manual labor may actually decrease for some people if the bicycle generator is implemented. PACE illustrates that the question of increased labor can only be answered for each household and for each person-based activity. There are other examples to compare a community's PACE. We focus on cell phone charging to illustrate because previous qualitative anthropological research (Mechtenberg, 2009) suggests that this is a common electrical device being used.

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Table 2 The “free energy” devices discussed in this section in terms of system capital costs and power capacity. Device Back pack with solar panels Piezoelectric shoes Merry-go-round (BYU's design) Merry-go-round (our design)

Power range (W)

Total capital cost (US$)

Unitary capital cost ($/W)

3–5

130–250

30–60

3–12 100

2000–4000 5000–6000

80–300 50–$60

100–600

500–2000

2–10

(and built) locally which is effective regardless of their energy efficiency (recall that for some populations they are more efficient as well). Free electrical energy and the merry-go-round Generator

amount of food Calories that will be consumed (or vice-versa the amount that needs to be stored in the human body). The diagonal lines represent the amount of time that the storage device (human muscles) will operate at a given power output level. For example, a person biking for 30–60 min (t= 0.5–1.0 h) will consume 150–400 food Calories and can mechanically output 100–150 W of power during this time. Fig. 7 plots the three interconnected physical units of power energy, and time to charge a battery (or it could be to run the device). It illustrates the range of HP-ed electricity generating devices in terms of 0.1–1200 W of electrical power, 1–5000 Cal consumed, and 0.1– 10 h of charging different batteries (Mechtenberg, 2009). In the United States, R&D has focused on piezoelectric technology and one innovation is human-powered backpacks or knee generating devices (STEMiNC, 2011; Donelan et al., 8 February 2008). These are backpacks or knee connected devices that can charge cell phones or operate small electrical devices with little Calories needed (little human effort). Product energy efficient versus societal effectiveness is key to distinguish. Hand-crank, bicycle, and merry-go-round generators are devices that are potentially more effective. In the United States other factors besides efficiency, such as convenience, take precedence in design, which is why these high-tech expensive HP devices may make sense for the US but may not make sense for Africa. In Africa energy devices which are less effective are ones which cannot be maintained locally (Sanchez, 2010). These HP devices can be maintained

Free electrical energy can be generated without substantial effort (or while adding value to human activities). Our term “free energy” is not free energy in an economic sense because there are capital and maintenance costs. It is not free energy in the perpetual motion view of free energy. It is free energy in a societal view; energy is obtained as a by-product of the primary activity. The following list illustrates the concept: (A) Backpacks or shoes with piezoelectric equipment to capture electricity from walking (B) Bicycle generator (C) Merry-go-round generators. The concept of “free energy” (but not necessarily the term) is most commonly discussed in terms of the first two technologies: the piezoelectric generator is attached to a soldier's shoes or backpack (Starner, 1996; STEMiNC, 2011) and generates enough electricity to charge a cell phone or a music playing device. The other common device in the design literature is organic solar panels, which can be integrated into materials such as backpacks (Samsonite, 2011) which are worn by humans, but not directly considered here (see The bicycle generator compared to other electricity generating devices section ). Both of these devices are “free energy” devices because they generate electricity without adding significant change to the activities that the soldier and/or villager is already doing. Free energy is energy that can be harvested without changing a normal day-to-day activity. A merry-go-round generator can be discussed as a free energy device, because children burn energy while playing on the playground. The difference in our experience between the MGR generator and the other two devices is that the MGR can be made and sustained locally and is inexpensive in terms of $/W.

Fig. 10. Off-grid microgrid optimization simulation set-up as viewed in HOMER Energy.

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If the design of the MGR system changes the percentage going into electrical energy, the merry-go-round should produce 100–600 W.

Table 3 Input assumptions in HOMER Energy. Traditional input assumptions into HOMER Energy simulation program. Lifetime — 25 years Interest rate in Uganda = 12.7% Each of the following has sensitivity analysis for values or between ranges. Capacity shortage = 0%, 5%, 10%, 50% Installation of Systems: solar panel system $8–18/W (solar panel $5/W), wind turbine system $3–5/W, diesel generator $1–1.5/W, human bicycle generator system $0.50–2.00/W Human labor cost (grid pricing rate in $/kWh): $0.50–$5.00/day but no one bikes more than a typical 8 h manual labor job. Used interconnection ($/lifetime) charge as capital costs for bicycle generator. Used standby-by grid connection ($/yr) costs as operation costs for bicycle generator. Novel economic input assumptions. Three choices for bicycle generator costs per kWh set-up in HOMER as an electric grid with a 100 Watt max capacity. Choices

Electricity cost

Discussion

1. At night

$1000/kWh

2. Workday

$1.20/kWh to $6.00/kWh

3. Morning evening

$0.00/kWh

Bicycle generator should not be used at night. No one (even in the US) can pay this kind of electricity rate and other systems are orders of magnitude more optimal than this rate. 8 hours a day there could be a new manual labor job that pays $1–5/day. This is a Private Good that someone could pay to have a person bike for them. Set up 2 h in morning and night as Public Good availability. Whether the public good is used depends on the power load demand.

The merry-go-round generator was first implemented in SubSaharan Africa by Brigham Young University (BYU) mechanical engineers (BYU, 6 Feb 2008). It is currently being imported from the US to Ghana and used in schools to generate electricity that is used for lighting (Fig. 8). According to Empower Playgrounds website (EP, 2005), their (BYU) system including teaching materials and lanterns is $7000 (the price the MGR generator alone is not indicated). It produces about 100 W of power, dependent upon the number of children playing on it and the rotational speeds. The fact that the system is only producing 100 W is an indication that it was intended for converting a large percentage of the kids' energy into rotational energy instead of electrical energy.

P Kid ¼ METValue  MassofKid  1:16unit conversion  0:25efficient

ð4Þ

P all children ¼ P kid  10children

ð5Þ

P electrical ¼ C electrical  P all children

ð6Þ

where the MET value can range from 7 to 12 (based on other children activities such as soccer); “mass of kid” is assumed to be 34 kg (middle school age); 25% is the efficiency of the human body to convert food Calories into mechanical energy, 10 children can play on the MGR at one time (and stored in a battery for later use), and “Celectrical” can range from 25 to 50%. The Celectrical design variable is how much energy is in the mechanical rotation of the MGR versus how much goes into generating electricity (some percentage also goes into heat from friction). This variable can be changed depending upon how freely the designer wants the MGR to spin. BYU's design allocates that 25% of the energy to go into electricity generation. Our experience of talking to school children in Uganda and observing them play is that their use of all mechanical MGR systems are much slower than US designs, and therefore they actually desire a slower moving system. Thus allocating 50% of the energy into electricity generating and the other 50% into rotation is not an unreasonable assumption. Fig. 9 has been generated to help illustrate how changing (a) the MET value — how much energy the children are using and (b) the electrical percentage of the energy affects the range of power output. Another difference between our design and the BYU model is that ours is made with local parts and by local technicians, while their model is imported. By making the system in the country the cost in lowered and maintenance is more reliable. Table 2 compares costs of devices that have been discussed and compared to solar panel backpacks (Voltaic, 2011): piezoelectric generators in shoes, and the MGR generators (both our model and BYU's). Although the backpacks and the shoes receive scientific R&D funding, typical international development energy designs often receive only philanthropic backing. It is worthwhile to discuss whether or not human capacity building can be considered an engineering innovation by merging engineering with the social sciences (Nieusma and Riley, 2010). The innovation of the MGR generator grew out of consideration of social constraints. It is not technologically innovative

Human Power Electricity Price ($/kWh)

Optimal System Type

Human/Wind Human/Wind/Battery Human

House Hold: HH (kWh/d) Fig. 11. Three optimal system types (Human — no shading, hybrid Human with Wind — gray shading, and hybrid Human with Wind and Battery — cross hatched) calculated considering sensitivities of cost ($/kWh) and demand (kWh/day).

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Human Power Electricity Price ($/kWh)

Optimal System Type

Human/Wind Human/PV/Battery

House Hold: HH (kWh/d) Fig. 12. Microgrid optimization system results with similar inputs as in Fig. 10, but now with no wind resources available.

per say; rather, it is a socially innovative solution that aligns itself with engineered appropriate technology. When looking at which free energy devices make sense in Uganda, our locally designed MGR generator appears to be the best in terms of $/W. In addition, it provides all of the benefits of using locally maintainable devices (sustainability, creating local jobs, etc.). The BYU's MGR cannot be maintained locally and when it breaks down, it cannot be repaired easily because all the parts were imported from the United States. The bicycle generator compared to other electricity Generating devices We will now provide an economic comparison of the bicycle generator and other common electricity generating devices: solar PV panel, diesel generator, and wind turbine generator. These alternatives are chosen because they are the devices that we have found most often given as donations to developing countries as well as purchased or promoted (in the case of solar PV panels and wind turbine generators). Due to the constraints of this single research paper on HP, we use our data collected from Fort Portal, Uganda, including capital costs and operational costs based on site constraints. We model our optimization simulation with HOMER Energy (HOMER Energy, 2007) using 1-year of measured wind speeds and solar radiance as well as generated power load curves from the G8 Task Force on Renewable Energy (Corrado and Moody-Stuart, 2001).

Fig. 9 has a labor cost for a bicycle generator rider input, because HOMER requires an input for hourly cost (grid rate) for consuming electricity from the grid system ($/kWh). Note that we are using HOMER Energy in an innovative manner where the “HOMER Energy grid” is set up as a “bicycle generator”. However, it introduces an interesting topic about implementation that illustrates the range of economies where a bicycle generator might be implemented. There are three choices. These choices come from a perspective whereby electricity might be assumed to be as accessible and reliable as a public or private good. Water is considered a public good such that it is assumed to be nonexcludable and non-rival. If basic critical load electricity services were a public good, then people would have access to it (bicycle generator) and it would be free. We have indications in Kenya and Uganda that people who do not have the ability to pay for electricity, will stand in line to charge batteries for free. However, people who have access to

HOMER Energy optimization of all possible alternatives This HOMER model comes from the G8 Task Force recommendation of 100 Wh/day/Household (HH) to 1 kWh/day/HH of electricity to meet the Millennium Development Goals (MDGs) (UN, 2008). The power load models the household (HH) electricity usage in terms of the development goals. Modifying HOMER Energy's new microgrid optimization feature, a new system was created. We used the solar radiance and wind speed measurements that we took from a research grade data logger and sensor monitoring system installed at this site. Fig. 10 shows how we set this up in HOMER Energy using the grid connection feature as the bicycle generator. We computed a straightforward sensitivity analysis comparing the amount of electricity/day required by the household and the cost to pay a person to bike on the bicycle generator.

Fig. 13. In these two scenarios (0.3 kWh/month/HH energy systems), 50 households share one bike cycled 6 min a day only (or ~ 1 h a week) and the solar panels get 5 h of sunlight every day.

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Fig. 14. In these two bicycle scenarios (3 kWh/month/HH energy system), 10 households share a bike and each HH has someone bike either 6 min/day or 1 h/day while the solar panels receive 5 h of sunlight every day (assuming no cloudy days).

money will pay for electricity rather than biking (private good). Moreover, we assume that policies and society would prevent the bicycle generators to be used at night. Table 3b discusses how these three assumptions and inputted into HOMER Energy. Again we reiterate that biking on a bicycle generator has a lower MET value than typical manual labor jobs common in Uganda and developing countries (like coffee bean and tea leave picking in the hot sun). Choice one is choosing an electricity grid rate such that no one bikes at night (it is a way to prevent the software from choosing this type of electricity). Choice two is a bicycle generator used in a small business and paying someone to bike (labor at $/kWh). If the bicycle generator were used in a domestic setting, there would be no requirement to pay a person to bike (which would make the optimal range results even greater — only the grid connection costs matter and it is used as a public good instead of a private/labor-based good). We have excluded choice 3 ($0.00/kWh rate) in the following analysis even though people are using the bicycle generator as a public good. We do this to prevent free energy concepts from interfering with the interpretation of economic optimality of human power and because we already discussed those issues. Fig. 11 shows that given the discussed inputted assumptions and values the bicycle generator would be optimal compared to other devices under the constraints of low electricity consumed per day (kWh/d) and low human power price ($/kWh) during the day, but no human power at night. In Fig. 11, the wind turbine is never an optimal option for extremely low HH power and where people earn less than $1/day. 9 However, even up to $2/day and below Uganda's black line of 20 W/ capita, HP makes sense. 10 Furthermore, even when a wind turbine is chosen for relatively high wages and electricity use, it is optimal to have a bicycle generator as back-up for days when it is not windy. 9 $1/day is $1.25/kWh or assumes that a person for one day of a manual labor job (like tea picking in the hot sun) is 800 Wh or 0.80 kWh mechanical work output (electricity generated). 10 $2/day is $2.5/kWh and below 0.1 kWh/day Human only system is optimal (no shading).

The diesel generator and the solar panel are never calculated as an optimal system for these low economic and power consumptive regions. Yet the diesel generator is the most frequently used system in developing countries and the solar panel is being imported and encouraged as a sustainable energy option even though it is not sustainable in terms of local manufacture or maintenance. 11 This result may help to shed light on why some African rural electrification programs fail. For years economic development has stated that if the ability-topay was quantified, then the poor are never too poor to pay for electricity. Sanchez (2010) discusses the statement that “poor people may not be able to pay” and that this statement may not be a myth. Our result gives strength to the fact that below $3/day people use the bicycle generator as a public good (not a private good). We have two cases that even an inefficient bicycle generator is successful when it is a public good ($0/kWh). In conclusion, the qualitative case study and HOMER simulation calculations illustrate that HP-ed devices are optimal under multiple accessibility and reliability conditions, and it should be included in the portfolio of electricity generating devices to be considered. This is especially true for solar panels during cloudy days or for people who have no access to money or solar rural electrification programs (with subsidies) as discussed in the next section.

Bicycle generator compared to solar PV panels Here, a similar HOMER model is shown with a solar panel system, diesel generator, bicycle generator and battery as possible components (with wind resources removed). The following Fig. 12 illustrates that a bicycle generator is optimal up to paying someone $3/ day when solar panels and solar resources are available. The same sensitivity analysis of adjusting the power load and amount of payment for a rider is shown. 11 Many suppliers are readily available in the market where cell phones are charged and diesel generator rewinder technicians are employed.

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Table 4 Basic product attributes of the imported solar panel system in Uganda compared to the bicycle generator. Electricity generation product attributes

One bicycle electric generator

One solar PV panel

Capital cost

$100 (used)–$250 (new) $5/year approximate

$150–$1200

30 years 0–250

15 years 5, 10, 14, 25, 70, 100, 130, 235, 400 No (sun hours) Same voltage and capacity None High (outdoors) Imported to Africa

Operation and maintenance costs Replacement years Power level (W) On-demand power Storage

Yes (human muscle) Same voltage and capacity Level of work 0.5–8 h/week day Theft probability Low (indoors) Sustainability Local Built in one day in manufacturing Africa Repair locally Easily repaired; all materials and expertise are available Toxicity Low

$0/year approximate

Almost impossible to repair in Africa, but can be replaced In question due to lack of recycling programs

Again, the bicycle generator is optimal in multiple situations of low cost and low electricity consumption. When the bicycle generator is not optimal (in areas above $5/day and electrical energy consumption above 0.6 kWh/day) the best choice is the solar panel with a battery and a bicycle generator used as a backup system. For 0% capacity shortage, a bicycle generator is chosen as back-up up to 1 kWh/day/ HH consumption (30 kWh/month/HH) at over $5/day labor rate. However, this comparison only looked at one bicycle generator. In fact, a single bicycle generator can serve multiple households as it can be shared. To compare solar panels and bicycle generators based on multiple households, we assumed the best conditions for both systems (no theft and no solar panel efficiency loss over time or due to temperature). In this scenario, we are only comparing the capital costs and assume that the bicycle generator is used as a public good that people can ride it to get free electricity (similar to how water is pumped from a river or well and used as a public good). This also deals with the fact that multiple households can share a single bicycle generator. Fig. 13 shows the difference in the capital costs based on the number of households that are supplied electricity from a single grid. Fig. 13 shows that the cost comparison of 100 households having enough electricity of 0.3 kWh/month/HH. We assume US$1000 for a solar panel system and US$200 for two bicycle generators. This comparison also assumes that (1) people already have small batteries they take to charging stations and (2) people have bicycles that they can use with a purchased stand, belt, and vehicle alternator. The assumption for solar panels is: Capital CostPV ð$Þ ¼ 10 ð$HHÞ Number of HH

ð7Þ

The slope of the line is derived from $5/W cost of solar panel and 5 h of sunlight to get $1/Wh. Then using the 0.3 kWh/month/HH (or 10 Wh/day/HH) assumption from 10% of the G8 Task Force value, the slope is $1/Wh ∗ 10 Wh/day/HH = $10/HH. When one changes the assumptions to more electricity (from 0.3 kWh/month/HH to 3 kWh/month/HH), then the difference is larger (from $800 to at least $5000). Here, we assume that people in a household share biking based on (1) interviews of how Ugandans have used the bicycle generator and (2) on how long healthy US citizens exercise — 1 h/day limit. However this should be investigated further. Fig. 14 shows that even if the capital cost of the bicycle generator is as much as a solar panel ($5/W), the bicycle generator is cheaper

when shared between 10 households and this difference grows more dramatic for 100 households. Also, the bicycle generator can last longer than a small solar panel which loses its efficiency over time. Furthermore, the capital and operational cost are only two of many product attributes to consider. They are many other user preferences (Müggenburg et al., 2011; Lemaire, 2011). Table 4 is an overview of other issues that policy makers could compare. The most detrimental attribute is sustainability. The human bicycle generator can be locally manufactured and maintained. 12 This can be done by purchasing a vehicle alternator and connecting it to the bicycle wheel to charge existing batteries. The main drawback of the bicycle generator is the required HP and more maintenance. The main drawback of solar panels is that they lose efficiency and are weather dependent. During a crisis (or cloudy day) the bicycle generator can provide light on-demand, but the solar panel may not. This synergy between the two is why we are arguing for HP to be part of an energy portfolio. For example, in health centers that depend solely on solar PV systems, they experience emergencies when the batteries of the solar panel systems have been exhausted. Because doctors and nurses cannot make the sun come out, the patients are at higher risk without a system that can be on-demand. Bicycle generators are on-demand capable for critical power loads during emergencies. However, economic market analysis should compare customer preferences under different situations besides emergencies. Bicycle generator compared to diesel generators Currently, countries without a large electric grid spend millions to run diesel and petrol generators. In Liberia, it is estimated that at least 15 MW of electricity is produced by diesel generators (REEEP, 2010). The Ministry of Energy stated that Uganda has 150 MW of electricity from diesel generators (MEMD, 2009). In this section, we calculate that local businesses in Uganda with small diesel generators have costs from $0.39/kWh up to $11/kWh, but have not been able to find a reliable citation for costs per kWh for the larger thermal plants. High costs are a result of a large diesel generators being used on a small load, which is less efficient, because the generator is idling. For example, when a generator rated at 5 kW is used to operate a 5 W hair clipper load at a barber shop, then it is only operating at 0.1% power load. Fig. 15 shows the electricity costs and the electricity consumed of twenty-one different businesses that we interviewed in Uganda who were choosing to use diesel generators as back-up to an unreliable electric grid. Some of these businesses made photocopies or charged cell phones; others were video halls. Overall, there was a pattern: all of these businesses only use the diesel generator as a back-up electricity generator when the grid fails and the businesses which match generator to power load had lower costs ($0.45/kWh) versus those who did not ($11/kWh). Fig. 15 is based on interviewing business operators about what appliances they used, how much fuel they used, the price of fuel that was used, how long they could run their appliances, and how much of a profit they made from their economic activity. Using a regression model, the electricity operational costs for the twenty-one businesses were fitted to the data points with an R 2 of 0.82. It is surprising to note that in all the business activities, a profit was realized by the business owner who was using a diesel generator during a power outage; other businesses did not use diesel generators because they could not afford to (they would just close when the electric grid was off). The barber shops and cell phone charging stations were the smallest consumers of electricity (0.25–0.5 kWh) and with the smallest 12 Many Ugandan markets have abilities to build bicycle generators, but they cannot build solar panels. When a solar panel breaks, it must be replaced completely. When a bicycle generator breaks, it can be repaired. Even the alternator can be rewound.

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Fig. 15. Electricity fuel cost curve based on various business activities using either a diesel or petrol generator as the source of their electricity.

sized generators, yet they still had the largest fuel cost (>$4/kWh). The video halls with subwoofers, refrigerators, lights, and other appliances had the largest consumption of electricity (2.25–3.0 kWh) and the lowest fuel cost (b$1/kWh). Using 50 common generator sets and HOMER Energy modeling, we calculated the cost of electricity depending on the operating points (Fig. 16). For example, a 100 kW generator running at 1 kW would be a 1% of full load. Virika Hospital, in Fort Portal, received a donated 68 kW generator so that they could run all possible electrical loads (currently and projected into the future), yet they complained

in interviews that they were glad to purchase the inferior 9 kW diesel generator because now they do not consume copious amounts of fossil fuel. The hospital's average base load, when measured using our Hobo data logger, was 1 kW. This means that they operated at a 1.4% load at a cost of at least $1.20/kWh; 10 times the US costs of $0.12/kWh (EIA, 2009). At the most efficient point, a generator can have a fuel cost of $0.39–$0.75/kWh. At part load, the generator's efficiency falls off and the electricity costs ($/kWh) skyrockets to over $11/kWh. If loads change often, then it is important to note that much of the

Fig. 16. Diesel generator's rated power (kW capacity) versus percentage of load based on 50 common generator sets operating data. For a chosen generator size (kW), the cost of the electricity varies between $0.39/kWh to $11/kWh depending on the power load demand when it is operated.

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Fig. 17. Progression of co-designed and locally built electricity generating devices from HP (in first three boxes) to mechanical to electrical generators (next three boxes) to thermal generators (next two boxes) to biogas generator (next box) and finally to microgrid combinations of the previous single systems (final box).

research literature on microgrids suggest two diesel generators and a control strategy to match loads properly is optimal or at least a generator with a battery and potentially two storage devices (Maclay et al., 2007; Nayar et al., 2008; Touryan and Touryan, 1999). If an energy system is designed robustly then HP is not economically efficient except for crisis (no wind, no solar, batteries exhausted, and diesel unavailable). Although this research is more concerned with human development as it relates to available and reliable electricity, we acknowledge that an additional benefit to implementing HP instead of diesel generators is that HP could reduce carbon emissions substantially and aid in reducing fossil fuel consumption. However, we choose to leave this for another publication on the intersection between climate change, energy, and development (Gilau et al., 2007; Olsen, 2007; Dutt, 2010; Casillas and Kammen, 2010) .

Economic conclusions after device comparisons The need for electricity is high but the supply is low, which creates an inefficient economic condition. The economics of HP-ed electricity generation needs to be researched more carefully, but appears to be viable at the $1–3/day income level. After comparing the kinesiology of tea picking and manual farming to the effects of using a bicycle generator, the authors think that it would be less manual labor than these activities in terms of Calories burnt. Thus, a bicycle generator rider would have the potential to receive more money for less manual labor. Furthermore, the bicycle generator built in local villages is lower in cost than a similar capacity solar panel. The bicycle generator has been implemented in Kenya and Uganda with villagers lining up to charge their batteries. Further investigations in Kampala and Fort Portal will continue until 2012 and are looking at more economic details. Access to money should never be underestimated regardless of the level. The unemployment and underemployment rate in Uganda and throughout Sub-Saharan Africa is extreme, if one can create jobs within the local economic system, then it should be seriously considered especially assuming it would be less manual labor (lower METs). In conclusion, we lay out many situations in which HP might make sense economically compared to the common electricity generating devices in use. However, in all these cases we are not arguing to pay someone to bike for electricity (although we are noting it is possible). Instead we are arguing it as a gateway policy to build local microgrids. In this next section, we highlight a mechanism that could bring the

bicycle generator to villages. Upon learning how to build a bicycle generator, other devices can be built and implemented. With a critical threshold of devices, a local microgrid can be created. HP policy implications — increased design capability Policy implications for HP based on locally manufactured devices only make sense in a long-term view of microgrid development. The bicycle generator is intended as a stepping stone towards other innovations; it is not intended to be the permanent and final device to provide electricity. For example, money to import diesel and diesel generators could stay in the country and be used for HP-ed technologies and for creating locally made microgrids. Then this would create a new energy market that could first be used for HP-ed technologies and then for the devices we are currently building in Uganda, but have not presented in this paper. The possible devices are highlighted here. Fig. 17 illustrates the progression for our microgrid concept for development – all built based on the understanding of a bicycle generator and we model these microgrids emerging in a similar manner – with a new technical institute certificate and degree program. This is based on the success of the German government funded solar panel technician program. Uganda's Ministry of Energy and Mineral Development (MEMD) 2004 Annual Report discussed in detail the inclusion of solar PV technology into the technical institutes funded by the German

Table 5 Outlining the physics variables in HP compared to the active local knowledge and everyday use of physics. Physics concepts needed to understand first level electricity generating devices

Knowledge level experts

Rotational energy from human foot or hand Center of mass over stable foundation Gear systems to match RPM input to the RPM needed for generator/alternator Generator/Alternator energy transformation to electrical energy

Auto mechanics welders

Electrical power levels; voltage and current; inverters; rectifiers; and transformers

Welders Auto mechanics Auto mechanics electrical technicians generator rewinders solar PV technicians Solar PV technicians electrical technicians

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Fig. 18. Technicians design of bicycle electric generator which can power a color TV or easily charge a motorcycle battery.

government (MEMD, 2005). Before this program, there were no African solar PV technology technical certificates. In the first implementation of this program, there were 106 instructors from 43 government-funded technical institutions who offered Ordinary Diploma in Electrical (ODE) and Electrical Installation (EI) courses. These programs were expanded into the private sector. Now German solar PV companies no longer have to fly engineers from Germany to Uganda to install and perform maintenance on these systems. This was a wonderful development for solar panel technology markets creating new employment for Africans in Uganda. However, more can be done which we investigated in terms of one institute's physics of energy knowledge. These technical schools produce the following professionals: welders, electrical diagnostic and installation technicians, auto mechanics, auto electric mechanics, motor rewinders and solar electric mechanics. St. Joseph Technical Institute Virika in Fort Portal, was one of these schools. We interviewed their knowledge with qualitative concept maps of physics knowledge (Mechtenberg, 2009). With this conceptual knowledge map understood, it is conjectured by the authors that Uganda has all the viable technology and technical experience to begin locally manufacturing, building, and maintaining electricity generating devices. For example, to design a typical HP device there is a set of basic physics, mechanical and electrical engineering concepts that need

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to be present. Table 5 shows the local expert who teaches and uses these physics concepts, and thus illustrates the type of technical professionals needed to create these devices in Uganda. When technical institute instructors know how to maintain and repair a vehicle and generator using physics knowledge, then the technical institute has the knowledge to design and build electricity generating devices. Table 5 illustrates that the technicians know the physics required to build their own devices. The technicians at St. Joseph's Technical Institute designed and built the bicycle generator pictured below (Fig. 17). As can be seen in Fig. 18, the technicians are using the bicycle generator to run a color TV. This model was also used to charge a DC car and motorcycle for public transport (bodaboda) battery. This design was not handed to the Ugandan technicians as so many other ‘appropriate’ technology or technology transfer programs have done in the past; rather it is and continues to be co-designed for empowerment as explained in the following technical school principal's quote: “We are trying with what we can and what made me happy is the new thinking and innovations these technicians are coming up with. It widens their understanding and opens the mind towards creativity.” — Mirembe Edfson, Principal, St. Joseph's Technical Institute, 2011. This system is now in its final prototype phase, was introduced at a demonstration with business interest, and is being introduced to the market via these contacts. The current model includes a generator that the Ugandan technicians developed based on Empower Design's curriculum, Piggot's Wind Turbine Workshop book (Piggott, 2001), and Kamkwamba's “The Boy Who Harnessed the Wind” (Kamkwamba and Mealer, 2010). The new generator design is made from permanent magnets and hand-spun coils. Using customized generators has the potential to decrease the price of the system if designed to match the human power output (currently there are too many magnets and over-designed). In addition, the locally made generators have lower resistance than car alternators which were designed for 1–2 kW. Fig. 19 pictures the current model. Fig. 20 is a close up picture of the low RPM AC generator geared system co-designed and built by the technicians in Fort Portal. Entrepreneurial businessmen in Uganda asked two questions of the authors immediately: (a) what appliances can the bicycle generator run? and (b) can one run the car alternator with a wind turbine

Fig. 19. Current prototype design of the bicycle generator with locally constructed low RPM generator.

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Fig. 20. Close up image of locally designed and constructed low RPM DC generator (with imported magnets).

or a water mill? This directed the authors to develop a complete multi-module innovation-based project focused physics and business of energy curriculum and we will be talking to the Ministry of

Education and Sports (of Uganda) about a new Technicians' Certification soon. Educating local people on how to design energy systems is an essential component of implementation and sustainability. The

Fig. 21. Three levels of electricity generating devices and the technician expertise needed to locally build microgrids (note: bicycle generator is the beginning device). This is the basis of our Empowering Ugandans to Power Uganda program.

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success of the bicycle generator and the potential for HP to be a gateway to the design of other electricity generating devices is called our “Empowering Ugandans to Power Uganda” program. Fig. 21 illustrates that our program has been designed and at least the first prototype built up to the 2nd Level. This means that we have built 5 prototype (beta and/or alpha level) of the following: horizontal and vertical wind turbine, hydroelectric generators, hand-crank generators, merry-go-round generator, cow-go-round generator and waste incinerator steam generator. Current research is being implemented to connect the devices for our first locally built Ugandan microgrid. In our R&D experience, the first device is the bicycle generator which is best built with a 4-person team of technicians with the expertise outlined in Fig. 21. When transitioning between the 1st level and 2nd level, it is good to add more technicians to the team as well as to join with local African engineering and business institutions (if possible) so that some of the devices can begin to be marketed. Currently, our 3rd Level exploration only considers imported or retrofitted biogas generators with locally built digesters. Together these three levels of electricity generating devices can be combined into locally built microgrids. Some of our colleagues are beginning to market the bicycle generator. The social issues of trusting imported technology over local manufacturing should be further researched. However, Moses Musaazi's Technology for Tomorrow Limited (Ugandan run company) has become internationally known for its success in locally designed and manufactured innovations — from sanitary pads for schoolgirls to incinerators for health clinic waste management. His expert opinion of the bicycle generator is that it is a device that, if locally manufactured and built, has the potential to be a thriving product on the market because it meets a need that is currently unmet. Purchasing a technology that one can afford is preferred to looking for an aid donation (Moyo, 2009). Currently, the Ugandan government (as many other low HDI nations) has tried many pilot programs in almost every category except HP: vertical-axis wind turbines, Stirling engines, incinerator generators, solar-thermal steam engine generators, and geothermal steam engine generators (MEMD, 2005, 2006, 2008, 2009). Some of the pilot programs stop after (1) the imported technology breaks due to lack of knowledge of how to repair the equipment (not sold in Uganda) and (2) the program is no longer supplied with funds to overcome the learning curve of new technologies. In our vision, we imagine the education and empower curriculum taught in all technical institutes and engineering universities as well as within Physics courses at the secondary education level (Kamkwamba and Mealer, 2010). For example, consider that Uganda has 56 technical institutes. In six months to a year, 5 villages could have an energy microgrid from each technical school (5 bicycle generators, 1 MGR, 2 cow-roundgenerators, and 1 hand-crank surgical lamp). In another year, the number of microgrids would double around each technical institute. That would mean 560 villages would have the beginning of a micro-grid from bicycle generators (cheapest option) or a complete microgrid (multiple devices) depending on what they could afford (based on how much they already spend in cell phone charging expenses). However, the key point is that once technicians understand the bicycle generator, then they can begin designing and building other electricity generating devices and use the bicycle generator only as back-up electricity. We hope that this methodology of implementation lays the foundation that will enable further policy implications for emerging microgrids. Our foundation begins with physics and business of energy courses and HP technologies. We then propose to move to other local power options (wind, water, thermal, etc.) within local social and economic constraints.

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Conclusions In order for human development to increase, countries need to have access to reliable electricity. Low HDI countries that design and install electricity generating devices in sectors of society that can utilize the electricity in an effective way for capacity and capability growth will increase development for education, health care, and economics. Approximately two billion people in the world have no access to electricity; of those people that do have access, a large percentage only have limited access meaning that load shedding is frequent. For example, in Kampala, Uganda recent electricity failure protests are due to having less than 67% of the hours in a week with electricity or a 24-hour load shedding schedule every third day in addition to unscheduled blackouts. In the past, donors have been quick to provide diesel generators and solar panels. However, HP-ed devices should also be considered in the portfolio of devices that can meet electricity needs in low HDI nations (in terms of availability and reliability, backup options to solar panels, climate change mitigation, abating diesel generators, and economic efficiency). HP is a viable option when looking at both the economic analysis (HOMER Energy) as well as the human activity efforts that PACE considered. As has been shown, HP electricity for a community far from a charging station could decrease food Calories consumed. Therefore, HP should be considered as an option for low HDI nations. In addition, we seek to break developing countries' dependence on aid for consumption as opposed to capacity or capability growth. The devices that are proposed in our research are locally designed and built to ensure that these devices are sustainable and affordable (although many parts in the local market are imported, the locally built devices are maintainable). HP is a gateway to a fundamentally new type of electricity infrastructure: microgrids (Lasseter and Paigi, 2004). The bicycle generator and the other HP-ed devices mentioned in this paper are key stepping stones because they contribute to the knowledge, tools, technical skills, and marketing that is needed to continue a microgrid system. They are also the cheapest electricity service imaginable. Our goal is to present the first unique electricity system co-designed and building in Uganda that are micro-economically efficient and entrepreneur-based. In future research, we will also begin to present the devices co-designed and built by women (WOUGNET, 2009) including our woven wind turbine blades for our wind turbines and solar cookers. Role of the funding source Primary financial support for this research came from the Office of Vice President Research (OVPR) office at University of Michigan that was approved by the Michigan Memorial Phoenix Energy Institute, former director Gary Was. Secondary and key funding for this research came from African Studies Center at University of Michigan. Acknowledgments The authors would like to acknowledge guidance from Marc Ross for supporting this research from its inception. We would also like to thank the anonymous reviewers for input and valuable edits. We would like to thank Thomas Seager and Susan Spierre for additional edits and support. The authors would also like to thank the technicians who actively engage and promote this R&D work with us: John Abigaba, Tom Tugume, Saul Mugasa, Deo Buguma, Patrick Nyakoojo, Gerald Muhumuza, Peter Kyazze, Mirembe Edfson, Joseph Kawuki, Brian Sebuliba, and Godfrey Kizza.

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Appendix A Table A.1 Data collected from Sports Handbook (Ainsworth et al., 1993, 2000). Human energy rate (METs to Watts output for 80 kg person) Activity Type

METS (ratio)

Cal/h

Watts In

Watts out (25%)

Sleeping Inactivity Holding baby Tourist traveling Baking Tailoring weaving House cleaning Farming Walking Soccer Bicycling b10 mph Cycling > 13 mph Running 12 min/mi Running 7 min/mi Running extreme

0.9 1.0 1.5 2.0 2.5 3.5 2–4 3–8 4–7 4–12 3–4 8–9 8–9 14–15 18

72 80 120 160 200 280 160–320 240–640 320–560 320–960 240–320 640–720 640–720 1120–1200 1440

80 90 140 190 230 330 190–370 280–740 370–650 370–1100 280–370 740–840 740–840 1300–1400 1700

N/A N/A 35 W 48 W 58 W 83 W 48–93 W 70–185 W 93–163 W 93–275 W 70–93 W 185–210 W 185–210 W 325–350 W 425 W

The Metabolic Equivalency of Task (MET — Ainsworth et al., 1993, 2000) value is based on oxygen rate measurements (rate of oxygen consumption) to calculate the rate of food Calories consumed (called the “Standard Calorific Equivalent of Oxygen”). It is normalized based on the weight. The following is the calculation of METs to Cal/h. P Tailoring weaving−80

kg person

ðCal=hÞ ¼ 3:5 METS  80 kg ¼

3:5 Cal h  80 kg ¼ 280 W kg

So, a person who weighs more would have a larger Cal/h value calculated for the same MET value than a person with a lower weight. The following is a sample calculation for a person tailoring weaving taken from the Sports Handbook: P METS¼3:5 ðWattinÞ ¼ 280ðCal=hÞ

1ðWÞ ¼ 330 W: 0:86ðCal=hÞ

This is only the rate of energy consumption happening inside the human body through complex biological processes (processes chemicals into reactions for other chemicals and electrical signals to muscles). These biological processes activate muscles to do mechanical work. This mechanical work efficiency varies between person to person and muscle group used. However, we will use 25% efficiency as a low conservative value for a mechanical output into a bicycle generator with legs. The following is a sample calculation for the same person: P METS¼3:5 ðWattoutÞ ¼ ηefficiency of ¼ 83 W

muscles 330

ðWÞ ¼ 0:25  330 W

This would be the amount of work going into a HP-ed device. This value is above 20 W/Capita and equivalent to the amount of work done for humans to do tailoring or weaving. HP-ed electricity generating devices is about creating societal efficiencies, designing local solutions, and many times less than the manual labor already practiced in countries with HDI's below 0.55. Appendix B A key distinction between Average Base Power Used versus Power Plant Capacity should be explained. Average Base Power Used is calculated as the following: PC average ðW=CapitaÞ Energyannual ðkWhÞ 1; 000 W =CapitaðpopulationÞ ¼ timeðhÞ 1 kW

For Uganda, the 2008 annual electricity consumption was 1.958 billion kWh according to US Energy Information Agency (EIA) and the population was 31,657,000 according to the World Bank. In a year, there are 8760 h. So the calculation is the following:

PC Uganda ðW=Capita Þ 1; 958; 000; 000 ðkWhÞ 1; 000 W =31; 657; 000ðpopulationÞ ¼ 8; 760ðhÞ 1 kW ¼ 7:06 W=Capita:

This is below the 20 W/Capita value presented for HP. The Ugandan electrification rate is 8.9% (Dasappa, 2011). Contrast this with the United States. For the US, the 2008 annual electricity consumption was 3906.443 billion kWh and the population was 304,375,000. So the calculation is the following: PC US ðW=Capita Þ 3; 906; 443; 000; 000 ðkWhÞ 1; 000 W =304; 375; 000ðpopulationÞ ¼ 8; 760ðhÞ 1 kW ¼ 1; 465 W=Capita:

This is way above Fig. 1's black dotted line for possible HP implementation. However, there are exercise gyms in the United States which are electrifying their buildings with the mechanical output from customers (via HP-ed electricity generating devices like bicycle generators). So, even in the United States it is being employed. Furthermore the electrification rate in the United States is above 99% according to United Nations Development Programme (UNDP). The Average Power is only half of the story. The other part of the story has to do with reliability and Power Capacity or Peak Power Potential. This is calculated as the sum of the power plants individual capacity within the country:

PP peak ðW=CapitaÞ ¼

N X

ðPower PlantðWÞÞi =CapitaðpopulationÞ

i¼1

For Uganda, the EIA 2008 power plant capacity was 0.5150 million kW versus the United States which was 1010 million kW. So, the Peak Power Potential for Uganda was 16.27 W/Capita and US was 3318 W/Capita. This means that the capacity factor for both centralized grids is 43% and 44%, respectively. Although the capacity factor is similar in percentage, the actual values for the difference are huge. We define this difference as a buffer. The buffer region for electricity management (balancing power load demand with power load supply) is drastically different. The buffer is calculated here as the difference between the two. Uganda has only a buffer of 9.21 W/Capita where the United States has a buffer region of 1834 W/Capita. In Uganda, if only 10% of people turned on an additional 100 W incandescent light bulb, the electric grid could not handle it (the demand does this and so the grid has to shed power loads — unreliable and only some hours of electricity). However, in the United States, every single person could purchase/build/use another household worth of average electrical power (1.8 kW) and the electric grid could handle the extra 304,375,000 homes (no power load sheeting — reliable grid and electricity all hours of the day). Fig. B1 is a graph of power plant capacity per capita versus average based power used to illustrate the direction of increasing capacity, importers of electricity, versus buffer between power capacity and average base power used. The buffer calculation is done with the following equation.

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Fig. B.1. Average base power used (W/Capita) versus Power Plant Capacity (W/Capita) with bubble size and color calculating the difference between the two. Recall that average base power used is calculated from annual electricity consumption.

Fig. B.2. Ranking of buffer between average base power used versus peak power potential (W/Capita). Note: some countries import the majority of their electricity (negative buffer).

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Appendix C

Fig. C.1. Median versus uncertainty between low, medium, and high human development in terms of average power per capita in 2008.

Fig. C.2. ESD research literature discusses the vast differences between the high of LOW HDI and the low of MED HDI: for example, Mozambique and Sri Lanka. This is true and we think about it in terms of the uncertainty between groupings. For example, all countries in the Medium HDI level (or with an expected life expectancy of more than 62 years) consume more than 68 Watts/Capita. HP at 20 W/Capita line is almost 1/3rd of this value. Furthermore, there is no Low HDI country which consumes more than 110 W/Capita. HP is 1/5th of this value. HP should be included in the portfolio of energy options for this low region for food Calorie reasons (Section 2), free energy or energy harvesting reasons (Section 3), economic reasons (Section 4), and educational gateway reasons (Section 5).

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