Cost and Commercialization Analysis for
Cold Storage Technology in Kenya
D-Lab WQ 2014
Cool Chain Analysis Group
Anthy Alexiades
Judith Ibáñez Sánchez
Kenneth Lekashman
Whitney Muse
Cool Chain Analysis, Kenya
Table of Contents
Executive Summary
I. Introduction
II. Background
Agribusiness
Supermarkets
Gender in Kenyan Agriculture
Energy Sector
Energy Resources & Solar Market
Energy Consumption & Development Policies
Solar Resource and Market
Finance Sector
Considerations Financing Agricultural Value Chains
Microfinance Sector in Kenya
III. Methodology
4 Lenses Project Approach & Impact
Environmental
Social
Economic
Technological
Energy Simulation Methodology
CoolBot2K - Cooling Demand Model
HOMER - The Micropower Optimization Model
Other Constraints and Sensitivity Parameters Explored in HOMER model
IV. Results & Recommendations
V. Bibliography
VI. Appendices
A.
B.
C.
D.
Coldroom Characteristics Input to CoolBot2K
Local Climate Inputs to CoolBot2K
4 Lenses
Stakeholder Analysis
2
Cool Chain Analysis, Kenya
Executive Summary
The aim of this report is to investigate energy demand, cost and financial feasibility of
CoolBot installation in Western Kenya. In order to understand the benefits and impacts of the
introduction of this technology through the four lenses of social, technical, environmental and
economic interests, a review of the agricultural, energy and finance sectors were conducted.
Initial review of these sectors show that there is ample opportunity and demand for cool room
storage in the region. Further encouraging, cool chain interventions have great potential to
directly and indirectly benefit all four target lenses. Using HOMER, cost estimates for meeting
the energy demands of a CoolBot were modeled for three energy systems: solar photovoltaic
(PV), a diesel generator, and a hybrid of the two. Results show that in spite of the high capital
cost, PV offers the lowest levelized cost of $0.20/kWh. Understanding the cost of coolroom
financing as well as the incentive structure of agricultural supply chains, two possible financial
instruments have been proposed. Given the substantial capital and operating costs of the
CoolBot, as well as the financial and technical education needed, we have proposed that
microfinance institutions or NGOs specializing in rural asset financing and education are needed
in order to aggregate growers and assist them through the learning curve in the initial stages. In
order to reach long term financial sustainability, we identified forward contracts as an
appropriate instrument that both engages smallholder farmers as well as leverages incentives
across the supply chain.
3
Cool Chain Analysis, Kenya
I. Introduction
The agricultural sector in Kenya provides income for over 75% of the population and
generates nearly 30% of the nation’s GDP (CIA), but it is estimated that greater than 30% of
produce is lost to spoilage before it reaches consumers (ICIPE). The loss is driven by many
factors whose relative contributions are difficult to quantify, but include: appropriate handling
and post-harvest practices, counter-productive policies - such as applying levies per package,
rather than by weight, which encourages use of large bags and overfilling (personal
communication, Crump) - and lack of access to cold storage across the supply chain.
Unfortunately, this key labor sector lacks the training and resources needed to manage
postharvest loss. As a result farmers must sell their produce immediately after harvest,
weakening their ability to negotiate prices and resulting in inconsistent and suboptimal income.
Issues of postharvest loss extend beyond the farmgate and exist at every step throughout the cool
chain. Within this dilemma exists opportunity in the horticultural sector in Kenya. Addressing
the causes of postharvest loss will enhance profits for farmers, increase consumer access to
nutritious foods, and reduce the environmental impact of the agricultural sector. The benefits of
improved post harvest management extend beyond the direct economic impact and can
contribute to overall social and economic welfare in a variety of ways; many benefits are
unpredictable and others too complex to accurately calculate, but will be discussed qualitatively
in this report.
Researchers at the University of Nairobi, in collaboration with the Horticulture
Collaborative Research Support Program (Hort CRSP) at UC Davis have begun a feasibility
study on using a low cost cooling system known as the CoolBot to reduce post harvest loss at its
most vulnerable stage, immediately after harvest. The proposed innovation seeks to address the
challenges at the farmgate of the horticultural commodities value chain. While preliminary
testing may prove feasibility, strategies for scaling up and out will need to be explored to ensure
benefits are realized outside of the testing phase.
There are two main objectives for our Cool Chain Analysis project. First, we will assist
HortCRSP in better quantifying the capital and operating costs of a CoolBot cold storage system
for rural farmers in the Nyanza province of western Kenya. With these costs and constraints in
mind, we will also propose different financing schemes and instruments that can be employed for
commercialization.
II. Background
Agribusiness
In Africa, agribusiness input supply; processing, marketing, and retailing add about 20%
of GDP (World Bank, 2013). In terms of output, a significant share of Africa’s agricultural
output is made up of bulky, perishable crops that are non-tradable in unprocessed form. Some of
the policy interventions needed include investment in infrastructure (e.g., roads, electricity,
communications, and water) to support rural processing zones in rural towns. In general, these
investments are huge, which often makes them suitable for public–private partnerships given the
severe constraints on public–sector resources and capacity (World Bank, 2013). Lack of finance
4
Cool Chain Analysis, Kenya
is recognized widely as a perennial constraint to agribusinesses development. Formal lending to
agriculture is limited severely by agriculture’s seasonality and high risk, the absence of formal
land titles, the heterogeneity of agriculture across commodities and regions, and bankers’
inexperience with agribusiness (World Bank, 2013). Potential government intervention in the
financing for businesses and reduction of tariffs on processing equipment to promote
agribusiness development would be substantial. Policies that support entrepreneurship, highquality products, grades and standards, and certification of farmers are also important in
promoting agricultural marketing on the continent.
Supermarkets- A Potential Opportunity
Supermarkets currently account for less than 5% of fresh fruits and vegetable sales even
in Nairobi. We anticipate that supermarket chains’ fresh fruit and vegetable market share will lie
between 10% and 20% in 10 years time [Tschirley]. As supermarkets are the predominant user of
cooling technology (see Chart 1, Postharvest loss Prevention Method) and the projection of
supermarket sales of fresh horticulture is set to rise dramatically over the next decade, this means
a possible intervention with a CoolBot technology could be beneficial for many rural farmers in
the Nyanza province. Further encouraging, supermarket prices were found to be 15% to 60%
higher than prices for comparable products in traditional markets.
Chart 1. Postharvest Loss Prevention Method
Source: HortCRSP, 2013
Gender in Kenyan Agriculture
Women represent a large percentage of the workforce in the area in the context of
agriculture. The allocation of female labor to rural off-farm wage labor in emerging modern
agro-industries might have indirect effects on the allocation of household resources and as a
result on both women and children. This has a great deal of potential side effects, on the one
hand, the wage income generated by women might increase their decision power in the
household (Maertens). On the other hand, resources, including land, household labor and the
5
Cool Chain Analysis, Kenya
claim on income from other household farm and non-farm activities, might be taken away from
women working outside the home and the family farm. If one is serious about the development
of high-value agricultural trade as a strategy for poverty alleviation and inequality reduction,
there is a need for integrating insights on labor market effects of modern supply chains, including
gender aspects, in policy thinking. In addition, while female income is positively related with
spending on children’s’ education, the feminization of rural labor markets might have adverse
effects on the schooling of girls if they withdraw from school either to participate in the labor
market or to replace their mothers in household maintenance and child care activities (Maertens).
In addition there is a need for more empirical evidence on issues of gender discrimination
in rural labor markets. As Chart 2 shows, gender is highly polarized among occupation in the
area with in their sample, women exclusively working as urban market vendors and the
supermarket being dominated by men particularly the managers. This breakdown is nearly polar
in this study which means exclusively concentrating on supermarkets might have negative effects
on women who currently work selling produce.
Finally an unresolved issue is whether modern supply chains that are governed through
high standards, including labor standards, perform better in this respect than more traditional
chains, where often no labor standards are used or enforced.
Chart 2 Gender Across the Supply Chain
Source: HortCRSP, 2013
Energy Sector in Kenya
Energy Resources & Solar Market in Kenya
Though the CoolBot-controlled air conditioning system consumes less energy than
traditional refrigeration systems, providing refrigeration in a hot climate requires a relatively
large amount of electricity and farmers in the rural area targeted for this study are not likely to
have a connection to the utility grid. Understanding the state of development of the energy
6
Cool Chain Analysis, Kenya
sector in Kenya and an accurate assessment of appropriate energy sources will be critical to the
success of the CoolBot project in Kenya.
Kenya has among the world’s highest proportion of renewable primary energy in its
electricity generation profile. Large hydropower systems make up nearly 45% of total installed
capacity (CIA). An additional 13% of electricity is produced from other renewable sources
(CIA) including geothermal and cogeneration of bagasse in sugar factories across the country.
The remaining 42% is generated from fossil fuels such as heavy fuel oil and liquid petroleum gas,
with very minimal coal, which is used primarily for industrial purposes in Kenya, and no natural
gas is found in the electricity fuel mix.
In 2010, Kenya produced 7.33 billion kWh of electricity and had an installed generating
capacity of 1.7 million kW (CIA). With a population of roughly 44 million people, Kenya’s per
capita electricity consumption is 160 kWh as compared to 13,000 kWh per capita in the U.S.
Unfortunately, only 18% of households in Kenya are connected to the grid (Kiplagat et al.
2011), and therefore this relatively clean grid-electricity provides only around 6% of total energy
supply for all applications including residential and commercial heating, lighting, industrial
energy use, and transportation.
Figure 1 Energy Supply in Kenya
Source: Kingplat, 2011
Figure 1 shows the proportion of total energy supply. A report commissioned by the
Kenyan government published in 2008 reports that “The bulk of the population continued to
obtain their primary energy from biomass energy often obtained unsustainably tending to deplete
the resource base. It is estimated that over 89 % of the population depend on biomass.” (Kerea
2008).
Energy Consumption & Development Policies
The vast majority of energy consumption is for residential use. This is partially due to
the inefficiency of burning fuel-wood and charcoal for heating applications; if electricity was
available to more consumers, this same quantity of energy could be supplied via cogeneration
while depleting far fewer resources. For this reason, the Kenyan government has an aggressive
plan to expand access to grid electricity and increase total generation. New policies aim to
attract private investment to the energy sector and have already resulted in a new 90-MW heavy
fuel oil power plant (BWSC), and a 5-MW wind farm (Kiplagat 2011). The government aims to
greatly increase the capacity for bagasse cogeneration. Geothermal, hydropower, wind and solar
resource potentials have been well-quantified and are also likely candidates for expansion of
electrical capacity (Kerea 2008).
7
Cool Chain Analysis, Kenya
Agriculture is a very minor consumer of overall energy; the analysis by Kiplagat (2011)
further shows that only 1.82% of petroleum consumption in Kenya is for agricultural purposes.
This data indicates that although agriculture contributes more to GDP than any other single
sector of the economy, it is very low energy-intensive; hence its importance as the primary
source of income for Kenyans. The proposed technology, cold storage utilizing the CoolBot
technology, would not seek to replace manual labor, but rather to add value and resilience by
preserving crops. A well-developed cold chain could contribute significantly to demand for
energy service in the future.
Solar Resource and Market
Kenya is a prime candidate for solar energy as its equatorial position receives a high
amount of solar radiation year-round. The PVWATTS model created by the National Renewable
Energy Laboratory calculates an average insolation of 5.48 kWh/m2/day with a minimum of 4.94
in June. Kenyans are well-aware of this advantage: Kiplagat (2011) reported that “Kenya has the
world's highest household solar ownership rate with about 30,000 small (20–100 W, per
household) systems sold per year” and an estimated capacity of 6 MW in rural areas. Solar PV
costs have been dropping dramatically in the past few years as new raw material (silicon)
supplies and manufacturing have been developed in China. Ondraczek (2014) reports that
“based on actual technology costs and Kenya's solar resource, the LCOE from PV is estimated at
USD 0.21/kWh for the year 2011, with scenario results ranging from USD 0.17–0.30/kWh.” If
this price can be realized at the small scale required to operate a CoolBot, it will be cost
competitive with areas featuring grid-connectivity, as utility rates range from $0.18 to 0.24/kWh
plus fees where it is available in Kenya (Shah 2014). A competitive feed-in tariff of $0.20/kWh
is offered for small producers which improves the financial incentive to produce solar and other
small generation systems.
Finance Sector
Considerations in Financing Agricultural Supply Chains
Agriculture has been changing rapidly from one of fragmented production toward
integrated market systems, or value chains. Driven by economies of scale, globalization and new
consumer demands on quality and convenience, multinational corporations increasingly
dominate the sector. With this in mind, significant consideration is needed to analyze the effects
on small farmers that have the most to gain and lose in today’s rapidly changing agricultural and
economic environment.
Increasing smallholder participation in supply chains is a critical component in
understanding project scale. The high cost of conventional cold rooms is out of reach for
majority of smallholder farmers involved in horticultural production. However, as Figure 2
shows, intervening with temperature control early on in the supply chain offers the most benefit
to the market by extending the long-term shelf life of produce. Therefore, unique financing
structures will need to be employed in order leverage and balance incentives across the supply
chain.
8
Cool Chain Analysis, Kenya
Figure 2: Cool Chain Framework for Incentive-Compatible Analysis
Source: Author’s illustration
III. Methodology
Project Impact: 4 Lenses
Environmental
Some environmental benefits of reducing waste by providing access to preservation
technology can be expected in the form of conserved resources. Even without extensive use of
fertilizers, which cause eutrophication of water ecosystems, the conversion of land for
agricultural use can result in deforestation and habitat destruction. Preservation technology
indirectly translates to increased productivity, allowing the amount of food to meet demand to be
grown on fewer acres of land.
The burden of energy demand, however, could negate these gains, particularly if the
energy source is fossil in origin or from woodfuel as there is currently a biomass deficit (wood
and agricultural refuse is being combusted for heating at a rate that exceeds replacement). This
dependence on gathered wood causes deforestation, resulting in topsoil degradation, increased
flooding, and loss of biodiversity and contributes to global climate change by reducing the
forests which act as a carbon sink (Pisces).
The need for cooling technology is inherent. The current practice is to transport crops at
night or try and leave them in the shade. Ambient temperatures are well over 30° C in much of
Kenya which increases deterioration over 20 times of that of 0 °C (Class Lecture 01/2104). Low
temperatures reduce metabolic processes that incur spoilage from disease and ethylene, this
makes the prospect of cheap cooling technology very attractive.
9
Cool Chain Analysis, Kenya
Social
Many of the world’s poor rely on agriculture for their livelihood. Improvement of farmers’
access to markets has become a key element to in strategies to promote poverty reduction. The
majority of the farmers in Kenya sell directly at the farmgate, because transport to other markets
is too expensive and time consuming for them. Instead, brokers go to the farmers and purchase
what quality and quantity they need. Farmers do not have formal contracts with traders of other
buyers because they can’t assure the quantity and quality that is highly depending on the season.
As a consequence, farmers have really low negotiation power and alternatives, and they rarely
can decide with whom they want to collaborate with (SSejjemba). In addition, these brokers often
are very gender biased and will not negotiate or take on female clients for contracts it is observed
that less than 10% of female farmers in smallholder contract-farming schemes are in Kenya
(Maertens). This means that a transition to a modern supply chain made possible through cooling
systems would be associated with increased benefit for females who represent as much as 80%
of the farmers in Kenya. Understanding how to engage these stakeholders appropriately is an
important first step in financing agricultural value chains.
Collective action, such as farmer cooperatives or savings groups, is one way to reduce
transaction costs and improve coordination in production and marketing. These smallholder
farmer groups can pool resources to obtain access to equipment and transportation services
required for involvement in advanced supply chains. Collective action is valuable tool to use the
early stages of incorporating those outside of formalized agricultural value chains. Not only is
financial risk and benefits shared among members, collective action can increase social capital
on a local level and balance power and participation across the supply chain.
Economic
The impact of the introduction of a new technology can have unpredictable, far-reaching,
ripple effects on the market. A grant proposal written by Jane Ambuko of the University of
Nairobi HortCRSP’s project highlights the plight of farmers who currently produce low-value
grains – in part, because it is reliable and less prone to spoilage than vegetables, which require a
speedy, well-developed supply chain to reach markets in turnaround times as little as three days
before significant losses occur. Farming families who primarily produce grains still must buy
the staple vegetables they require for a healthy, diverse diet. Access to cold storage could enable
these small growers to produce new higher-value crops that previously would have been too
risky. The benefit of such access extends beyond the direct economic benefit to the consumer.
Since farmers are able to produce a higher value crop, this can lead to an increase in income that
can be directed to needed school fees, more purchases in the market and further investment into
their farm. All these expenditures can greatly benefit small farmer households as well as the
economy as a whole. Cool room storage will also allow growers to be more dynamic in the
market. Without post harvest management, farmers are forced to sell produce immediately after
harvest to reduce spoilage and optimize the volume of their crop sold. By prolonging the shelf
life and quality, growers can have time to find the best market prices. This can help stabilize
prices for stakeholders across the supply chain to the consumer.
Technological
Coolrom Construction/Costs
Cool room construction should be optimized through further research and
10
Cool Chain Analysis, Kenya
experimentation. The current materials setup consists of a 6’x8’x8’ room, an A-C unit, and we
ran three potential energy models through it: diesel, solar and a hybrid. We also found in Jane’s
proposal that the CoolBot itself would only cost $150 as opposed to $299 as the owner of the
company is eager and willing to partner with projects such as ours. With a more detailed analysis
of the cool room design up to date with the insulation material composed of the local agricultural
products further recommendations on size, layout and a formulation of a best-case scenario could
be offered. Insulation material can have a dramatic effect on the efficiency of the CoolBot
System and the size of the room may be heavily dependent on how much active storage space is
sacrificed for additional insulation.
Power Source
The three power sources for the CoolBot system evaluated in this paper are the use of
photovoltaic panels and an inverter, a gasoline generator, and a hybrid system. PV panels are a
very attractive option due to the availability of the grid in Kenya being at around 18%. The
economic feasibility of this project revealed for our testing that PV panels were the best value.
However, as the possible placement of the cold storage room changes from a rural to an urban
setting, the availability and price may greatly change. Careful protection of system components,
such as batteries and inverters, must be considered.
The use of a diesel generator is recommended instead of a gasoline generator. Although
this represents a higher initial cost, the maintenance cost is typically much lower and the
generator lifetime is significantly higher. Diesel generators have a typical capacity of 3-6 kW;
while this is greater than the power necessary to supply the air conditioning unit and the CoolBot,
the capability of powering other devices has social and economic implications that must be
considered for any system providing electricity.
Postharvest Handling Education
A very large component is to enable programs to properly educate farmers on handling
procedures. The biggest enemy in post-harvest management is in fact humidity control. It only
takes a small amount of water to reduce quality and potentially ruin a product. Even with using a
humidifier, the cold air in a cooler cannot hold as much water as warm air, meaning things are
going to dry out. Techniques to work against this include but are not limited to, covering storage
crates with a wet sheet that is regularly spritzed, or lining crates with garbage bags. This among
handling procedures are vital and without that component the implementation of a cool room
would be a waste of resources.
Energy Simulation Methodology
CoolBot2K - Cooling Demand Model
A previous D-Lab group (Pritoni et al. 2011) constructed a model to estimate energy
demand for a cold room system in Uganda; that model, called “CoolBot2,” was adapted for use
in this project. Input data required includes: the location and annual hours of peak sunlight of
our site and data on cool room construction in order to estimate heat transfer through the
insulated walls; daily temperature and humidity profiles in order to calculate an hourly profile of
the energy output required by the air conditioning unit. The daily weather data used was from
the hottest day in 2013 which occurred Feb 27, in order to simulate the maximum expected
energy demand. Appendix A and B show all data input to this model for the baseline scenario a
6’x8’x8’ cold room made of two sheets of corrugated tin enclosing 2 inches of (unknown type) insulation
11
Cool Chain Analysis, Kenya
material.
It should be noted that though the model appears to be capable of evaluating very detailed
properties of insulation and construction materials, the input cells for wall thickness and
conductivity are not used in the demand calculations; only wall and roof dimensions and R-value
are influential parameters. Due to the lack of specific information pertaining to the CoolBot
testing facilities that will be used by our partners in Nyanza, an R-value of 22 and 6x8
(recommended by the CoolBot manufacturer for use with a 10,000Btu/h A/C unit) was used in
the baseline scenario (other scenarios are described in Sensitivity Analyses section below).
Another important input assumption is the efficiency of the A/C; these are typically given as a
SEER index value and the conversion to coefficient of performance (COP) is shown in the model
spreadsheet.
The cost features built into CoolBot2 were not utilized to develop the cost results
contained in this report.
HOMER - The Micropower Optimization Model
The hourly energy profile generated by CoolBot2 was used to construct a load profile in
the Energy microgrid modeling software HOMER (Legacy version 2.68 beta, Feb 8, 2012). A
hybrid microgrid model was constructed in HOMER (see screenshot below, Figure 3.) featuring
a variable quantity of photovoltaic (PV) panels, a diesel generator (Generator1), batteries
(unlabeled), and an inverter (Converter) to convert the DC-generated current to AC for the air
conditioner (Primary Load 1). The components were connected as shown in Figure 3.
Figure 3. HOMER Scenario Hybrid_PV-Diesel_noGrid
Detailed input parameters for each component were as follows:
1. Primary Load 1
The hourly demand profile output by CoolBot2 was entered as a “January weekday” in HOMER, and the
default values for random variability were accepted: 15% Day-to-day and 20% Timestep-to-timestep.
The “Scaled Annual Average” was shown to be 14.2 kWh/d which corresponded with the calculations in
CoolBot2.
2. Solar Resource:
The study area location (0.67° S 34.78° E) was entered and HOMER retrieved climate data from the
internet. This data was verified by comparison to the PVWATTS online tool (NREL). The “Scaled
Annual Average” Radiation was shown to be 5.729 kWh/m2/d.
12
Cool Chain Analysis, Kenya
3. Solar PV Panels:
Inputs shown in screenshot provided in the chart below.
The price of solar panels in Kenya was cross-referenced with
several sources; Ondraczek (2014) reported that the capital
cost for a 10,000-kW PV system in Kenya was $2,500/kW,
with levelized COE of USD 0.21/kWh in 2011. Assuming
that the cost for a smaller system would be higher, we
initially accepted an older report of $2000/0.6 kW plus $1000
installation cost, the equivalent of $5000/kW including
installation. News reports (e.g. Standard Media UK, 2013)
were found claiming the price of solar panels has plummeted
40% over the past 3 years (since 2010), however none of
them reported an actual price or included references to
legitimate sources. Finally, an Alibaba search showed that a
4 kW PV system was available from a manufacturer in China
for $9,000. Recognizing that Kenya has a well-developed
solar market and supply chains must already exist, the $1000
installation estimate was applied. In addition to the inputs
shown in the figure to the left, an O&M cost of $10/year was
added to account for necessary cleaning (adopted from
Pritoni et al. 2011). The 0.66° slope was suggested by
HOMER (oriented to the equator); the 90° (west-facing)
Azimuth was chosen by comparing 0, 90, 180 and 270° and
selecting the direction that corresponded to maximum power
production. All other PV inputs were HOMER default
selections; No tracking system was selected, and the effect of
temperature was assumed to be accounted for by the derating
factor.
4. Generator
Although the load profile showed that the peak power
demand would be 2.2 kW, it was recognized that when configured with batteries and PV, it may be
possible to use a smaller generator merely for backup supply. Therefore, the model was allowed to select
the optimal generator capacity from an initial range of 0, 0.1, 0.5, 1.2 and 2.2 kW. It was initially
intended that this would be further optimized, but given the results (no generator necessary for lowest
COE), these choices were accepted without further exploration. An equipment search was conducted
using Alibaba.com, and found that suitable 2.2 kW generators with 1800 rpm (higher speeds tend to wear
out much more quickly) are available for $250. Installation was presumed to be minimal (no supporting
documentation) so a $100 estimate was applied. O&M cost of $0.2/hour was adopted from Pritoni et al.
(2011). HOMER’s default “Minimum load ratio” of 30% and efficiency curve were used, in addition to
the “lifetime operating hours” of 15,000 which was accepted after being found to correspond with
multiple claims by online forum users of diesel generators for rural home primary energy supply.
5. Batteries
A Kenyan company, Sollatek (2014) with an online store was used to price deep cycle batteries
specifically designed for use in solar PV systems. A 100 Ah, 12-V, 1.2 kWh battery was selected which
costs $158 each. The HOMER default value of 31,730 kWh lifetime throughput and all other default
properties were used. The model was instructed to consider quantities of 0, 1, 3, 6, 9, 12, 15, and 18.
6. Inverter
Very sparse research was conducted on the inverter properties and cost; the Pritoni et al. (2011) cost of
$400 was applied without confirmation, and all HOMER defaults (90% Efficiency, 15 year lifetime) were
13
Cool Chain Analysis, Kenya
accepted. The model was instructed to consider quantities of 0 and 5 kW (excess capacity).
7. Diesel Fuel
The current price of diesel $1.27/L (February 2014) was applied; no limit was placed on consumption and
the fuel properties (43.2 MJ/kg LHV; 820 kg/m3 density; 88% Carbon content; 0.33% Sulfur) were
unaltered from their HOMER default values.
Other Constraints and Sensitivity Parameters Explored in HOMER model
Maximum allowable annual capacity shortages of 0, 10 and 25% were evaluated. The CoolBot2
model was not designed to allow a range of temperature control, and therefore capacity shortage was used
as a proxy for a thermostat that will allow temperature to deviate from the set point.
Minimum renewable fractions of 0, 25, 50, 75 and 95% were initially explored, but results
showed this constraint to be unnecessary as the optimal result was consistently 100% renewable with no
such requirement.
V. Results & Recommendations
Energy Demand Simulation Results (CoolBot2K)
The version of the CoolBot2 model used to generate the results in this report, and including
sample output from HOMER, is available to collaborators through the links provided in the References
section of this report. Various estimates of energy demand were made based on the temperature and
humidity profile of the hottest day of 2013 (Feb 27) in Kisumu, Kenya and the input assumptions stated in
the Methodology section and found in the Appendix; details on other scenarios are briefly described
below in the Sensitivity Analyses section. The graph in Figure 4 shows the output from the
CoolBot2K model for the baseline scenario.
Figure 4. Sample daily input power required by SEER 9 air conditioner to cool 6x8x8’ room.
It should be noted that the CoolBot2 model does not account for thermal loads stored inside the
room; Jim Thompson cautions that the heat from the produce itself may be more significant than the heat
14
Cool Chain Analysis, Kenya
transfer that occurs through walls (personal communication, 3/13/2014). The CoolBot2 model also does
not account for heat lost from an open doorway, therefore care should be taken to ensure that loading and
unloading occurs in cooler periods of the day. Finally, an overall insulation R-value of 22 h ft2 °F/Btu was
used along with the assumption of a 6x8x8 ft room; results under other conditions could vary
considerably from this estimate.
Energy Demand Simulation Results (HOMER)
Using the configuration and input parameters described in detail in the Methodology section, an
optimal system was configured with levelized cost of electricity (LCOE) of 0.178$/kWh. If achievable,
this is exceptionally competitive with the lowest grid price currently available in Kenya. The system
features 3 kW of PV capacity, a single battery, and inverter connected to the air conditioning unit; the
addition of a diesel generator was not found to contribute to lower cost under these input assumptions. If
cost assumptions are accurate, the energy system should require $8,058 in capital and over the 25 year
lifetime of the project, users should expect to pay $0.18/kWh produced with a net present cost of $9,299.
With this system, the user should expect up to 21% shortage, or the equivalent of 1,093 kWh/year unmet
load; however, the addition of 2 extra batteries will reduce the unmet load to 17% and increase LCOE by
only a fraction of a cent (0.179$/kWh). This scenario was unconstrained by any requirement to be
renewable - HOMER simply found that the capital investment is worth the long term operating cost of
fuel. Given the annual fuel cost, $2542/year, of a system run entirely by diesel, we can show
simplistically that the PV system’s payback is less than 4 years (4 x $2542 > $8,058). [Note that this fuel
cost is applies to a system with 0% annual capacity shortage].
The top six lowest LCOE systems all require no diesel generator, feature 3 to 4 kW of PV, and
offer an LCOE of no more than 0.20$/kWh. The top eight results for this scenario are shown in Table X.
Table 1. Top Results for HOMER Scenario 1 (PV-Diesel Hybrid, No grid; R-22 6x8x8-ft load, 25%
allowable capacity shortage)
15
Cool Chain Analysis, Kenya
Sensitivity Analyses and Recommendations for Future Work
Other scenarios were run to explore the robustness of the analysis as well as to provide our partners with
additional perspective and alternatives:
i. PV Cost $5,000/kW
The cost of solar panels is an uncertain and important parameter. In the interest of
evaluating the sensitivity of these results to the cost of PV, scenarios were run with double the
assumed cost per kW. At $5,000/kW (generator and fuel cost held constant), the top three results
were again 100% renewable-powered systems. In these results, the lowest LCOE system featured
4 kW of PV and 6 batteries with an LCOE of 0.387$/kWh and capital cost of $23,700. The
fourth-cheapest result employed a generator, but only to produce 20% of the required load; in
addition to a generator the fourth result requires 3 kW PV, 6 batteries, has an LCOE of
0.429$/kWh and no capacity shortage. These results may also be further explored in the
CoolBot2K spreadsheet. The 20th result is the first to propose no PV panels; it features an
attractively low capital cost of less than $1700, but a net present cost over the life of the project of
$42,500.
ii. Half-sized Coolroom
Another scenario was run with a room made of the same materials but of dimensions
3x4x8 ft. In this case smaller PV panel and generator sizes were included in the search space
(minimum 100 W). As would be expected, the energy input required was lower (9 kWh/day and
peak power 1.5 kW, compared to 14 kWh/d and 2.2 kW in the 6x8x8 ft room). The optimal
result in this scenario featured 2 kW of solar and one battery; no diesel; a 16% capacity shortage;
LCOE of 0.18$/kWh and $5,600 capital investment, $6,500 NPC over the 25-year lifetime.
Larger room sizes were not explored during this project. This is another important area
for consideration in future work; transportation of goods to an aggregation site for cold storage
may not make logistical sense for most crops with short storage periods. Room size should be
optimized for both energy efficiency and logistical efficiency.
iii. R-value = 44 h ft2 °F/Btu
An interesting area for future work would be to evaluate the cost tradeoff of additional investment
in insulation material relative to energy cost. By doubling the R-value of insulation to R=44, the
impact on cost of energy supply was explored. As with room size reduction, this design choice
dramatically affects the energy demand by slowing the transfer of heat into the room and
maintaing cool temperatures with less A/C activity; energy demand decreases to 7.6 kWh/day and
1.2 kW peak in this scenario. The optimal result features LCOE 0.191$/kWh and capital
investment cost of $5,600 using 2 kW PV, no generator, and one battery; capacity shortage is 6%.
iv. Project Lifetime = 5 years
The final scenario entertained was an economic variable, project lifetime. In all previous
scenarios, cost was evaluated with a lifetime of 25 years. This variable has a significant effect on
LCOE, as far fewer kWh are produced given the same investment; however, HOMER also
accounts for the salvage value of equipment. The optimal results again were found to have no
generator; 3 to 4 kW of PV, 1 to 3 batteries, of LCOE of 0.234-0.253$/kWh. While initial capital
remained proportional to earlier results (3 kW => $8,058), the net present cost was $4,000-5,500
due to salvage value reclaimed. Annual operating costs in this scenario were negative, again
reflecting utility for 5 years followed by reclamation of equipment value.
16
Cool Chain Analysis, Kenya
Recommendations for Commercialization
The diversity of constraints, energy scenarios and significant costs associated with
CoolBot installation in Nyanza are important considerations when exploring financial
instruments available for commercialization. Furthermore, the agricultural supply chain in
which we seek to engage in adds yet another level of complexity. While there are several
financial tools available to finance agricultural value chains, each tool is appropriate at different
stages when advancing informal agricultural value chains for smallholder farmers. We will
propose two tools that best engage the smallholder farmer as well as comply with incentives
across the supply chain. The first, microfinancing with assistance, can initiate smallholder
participation in post harvest management. Secondly, in order to sustain long term financial
feasibility, a complementary instrument known as forward contracts can be employed beyond
initial stages.
Initiating Smallholder Farmer Engagement
Judhi Kilmo, a microfinance institution (MFI) in Kenya, has recognized the unique
structure and opportunity in rural asset financing for smallholder farmers in Western Kenya.
This MFI provides not only capital, but also technical assistance that helps the entrepreneur
acquire the knowledge and skills needed to scale up and succeed. They offer lower interest rates,
staggered payments, and longer repayment periods that align with the client's sales performance1.
Juhudi’s model is an appropriate tool for financing post harvest storage facilities for smallholder
farmers that are unintegrated in formal agricultural markets and require more than venture capital.
Due to the significant startup and operational costs of the cool room, this model will require
significant farmer aggregation in order to repay the initial loan, manage the cool room, and
sustain profits beyond repayment. Additionally, sufficient financial and technical education is
needed in order to ensure growers can maintain control of their crop and cool room. An MFI
like Juhudi can become a vital player in assisting grower adoption of sound business practices in
the nascent stages of new post harvest management practices. We also believe that Store-It-Cold
(CoolBot supplier), a stakeholder with significant interest in project success, can be a valuable
asset in technical education for post harvest managers in smallholder farmer groups. They may
also have insight on proper business management or organization of coolroom operations.
Given the unique cultural and temperate conditions in Nyanza, further analysis is needed
in order to truly understand ideal interventions and approaches that can initiate smallholder
farmer engagement. Local knowledge and more research specific to the region is needed to
ensure suitable interventions for farmer aggregation as well as appropriate financial management
strategies of the CoolBot. Since such information is unavailable within the scope of our project,
further analysis has been given to understanding long term financial strategies that are selfsustaining, engage smallholder farmer groups and comply with financial incentives for
stakeholders across the supply chain.
Formalizing Smallholder Participation
In communities where smallholder farmers are formally organized, more sophisticated
models can be used to integrate and advance the value chain with incentive-compatible financing
structures in mind. These tools can be more complex, however they can also stabilize prices,
1
http://www.juhudikilimo.com/
17
Cool Chain Analysis, Kenya
reduce risks and the cost of financing2. The instrument most applicable to our client that
maintains smallholder engagement as well as incentive-compatibility is forward contracts.
Forward contracts obligate the parties involved to buy or sell certain amount of horticultural crop
at an established price and future date. Ideally, the parameters of the agreement are determined
by both the producer and buyer prior to a crop planting to ensure optimal planning.
As Figure 5 shows, these contracts can be used as a finance tool in two different ways.
First, they can be used as collateral to a bank or MFI when smallholder group requests a large
amount of capital. Since these contracts include the promise and timeline of income generation,
loans based on this collateral can be tailored to the clients need and cyclical income.
Alternatively, instead of an MFI or bank, the buyer can advance the funds to the grower as initial
capital. The grower can then repay in kind at resulting delivery, or in cash as agreed upon in the
contract.
Governments and NGOs can play an important role in this process as well. Significant
farmer education is needed to adapt to the technical and financial requirements of smallholder
groups as well as new post harvest handling and storing protocol. NGOs can play a key role in
easing smallholder farmers through this learning curve. They can also provide important seed
capital needed for farmer aggregation as well as cool room installation. Governments can also
provide guarantee funds in order to insure contracts in the initial establishment of forward
contracts. Once markets mature, governments should ensure these contracts are fairly negotiated
and fulfilled.
Figure 5. Forward Contract Analysis
Source: Author’s Illustration
2
Jones, Linda and Miller, Calvin, Agricultural Value Chain Finance, FAO, 2010.
2
18
Cool Chain Analysis, Kenya
Forward contracts reduce risk to both buyers and sellers, stabilize prices and also encourage
efficient markets. They are a viable tool in post harvest management as it can balance risk and incentives
of both parties involved. However, there are drawbacks to this model. First, it requires reliable market
information to ensure fair contracts are established. Fortunately, the spread of Information and
Communication Technology (ICT) in Kenya has allowed for companies like M-Farm to offer daily
market prices via text message to a broad network of growers and distributors. Another limitation of this
model includes the need for standardized commodity requirements by grade and quality. In order for
forward contracts to be fairly established and fulfilled, there must be industry agreement and government
regulation on these standards.
VI. Conclusion
This project represents only part of a much larger problem. We hope that our findings
using the Homer Model and the Forward Contract Model would be useful in terms of
establishing some parameters for coolbot testing and long term feasibility in Nyanza. Through
our evaluators and research, we have considered our models may in fact have on-site costs that
are much cheaper than our current figures because of the possibility of saving energy through
powering the system off during the night when it is cooler, for this reason further models need to
be made testing this reduced cost. In the earliest stages of our project, HortCrsp suggested to
only consider tomatoes, french beans, cabbage, potatoes and kale. Our suggestion is to refine this
list to find which crops will actually be the most appropriate and feasible. Beyond the
constraints and limitations previously discussed in our energy model, several other
considerations for implementation should be made:
● It would be beneficial to find crops that present a high-to-intermediate demand growth,
offering the poor an opportunity for smallholder farmers to gain or retain a market share.
● While medium and larger scale operations can benefit from economies of scale as well
as better access to credit, there may be products offering smallholders a competitive
advantage.
● Additional information is needed on how initiate farmer aggregation specific to our
target region and what financial structures can be established to maintain collective
action.
● Farmer willingness-to-pay and adapt to new technologies is also unknown.
Understanding how to educate growers on the benefits of post harvest management will
be an important consideration before implementation
● A very large component of this product that we did not speak enough to will be the
impact that new cooling technology has on both rural and urban women. Since the cold
storage building is communally-owned, the relationships between farmers utilizing the
building is key. While men are typical the landowner and engage in more formal
agreements, women are the farmers. How will this dynamic playout in collective action
within the smallholder groups as well as between the group and buyers?
● Finally, women tend to produce crops for home consumption, while men tend to
produce cash crops which the CoolBot system is planned towards.
The CoolBot cold storage system is a potentially very useful tool to reduce postharvest losses of
horticultural crops. This technology’s success is not possible without making careful
considerations of many factors including power supply options, financing options, along with
understanding current market conditions in the country.
19
Cool Chain Analysis, Kenya
References
Link to CoolBot2K model:
https://docs.google.com/spreadsheet/ccc?key=0AiyzdCi5Vwt8dFRjSHQwZHlSejNwRW0tanlY
RXdyQWc&usp=sharing
Link to HOMER files:
https://www.dropbox.com/sh/npodz31c94475lm/qaqWK5c7hf
1. Africa Agriculture Status Report: Focus on Staple Crops. Nairobi, Kenya. Alliance for a Green
Revolution in Africa (AGRA). 2013.
2. CIA. The World Factbook 2013-14 Kenya. Washington, DC: Central Intelligence Agency,
2013. Retrieved 30 Jan 2014 from https://www.cia.gov/library/publications/the-worldfactbook/index.html
3. Fengler, Wolfgang. "News." Demographic Transition and Growth in Kenya. World Bank, 28
Apr. 2010. Web. 10 Mar. 2014.
4.Fischer, Elisabeth and Qaim, Matin, (2010), Linking Smallholders to Markets: Determinants
and Impacts of Farmer Collective Action in Kenya, No 48, Courant Research Centre: Poverty,
Equity and Growth - Discussion Papers, Courant Research Centre PEG
5. HortCRSP. Technologies for horticultural development: CoolBot provides inexpensive,
effective cooling. Retrieved 30 Jan 2014 from
http://hortcrsp.ucdavis.edu/main/media%20page/technologies_CoolBot.pdf
6. K.F. SSejjemba (2008) Value chain analysis. Maastricht School of Management
7. Kiplagat, J. K., Wang, R. Z., & Li, T. X. (2011). Renewable energy in Kenya: Resource
potential and status of exploitation. Renewable and Sustainable Energy Reviews, 15(6), 29602973. doi: http://dx.doi.org/10.1016/j.rser.2011.03.023
8.Maertens, Miet. "Pathways out of Poverty." Are African High-value Horticulture Supply
Chains Bearers of Gender Inequality? (2009): n. pag. FAO.org. Web. 14 Mar. 2014.
9. Nigigi, Margaret, and Nicholas Minot. "Are Horticultural Exports a Replicable Success Story?
Evidence from Kenya and CÙte DíIvoire." Ifpri.org. International Food Policy Research Institute,
2004. Web. 12 Mar. 2014.
10. NREL. PVWATTS model. National Renewable Energy Laboratory, Golden, CO. Accessed
09 Feb 2014 from
http://rredc.nrel.gov/solar/calculators/pvwatts/version1/International/pvwattsv1_intl.cgi
20
Cool Chain Analysis, Kenya
11. Nzila, C., Dewulf, J., Spanjers, H., Tuigong, D., Kiriamiti, H., & van Langenhove, H. (2012).
Multi criteria sustainability assessment of biogas production in Kenya. Applied Energy, 93(0),
496-506. doi: http://dx.doi.org/10.1016/j.apenergy.2011.12.020
12. Ondraczek, J. (2014). Are we there yet? Improving solar PV economics and power planning
in developing countries: The case of Kenya. Renewable and Sustainable Energy Reviews, 30(0),
604-615. doi: http://dx.doi.org/10.1016/j.rser.2013.10.010
13. Pisces (2013). How Bioenergy Can Help Local Communities Adapt to Climate Change:
Lessons from Nyanza Province, Kenya. Prepared for PISCES by the University of Edinburgh
April 2013.
14. Pritoni, M., DeForest, W., Hoy, B., & Rundquist, A. 2011. CoolBot2 cooling demand model.
D-Lab Uganda CoolBot Team.
15. Reuters. (2013). Kenya energy regulator cuts electricity tariffs Retrieved 12 Feb 2014 from
http://www.reuters.com/article/2013/11/19/kenya-electricity-idUSL5N0J41WJ20131119
16. Shah, Samir (2014). Electricity costs in Kenya Retrieved 12 Feb 2014 from
http://rayofsolaris.net/misc/kenya-electricity/
17. Sollatek. 2014. Online store. Accessed 03 March 2014 from
http://www.sollatek.co.ke/product/100AHsolarbattery/
18. Standard Media UK. Dec 20, 2013 “Solar Technology Uptake Lowers Price of Panels by
40%.” Accessed 09 Mar 2014
19. Thomas Koenig, et al (2008) Market-driven development and poverty reduction: A value
chain analysis of fresh vegetables in Kenya and Tanzania
20. Tschirley David, and Muendo Kavoi. Tegemeo Institute of Agricultural Policy and
Development. N.p.: Ergeton University, n.d. Tegemeo Institute of Agricultural Policy and
Development. Web. 14 Mar. 2014.
21.World Bank, UNSC, . (2012): Action Plan of the Global Strategy to Improve Agricultural and
Rural Statistics for Food Security, Sustainable Agriculture, and Rural Development.
21
Cool Chain Analysis, Kenya
VI. Appendix
Appendix A. Coldroom Characteristics Input to CoolBot2K
**Shaded box indicates that CoolBot2 default value was accepted.
Appendix B. Local Climate Inputs to CoolBot2K
22
Cool Chain Analysis, Kenya
Appendix C: Four Lenses Considerations
Environmental
Technological
Social
Economic
Pollution/GHG
Avoided fertilizereutrophication and
emissions
Resources:
A/C Unit, 6x8
Room
Solar-Diesel
Hybrid Energy
System
Employment: Offer
jobs to youth and
women (Accounts for
80% of farming
population).
Protection from Market
Variability: Farmers are
protected from erratic prices
Performance
Metrics:
Reduced Waste
Improved
Efficiency
Gender Equality: A
shift to a modern
supply-chain with high
value crops is
associated with the
benefit of rural women
and reduced gender
inequalities.
Surplus Product: For Fruit
and Vegetable Prices and
increase year-round access
with a surplus produced.
Renewable Energy
Generation:
Decrease dependence
on wood fuel
consumption.
Production
Cost:
• $299 CoolBot
• $700 Air
conditioner
• $2,000
Insulated room
•Coolbot
website: $200
Electricity
costs/month
D-Lab estimate:
$85 - 160/month
(COE solar)
Cooperative Farming:
Creation of new
cooperatives his which
in many cases have had
increased value of the
products via adopted
practices of washing,
packaging, storing
and/or transport.
Increased income for
farmers increases demand for
other local goods. Improves
ability to negotiate for high
prices at farm gate. Potential
gains from organization of
Farmer Cooperatives.
Reduced
Spoilage:Low
temperatures reduce
metabolic processes
that incur spoilage
from disease and
ethylene
New Handling
Procedures:
Will be
instituted to help
insure higher
quality product.
Improved
Productivity
Reduce labor hours
wasted
Business Model is repeatable
in other locations with
CoolBot technology and
price.
Land use:
deforestation and
habitat destruction for
agriculture reduced by
better management of
existing cropland.
23
Appendix D: Stakeholder Analysis
STAKEHOLDER ANALYSIS: COOL CHAIN ANALYSIS, KENYA
Project
Impact on
interests
(1-10)
Importance
Degree
of SH for
of
success of
influence
project
Stakeholder Groups
Role in Project
Interests at
stake in relation
to project
Smallholder Farmers in
Nyanza
Complete training in
new postharvest
handling, cooperative
organization and cool
storage/supply chain
management
Livelihood, health
& welfare
10
Very
Very
Project ID, Preparation &
Appraisal, Implementation,
Supervision, M&E
University of Nairobi
PI/Project Champion
for feasibility of post
harvest solutions
Successful
development &
deployment of
research
8
Very
Significant
Project ID, Preparation and
Appraisal, Implementation,
Supervision , M&E
6
Some
Moderate
Supervision, M&E
7
Very
Significant
Preparation & Appraisal,
Implementation
6
Very
Moderate
Preparation & Appraisal,
Supervision, M&E
Jomo Kenyatta
University of
Agriculture and
Technology
Spearhead studies on
postharvest quality
evaluation
Store-It-Cold
Offer product at 50%
of price and will
provide guidance on
business development
HortCRSP/USAID
Technical support to
field staff. Building
relationships with
possible partner
organizations. Support
in survey design and
analysis.
Build current data
set on &
understand of
postharvest crop
quality
New market
development,
social objectives,
testing in new
climate
Carryout mission
and objectives as
an organization
Stage in project process
Cool Chain Analysis, Kenya
Private Sector &
Entrepreneurs
Kenyan Government
Local Opinion Leaders
Kenyan Youth
Kenyan Women
Early adopters, share
risk and build market
Support social,
economic and political
agendas that influence
project success (ex:
regulation of formal
contracts and
horticultural quality
standards)
Support project in
local areas and
encourage adoption
Engage in new
postharvest handling
strategies and take
leading role in
coolroom and supply
chain management
Engage in new
postharvest handling
strategies and take
leading role in
coolroom and supply
chain management
Profit from an
emerging market
7
Somewhat
Significant
Project ID, Implementation,
Evaluation
Obligation to
society, social and
economic
development of
Kenya
5
Some
Some
Implementation, Evaluation
Stronger
community, more
produce available
for consumption,
more income
7
Significant
Moderate
Project Identification,
Preparation and Appraisal,
Implementation, Evaluation
Profitable
enterprise
opportunity, will
not have to migrate
to urban areas
8
Moderate
Moderate
Implementation, Evaluation
Opportunity to
move from
subsistence to
profitable farming
operations,
leadership
9
Significant
Significant
Implementation, Evaluation