The Modi Research Group’s New York City Energy Mapping Project based on this study  was jointly presented by Professor Vijay Modi and PhD student, Bianca Howard at the NorthEast Clean Heat and Power Initiative conference. The interactive map represents the total annual building energy consumption at the block level and at the taxlot level for New York City, and is expressed in kilowatt hours (kWh) per square meter of land area. The data comes from a mathematical model based on statistics, not private information from utilities, to estimate the annual energy consumption values of buildings throughout the five boroughs. To see the break down of the type of energy being used, for which purpose and in what quantity, hover over or click on a block or taxlot. The map has recently been featured in various news article sources like NYTimes, WSJ and CNET.

Check out the interactive map below.

In April, Ayse Selin Kocaman, a Ph.D. student in the Modi Research Group, was awarded with first place in the 2011 Production and Operations Management Society (POMS) College of Sustainable  Operations Ph.D. Proposal Award Competition with her dissertation titled “Connecting People to Electricity- Single Level and Multi-Level Grid Network Design for Rural Electrification.”

In a technological landscape that is altered by emergence of off-grid and distributed approaches, there is a need amongst infrastructure planners to evaluate the costs of networked approaches vis a vis off-grid approaches and to make rapid assessment of the progress in rural electrification. However, it is not easy to estimate the cost of networked infrastructure taking into account both the spatial distribution of demand and the optimal placement of infrastructure to meet that demand. Through its algorithms, Selin’s proposal can enable the tools that allow planners to make assessments about networked infrastructure rapidly and accurately.

The first heuristic algorithm, Selin proposes, provides a quick solution for the partial electrification problem where the grid network can only connect pre-specified number of households with low voltage lines. It also, helps understanding the effect of household settlement patterns on the electrification cost. Moreover, she describes the first multi-level heuristic algorithm that can simultaneously select the locations and service areas of transformers without requiring candidate locations and builds network in both medium voltage and low voltage levels in a power distribution system. The algorithm minimizes overall infrastructure costs while considering the cost of the transformer, the costs of building out low voltage line downstream
towards the spatially distributed demand and medium voltage line upstream towards the source.

The algorithms have been applied to real world rural settings in Africa, where household locations digitized from satellite imagery are prescribed. Results shows that the algorithms provide stable network designs with realistic values and they can be used as powerful tools by planners to rapidly estimate the cost of installing a distribution system.

• Survey instrument for overall energy planning: Energy Investigation
• Guide for energy investigation (English): Energy Investigation Guide (english)
• Guide for energy investigation (French): Energy Investigation Guide (french)

Rural electrification is critical to poverty reduction and underlies the achievement of many of the Millennium Development Goals in sub-Saharan Africa including objectives related to health, education, agriculture, environmental sustainability and gender equality. In many countries, rural electrification rates have remained in the single digits, leaving households to rely on expensive and inefficient fuel-based lighting, disposable batteries, and limited access to power for mobile phone recharging. Programs to extend national electricity grids have often lacked systematic planning to account for population distribution, the needs of social institutions such as rural schools and health centers, and the potential for off-grid or decentralized systems such as solar photovoltaics to cost-effectively serve remote and sparsely populated areas. Coordination across sectors, a national perspective, incorporation of a range of off-grid technologies, and a longer planning horizon (e.g. 10 years or more) are needed to rapidly and cost-effectively scale-up rural access to electricity.

The Modi Research Group at the Earth Institute at Columbia University has developed an electricity planning and investment costing model to support national efforts to expand electricity access. This Python-based tool performs spatial processing and analysis, using simple geospatial and population data, and algorithmically generates a comprehensive and cost-optimized electricity plan, including a map of the projected grid extension grid, sites to be served by off-grid technologies, and all related costs. The model has been applied in Senegal and Kenya, and has generated interest among energy planners in ministries, utility companies, and international organizations. The project has been supported by the Bill & Melinda Gates Foundation and the World Bank’s Africa Energy Group.

The project team consists of graduate students and staff with expertise in economic development and energy policy, as well as skills in GIS analysis, and computer programming.

Related Papers/Documents:

National Electricity Planning in Kenya

CU Energy Group Report to the World Bank on Senegal

National Electricity Planning in Senegal

Contact researchers:

Edwin Adkins:  jea98@columbia.edu

Selin Kocaman: ask2170@columbia.edu

Roy H. Han: rhh2109@columbia.edu

ABSTRACT

To achieve the Millennium Development Goals (MDG’s), all households in sub-Saharan Africa will
need to have access to basic infrastructure services. The challenge in meeting this goal is in
bringing this access while simultaneously driving down the costs. With an understanding of cost
drivers and the implications of achieving scale it becomes possible to plan a pathway to
successful infrastructure services access expansion. The analysis presented in this paper
addresses the issue of local and national electricity distribution planning in Senegal using a
model that identifies cost drivers of targeted electrification, providing useful policy guidance to
both national and local planners. A sensitivity analysis was conducted to capture connection
cost and coverage (access) variations as a function of demand, fuel, and policy uncertainties.
The local (an area of 400 sq km in northern Senegal) and national case studies of Senegal yields
the following key results. For both case studies, a high percentage (20-50%) of the currently
non-electrified population live in areas where grid expansion is more cost favorable than the
decentralized energy supply technologies. Expansion outcomes (costs and access) are very
sensitive to demand levels and capital cost of Medium Voltage lines and transformers.

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- National Electricity Planning in Senegal

Success in an infrastructure project depends as much on local support and participation as it does on coordination between politicians, financiers and utilities (Tufte and Mefalopulos 2009). We wanted to create a freely accessible tool for non-technical people to experience the infrastructure planning process and see the impact of different decisions on the community. By experimenting first-hand with web-based software, a user can understand on a map how changes in population, pricing and fiscal policy influence where infrastructure is built, who will get access and why different technologies such as off-grid solar, mini-grid diesel or bio-diesel and grid affect cost.

Our lab combined technical expertise from remote sensing, operations research and electrical engineering into an easy-to-use system so that local leaders, politicians, financiers and utility owners can focus on communicating visually and negotiating between different electrification scenarios.

• Local leaders: Will the construction affect my community?
• Politicians: How many businesses and households in my district will get access?
• Financiers: What are the risk and return on investment?
• Utility owners: Is it technically and financially feasible?

Where do people live?
The remote sensing component finds where people live using image recognition on satellite imagery.

Results from the remote sensing component provide a spatial census, enabling us to estimate population density and spread with reasonable accuracy. Different settlement patterns hint at different electrification strategies: sparsely distributed clusters as in Ghana or Mali are good candidates for off-grid technologies such as solar, while larger clusters as in Tanzania justify diesel mini-grids and densely packed Kenya find grid electrification to be cost-effective (Zvoleff, Kocaman, Huh, Modi 2009).

The command-line software to perform remote sensing was completed in 2008. We are in the process of optimizing the software to run on graphical processing units (GPUs) to make the system accessible via web.

How can we provide access to electricity?
The econometric and operations research component uses demographics and pricing models to project electricity demand, cost and placement (Parshall, Pillai, Mohan, Sanoh, Modi 2009). Users can freely explore what-if scenarios by changing the many parameters and see on a map what technology makes sense for each community, where and how much it will cost.

We have created a web-based prototype of the infrastructure planning component that is being used this semester by students of the Master’s in Development Practice program at Columbia University. We are currently improving the map-based user interface and you will be able to use it through your browser soon.

The power of open source software
Both systems are built entirely using open source components such as Python, GDAL, GEOS, Lush, OpenLayers and AMQP.

References

Alex Zvoleff, Ayse Selin Kocaman, Tim Huh, Vijay Modi. (2009) “The impact of geography on energy infrastructure cost.” Energy Policy, 37, 4066-4078. [link]

Lily Parshall, Dana Pillai, Shashank Mohan, Aly Sanoh, Vijay Modi (2009) “National electricity planning in settings with low pre-existing grid coverage: development of a spatial model and case study of Kenya.” Energy Policy, 37, 2395-2410. [link]

Pedro Sanchez et al. (2007) “The African Millennium Villages.” Proceedings of the National Academy of Sciences 104 (43). [link]

Thomas Tufte, Paolo Mefalopulos (2009) Participatory communication – a practical guide. World Bank Working Paper. [link]

Talks

How Python is guiding infrastructure construction in Africa
PyCon Atlanta
February 20, 2010 [video]

The impact of geography on energy infrastructure cost
Millennium Villages Student Research Showcase
February 18, 2009 [video]

Automatically finding houses in rural satellite images with multiband convolutional neural networks
Millennium Villages Student Research Showcase
February 18, 2009 [video]

Finding and connecting people in Africa to infrastructure using remote sensing and geospatial optimization
O’Reilly Where 2.0 Conference
March 31, 2010

Credits

This report summarizes the findings of a survey conducted on the use of energy in different sector in the Millennium Villages Project (MVP) cluster of Potou (Senegal). The survey included energy use in schools, health care centers, public buildings, agriculture, fisheries as well as shops and businesses.

The survey concluded that there has been a noticeable progress made in the delivery of energy needs of important structures in the Potou cluster since the MVP project began, for example: (as of Jan 2009) 6 schools, 12 heath care centers and 4 public have been electrified. Also 35 farms were using new energy sources, 10 isothermal boxes for preserving fish and 3 new mills have been installed.

The grid connections exist and are expanding in Leona and Potou since 2007 and have seen 343 household connections since then. The grid has arrived in Thiowor as of January 2009 and as of today 98 household connections have been made out of 197 requests. Almost 95% of the shops in the semi-urban areas have been grid electrified.

Field research: Jose Barnuevo; summary and presentation: Rahul Kitchlu

Download reports:

Energy Systems Update – Senegal – Short Report

Energy Systems Update – Senegal – Full Report

ABSTRACT

In Senegal, as elsewhere, rural electrification is critical to poverty reduction. A national electricity scale-up is necessary for meeting the Millennium Development Goals over the next ten years, and one of the priorities is to electrify all health centers and schools. Rapid electrification of rural institutions and households in Senegal likely will require coordination across sectors and a range of energy technologies, including decentralized solutions.

The Columbia Earth Institute has developed a comprehensive energy planning methodology using straightforward Excel- and GIS-based tools. The toolset based on this methodology allows country teams to make investment estimates for a range of electrification scenarios given various technology options, coverage targets, fuel costs, etc. The tools also provide mechanisms for multiple stakeholders to share resources for energy planning.
The tools calculate the cost of scaling up electricity distribution. They output costs broken down into various components (e.g. capital, recurring, and replacement) but do not provide a complete financial analysis of the rate of return on particular investment schemes.
This report details the Earth Institute methodology, describes data obtained in Senegal, and presents cost estimates for selected electrification scenarios.

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• Costing for National Electricity Interventions in Senegal

ABSTRACT

We develop a spatial electricity planning model to guide grid expansion in countries with low pre-
existing electricity coverage. The model can be used to rapidly estimate connection costs and compare
different regions and communities. Inputs that are modeled include electricity demand, costs, and
geographic characteristics. The spatial nature of the model permits accurate representation of the
existing electricity network and population distribution, which form the basis for future expansion
decisions. The methodology and model assumptions are illustratedusing country-specific data from
Kenya. Results show that under most geographic conditions, extension of the national grid is less costly
than off-grid options. Based on realistic penetration rates for Kenya, we estimate an average connection
cost of $1900 per household, with lower-cost connection opportunities around major cities and in
denser rural regions. In areas with an adequate pre-existing medium-voltage backbone, we estimate
that over 30% of households could be connected for less than $1000 per connection through infilling.
The penetration rate, an exogenous factor chosen by electricity planners, is found to have a large effect
on household connection costs, often outweighing socio-economic and spatial factors such as inter-
household distance, per-household demand, and proximity to the national grid.

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• National Electricity Planning in Settings with Low Pre-Existing Grid Coverage: Development of a Spatial Model and Case Study of Kenya

ABSTRACT

Infrastructure planning for networked infrastructure such as grid electrification (or piped supply of
water) has historically been a process of outward network expansion, either by utilities in response to
immediate economic opportunity, or in response to a government mandate or subsidy intended to
catalyze economic growth. While significant progress has been made in access to grid electricity in Asia,
where population densities are greater and rural areas tend to have nucleated settlements, access to
grid electricity in Sub-Saharan Africa remains low; a problem generally ascribed to differences in
settlement patterns. The discussion, however, has remained qualitative, and hence it has been difficult
for planners to understand the differing costs of carrying out grid expansion in one region as opposed to
another. This paper describes a methodology to estimate the cost of local-level distribution systems for
a least-cost network, and to compute additional information of interest to policymakers, such as the
marginal cost of connecting additional households to a grid as a function of the penetration rate. We
present several large datasets of household locations developed from satellite imagery, and examine
them with our methodology, providing insight into the relationship between settlement pattern and the
cost of rural electrification.

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• The Impact of Geography on Energy Infrastructure Cost
  

The current infrastructure planning and implementation framework has often been inefficient in consolidating expertise and resources for more equitable and rapid scale up of access to services.  In response, we are developing a platform that is able to provide decision makers – utilities, planners, governments, communities – with the tools to make rapid data-driven assessments on how to roll out infrastructure at various administrative levels (national, district, and community). Continue Reading

Abstract

If solar power is to provide substantial portions of our electricity needs, it will first become cost effective when it provides peak power in the daytime, without the need for storing the energy.   Indeed since human electricity consumption is frequently small at night and larger when the sun is shining, there is already a natural correlation.  Existing power systems are currently geared to provide this variable demand, with baseload plants cheaply providing a constant level of power, and dispatchable plants dynamically (and more expensively) supplying the rest.  This leads to the frequent suggestion that one can exploit the correlation between sunlight and electricity by using energy from solar panels during the day to offset some of the load previously generated by dispatchable plants.

This paper addresses the question of how much of the load can be substituted by the solar electricity, without leaving the solar power plant substantially idle or requiring the solar power to be stored.  It uses historical sunlight and electrical load data from 32 regions of the United States to determine the photovoltaic (PV) power generation capacity that could be installed such that “almost all” of its energy output would occur at times of high demand. Specifically, what is the maximum deployment that permits 95% of the annual output from PV to be utilized without reducing the output of the baseload plants?

Our results for these 32 regions are that 7.8% of the total annual electricity demand could be met by installing 59 GW of PV panels.  This represents about a fourth of the present electrical energy supplied by dispatchable plants.  If solar power were equally effective in the rest of the United States, nearly 200 GW of PV capacity could be put to use without any energy storage.  Thus, in the near term, there is enormous room for expanding the roughly 1 GW installed base of PV power without investing in night-time energy storage.  The paper also provides insight into how year to year variability of sunlight and demand impact the results.

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• Solar Power Without Storage