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A geospatial assessment of the techno-economic wind power potential in India using geographical restrictions
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Energy Systems Analysis.
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Energy Systems Analysis.
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Energy Systems Analysis.
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Energy Systems Analysis.
2016 (English)In: Renewable energy, ISSN 0960-1481, E-ISSN 1879-0682, Vol. 97, 77-88 p.Article in journal (Refereed) Published
Abstract [en]

India is a privileged country in terms of wind resource regime. However, most of it remains untapped at the same time as ca 240 million people lack access to electricity in the country (19% of the total population). This calls for a thorough estimation of the amount of wind energy that could be technically and economically seized to assess the potential penetration of wind power into the country's energy system. The utilization of wind energy is associated with a plethora of localization criteria and thus it should be systematically addressed by spatial assessments to guarantee its harmonization with socio-economic systems, infrastructure and ecosystems. This study focuses on onshore wind power and strives to provide with estimates of techno economic potential based on state of the art wind power technology. Socio-economic, geographical and technical criteria regarding the localization of wind farms are outlined and implemented through a detailed a Geographic Information Systems (GIS) analysis. The levelized cost of wind generated electricity is then calculated geospatially. According to this assessment there are several states that signify high yearly wind energy yield, such as Rajasthan, Andhra Pradesh and Gujarat, whilst Goa and other states indicate the least or negligible wind power potential. The levelized cost of generating electricity ranges between 57 and 100 USD/MWh, which places wind power in a competitive position in the Indian electricity market.

Place, publisher, year, edition, pages
Elsevier, 2016. Vol. 97, 77-88 p.
Keyword [en]
Wind energy, India, Economic potential, GIS
National Category
Energy Systems
Identifiers
URN: urn:nbn:se:kth:diva-192380DOI: 10.1016/j.renene.2016.05.057ISI: 000380600500008Scopus ID: 2-s2.0-84973131294OAI: oai:DiVA.org:kth-192380DiVA: diva2:969003
Note

QC 20160913

Available from: 2016-09-13 Created: 2016-09-12 Last updated: 2017-05-24Bibliographically approved
In thesis
1. Spatially explicit electrification modelling insights: Applications, benefits, limitations and an open tool for geospatial electrification modelling
Open this publication in new window or tab >>Spatially explicit electrification modelling insights: Applications, benefits, limitations and an open tool for geospatial electrification modelling
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Developing countries confront the challenge of generating more electricity to meet demands in a sustainable manner. According to the World Bank’s 2015 Global Tracking Framework, roughly 15% of world population (or 1.1 billion people) lack access to electricity, and many more rely on poor quality electricity supplies. In September 2015, the United Nations General Assembly adopted Agenda 2030 comprised of a set of 17 Sustainable Development Goals (SDGs) and defined by 169 targets. “Ensuring access to affordable, reliable, sustainable and modern energy for all by 2030” is the seventh goal (SDG7). While energy access refers to more than electricity, it is the central focus of this work.

Models addressing electrification and access typically need large volumes of reliable energy-related data and information, which in most developing countries have been limited or not available. This paucity of information has decelerated energy planning in the developing World. That situation has fundamentally changed with increasing availability and application of Geographic Information Systems (GIS). GIS layers can provide location specific energy-related information that has not been previously accessible. The focus of this thesis lies on integrating a simple electricity supply model into GIS. In so doing a novel open source spatial electrification tool is developed. It estimates power capacity needs and associated investment (and other) costs for achieving universal access to electricity in developing countries.

The dissertation includes a cover essay and six appended papers presenting quantitative methods on coupling selected aspects of GIS and energy systems. It strives to answer three key research questions. 

The first research question is: What is the spatially explicit renewable energy potential that can be technically and economically exploited? This information is currently either missing or scattered in developing countries. The provision of low cost, locally available energy can provide a significant opportunity to empower a better standard of living. The first paper presents a GIS based approach to assess the onshore technical wind energy potential on the African continent by applying socioeconomic and geographic restrictions regarding the localization of wind farms and state of the art wind data analysis. The second paper builds on this knowledge and moves one step further by assessing the economic potential and providing cost indicators to assess the viability of wind power (this time in India). The third paper maps the economic wind power potential in Africa based on the methodologies developed in the two preceding papers. Not only wind power but most energy resources have a spatial nature and their availability is linked to geography. Evaluating these other energy sources (solar, hydro etc.) are included and analysed in Papers IV-VI.

The second research question is: what is the least-cost set of technologies needed to meet different levels of electricity use accounting for different geographies? Increasing access to electricity effectively requires, inter alia, strategies and programmes that address and account for the geographical, infrastructural and socioeconomic characteristics of a country or region. Paper IV introduces a GIS based methodology to inform electrification planning. It builds on the previous work by taking into account the techno-economic wind, and other resource mapping. This methodology is applied in Nigeria in order to determine the least cost technology mix considering the country’s infrastructure and resource availability on a spatial basis. Paper V utilizes this method and in so doing demonstrates the importance of geospatial calculations in energy access planning. It highlights differences in investment estimates between alternate scenarios with regards to energy demand and technology deployment. Paper VI enhances this methodology and applies it to every square kilometre of Sub-Saharan Africa. The method is subsequently implemented in an Open Source Spatial Electrification Tool (OnSSET) to facilitate education, repeatability and further research.

Finally, the third question is: Are there gains to be had by linking geographically explicit analysis with typical (non-spatially explicit) long term energy systems models? The work shows that not only do long-term systems models influence geospatially optimal technology deployment. But vice versa, their output influences long term systems models’ investment profile.  That is because the geospatial disaggregation allows for a better determination of grid versus off-grid connections, and in turn power demand on the national grid. This thesis demonstrates that energy system models should take into consideration the geographic dimension of energy-related parameters, as these play a fundamental role in determining the optimal energy system of a region.

Place, publisher, year, edition, pages
Stockholm, Sweden: KTH Royal Institute of Technology, 2017. 88 p.
National Category
Energy Engineering
Research subject
Energy Technology
Identifiers
urn:nbn:se:kth:diva-207801 (URN)
Public defence
2017-06-08, M3, Brinellvagen 68, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20170524

Available from: 2017-05-24 Created: 2017-05-24 Last updated: 2017-05-24Bibliographically approved

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