Abstract
With growing economy, several cities and towns in India are experiencing a substantial growth in their gross and peak electricity demands. While Municipal Corporations and the electricity supply agencies are struggling to cope with growing energy demand of cities, many think solar electricity generation through rooftop Photovoltaic (PV) is a viable solution for this problem. Quantification of available rooftop is necessary to estimate the potential of energy generation in Indian cities through rooftop solar PV panels. This paper proposes an automated object-oriented approach to extract total available area of residential rooftops. A smaller residential neighbourhood in Bhopal city has been selected as Test Site to test the proposed method. Data sets used are World View 2 Stereo pair and Multispectral images. It is found that the test area has the potential to meet 265% of its daily local energy demand through rooftop solar PV panels. Though Indian government had announced separate scheme under the Jawaharlal Nehru National Solar Mission (JNNSM) to promote installation of rooftop PV, development of this sector is still in nascent stages. This paper also suggests some policy level interventions to promote rooftop PV at domestic level in similar tier-II cities of India.
Highlights
At the 2009 climate summit, India undertook to cut its greenhouse gas (GHG) emissions intensity by 20% - 25% by 2020 compared with 2005 levels
It is found that the test area has the potential to meet 265% of its daily local energy demand through rooftop solar PV panels
MP has the lowest installed rooftop solar PV capacity compared to other states (Figure 2(a)) in spite of having more Global Horizontal Irradiance (GHI) than Indian average (Figure 2(b))
Summary
At the 2009 climate summit, India undertook to cut its greenhouse gas (GHG) emissions intensity by 20% - 25% by 2020 compared with 2005 levels. The estimation was done on the basis of census data available on percentage of concrete roof and population The problem with this kind of estimation is three-fold: 1) census data is available in every ten years; whereas, land-use pattern of Indian cities is very dynamic. For successful implementation of JNNSM, up-to-date data is required in every three to four years; 2) In India, census data for dwelling units is available for wards [administrative divisions within cities] which are different from electricity distribution zones. As a result, estimated solar potential from census data cannot be compared with the electricity demand of that area. To overcome these challenges one needs a quicker and repeatable technique which can provide us rooftop data at any spatial scale. This paper proposes an automated method to extract residential rooftop area at neighbourhood level
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