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Potential by technology / Solar

The World Bank and the International Finance Corporation (IFC), collectively the World Bank Group, have published these solar resource maps alongside a Global Solar Atlas consisting of global, regional and country maps, to support the scale-up of solar power in Armenia.

This work is funded by the Energy Sector Management Assistance Program (ESMAP), a multi-donor trust fund administered by The World Bank and supported by 13 official bilateral donors.

The World Bank Group has selected Solargis as its global provider of solar resource data and related services. These maps has been prepared by Solargis, under contract to The World Bank, based on a solar resource database that they own and maintain.

Direct Normal Irradiation (DNI)

This solar resource map provides a summary of the estimated solar energy available for power generation and other energy applications. It represents the average daily/yearly sum of direct normal irradiation (DNI) covering a period of 17 recent years (1999-2015).The underlying solar resource database is calculated by the Solargis model from atmospheric and satellite data with 30-minute time step.  The effects of terrain are considered at nominal spatial resolution of 250 m.

There is some uncertainty in the yearly DNI estimate as a result of limited potential for regional model validation due to a lack of high quality ground measurement data, which is estimated to vary regionally from approx. 8% to 15%.

DNI is the most important parameter for energy yield calculation and performance assessment of concentrating solar power (CSP) and concentrator solar photovoltaic (CPV) technologies. DNI is also important for the calculation of global irradiation received by tilted or sun-tracking photovoltaic modules.

Global Horizontal Irradiation (GHI)

This solar resource map provides a summary of the estimated solar energy available for power generation and other energy applications. It represents the average daily/yearly sum of global horizontal irradiation (GHI) covering a period of 17 recent years (1999-2015).

The underlying solar resource database is calculated by the Solargis model from atmospheric and satellite data with 30-minute time step. The effects of terrain are considered at nominal spatial resolution of 250 m.

There is some uncertainty in the yearly GHI estimate as a result of limited potential for regional model validation due to a lack of high quality ground measurement data, which is estimated to vary regionally from approx. 5% to 8%. GHI is the most important parameter for energy yield calculation and performance assessment of flat-plate photovoltaic (PV) technologies.

 

Photovoltaic (PV) Power Potential

This solar resource map provides a summary of estimated solar photovoltaic (PV) power generation potential.

It represents the average daily/yearly sum of electricity production from a 1 kW-peak grid-connected solar PV power plant, calculated for a period of 17 recent years (1999-2015).

The PV system configuration consists of ground-based, free-standing structures with crystalline-silicon PV modules mounted at a fixed position, with optimum tilt to maximize yearly energy yield. The optimum tilt ranges from 27° to 35° towards the equator. Use of high efficiency inverters is assumed. The solar electricity calculation is based on high- resolution solar resource data and PV modeling software provided by Solargis. The calculation takes into account solar radiation, air temperature, and terrain, to simulate the energy conversion and losses in the PV modules and other components of a PV power plant. The cumulative effect of losses due to dirt, snow and ice on the PV modules, and the losses from cables, inverters and transformers, is 9%.

The power plant availability is considered to be 100%.

The underlying solar resource database is calculated from atmospheric and satellite data with a 30-minute time step, and a spatial resolution of 250 m.

 

 

Copyright © 2017 THE WORLD BANK

The World Bank, comprising the International Bank for Reconstruction and Development (IBRD) and the International Development Association (IDA), is the commissioning agent and copyright holder for this publication, acting on behalf of The World Bank Group. This publication, and the underlying dataset, is licensed by The World Bank under a Creative Commons Attribution license (CC BY 3.0 IGO).

Users should cite The World Bank as the data provider, and make reference to ESMAP as the source of funding for this publication.

Considering the nature of climate fluctuations, inter-annual and long-term changes, as well as the uncertainty of measurements and applied methods, The World Bank, International Finance Corporation, and Solargis do not take any responsibility whatsoever, and do not give any warranty, on the accuracy of the data that were used to produce these maps. Solargis has done its utmost to make an assessment of solar climate conditions and the performance of solar power systems based on the best available data, software, and knowledge. It is recommended that these maps be used as a guide of solar resource potential rather than an instrument to plan or develop solar power installations.

The boundaries, colors, denominations and any other information shown on these maps do not imply, on the part of The World Bank, any judgment on the legal status of any territory, or any endorsement or acceptance of such boundaries.

To obtain additional maps and information, please visithttp://globalsolaratlas.info