An irradiance-neutral view on the competitiveness of life-cycle cost of PV rooftop systems across cities. (September 2017)

• Record Type: Journal Article
• Authors: Bieri, Monika; Winter, Kevin; Tay, Stephen; Chua, Andy; Reindl, Thomas
• Is Part Of: Energy procedia. Volume 130(2017)
• Page Start: 122
• Page End: 129
• Publication Date: 2017-09
• Subjects: LCOE -- rooftop PV systems -- renewable energy policies -- financing of solar PV; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2017.09.408
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: When calculating the life-cycle cost of solar electricity, there are three main factors that influence the outcome: i) the irradiance conditions, ii) the initial investment cost, and iii) the cost of financing. This work compares the cost of solar electricity in Singapore with those in other major cities around the world: Kuala Lumpur, Jakarta, Bangkok, Manila, Phnom Penh, Beijing, Delhi, Tokyo, Zurich, Munich and San Francisco. It computes an "adjusted" levelised cost of electricity (LCOE), which compares the competitiveness "as if" they all had the same irradiance conditions ("irradiance-neutral"). This should give policy makers a view where their cities stand in terms of investment cost and financing, which they could actively influence (in contrast to the solar resource). Taking into account its lowest system cost and highest irradiance, Delhi leads the "un-adjusted" LCOE ranking, followed by Bangkok and Singapore. After "adjusting" the LCOE, however, Beijing would rank first, with Munich and Singapore being second and third, respectively. While Delhi drops to the fourth position, Munich, despite having the second worst irradiance conditions, improves significantly due to its low interest rate environment. Besides system cost, the study shows that accessible financing at low interest rates remains an important driver to accelerate the adoption of solar energy in larger scale.