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Optimized market value of alpine solar photovoltaic installations

Solar photovoltaic (PV) is the most rapidly expanding renewable resource worldwide. Yet, its full potential may be hindered by mismatches with market demand and correlated production profiles. In this research, we explore a case study of innovative PV placements in alpine regions using two, soft-linked optimization models of Switzerland's electricity system. Using Swissmod, an electricity dispatch and load-flow model, and OREES, an electricity system model employing evolution strategy to optimize PV placement, we simulate market prices of optimized PV placements given multiple years of weather data, various CO2 prices, and considering future electricity infrastructure developments across Europe. Mountain placements result in higher market value and less required area relative to lower-altitude PV placement strategies. The higher market value is driven by better alignment with demand, particularly during winter when demand is highest. We found that optimized alpine placements offer revenues of panel capacity (EUR/kW/year) that are on average 20% higher than revenues from urban PV installations. Furthermore, the Swiss mountains could host more than 1 GW of capacity with even greater revenues (33%). Alpine PV installations, with their higher market values and increased value factors, can potentially be very profitable investments and are also valuable from a system perspective.
Renewable Energy, 186
ISSN:0960-1481
ISSN:1879-0682
- ETH Zurich Switzerland
- École Polytechnique Fédérale de Lausanne EPFL Switzerland
- University of Basel Switzerland
Optimization, 333.79: Energie, Photovoltaic; Market value; Dispatch model; Optimization; Alpine photovoltaics; Evolution strategy, Alpine photovoltaics, Evolution strategy, Dispatch model, Photovoltaic, Market value
Optimization, 333.79: Energie, Photovoltaic; Market value; Dispatch model; Optimization; Alpine photovoltaics; Evolution strategy, Alpine photovoltaics, Evolution strategy, Dispatch model, Photovoltaic, Market value
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