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![Figur 2. Total installerad solcellskapacitet angiven i MW i Sverige mellan 2000-2019, uppdelad per marknadssegment [1].](profile/Johan-Lindahl/publication/349180346/figure/fig1/AS:989747501617154@1612985601348/Figur-2-Total-installerad-solcellskapacitet-angiven-i-MW-i-Sverige-mellan-2000-2019.png)
Figur 2. Total installerad solcellskapacitet angiven i MW i Sverige mellan 2000-2019, uppdelad per marknadssegment [1].
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![Figur 3. Priserfarenhetskurvan för solceller mellan 1975-2018 [4].](profile/Johan-Lindahl/publication/349180346/figure/fig2/AS:989747501617155@1612985601380/Figur-3-Priserfarenhetskurvan-foer-solceller-mellan-1975-2018-4_Q320.jpg)
More than half of all grid-connected PV systems in Sweden at the end of 2019 were so-called villa systems. These are installed for self-consumption and are subject to several market-based support systems.
The inherent cost structure of Swedish villa systems is not yet explored, except for results from a simpler survey conducted in 2015. This study...
Citations
... Furthermore, an average DC-to-AC ratio was computed to determine the inverter curtailment and resulting hourly AC power output. A ratio 1.08 was derived from the average DC-to-AC ratio of 115 PV systems installed on single-family houses in Sweden collected for a study in 2020 [26]. The assumption was made that all PV systems had the same DC-to-AC ratio. ...
Understanding the photovoltaic (PV) power generation's temporal and spatial patterns is vital for grid balancing. This study aims to validate a simulation model for historical decentralized PV power generation, extending it to encompass the unique orientation of all PV systems within the Swedish municipality Knivsta. In a previous research project, a Convolutional Neural Network exhibited a 95% accuracy of identifying PV systems within Knivsta. In this project, using Light Detection and Ranging data, the orientation and area of detected PV systems was estimated. By combining this information with local weather and irradiance data, historical PV power generation was simulated. The regression analysis demonstrates strong correspondence between simulated and measured hourly generation for six reference systems, with coefficients of determination between 0.69-0.83. This study derives generic module parameters based on installation year and an average DC-to-AC ratio, enabling municipal-level simulations. Simulations for 2022, considering one scenario with optimal orientation for all PV systems and one scenario with derived real-condition orientations, reveal a smoothing effect in the daily pattern of aggregated PV generation, if considering real orientations. At the peak hour, power generation was found to be 10% lower when considering individual orientations compared to assuming optimal orientation across all facilities.
... However, central inverters are not a common choice for a single-family dwelling PV system. And even if the market share of micro inverters is increasing within the market segment of single-family dwelling PV systems, as they promise lower shading losses and longer lifetimes (Obeidat and Shuttleworth, 2017;Alferidi and Karki, 2017), the most common inverters for the small-scale residential sector in Sweden is still considered to be string inverters (Oller Westerberg and Lindahl, 2020). ...
... Assessing the future nominal cost of replacing the inverter 15 years into the future is not straightforward. The retailer price of a typical string inverter for a 10 kW p PV system was about 17,300 SEK, (excluding VAT) in Sweden 2020 (Oller Westerberg and Lindahl, 2020). However, the price of inverters has successively gone down historically. ...
... These costs are not subjected to a future experience curve in the same way as the inverter. As of 2020, traveling costs have been found to be on average 1000 SEK per installation (Oller Westerberg and Lindahl, 2020). Traveling time plus the time to change the inverter is estimated to be four hours. ...
In Sweden, the installations of solar photovoltaic systems are growing rapidly, and especially the market segment of small-scale distributed systems is experiencing positive growth. The current installation volumes exceed the expectations of the Swedish authorities. This study presents an up-to-date assessment of the levelized cost of electricity to be used for both agencies in their long-term scenario work of PV development and for private investors for estimating the upfront and future costs and risks associated with photovoltaic systems. The analysis is based on the turnkey system cost of 6,098 single-family dwelling photovoltaic systems commissioned in Sweden between the 1st of January 2019 and 1st of July 2020. The statistics of system investments costs are complemented by literature studies and by interviews of relevant stakeholders for the other input parameters needed to calculate the Levelized Cost of Electricity (LCOE). A Monte Carlo analysis was applied on all the input parameters provides relevant insight into the range of LCOE values. The unsubsidized levelized cost of electricity for most systems ranged from 0.85 SEK/kWh (25th percentile) to 1.15 SEK/kWh (75th percentile), with a mean at 1.02 SEK/kWh at reasonable real discount rate of 2%, but that extreme values can reach 0.30 SEK/kWh at a 0% discount rate and 5.70 SEK/kWh at a 5% discount rate. Taking into account the current (2023) Swedish tax reduction for investment in green technologies that amounts to an effective deduction of 19.4% of the total system investment costs lowers the LCOE to mean at 0.82 SEK/kWh at real discount rate of 2%. The LCOE for single-family dwelling photovoltaic systems are generally lower than the assumed LCOE in long-term scenario studies of the Swedish electricity system. This finding helps to explain to the authorities the unexpected fast deployment of distributed photovoltaic systems in Sweden.
