| 1. |
- Rydehell, Hanna, 1989, et al.
(författare)
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The impact of solar PV subsidies on investment over time-the case of Sweden
- 2024
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Ingår i: Energy Economics. - 0140-9883 .- 1873-6181. ; 133
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Tidskriftsartikel (refereegranskat)abstract
- Over the past decade, different economic incentives have been created to increase investments in solar photovoltaics (PV). Although research outlines that investors in renewable electricity technologies (RET) are heterogeneous, policies have not taken this into account when designing subsidy programs. This paper aims to analyse the relationship between policy incentives and the willingness to invest in PV systems for different investor groups, including households, companies, associations, and public organizations. Using data from all applications to the capital subsidy program for PV in Sweden between 2009 and 2021, we analyse the impact of the subsidy level on investments over time. Our analysis shows that the subsidy has had a positively significant impact for households and private companies as investor groups. However, we also found that other variables have had a significantly positive or negative effect on the willingness to invest for different investor groups. This stresses the need of going from “one size fits all” policies to policies that better adapted to different investor characteristics. To meet the urgent need to accelerate the diffusion of RETs, our results show the impact of investor heterogeneity on policy responsiveness and provide avenues for the design of targeted policies.
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| 2. |
- Frimane, Azeddine, et al.
(författare)
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Identifying small decentralized solar systems in aerial images using deep learning
- 2023
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Ingår i: Solar Energy. - : Elsevier BV. - 0038-092X .- 1471-1257. ; 262
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Tidskriftsartikel (refereegranskat)abstract
- Statistics on installed solar energy systems (SES) play a crucial role in the solar energy industry, providing valuable information for a wide range of stakeholders, such as policy makers, authorities, and financial evaluators. For example, grid operators rely on accurate data on photovoltaic penetration levels to ensure the quality and stability of the power supply. In this research, we present an automatic approach helping generate these statistics using deep learning and image processing techniques. Our proposed model is a machine learning approach that utilizes a specific architecture of convolutional neural networks (CNN) called the "U-net'' to detect SES from aerial images. We experimented different network settings to enhance the SES identification performance.In this study, the model was evaluated using two datasets from different locations, one from Sweden and one from Germany. Additionally, the model was trained and tested on a combination of both datasets. The impact of image resolution was also examined. The experimental results show that this architecture performs better than many recent CNN models that have been proposed in the literature for the task of SES identification from aerial images. To make it easy for others to replicate our findings, We have shared all the scripts, software, and dependencies required for running the model in this paper, along with instructions on how to use it in Appendix A.
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| 3. |
- Lindahl, Johan, et al.
(författare)
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Mapping of decentralised photovoltaic and solar thermal systems by remote sensing aerial imagery and deep machine learning for statistic generation
- 2023
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Ingår i: ENERGY AND AI. - : Elsevier BV. - 2666-5468. ; 14
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Tidskriftsartikel (refereegranskat)abstract
- As a mean to monitor the rapid expansion of the highly decentralized PV market, identifying solar energy systems in aerial imagery by deep machine learning, is a research field that is getting increasing interest. One general challenge in the field is to create testing data of high quality that are representative of the end-use application. In this study we use the open source convolutional neural network developed within the DeepSolar project and apply it in the country of Sweden, for the purpose of generating market statistics, by scanning three complete municipalities for small decentralized photovoltaic and solar thermal systems. The evaluation of the performance is done against a highly accurate ground truth, which was created by cross-checking the classification results with the inventory of the local distribution system operators and the database of photovoltaic systems that have received a capital subsidy in Sweden, and combining that with physical onsite inspections. A process of generate additional training data and re-training the algorithm after each municipality scan was developed, which successively improved the accuracy, resulting in that 95% of all detectable photovoltaic, excluding building integrated and vertical systems, and 80% of all detectable solar thermal systems were correctly identified in the last municipality scan. The accurate ground truth allowed a quantification of why some systems are not detected. The generated dataset of solar energy systems could be connected to existing building and property inventories, which allowed creation of market segment statistics with remarkably high detail information.
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| 4. |
- Molin, Lisa, et al.
(författare)
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Validation of a PV generation model for simulation of wide area aggregated distributed PV power generation that takes into individual systems locaiton and orientation into account
- 2023
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Ingår i: 40th European Photovoltaic Solar Energy Conference and Exhibition (EUPVSEC). - : EU PVSEC. - 3936338884 ; , s. 020527-001-020527-015
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- 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.
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| 5. |
- Zainali, Sebastian, et al.
(författare)
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LCOE distribution of PV for single-family dwellings in Sweden
- 2023
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Ingår i: Energy Reports. - 2352-4847. ; 10, s. 1951-1967
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 6. |
- Lindahl, Johan, 1984, et al.
(författare)
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Economic analysis of the early market of centralized photovoltaic parks in Sweden
- 2022
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Ingår i: Renewable Energy. - : Elsevier BV. - 0960-1481 .- 1879-0682. ; 185, s. 1192-1208
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Tidskriftsartikel (refereegranskat)abstract
- Sweden is one of the countries that experience growing installation volumes of Solar photovoltaic. Traditionally, in Sweden, most of the solar photovoltaic investments and policy incentives have focused on distributed photovoltaic systems. Yet, despite limited policy incentives and pessimistic forecasts, an increasing number of centralized photovoltaic parks have been commissioned and plans for substantial new capacities are communicated. Hence, the current paper investigates why. Detailed information about the underlying costs of six PV parks commissioned in2019 and 2020 in Sweden were obtained by in-depth interviews with stakeholders and were analysed through levelized cost of electricity calculations. We conclude that the unsubsidised levelized cost of electricity ranged from 27.37 to 49.39 €/MWh, with an average of 40.79 €/MWh. This is lower than what are assessed for photovoltaic parks in some recent Swedish electricity system scenario studies. The main reason for the discrepancy is identified to be the assumed interest rates in the system scenario studies and the actual cost of capital experienced in the market. Comparing the levelized cost of electricity values with the market value of solar photovoltaic electricity on the spot market show that four of the six studied parks would be profitable under a merchant business model with the last years spot prices. If the downward price trend continues, Sweden may face an unexpected expansion of photovoltaic parks.
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| 7. |
- Lindahl, Johan, et al.
(författare)
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Socioeconomic and demographic factors behind the deployment of domestic photovoltaic and solar thermal systems in three Swedish municipalities
- 2022
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The adoption of domestic photovoltaic systems has in numerous studies been proven to be influenced by peer effects and socioeconomic factors such as income, age, gender, education etc., which has led to irregular spatial installation patterns. Only a few studies regarding domestic solar thermal systems indicate that the same effect exist for this technology. However, the interaction between photovoltaic and solar thermal deployment and the similarities or differences in socioeconomic factors have not been investigated in detail so far. This study identifies the most prominent socioeconomic factors behind both domestic photovoltaic and solar thermal adoption in three different municipalities in Sweden, based on a complete set of 452 photovoltaic and 359 solar thermal collector systems installed until 2020, which was identified and classified by a method that uses machine learning and aerial imagery. A moderate (absolute Pearson correlation, |ρ|, > 0.3) to intermediate (|ρ| > 0.5) correlation between photovoltaic and solar thermal penetration was found on demographic statistical area level, and several of the previously reported influential socioeconomic factors for domestic photovoltaic installation were confirmed also for domestic solar thermal adoption in Sweden.
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| 8. |
- Keller, Jan, et al.
(författare)
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Potential gain in photocurrent generation for Cu(In,Ga)Se2 solar cells by using In2O3 as a transparent conductive oxide layer
- 2016
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Ingår i: Progress in Photovoltaics. - : Wiley. - 1062-7995 .- 1099-159X. ; 24:1, s. 102-107
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Tidskriftsartikel (refereegranskat)abstract
- This study highlights the potential of atomic layer deposited In2O3 as a highly transparent and conductive oxide (TCO)layer in Cu(In,Ga)Se2 (CIGSe) solar cells. It is shown that the efficiency of solar cells which use Zn-Sn-O (ZTO) as an alternativebuffer layer can be increased by employing In2O3 as a TCO because of a reduction of the parasitic absorption inthe window layer structure, resulting in 1.7 mA/cm2 gain in short circuit current density (Jsc). In contrast, a degradation ofdevice properties is observed if the In2O3 TCO is combined with the conventional CdS buffer layer. The estimated improvementfor large-scale modules is discussed.
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| 9. |
- Lindahl, Johan, 1984-, et al.
(författare)
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Deposition temperature induced conduction band changes in zinc tin oxide buffer layers for Cu(In,Ga)Se2 solar cells
- 2016
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Ingår i: Solar Energy Materials and Solar Cells. - : Elsevier BV. - 0927-0248 .- 1879-3398. ; 144, s. 684-690
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Tidskriftsartikel (refereegranskat)abstract
- Thin film Cu(In,Ga)Se2 solar cells with ALD-deposited Zn1-xSnxOy buffer layers were fabricated and the solar cell properties were investigated for varying ALD deposition temperatures in the range from 90 °C up to 180 °C. It was found that a process window exists between 105 °C and 135 °C, where high solar cell efficiency can be achieved. At lower ALD deposition temperatures the solar cell performance was mainly limited by low fill factor and at higher temperatures by low open circuit voltage. Numerical simulations and electrical characterization were used to relate the changes in solar cell performance as a function of ALD deposition temperature to changes in the conduction band energy level of the Zn1-xSnxOy buffer layer. The Zn1-xSnxOy films contain small ZnO or ZnO(Sn) crystallites (~10 nm), resulting in quantum confinement effects influencing the optical band gap of the buffer layer. The ALD deposition temperature affects the size of these crystallites and it is concluded that most of the changes in the band gap occur in the conduction band level.
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| 10. |
- Edoff, Marika, et al.
(författare)
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Gas flow sputtering of Cu(In,Ga)Se-2 for thin film solar cells
- 2015
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Ingår i: 2015 IEEE 42ND PHOTOVOLTAIC SPECIALIST CONFERENCE (PVSC). - 9781479979448
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Konferensbidrag (refereegranskat)abstract
- Gas flow sputtering of Cu(In,Ga)Se-2 (CIGS) from two opposing Cu(In,Ga)Se-2 targets with slightly Cu-poor stoichiometry was performed, using i) selenium only provided by the target and ii) using additional selenium from an elemental source inside the sputtering system. In both cases the composition of the sputtered CIGS film was similar to the target. A sputter process without additional selenium supply led to poor cell results at about 2 % efficiency. After introducing a posttreatment in selenium atmosphere immediately after the sputter deposition, the cell results were dramatically improved to 12 %. With selenium added during the sputtering process, 13.7 % conversion efficiency was obtained without any post treatment. Gas flow sputtering uses a high gas flow to transport the material from the plasma to the growing film, thereby the atoms will be thermalized, similarly to in an evaporation process. Reactant gases can be supplied close to the substrate, outside the plasma, thereby reducing the risk for sputter damage.
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