# CO2 Footprint of DC Solid State Transformer for Linear
PV Power Plant

Pierre Le Métayer, Adriana Campos, Piotr Dworakowski

► To cite this version:

Pierre Le Métayer, Adriana Campos, Piotr Dworakowski. CO2 Footprint of DC Solid State Transformer for Linear PV Power Plant. The 26th European Conference on Power Electronics and Applications, GDR SEEDS France & EPE Association, Mar 2025, Paris, France. 10.34746/epe2025-0237. hal-05088511

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# CO₂ Footprint of DC Solid State Transformer for Linear PV Power Plant

Pierre Le Métayer, Adriana Campos, Piotr Dworakowski

SUPERGRID INSTITUTE

23 rue Cyprian

Villeurbanne, France

+33 4 28 01 23 23

pierre.lemetayer@supergrid-institute.com

https://www.supergrid-institute.com

## Acknowledgements

This work is a result of OPHELIA project funded under "France 2030" program operated by ADEME and involving: Compagnie Nationale du Rhône, Nexans, Schneider Electric, SNCF and SuperGrid Institute.

## Keywords

«Life Cycle Assessment (LCA)», «Solid-State Transformer», «Photovoltaic», «PV inverter», «MVDC».

## Abstract

This paper presents a comparison of the carbon footprint of a DC SST designed for a linear PV application with MVDC collection network, and its counterpart for a traditional MVAC architecture. A method is proposed, allowing to calculate the CO₂ footprint of the DC SST accounting for the manufacturing emissions of the PV modules. It is found that the energy efficiency of the conversion chain tends to be less and less significant to the overall carbon footprint as the energy mix shifts towards renewable energy sources. The manufacturing emissions of the conversion chain are thus to be reduced in the future. For PV power plants this can be achieved thanks to MVDC collection network.

## Introduction

The European Union targets carbon neutrality by 2050. The direct current (DC) networks and power electronics converters have been supporting the massive integration of renewable energy sources (RES) aiming in decarbonizing the energy mix [1]. The high voltage DC (HVDC) has enabled large offshore wind power plants, mainly in the North Sea [2]. The photovoltaic (PV) power plants rely on power electronics

inverters which have become a commodity [3], [4].

The Renewable Energy Sources (RES) contribute to decarbonizing the energy mix, but they are not environmentally neutral due to initial carbon emissions necessary to build the power plant. To reduce the environmental impact of PV power plants, a solution is to install PV power plants along motorways, railroads, rivers etc. These linear PV power plants provide a response to land scarcity, as they help optimize the use of long, narrow land surfaces and structures that have already been designated for other uses, leaving natural spaces as they are [5]. Moreover, an innovation in collection network architecture using medium voltage DC (MVDC) [6] is expected to offer reduced carbon emissions.

Carbon emissions are one of the environmental impacts which can be measured using the Life-Cycle Assessment (LCA) methodology [7], and one of the most discussed in our society. The electric power system is one of the major contributors of CO₂ emissions, and the related emissions of some elements of the power chain such as transformers has already been investigated [8].

Recently, some interest has arisen to quantify the carbon emissions of power electronic devices, since they are expected to be more and more present in the grid. The importance of including the environmental analysis in the design of power electronic devices has already been highlighted in [9], [10]. The carbon emissions would become another Key Performance Indicator (KPI) in a multi-parametric optimization. This was illustrated in [11] where the design of a dual active bridge (DAB) DC solid state transformer (DC SST) was presented, minimizing the CO₂ footprint.

The LCA methodology has been used to assess the environmental impact of power electronics from the component level all the way to the inverter level. In [12], the difference between Si
and SiC semiconductors in terms of energy inputs and efficiency gains has been evaluated. This was done by quantifying the emissions related to the manufacturing and use phases of these components.

In [13] the LCA of a 150 kW inverter was done, presenting in detail each subpart of the converter and proposing a general method for eco-designs or comparisons of topologies. It was found that the manufacturing and use phases have the greatest environmental impact in the life cycle of the converter, and that the energy mix can greatly affect the indicators.

This article presents a CO₂ footprint comparison of two types of conversion chain for a linear PV power plant:

- PV inverter and transformer connected to a medium voltage AC (MVAC) collection network,

- DC SST connected to an MVDC collection network.

The novelty of this paper resides in two aspects: the objects subject to the LCA and the comparison of different calculation methods. Regarding the first aspect, the LCA is performed on an oil-insulated DC SST for PV application based on MVDC collection network. This analysis is based on the bill of material data of a real DC SST prototype and compared with AC state of the art conversion chain data. Regarding the second aspect, the calculations are performed based on three approaches:

- “Load-like” - compensating losses with local energy mix,

- Renewable source - neglecting power losses,

- Renewable source, constant energy - compensating losses with PV.

The last method allows to calculate the CO₂ footprint of the DC SST accounting for the manufacturing CO₂ emission of PV modules.

This article is organized as follows. First, a case study of linear PV power plant is presented. The equivalent AC and DC conversion chains are shown. The DC SST design is detailed. Secondly, the carbon footprint assessment methodology is presented, with a focus on the use phase. Finally, the results for the DC SST and AC conversion chain are compared and discussed.

## Linear PV power plant

Conventional (rectangular) PV power plants require large areas (approximately 1 ha/MWp) and the available lands are limited. Moreover,

they raise several debates on landscape and environmental impacts [6]. Linear PV power plants installed along motorways, railroads, canals, rivers etc. reuse the lands which have already been designated for other uses. Moreover, they do not oppose the exploitation of other resources like agricultural or forestry. The power density of linear PV power plants is evaluated between 0.5 and 2 MWp/km. The potential for linear PV power plants in France represents up to approximately 35 GWp [14].

The case study 20 MW linear PV power plant is spreading along 20 km. A radial MVDC collection network is proposed, either in AC at 20 kV or in DC at ±20 kV, as presented in Fig. 1. The selection of MVDC voltage was done considering the most common distribution voltage in France and the recommended equivalent DC voltage according to [15]. In AC, there is one MVAC-HVAC station and 80 LVDC-MVAC stations with an AC power conversion chain composed of a 250 kW PV inverter and 50 Hz transformer. In DC, there is one MVDC-HVAC station and 80 LVDC-MVDC stations with a DC power conversion chain including a 250 kW DC SST.

<figure><img src="image_2.png" /><figcaption>Fig. 1: a) Electrical architecture of a linear PV power plant: MVAC collection network, b) MVDC collection network. The scope of the LCA is limited to power conversion chains in red.</figcaption></figure>
## Power conversion chain

The AC power conversion chain is composed of a 250 kW PV inverter and 50 Hz transformer as presented in Fig. 2a. Sungrow SG250HX and Schneider Minera 250 kVA 20 kV transformer are selected as references. The efficiency at the different power points of the inverter in the AC solution are obtained from the datasheet curve of the considered industrial sting inverter [3]. The transformer efficiency curve is obtained from the losses of the Ao-10% Ak category given in [16]. This AC conversion chain includes elements with efficiencies at the high end of their categories.

The DC power conversion chain includes a 250 kW DC SST. The single line diagram of the DC SST is presented in Fig. 2b. It is composed of multiple boost MPPT converters and a unidirectional step-up isolated DC-DC converter. The DC-DC converter is designed as monolithic and it includes an inverter and an oil tank equipped with a medium frequency transformer (MFT), a diode rectifier and output MVDC filter [17], [18]. The targeted efficiency is 98.5% (European weighted average) which is higher than the state of the art (although at the high efficiency end) AC equivalent solution at 98.0%. While offering high energy efficiency, the DC SST is smaller and lighter.

Since the MPPT converters are common to both converters they are removed from the comparison. The MPPT stage efficiency is removed by considering an efficiency of 99.5%, based on values reported in [19], [20].

<figure><img src="image_3.png" /></figure>

<figure><img src="image_4.png" /><figcaption>Fig. 2: a) AC and b) DC power conversion chain</figcaption></figure>

## DC SST design

The DC SST is based on the Phase Shifted Full Bridge (PSFB) topology, as its relevance for the collection of PV power in MVDC has been shown in [17]. The design choices summarized in Table I are made to maximize conversion efficiency. The choice of the switching frequency of 10 kHz is made in this sense as it is the lowest frequency (hence lower losses) for which the MFT magnetostriction is not audible (the magnetostriction happens at twice the switching frequency for a full bridge). The sizing of the values of passive components is done following the method described in [21], optimizing the efficiency weighted average called PV "European efficiency" indicator [22]. The choices of semiconductor components such the LV inverter MOSFETs and MV rectifier diodes are also oriented towards the high efficiency goal, using SiC to keep switching losses low. The use of SiC diodes leads to the necessity to have series connected diodes [23] (maximum 3.3 kV rating in market available diodes). Parallelization of components is also used in order to keep a high efficiency at full power. Film capacitors are used for both input and output DC-links. The magnetics component (MFT and output inductors) cores consist of 3C97 ferrite cores [24] with low losses temperature dependence, ideal for the PV application. The particularity of this DC SST presented in Fig. 3 is that the whole medium voltage circuit is immersed in an oil tank to benefit from the dielectric and thermal properties of the oil. The tank is a steel tank similar to that of a traditional oil immersed 50 Hz transformer, but the usual mineral oil is here replaced by a synthetic ester (Midel 7131 [25]). This dielectric fluid is less flammable and more biodegradable than mineral oil.

<table><caption>Table I: DC SST design choices</caption><tr><td>Inverter</td><td>1.7 kV SiC MOSEFT [26], 2 modules in parallel per position</td></tr><tr><td>Switching frequency</td><td>10 kHz</td></tr><tr><td>Capacitors</td><td>Polypropylene film</td></tr><tr><td>Magnetics core material</td><td>3C97 Ferrite [24]</td></tr><tr><td>Insulating liquid</td><td>Synthetic ester Midel 7131 [25]</td></tr><tr><td>Rectifier</td><td>1.7 kV SiC Schottky diodes [23], 2 in parallel and 7 in series per position</td></tr></table>
<figure><img src="image_5.png" /><figcaption>Fig. 3: DC SST prototype</figcaption></figure>

# Methodology to assess the CO₂ footprint of the conversion chain

## Scope definition

This paper focuses on the CO₂ footprint assessment only and does not cover other indicators present in a complete LCA. Also, this work does not consider the end-of-life phase because of a lack of relevant data. One can expect this phase to be quite similar for both conversion chains, because of the similar integration, and the comparison should thus not be greatly impacted.

## Life Cycle Inventory and Impact Assessment

### Manufacturing phase

The table below provides the different materials and their mass, for both conversion chains.

<table><caption>**Table II: Materials used in the conversion chains**</caption><thead><tr><th rowspan="2"></th><th colspan="2">AC</th><th colspan="2">DC</th></tr><tr><th>Material</th><th>kg</th><th>Material</th><th>kg</th></tr></thead><tbody><tr><td>Semiconductor</td><td>SiC MOSFET</td><td>16*</td><td>SiC MOSFET and diodes</td><td>16* + 22*</td></tr><tr><td>Inverter frame</td><td>Plastic</td><td>30</td><td>Aluminum</td><td>30</td></tr><tr><td>Capacitor</td><td>Film</td><td>5.5</td><td>Film</td><td>7.6</td></tr><tr><td>Heatsink</td><td>Aluminum-air cooled</td><td>29.7</td><td>Aluminum-air cooled</td><td>29.7</td></tr><tr><td>Busbar</td><td>Copper</td><td>1.3</td><td>Copper</td><td>1.5</td></tr><tr><td>Transform core</td><td>Electrical steel</td><td>480</td><td>Ferrite</td><td>172</td></tr><tr><td>Transform winding</td><td>Aluminum</td><td>120</td><td>Copper</td><td>26</td></tr><tr><td>Insulation</td><td>Mineral oil</td><td>275</td><td>Synthetic ester</td><td>306</td></tr><tr><td>Tank</td><td>Steel</td><td>400</td><td>Steel</td><td>565</td></tr></tbody></table>

The carbon emission factors of the materials used in this study are summarized in the table below.

<table><caption>**Table III: Emission factors - manufacturing**</caption><thead><tr><th>Material</th><th>Emission factor (kgCO₂e/kg)</th><th>Source</th></tr></thead><tbody><tr><td>Copper Baseplate</td><td>10.98</td><td>[13]</td></tr><tr><td>SiC Chip</td><td>90000*</td><td>[9]</td></tr><tr><td>Film capacitor</td><td>47.00</td><td>[9]</td></tr><tr><td>Electrical steel</td><td>4.00</td><td>[8]</td></tr><tr><td>Ferrite</td><td>2.03</td><td>[27]</td></tr><tr><td>Copper conductors</td><td>3.80</td><td>[8]</td></tr><tr><td>Aluminum conductors</td><td>5.90</td><td>[9]</td></tr><tr><td>Mineral oil</td><td>3.00</td><td>[8]</td></tr><tr><td>Plastic frame</td><td>6.21</td><td>[8]</td></tr><tr><td>Aluminum heatsink</td><td>27.90</td><td>[9]</td></tr><tr><td>Copper busbar</td><td>10.98</td><td>[9]</td></tr><tr><td>Steel</td><td>1.80</td><td>[8]</td></tr></tbody></table>

The boundaries of the processes considered for the emission factors presented here are not always consistent. For example, in [27], the boundaries of the system contain the raw material acquisition and the manufacturing phase of the ferrites. In [8] a more detailed breakdown is considered for the carbon footprint of the transformers, considering raw material extraction and its transportation to the manufacturing site, then manufacturing of the different sub-components and its transportation to the manufacturing of the final product and finally, the manufacturing of the transformer itself. This highlights the paramount need for reliable databases of emission factors with a clear statement of their limits.

Another weak point of the emission factors presented here is that they are static values, not depending on the evolving energy mix. Databases including energy mix dependencies would enable the projection of current design results into the future.

### Transportation phase

The transportation phase emissions depend on the distance between the manufacturing place and the use place, and the means of transportation used. The extreme cases from [11] are taken and presented in the table below.

<footnote>*cm²</footnote>

<footnote>*kgCO₂e/m²</footnote>
<table><caption>**Table IV: Emission factors - transportation**</caption><thead><tr><td>Scenario</td><td>Footprint (kgCO<sub>2</sub>e/t)</td></tr></thead><tbody><tr><td>China (ship+road diesel)</td><td>704</td></tr><tr><td>Europe (electric rail)</td><td>17</td></tr></tbody></table>

The “China (ship+road diesel)” scenario will always be considered in the results presented below. Considering the “Europe (electric rail)” scenario would result in a negligible contribution from the transportation phase to the overall carbon emissions.

## Use phase

The use phase emissions are evaluated over 10 years. This is at the low end of life expectancy for PV converters.

In [11] the calculation of use phase emissions is performed by considering that the energy losses of the converter still need to be produced. This additional electricity production is then translated to carbon emissions, dependent on the local energy mix emission factor. It is important to note that this calculation approach is only valid when applied to a load application. A certain power is needed to operate the load, whatever the conversion chain losses are. Now, for a renewable energy source application, this calculation approach would represent the assumption that the energy lost due to the conversion chain efficiency must still be produced by the local mix. This method of calculation applied to our case study of renewable energy production will be called “load-like” in this paper.

A second way of calculating the CO₂ footprint of the use phase for a renewable power production conversion chain is to simply equate it to zero since no CO₂ is emitted during the use phase of the converter. However, in this case, the resulting usable energy decreases with the conversion chain efficiency. This method fails to consider the carbon emissions generated outside of the conversion chain, namely during the manufacturing phase of the renewable energy source. This calculation method will be called “renewable source”.

In order to account for the efficiency of the conversion chain, the carbon footprint associated with the energy losses can be translated to carbon footprint through the emission factor of PV production (for our particular case). This method will be called “renewable source constant energy (E)”.

The evolution of the energy mix has an impact on both first and third ways of calculating the carbon footprint. Indeed, in the case of the “load-like” calculation the transition to a low carbon energy mix will directly reduce the use phase carbon footprint. For the PV production case, the evolution of the energy mix will only influence the manufacturing of the PV installation elements. In [28] it can be seen that approximately 50% of the carbon footprint of PV panels comes from the electricity used during the manufacturing process. Thus, a new emission factor for PV production can be calculated by applying to 50% of this value the ratio of today’s energy mix with the future one.

## Mission profile

The mission profile used to calculate the energy production and losses of the conversion chains is built from power fractions and coefficients used in the PV “European efficiency” indicator [22]. The obtained transferred power distribution is shown in the figure below.

<figure><img src="image_6.png" /><figcaption>Fig. 4: Considered transferred power distribution obtained from European efficiency coefficients.</figcaption></figure>

## CO₂ footprint results

### Use phase scenarios

The different methods described in the previous section are applied to the calculation of the use phase for both AC and DC conversion chains. The results are presented in Fig. 5, stacked with the manufacturing and transportation phases in order to show the proportions of each phase.
<figure><img src="image_7.png" /><figcaption>Fig. 5: Carbon footprint repartition between the different phases, for the different calculation methods for AC and DC conversion chains</figcaption></figure>

It can be seen that with the “load-like” method, the use phase, and hence efficiency of the conversion chain, has a predominant impact on the overall carbon emissions. The high efficiency of the DC SST gives an advantage to the DC solution in this case.

With the “renewable source” method, the efficiency has no influence, and the manufacturing phase is the predominant one. The DC SST has here a minor advantage over the AC conversion chain. The manufacturing carbon footprint breakdown of both solutions is analyzed in the next section.

With the “renewable source, constant E” method the manufacturing phase is still predominant, but with the use phase representing 32% (AC) and 26% (DC) of the complete footprints. By considering the evolution of the energy mix towards renewables, it can be seen that the use phase in the “renewable source 2050, constant E” decreases. This scenario gives similar results as the “renewable source” method, reaching the same conclusion that the manufacturing carbon footprint of the conversion chain is the major contributor in the global emissions. However, it must be recalled that here, the manufacturing phase lacks the consideration of the energy mix update. Also, one must note that the design of the conversion chain with lower efficiency would result in larger cooling structures, and hence in an increase of the manufacturing carbon footprint.

## Manufacturing CO₂ footprint breakdown

To analyze the conversion chains' manufacturing footprints, the components of Table II are put together in categories. The structure category includes heatsinks, tank and inverter casing. The bridge category includes semiconductors and capacitors. The magnetics category includes transformers and inductors. The insulation category includes the dielectric liquid.

The repartition in terms of carbon footprint and mass of the AC conversion chain are presented in Fig. 6.

<figure><img src="image_8.png" /><figcaption>Fig. 6: AC conversion chain manufacturing mass and carbon footprint repartition.</figcaption></figure>

It should be noted that the transformer manufacturing carbon footprint found from the emission factors presented in Table III is coherent with the value obtained from the Koncar study [29] of 3.8 kgCO₂/kg cradle-to-gate emission factor (4845 kgCO₂).

The DC SST carbon footprint and mass are presented in the Fig. 7.

<figure><img src="image_9.png" /><figcaption>Fig. 7: DCSST manufacturing mass and carbon footprint repartitions.</figcaption></figure>

The carbon footprint and mass of both conversion chains can be seen as very closely linked. The only exception is the bridge category. However, this category represents a small portion of the total. Indeed, the mass ratio of 1.19 is very close to the carbon footprint ratio of 1.17.

The magnetic components represent a smaller portion of both the carbon footprint and mass in the DC SST case thanks to the operation at medium frequency. Indeed, not only does the MFT use less core material, but this material
(ferrite) also has a lower carbon emission factor than the electric steel used in the 50 Hz transformer.

However, in the studied case, the DC case structure part is more important than in the AC case. This is explained mainly by the inverter casing in the DC case being metallic compared to the plastic casing of the AC solution (837 vs 186 kgCO2). The rectifier and output filter also slightly increase the tank volume and hence its mass compared to the AC solution.

These arguments show that the DC SST has a major improvement potential advantage over the AC conversion chain thanks to the possibility of higher frequency and more compact designs. The limit of this is the thermal management, like in any high power density applications. Indeed, cooling of large power losses would have an impact on the conversion chain mass and carbon footprint. This must be considered when optimizing the DC SST for low carbon footprint. One can also note that the insulation carbon footprint of both solutions can be greatly decreased by changing the dielectric liquid. Indeed, mineral oil and synthetic ester dielectric liquid have similar emission factors but that of the alternative natural esters is much lower (2% of that of mineral oil [30]).

## Conclusion

This paper presented a comparison between the carbon footprint of a DC SST designed for a linear PV application with MVDC collection, and its counterpart for a traditional MVAC architecture.

It has been shown that the manufacturing part becomes the most significant carbon footprint contributor as the energy mix becomes more and more carbon-free. Contrary to the AC conversion chain, the DC SST can be designed at higher frequencies in order to achieve a reduction of the manufacturing carbon footprint.

In order to improve the modelling made in this paper and enable the optimized design of the DC SST, reliable emission factor databases need to be available. These factors need to take into account the energy mix so the performance of a certain design can be evaluated over different scenarios. The LCA of complete AC and DC linear PV plants must be performed in order to get the full picture of the interdependencies of the different elements of the installation in the calculation of the total carbon footprint and other environmental indicators.

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