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Electricity Market Impacts of Low-carbon Energy Transition in the Nordic-Baltic Region

The Baltic countries Estonia, Latvia and Lithuania are well connected to the Nordic countries Finland and Sweden on the electricity market, yet in a different position facing the transition to a low-carbon electricity system. While especially Sweden is a large electricity producer and net exporter, the Baltic countries suffer from a lack of capacity, which makes them highly dependent on trade. In addition, the present electricity mix of Estonia is very carbon intensive compared to the Nordic countries. There is a debate regarding nuclear power in Sweden. This paper explores four possible solutions for a Nordic-Baltic electricity system: with and without nuclear power in Sweden and with the current transmission network, as well as with a considerably expanded network. The impact on electricity mix, electricity prices, carbon dioxide intensity and import dependence in the Baltic countries from the EU transition to electricity systems with very low carbon dioxide emissions is investigated. The electricity and district heat market model Enerallt is used to quantify electricity prices, electricity trade and system costs. The results show that the development of the transmission network affects electricity prices and especially electricity trade in the Baltic countries. With transmission expansion, the demand weighted average prices in the Baltic countries increase from 62 €/MWh to 65 €/MWh and 70 €/MWh with and without nuclear power in Sweden, respectively. If transmission is expanded, phasing out nuclear power in Sweden can increase the revenue from electricity export by over 100% for the Baltic countries. However, significant new investment in wind power is required.


INTRODUCTION
During the last decade, the EU has seen a growing trend towards a larger share of energy from renewable sources. In 2018, the share of energy from renewable sources in gross final The Baltic countries depend on their neighbours to provide them with energy, mainly electricity and natural gas [18]. The HVDC transmission lines EstLink1 and 2 between Estonia and Finland were built in 2006 and 2014 [19], and Estonian net import from Finland was 3.7 TWh in 2019. Lithuania has been connected to Sweden since 2015 [20]. Thus, it is possible that decisions regarding energy policy in the Nordic countries can affect economic and energy security factors in the Baltic countries. Thus, improving the trade balance of energy commodities with competitive domestic resources is an issue which should be considered also from the point of view of supporting national economy.
So far, less attention has been paid to the long-term European transition to carbon neutral electricity systems and, as part of that, the role of Nordic countries' policies on the Baltic countries. Several policies to decrease CO2 emissions, which could have an impact on energy Year 2022 Volume 10, Issue 3, 1090407 transition in the Baltic countries could be imposed in the Nordic countries. Here, we focus on the effect of phasing out nuclear power together with ambitious transition to carbon neutral electricity systems. In Sweden, there is an ongoing debate about the future of nuclear power generation [21] due to, among other things, issues of health, the risk for accidents, the profitability of old nuclear reactors and nuclear waste disposal [22].
This paper investigates the effect on the Baltic countries from two policy decisions that may be present in a future European low carbon electricity system: (i) to phase out nuclear power in Sweden and (ii) to significantly increase the transmission capacity between the Nordic and Baltic countries. The study focuses on the effect on electricity prices and cross-border trade. Cross-border trade is further analysed to determine whether trade flows between the Baltics and their neighbours are balanced, or if there is a large net import/export. Findings are analysed and discussed in light of the electricity dependence of the Baltic countries on their neighbours, as well as the dependence of these small countries on policy decisions made in their significantly larger neighbouring countries of the joint electricity market. As the Baltic countries are dependent on their neighbours, it may be expected that these policies would bring about challenges for these countries. However, we show in this paper that there would be opportunities for these countries.
The overall structure of the study takes the form of six main chapters. After this introduction, literature review is presented. Then the materials and methods of this work are presented, followed by results, discussion and conclusion.

LITERATURE REVIEW
Several prior studies have surveyed aspects of energy transition. Blumberga et al. [23] applied a system dynamic model that took into account the cost of the capacity mix until 2050 in Baltic region. They found that by 2050, electricity imports would decrease due to the use of renewable energy sources. Bompard et al. [18] carried out investigations to assess electricity independence in the Baltic region in 2020 and 2030, showing that planned capacities are adequate to meet electricity demand. However, additional grid investment is needed to provide the security of supply. Helistö et al. [24] examined the role of thermal power in the presence of highly variable renewable energy generation in the Nordic-Baltic countries, Poland and Germany utilizing the Balmorel and WILMAR models. They demonstrated that the level of energy system flexibility and the share of different generation technologies affect electricity prices. CO2 emissions dramatically decrease in all their scenarios. Ramp rates and generation mix are affected by the share of renewable technologies. Lund et al. [25] analysed scenarios for a zero-emission transition in the Nordic-Baltic region, providing different scenarios using the Balmorel energy system model to assess the transition with respect to different technical, economic, regulatory and policy issues. They showed that cost minimization leads to a Baltic power sector dominated by renewables. They argue that policy actions are needed for the social side of this transition, such as social acceptance of wind power construction. To determine the effect of carbon price on energy security in Finland and the Baltic countries, Galinis et al. [26] studied two price paths by the Finnish-Baltic Energy Model (FIBEM). They showed that in both scenarios, the energy security level in the context of energy transition is not affected by the carbon price path. Chen et al. [27] used the energy model Balmorel to examine economic impacts of cross-border transmission in Northwestern Europe. Optimal transmission capacity is compared with the current and planned capacities. They showed that with transmission expansion total system cost is decreased. Moreover, more wind power is installed, resulting in less total carbon dioxide emissions. However, they found that benefits distributed asymmetrically among regions and this may be a barrier to increase power exchange cooperation. Streimikiene [28] applied MCDM tool and energy transition and energy poverty indicators to compare the Baltic states. It is found that Latvia is the best performing country according to the examined indicators. Jåstad et al. [29] studied the use of woody biomass in heat and power sector in Northern Europe by applying Balmorel. They demonstrated that increased use of woody biomass results in lower fossil emissions and transition to low carbon energy system would be more costly if biomass is excluded from the power and heat sector.
There are several previous studies that have focused on the effect of one country's decisions within the power sector on neighbouring regions. Kittel et al. [30] investigated the impacts of phasing out coal in Germany on the Central European electricity market using a dynamic electricity model. Their results indicate that this policy in Germany has a significant impact on the decarbonization effort and electricity trade in central Europe. Farsaei et al. [31] presented short and medium term scenarios regarding replacing hard coal with biomass in Finland before year 2030 due to recent Finnish legislation, along with restricting nuclear power in Sweden, showing that this policy will affect prices and CO2 emissions in the Baltic countries. Zakeri et al. [32] used the Enerallt model to analyse the effect of Germany's transition to variable renewable energy sources on the Nordic power market in terms of social welfare. They found that the energy transition in Germany increases the electricity prices in the Nordic region. Although the increase in the electricity prices decreases the consumers' surplus, social welfare will improve in the Nordic countries as producers' surplus increases due to market couplings with Germany. However, this improved social welfare is not evenly distributed in the Nordic countries. Swedish electricity consumers will lose the most among the Nordic consumers while Norwegian hydropower producers achieve the highest economic gain among producers. Glomsrød et al. [33] have demonstrated that the nuclear phase-out scenarios in Germany and Switzerland is likely to have a minor effect on electricity prices in Europe.
Previous studies focusing on the Baltic electricity system analysed the changes in local issues such as investment cost, capacity mix, cross-border transmission on economic aspects and security of supply in these countries under carbon neutral electricity system. This study investigates the possible impacts on the Baltic countries from non-local policies. Compared to [23] this study examines the expected effect of transition to carbon neutral electricity system on power import and export. of individual countries.

MATERIALS AND METHODS
In this paper, two models are employed: the greenfield investment model (REX) and the dispatch model (Enerallt). Four low-carbon electricity system scenarios (see Table 2), which differ in terms of the existence of nuclear power in Sweden and the level of transmission expansion, are explored. Figure 1 provides an overview of the methods used in this paper.

The REX model
The REX model [34] is a greenfield optimization model for capacity investment and dispatch with respect to electricity generation, transmission, storage and demand response. It seeks at minimum cost portfolio for the future electricity system with an overnight investment approach. The objective of the model is to minimize the total annual electricity system costs, given the constraints of meeting electricity demand, renewable energy resource potentials and a CO2 emission cap. The investment options for generation technologies, transmission and storage capacity are shown in Figure 1. For more details regarding the model, please refer to reference [34].
In this study, we model a future interconnected European electricity system for the year 2050 using an hourly time resolution with a CO2 emission cap of 10 g/kWh, roughly equivalent to a 98% reduction in CO2 emissions for the European electricity sector, as compared with the emissions in 1990. Since the study focuses on the northern part of Europe, we also provide a more detailed spatial resolution for this region. We assume all the regions are interconnected with high-voltage direct current (HVDC) transmission grids. The approximation is made based on the fact that many of the international connections are already controllable point-to-point HVDC connections and this trend is likely to continue in the future [35]. In addition, this assumption is consistent with the fact that the cross-border connections are treated with Net Transfer Capacities (NTCs) in market clearing process for many countries [36]. For more detailed assumptions see reference [34]. For the costs of different technologies, see reference  include Norway (NO1, NO2, NO3, NO4, NO5), Denmark (DK1, DK2), Germany (DE) and Poland (PL). Due to data availability, electricity exchange with Russia and Belarus is assumed to be fixed at 2018 level. Generation mix in modelled regions is modelled as technologyspecific. Included technologies are presented in the Appendix  (1) is to minimize short-term operation costs in the power sector (and in the district heating sector): � ℎ , + � , , + � � In (1) pij,t represents the power supply of technology i in bidding area j, pijk,t is the power supply of technology i in bidding area j that is exported to bidding area k and cij,t is the short-term marginal cost of production for technology i in bidding area j. Moreover, in eq. (1) hijn,t represents the heat supply of technology i in bidding area j in district heating network n, cij,t, is the short-term marginal cost of heat conversion of technology i in bidding area j. In eq. (2) dk,t is the electricity demand in bidding area k. Moreover, in eq. (2) hikn,t/ηi is the electricity demand of heat conversion technology i that is consumed in heat conversion process (e.g. heat pump). In eq. (3) NTCjk,t is the net transmission capacity between bidding areas j and k. In eq. (4) Pij,t is the available electricity generation capacity for the technology i in bidding area j. In eq. (5) rij is the ramping factor. In eq. (6) qkn,t is the heat demand in the district heating network n in bidding area k. Moreover, in eq. (6) heat supply of CHP technology i in bidding area k is coupled to the power supply pi,t by heat-to-power ratio θi,t. In eq. (7) Hikn,t is the available heat conversion capacity for the technology i in district heating network n in bidding area k. In the equations, t is the hour index. A more detailed description of the model (including description of hydropower simulation) is presented in references [31,42]. Moreover, validation of the model is presented in [42].

Long-term electricity system scenarios
In this study, the REX and Enerallt models are combined by utilising the optimal capacity scenarios of REX as input to Enerallt. The REX scenarios are based on the conceptual framework proposed by Kan et al. [34]. Four different scenarios are analysed ( Table 2). Nuclear power has been the subject of a long-running debate in Sweden [43-45]. Moreover, transmission expansion by 2050 may impact the results. Thus, these scenarios cover two hypotheses. In the first scenario (S1), nuclear power is removed from the electricity mix in Sweden, while transmission lines are fixed. In second scenario (S2), Sweden maintains the present amount of nuclear power and transmission lines are fixed. In the third scenario (S3), transmission lines are expanded and there is no nuclear power in Sweden. In the last scenario (S4), transmission lines are expanded and Sweden maintains nuclear power. Fixed transmission is the actual transmission capacity in 2014 and transmission expansion for 2050 comes from the REX model. The transmission capacities in the two variants are given in Appendix  Table 2. Basic features of the scenarios studied (Scenario 1 (S1), Scenario 2 (S2), Scenario3 (S3) and Scenario 4 (S4)) No. Scenario description Sweden nuclear power transmission Scenario 1 (S1) -fixed transmission (2014) The Enerallt model input, which comes from the REX model and includes capacity mix per country /region, is presented in the appendix (see Table A. 1- Table A. 3). We selected Finland, Sweden and the Baltic countries, for modelling at a country level. The Baltic countries are the target countries for this study, while Finland was included owing to its strong connection with Estonia and being a large producer and consumer, and Sweden was modelled because of the scenarios assessing the nuclear power decisions being made in the country.

Electricity system costs
Each of the above scenarios in Table 2 provides different electricity system costs. The cost components for the country are provided in the following equation: = + + + − (9) where is the total annual electricity system cost, is the annualized investment cost. The annualized investment cost is computed by considering a 5% discount rate. Since the transmission line capacities are symmetric it is assumed that transmission line investment costs are shared equally between bordering countries. is the fixed operation and maintenance costs (O&M cost). is the variable cost which includes the variable O&M cost and fuel cost. With regard to CHP production, fuel costs are allocated to heat and electricity using energy method and only fuel use in CHP electricity production is included in electricity system costs. In equation (9), is the exchange cost that is the cost of importing electricity minus the revenue from exporting electricity. is the congestion income: where and are the countries trading electricity through transmission lines in hour . , − , describes the area price difference between country and country . , − , is the commercial flow between two countries. Eq. (10) comes from the agreement between the Nordic TSOs that congestion income is shared in equal proportions [46]. Moreover, since transmission line capacities are symmetric between country i and country j [34], it is also assumed that investment costs for transmission line capacities are shared equally between country i and country j.
In order to compare the electricity system cost between countries, average cost is computed as follows: ave = � (11) where is the demand for the country .
The economic input data is provided by Kan  . Variable costs are estimated based on the electricity production data from the Enerallt model and fuel price and technology-based variable O&M cost presented in [34]. For CHP, the energy method is used to allocate costs for heat and electricity. However, only the electricity part is included. Exchange cost and congestion income come from the Enerallt model. In the scenarios of the Enerallt model, carbon dioxide emission trading price was assumed 30 €/ton CO2. However, there was practically no fossil electricity generation.

RESULTS
In this section selected metrics are used to analyse electricity dependence in the Baltic countries. Metrics include electricity supply mix and electricity trade to analyse the security of supply and CO2 intensity, as their improvement contributes to reducing electricity dependence. This topic can be treated under three headings: Effects on the electricity supply mix, impacts on electricity prices and trade and impacts on CO2 emissions. In each section, the effect of policies regarding nuclear power and transmission expansion is studied.
Effects on the electricity supply mix and electricity system costs Figure 2 shows electricity production in different scenarios. Electricity production data from 2017 is also shown to provide a comparison with the current situation [12]. Data for current situation of Estonia comes from [47]. Figure 2 shows that transmission expansion would affect electricity production significantly, causing the region to become more dependent on wind power. This level of dependency is less significant in Finland, as nuclear power capacity is considered constant. It is notable that in S3 and S4, no investment is made in solar PV, natural gas and biogas generators. Wind power production especially in the Baltic countries increases income from the electricity trade. Other policies in neighboring countries may affect the optimal capacity mix, which derives from the REX model (see Appendix Table A. 1-Table A. 3).
Electricity production in Lithuania increases significantly in all four scenarios compared to 2017. The electricity generation in Lithuania was 4.2 TWh in 2017. This amount is 12 TWh in S1 and S2, 27 TWh in S3 and 18 TWh in S4.

Sweden Finland
Estonia Latvia Lithuania  power in Sweden cause the lowest total system costs for the whole region considered here. For the Baltic countries and Finland, the transmission expansion scenarios entail less costs. For Sweden, cost decreases through transmission expansion while nuclear power is phased out. However, for Sweden the highest cost occurs in S4, where a significant investment cost is needed to provide a huge amount of nuclear and wind capacity.

Sweden Finland
Estonia Latvia Lithuania (ATESC is average total electricity system cost) †

Impacts on electricity prices and trade
The impacts of these different scenarios on electricity prices are presented in Figure 4. As shown in Figure 4, in S1 and S2, where transmission is fixed, no significant increase in prices was detected. By expanding the transmission line connection in the Nordic-Baltic electricity † Investment costs and fixed O&M costs are from REX model and the other costs are from Enerallt. Other costs include fixed and variable O&M cost and fuel cost. Fuel tax is not included in fuel cost. Only electricity part of CHP production is considered. Year 2022 Volume 10, Issue 3, 1090407 market and Poland, the scenario with nuclear power in Sweden (S4) has lower electricity prices than does the case where nuclear power in Sweden is decommissioned (S3). This decrease is 6%, 7% and 8% in Estonia, Latvia and Lithuania respectively. In transmission expansion scenarios (S3 and S4), Estonia has the lowest electricity prices (67 €/MWh in S3 and 63 €/MWh in S4), while Lithuania has the highest (74 €/MWh in S3 and 68 €/MWh in S4). In these scenarios, Lithuanian prices are even higher than Sweden (72 €/MWh in S3 and 66 €/MWh in S4) and Finland (72 €/MWh in S3 and 64 €/MWh in S4).
Unlike the Baltic countries, Sweden and Finland have the lowest prices in S4. This can be due to the large number of wind power installations in all countries and nuclear power in Sweden, which affect electricity price decreases in Finland and Sweden compared to the scenarios where transmission is fixed. In S4, maintaining the existing amount of nuclear power brings an opportunity for Sweden to obtain more income from exporting electricity.  Figure 5 provides an overview of import and export between the selected countries and the neighbouring countries. From the Figure 5, we can see that trade appears to be unaffected by Sweden's nuclear power policy when the transmission is fixed (S1, S2). In the transmission capacity expansion scenarios (S3, S4), all countries become net exporters. From S3 to S4, where transmission lines are developed, nuclear power in Sweden decreases the amount of trade in the other countries, especially in Lithuania (8.84 TWh). However, Sweden then exports more electricity. What is interesting about the last scenario is the trade between Lithuania and Poland. Lithuania mainly exports electricity to Poland in the capacity expansion scenarios (S3, S4). However, this trade decreases in the last scenario. Sweden is also exporting electricity to Poland. In S4, Sweden's net export to Poland is 51 TWh. It seems that in S4, where Sweden has nuclear power and transmission lines are expanded, it is less profitable to invest in wind power capacity in the Baltic countries. Thus, Sweden provides more electricity to Poland and the trade between Lithuania and Poland decreases. Through transmission In order to analyse countries dependency on importing electricity, hourly time series of trade have been studied. Hours can be categorized into peak, off peak1 and off peak2. Peak refers to the period from 8 am to 8 pm. Off peak1 refers to the time period from midnight to 8 am. Off peak2 refers to the time period from 8 pm to midnight. This classification is based on S1 Nord pool spot [48]. In transmission expansion scenarios (S3 and S4), all countries have less net import. In these scenarios, during peak hours and off peak 1 hours, maintaining nuclear power in Sweden causes more importing for the Baltic countries. Maintaining nuclear power in Sweden in S4 reduces dramatically the hours that Sweden is net importer. In S4, Sweden is net importer during 5% of hours, while this amount is 47% for Estonia, 30% for Latvia and 35% for Lithuania.
As shown in Figure 6, in S1 and S2, where transmission is fixed, nuclear power in Sweden cannot affect the amount and expected income from the electricity trade. In these scenarios, in all countries except Latvia, the electricity they import from other countries is generally more expensive than their income from export.
Transmission line expansion has a significant impact on revenue in the Baltic countries, especially in Lithuania, due to the large number of wind energy installation with large electricity generation capacity, which provides countries with an opportunity to trade electricity. Closer inspection of the Figure 6 shows that by expanding transmission lines, nuclear power removal in Sweden could increase revenue from export in all countries. Revenue from export is decreased in the Baltic countries when Sweden retains its nuclear power and new transmission lines are built between countries. This decrease is 38%, 26% and 46% for Estonia, Latvia and Lithuania, respectively. This can be due to a lower in wind power capacity in the Baltic region in S4 compared to S3, which results in less income from exporting electricity to neighbouring countries.  Figure 7 illustrates CO2 intensity rates in the studied countries. For CO2 intensity, CO2 emission is divided by the total power production per fuel source [49]. No significant differences were found in the CO2 intensity rates of countries in S1 to S2 or S3 to S4, where only nuclear power was changed. Transmission expansion affects the Lithuanian CO2 intensity significantly, as natural gas would not be needed. In S3 and S4, Finland, Estonia and Lithuania all generate electricity mostly with renewables, while Latvia switches 100% to renewables, resulting in further decrease in CO2 intensity rates in the Baltic countries. The reader should note that in the REX model, where the generation capacity scenarios stem from, at European level the CO2 emissions were the same in scenarios S1-S4.

Summary of results
The results for different scenarios are summarized in Table 3. Although the nuclear power policy is a national policy for Sweden, it affects the Baltic countries and Finland. If transmission capacity is fixed, allowing nuclear power in the future Swedish electricity system has little impact on the average electricity system cost for the Baltic countries. However, the inclusion of nuclear power in Sweden might have large impacts on the trade revenues for the neighbouring countries. Specifically, Estonia, Latvia, Lithuania and Finland face a 35%, 11%, 2%, 2%, and 35% drop in income from exporting electricity respectively, as compared to the case where nuclear power is not allowed in Sweden. Thus, Sweden's nuclear power policy on its neighbours' income is considerable even with the current amount of transmission connections.
In the case of optimal transmission expansion, the availability of nuclear power in Sweden enables a significant increase in revenue from electricity trade for Sweden as compared to no nuclear in Sweden. Meanwhile, the trade income for Finland and the Baltic countries is reduced. The average electricity system cost for Baltic countries is higher in S1 than in S3, while the electricity price shows an opposite pattern. In S4, the Baltic countries have less installed generation capacity compared to S3. However, the exchange cost and congestion income have affected the average electricity system cost in these countries. Thus, there could be a possible trade-off for the Baltic countries. In S3 when there is no nuclear power in Sweden, Baltic countries may experience higher prices. However, these higher prices are provided by lower cost due the electricity trade opportunity. In S4, they experience lower prices while they have less opportunity to trade electricity and this can bring about more costs. The main reason is that, in S3, nuclear power is not installed in Sweden, the Nordic and Baltic countries rely more on each other for electricity trade to share variable renewable energy and dispatchable resources, as compared with S4 where nuclear power is installed for Sweden. The relatively high income from electricity trade for the Baltic countries offsets the investment cost in S3. In addition, the exclusion of flexible nuclear power in the Swedish electricity system results in less flexibility for the highly renewable regional electricity, which drives up the electricity price.  Table 3. Scenario comparison for the modelled countries. The electricity trade revenue and the average total system cost for each region in the scenarios studied is shown. The reader should note that the average electricity system cost includes the annualised investment cost, fixed operation and maintenance cost, variable O&M cost, fuel cost, exchange cost and congestion income, as specified in eqs. (9) and (10) Trade revenue (Million Euro)

DISCUSSION
The present study was designed to determine the effect of long-term transition to carbon neutral electricity systems in Europe, together with local policies regarding nuclear power in Sweden and expanding transmission between countries in Northern Europe, focusing on the effects on the Baltic countries and the regional electricity trade. In this regard, the impacts on electricity market prices, electricity trade, the revenue generated by the electricity trade, electricity system costs and CO2 emissions are quantified. To the best of authors' knowledge, very little has been written to date on the question of how the Nordic countries' policies affect the Baltic countries in the context of transition to carbon neutral electricity systems. Moreover, studies that have surveyed the effect of policies in one region on other areas often ignore the impacts of transmission development.
Despite the results presented in this paper, some questions remain unanswered. The scope of this study was limited in terms of studying the Baltic countries by modelling Sweden, Finland and the Baltic countries. However, as the Nordic-Baltic electricity market is interconnected, the effect of national decisions on the whole region can be surveyed in future studies, also considering in detail plausible developments in adjacent large electricity market regions Germany and Poland. Considerably more work will need to be done to determine the security of supply in this region. This study employed some approaches that may have altered the results. First of all, Sweden is discussed more as a uniform country model than four different bidding zones. This may have affected the results, as some internal trade restrictions may have been ignored. Moreover, the REX model has some limitations that can change the outcomes. Results are very sensitive to the input coming from this model. The limitations have to do with spatial resolution, the lack of ramping constraints on thermal technologies and weather data, all of which are explained in Kan et al. [34]. For renewables, a fixed production profile was used. The GIS model proposed by Mattsson et al. was used here and the capacity factors were computed based on solar radiation and wind speed [50]. These profiles also can have an impact on the results.

CONCLUSIONS
According to the cost-optimal scenarios of the REX investment model, wind power is the dominating low carbon electricity generation in the region studied together with the existing hydropower. The REX model results show that with transmission capacity expansion, investing in solar PV, natural gas and biogas is no longer profitable in the studied region and the possibility for wind energy capacity installation increases. Along with the realization of these investments, the Baltic countries would turn to net exporters of electricity. In S3, where there is no nuclear power in Sweden, the net export would be 6.04 TWh, 4.98 TWh, and 15.39 TWh in Estonia, Latvia, and Lithuania, respectively. In presence of nuclear power in Sweden, these amounts decrease to 1.72 TWh, 2.72 TWh, and 6.55 TWh in Estonia, Latvia, and Lithuania, respectively. Transmission expansion would be beneficial for all Baltic countries in these scenarios. Their average total electricity system cost ( Table 3), as indicated by the scenarios studied, would decrease compared to the situation with current (2014) transmission capacity. This reduction of the average total electricity system cost in case of no nuclear power in Sweden is 29 €/MWh, 30 €/MWh, and 48 €/MWh in Estonia, Latvia and Lithuania, respectively. By maintaining nuclear power in Sweden, this reduction in average total electricity system cost is 16 €/MWh,24 €/MWh, and 23 €/MWh in Estonia, Latvia and Lithuania, respectively.
If the transmission capacity is kept at the current level, including nuclear power in Sweden has limited impacts on the average electricity system cost and electricity price for the Baltic countries. In the case of maintaining only the present transmission capacity, the Baltic countries would need to invest significantly more in their own generation capacity, yet they would not enjoy trade net revenues.
It is interesting to note that with respect to the factors studied in this paper, transmission expansion policy affects the results the most. The findings presented in this study provide new understanding of local policy implications at the international level, as listed above. Compared to the earlier studies, e.g., [23,25], this paper quantified in detail the expected country-level impacts of both European low carbon transitions and of the decisions of individual countries on the neighboring countries. The findings of the study have practical relevance for the Baltic countries. Phasing out nuclear power in Sweden can provide these countries with an opportunity to improve their electricity trade. However, it requires transmission expansion and significant new investment in wind power capacity. By greatly increasing the amount of wind capacity in the future, the efficiency of the energy system could be improved by electrifying district heating sectors or enhancing storage solutions. Then, less electricity would need to be exported to neighboring countries and wind power investment could help the decarbonization of other sectors as well. This option would bring benefits regardless of international transmission grid development.
Regarding the importance of wind power as the most potential RES source in the region, our results are in line with the earlier findings of [23,25]. It is important to remove both technical, economic and social barriers that can prevent the expansion of wind power in this region. This study did not fully encompass RES expansion in the entire Northern Europe countries. This is one important source of uncertainty in this study. Future studies may consider this expansion for Norway, Denmark, Germany, and the UK, as these countries are connected. Moreover, both the modelling of the demand flexibility and storage systems should be included in the planning. Especially, flexibility of demand can contribute significantly to balance the electricity system with large amounts of wind power.

ACKNOWLEDGMENTS
We sincerely thank Dr. Lina Reichenberg (Chalmers University of Technology, Aalto University) for her valuable comments. The work of A. Farsaei was partly funded by the PlanFES project of Aalto University Science Institute, and the work of A. Farsaei