IMPACT FOR THE DSO OF INTEGRATING STORAGE SYSTEMS IN A LOW-VOLTAGE GRID WITH DISTRIBUTED ENERGY RESOURCES

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1 th International Conference on Electricity Distribution Glasgow, 1-1 June 17 Paper 9 IMPACT FOR THE DSO OF INTEGRATING STORAGE SYSTEMS IN A LOW-VOLTAGE GRID WITH DISTRIBUTED ENERGY RESOURCES João FONSECA Maria Inês VERDELHO Ricardo PRATA Ernst & Young Germany EDP Distribuição Portugal EDP Distribuição Portugal joao.fonseca@de.ey.com mariaines.verdelho@edp.pt ricardo.prata@edp.pt ABSTRACT Implementation of solar photovoltaic (PV) systems in lowvoltage grids (LVG) has increased in recent years and future perspectives account for it to keep growing further with the creation of new energy strategies by the European Commission, as well as changes in regulations and policies in different countries. Technology advancements in solid state physics and electronics, followed by large commercialization, led to a fast decrease of PV systems prices which made them more affordable and a competitive solution for distributed energy production. Such changes require a reformulation of the way electricity distribution is perceived and present new challenges for Distribution System Operators (DSO) that have to find innovative solutions and might need to invest in new technologies such as batteries to manage energy supply. In the past few years there has been a considerable improvement in storage systems such as batteries, whereas it is believed that they will play an important role in future electric grids coupled with PV systems. With this assumptions, it is important first to understand the changes that occur in consumption and production load profiles along the year in a LVG with shifting PV deployment. As a result of this study, it was observed that, for the analysed LVG, it would be more economically efficient for the electric system, composed by clients and distributors, to introduce batteries at a client s-level and that the impact for the DSO will be negligible from a grid losses and grid violations point of view. INTRODUCTION Energy supply is facing significant changes in European countries which are increasing the investment in renewable energy sources (RES). An interesting case of study regarding this transformation is the Portuguese electric power system which has a high potential for the introduction of solar energy and such adaptation is still in an early stage. Solar energy is the fastest growing electricity generator from RES in European Union and Portugal ranks at third place, regarding the proportion of electricity generated from RES [1], only behind Austria (6.1%) and Sweden (61.%) with a total of.% of the electricity generated in 1 coming from RES []. Regardless of this high potential, only 1.% of country s electricity consumption is generated from solar energy. Future perspectives are aligned with the Energy Strategy set by the European Commission for [3] as well as goals established by the Paris Agreement in 1 []. METHODOLOGY A representative rural grid which is mostly composed by residential clients, 7 residential and 1 commercial, was identified having an installed power of kva, a peak load of kw and an annual electricity consumption of MWh during 1. This low voltage grid (LVG) is located in the municipality of Évora where data from solar was acquired. Its topology can be found in Figure 1. Figure 1 Topology of analyzed rural low-voltage grid. For this simulations, the PVSyst software was used and the value of an average yearly production of kwh/kwp was obtained. Data for the whole year with one hour resolution was acquired, which was afterwards interpolated for a time basis of 1 minutes in order to obtain normalized diagrams for PV electricity production. This can be found in Figure 3. As for the consumption at clients-level, all clients were divided into classes, being both residential and commercial/service clients. Then an adjustment was made to the different profiles done by ERSE (Portuguese energy regulator) which generated 9 consumption profiles for each group of clients with the same contracted power. These different profiles were then submitted to a variation in energy and time using a normal distribution. After obtaining both e consumption and production profiles, it was possible to conjugate them with different tariffs that are applied to each group of clients in order to later perform an economic analysis. Different tariffs schedules set by ERSE were used for this analysis. With the aim of understanding the benefits of introducing batteries in the system with an increase of PV deployment, the study was divided between the introduction of PV systems limited for self-consumption and the introduction of PV systems aiming for grid injection without batteries as well as self-consumption when batteries were added, which account for double of the installed PV capacity. This methodology process can be seen in Figure. CIRED 17 1/

2 :1 1:1 :1 3:1 :1 :1 6:1 7:1 :1 9:1 1:1 :1 :1 :1 1:1 :1 3:1 :1 :1 6:1 7:1 :1 9:1 1:1 :1 :1 th International Conference on Electricity Distribution Glasgow, 1-1 June 17 Paper 9 Figure - Modeling layout scheme used for building scenarios. 3 Yearly changes on consumption curve, Yearly changes on production curve autumn winter spring summer 1,1,, Figure 3 - Consumption and production curves along the year for the chosen location. CIRED 17 /

3 :1 1: 1: :3 3:1 : : :3 6:1 7: 7: :3 9:1 1: 1: 11:3 13: 13: 1:3 : : 17:3 19: 19: :3 : 3:3 :1 1:1 :1 3:1 :1 :1 6:1 7:1 :1 9:1 1:1 :1 :1 th International Conference on Electricity Distribution Glasgow, 1-1 June 17 Paper 9 RESULTS It was observed, in an annual basis, that electricity fluxes from medium voltage grid (MVG) to LVG are expected to decrease with an increase in PV capacity. Figure can also elucidate that most of these reductions will occur during peak hours. Contrarily, when storage was added, these fluxes had the tendency for a tenuous increase which can be justified by the round-trip efficiency of the batteries. Nonetheless, such increase is lower than the batteries efficiency differential because batteries are not used in full cycle during all year since they only absorb PV electricity. In the opposite direction the fluxes from LVG to MVG will increase exponentially with the increase of PV capacity and then decrease linearly with the increase of storage capacity. On a yearly average, this flux will be increased by a tenth of the electricity consumed by the LVG. 1% % 1% 9,% 91,% 7,3% Changes in electricty fluxes from MVG to LVG 3,1% 79,7% Off-peak Peak Total 76,9% 7,7% 7,9% 73,% 73,7% 7,1% 7,6% 6% 6,%,7%,%,3% 6,%,9%,1% 3,% 36,% 3,7% 3,3% 3,7% 3,3% % % 37,% 37,1% 37,% 37,% 36,9% 36,% 36,% 36,7% 36,6% 37,% 3,% 39,3%,3% % 1% PV % PV 3% PV 3 % PV 3% BAT 6% BAT [% electricity from LVG to MVG/ electricity from MVG to LVG] 1% Changes in electricity fluxes from LVG to MVG % 6% % % % 1% PV % PV 3% PV 3 % PV 3% BAT 6% BAT Figure - Bidirectional changes in electricity fluxes on a yearly average between MVG and LVG. It has to be pointed out that the impacts of different scenarios are on daily basis. It was observed, on a yearly average basis, that with an increase in PV capacity the electricity consumption decreased almost linearly on a vertical axis. Whereas with an increase in storage capacity this change was barely noticed before near sunset hours and deviated with a slight delay angle for evening hours leading to a decrease in the peak consumption. According to Figure, in the opposite direction fluxes will first increase exponentially with introduction of PV capacity and then decrease linearly when adding storage capacity to end-users. A slight delay to late hours of the electricity injected with the introduction of batteries was observed in Figure due to charging. Most of this reduction occurs during peak hours and will be a quarter of the maximum injection. Electricity fluxes from MVG to LVG Electricity fluxes from LVG to MVG 17, 3, 1 3 1% PV 1 % PV 1 3% PV 7, 1, 3 % PV 1 3% BAT, 6% BAT Figure - Bidirectional changes during a day representing yearly average electricity fluxes between MVG and LVG. CIRED 17 3/

4 :1 1:3 : : :1 6:3 7: 9: 1:1 11:3 1: :3 19: :1 1:3 : :1 1:3 : : :1 6:3 7: 9: 1:1 11:3 1: :3 19: :1 1:3 : :1 1:3 : : :1 6:3 7: 9: 1:1 11:3 1: :3 19: :1 1:3 : th International Conference on Electricity Distribution Glasgow, 1-1 June 17 Paper 9 Grid Losses I: Electricity Consumption peak To analyse the impact of an increased PV and storage capacity on grid losses, the two days with highest fluxes between MVG and LVG in both directions were identified. The highest flux from MVG to LVG occurs within the day of consumption peak and in the opposite direction when the highest injection of electricity to the grid was observed. Grid Losses II: Electricity Injection peak For the day of highest flux from LVG to MVG, no voltage or current violations were observed. Figure shows that percentage of losses by supplied energy has tendency to increase exponentially with increase of PV capacity (mainly related with reduction of flows from MVG) while it will decrease almost linearly with storage capacity. Losses distribution grid [3..1] [1.6.1] % %,% 3,% 1,% 1,% 1,% 1,%,%,%,%,% Losses on distribution grid 1 7, % losses by supplied energy total losses % losses by supplied energy total losses Figure 6 Grid losses for the day of consumption peak. As it can be seen in Figure 6, the grid losses remain almost constant during different scenarios for the day of electricity consumption peak both on a total energy observation as well as in percentage of supplied energy. This is justified by the fact that no major changes were observed on the consumption curve when both PV and storage capacities increase as it can be seen below. Figure Grid losses for the day of injection peak. Figure 9 elucidates the fact that there is a big variation on the load curves and that energy flows in both directions are in the same order, which can justify the high increase of internal fluxes of energy inside the grid between different end-costumers. Also the introduction of storage will increase hosting capacity for the introduction of more PV capacity based on a decrease in losses Electricity flux from MVG to LVG 1% PV % PV 3% PV 3 % PV 3% BAT 6% BAT Electricity flux from MVG to LVG 1% PV % PV 3% PV 3 % PV 3% BAT 6% BAT Figure 7 Electricity fluxes during consumption peak. For the analysed day, no fluxes of electricity from the LVG to the MVG were observed and consumption did not reached zero. The small changes with different scenarios also justify the small variation of grid losses, given that there is no creation of internal electricity fluxes. No current violations were observed in the different simulated scenarios. However, voltage violations occurred in two occasions, at 19: and at :1. Both were observed only during the following period of 1 minutes. As shown in Figure 7, these periods correspond to the highest consumption peaks and could be attenuated when batteries were programmed, which was not considered Electricity flux from LVG to MVG Figure 9 Electricity fluxes during injection peak. 1% PV % PV 3% PV 3 % PV 3% BAT 6% BAT CIRED 17 /

5 th International Conference on Electricity Distribution Glasgow, 1-1 June 17 Paper 9 Changes in consumption Given that neither current nor voltage violations were caused by an increase in PV or storage capacity, it can be said that their integration is plausible. It was also observed in Figure 1 a considerable difference between electricity consumption from end-users along the year and how this can be reduced in the different scenarios when integrating different technologies. Winter consumptions are almost twice the annual average and its reduction is very limited, given that there is not a big production of solar electricity. Contrarily, summer consumptions are almost half the annual average and its reduction can be decreased up to % of initial consumptions when PV is widely deployed. 1 1% 7% % % % Comparison of changes in consumption Comparison of changes in consumption [%] MIN MAX MED AVE Figure 1 Yearly variations on electricity consumption. Batteries at Client s-level vs Grid-level In this study it was considered that the placement of batteries at a client level is more efficient than the placement at grid-level. This comes from the fact that, even though the required capacity would be lower, these batteries would have a lower utilization factor since batteries in end-users can be used even when there is no flux of electricity from the LVG to the MVG. From an end-user perspective, batteries placement will be more beneficial at client s-level given that programming of batteries utilization is not considered. Therefore its impact will be only decreasing electricity consumptions during peak hours rather than being used for peak shaving of the overall load curve. Additionally there is the benefit of acting directly on internal electricity fluxes caused by the PV s being dispersedly installed. CONCLUSIONS As a conclusion from this study it was observed that for the given LVG that was analysed, there is no technological barrier to the implementation of PV and storage capacity from a grid losses perspective as well as current and voltage violations. It was also concluded that the introduction of batteries will lead to an increase of the hosting capacity for this grid given that it will reduce internal electricity fluxes between different end users as it decreases the grid losses alongside the consumption of the end-users. This benefit will be mostly observed during peak hours where electricity consumption was decreased by half when considering a PV installed capacity of % of kwp/kva which will be mostly beneficial to the end-user. Furthermore it was also possible to conclude that for the DSO the only drawback when implementing PV aided by storage capacity is that load curves will have a higher variation during the day, especially in days where it is observed a high difference between electricity consumption and production. However the annual consumption peak was assumed to stay constant since it occurred at off-peak hours and that batteries are not being programmed to discharge at different times to create peak shaving in off-peak hours. A solution proposed for future studies is the integration of a Technical Virtual Power Plant, where both the PV systems and storage installed might be controlled by the DSO, giving it the ability to program batteries to shift loads to create peak shaving as well as the interaction between different LVG with different load curves. There is also the possibility of using storage systems also at a MVG level to aid the transaction of electricity in-between grids. Lastly, given the current price evolution it was observed that for the end-user batteries would only be beneficial when prices are reduced to 1 /kwh which is estimated to be achieved by. Also, there is a need of changing the regulations regarding PV injection remuneration since the price for injection would need to be at market price. REFERENCES [1] Eurostat, 13. Renewable Energy Statistics. URL index.php/renewable_energy_statistics [] APREN, 1. Boletim das Energias Renovávies. URL energias_ dezembro_1.pdf [3] European Commission, 9. Action Plan Portugal. URL documents/dir_9 action_plan_portugal.zip [] UNFCCC, 1. Adoption of the Paris Agreement. URL ttps://unfccc.int/resource/docs/1/cop1/eng/ l9r1.pdf CIRED 17 /