Abstract Offshore wind farms are gradually being planned and built farther from the shore. The increased integration

Transcription

1 1 Analysis of grid alternatives for North Sea offshore wind farms using a flow-based market model Daniel Huertas-Hernando, Harald G. Svendsen, Leif Warland, Thomas Trötscher and Magnus Korpås Abstract Offshore wind farms are gradually being planned and built farther from the shore. The increased integration of wind power, also onshore, and the demand for improved power system operation give rise to a growing need for transnational power exchanges. Grid connection is a critical factor for successful large scale integration of offshore wind power. In this paper a comparison study between two different grid building strategies for offshore wind farms in the North Sea is presented for the 23 medium wind scenario of the TradeWind project [1] (32 GW installed wind capacity). These two strategies are: i) A strategy based on radial wind farm connections to shore and point to point interconnections between countries, called radial grid; ii) A strategy based on the use of offshore nodes to build an HVDC offshore grid, called offshore grid. The comparison addresses different power system aspects, such as the total socio-economic benefit associated with each strategy, power exchanges between countries, offshore wind power utilization, grid congestions and utilization of HVDC cable capacity. We find that the offshore grid gives a total benefit over the economic lifetime of the grid for the European interconnected power system of 2.6 billion Euro compared with the radial grid. Our results show that even for moderate amounts of installed wind capacity, the offshore grid strategy is better than the radial one, assuming the future European power system will have a large penetration of offshore and onshore wind power. Index Terms Renewable Energy, Offshore wind energy, Power system, Power market. I. INTRODUCTION EXPLOITATION of Europe s abundant offshore and onshore wind energy as well as other renewable energy sources, will reduce its dependence on fossil fuels, thereby reducing CO 2 emissions and improving the security of energy supply. The EU currently meets 5% of its energy needs through imports and this might increase to 7% if no action is taken [2]. The European Wind Energy Association (EWEA) has in its high wind scenario, a target of 21 GW wind energy for 22, of which 4 GW ( 148 TWh) comes from offshore wind. This number increases to 15 GW offshore for 23 [3]. These ambitious targets imply wide impacts related to transmission planning and system operation that need to be addressed. Interplay between market and grid dynamics becomes increasingly relevant with higher wind power penetration levels. Wind power production has zero fuel cost, so it will always appear on the top of the merit order list when the market is cleared. On the other hand, wind power is much more variable and less controllable than e.g. thermal or hydro power, so operation planning, All authors are with SINTEF Energy Research, Sem Sælands vei 11, NO Trondheim, Norway; Daniel.Huertas.Hernando@sintef.no Manuscript received March 12 21; revised month day, 21. forecasting, balancing and control become more challenging in the presence of substantial wind power in the system. Wind power is also likely to increase grid congestions, so development of strategies for a flexible and secure grid are essential for succesful large scale integration of wind power. Onshore wind is considered commercially viable at sites with good wind conditions and grid access. Offshore wind is still at a pre-commercial development phase, although the expected yield is significantly larger than for onshore wind, due to the much higher wind speeds offshore and abundant available areas [4]. In the long term, offshore wind farms might be developed to constitute a significant part of the total power system generation capacity. Simulation tools that combine market details concerning production, demand and exchange transactions with details regarding power flow dynamics and grid capabilities, are essential when investigating the impact of integrating wind power in the power system. II. POWER SYSTEM SIMULATION TOOL (PSST) In the European R&D project TradeWind [1], a model of the European power system was established and by simulations were run for different scenarios up to year 23. The main focus of TradeWind was to investigate how large amounts of wind power may affect the power system operation, and emphasis was put on market design and need for new transmission capacity. For this purpose a flow based market model, referred to as the Power System Simulation Tool (PSST), was developed. We briefly describe PSST in the next subsection. A. PSST description PSST is a simulation tool developed by SINTEF Energy Research [5], based on a market model with simplified grid representation, assuming aggregated capacities and marginal costs of each generator type within specified grid zones. PSST assumes a perfect market (nodal pricing) and runs an optimal DC power flow that minimizes the total generation costs in the system, for each of the year and taking into account the high voltage (HV) network topology, capacity limitations on generators and interconnectors, wind power variations, hydro power characteristics and fuel price scenarios. The free (controllable) variables in the optimal power flow problem are the power output of all generators and the flow on HVDC interconnections. The power outputs of the generators depend on the maximum and minimum capacity, the marginal cost relative to other generators and limitations of power flow on the physical lines. Aggregated wind farms are modelled as

2 TABLE I COUNTRY, LABEL, CONVERTER SUBSTATION (CVST) AND OFFSHORE WIND FARM (O) Germany Denmark Norway Netherlands Belgium UK DE DK NO N B GB DE CVST DK CVST N CVST B CVST o 6 N NO o 6 N NO 58 o N 58 o N 56 o N DK CVST DK 56 o N 1 DK CVST DK TABLE II OPERATIONAL COSTS 54 o N 52 o N 5 o N GB B CVST B CVST B DE CVST o 3 o E 6 o E 9 o E N DE 54 o N 52 o N 5 o N GB B CVST N CVST B DE CVST o 3 o E 6 o E 9 o E Fig. 1. Grid configurations: a) PSST radial grid; b) PSST offshore grid; c) Net-Op radial grid; d) Net-Op offshore grid; Red lines: AC grid; Blue lines (in c and d): Connection between AC node and CVST; White lines (in a, b) and Green lines (in c, d): HVDC connections; Google Earth maps in (a,b) under c 29 Google, c 29 Europa Technologies, Image c 21 GeoContent, c 29 Tele Atlas generators with maximum power equal to the available wind power for the specific, and with marginal cost set to zero, so that wind power plants will always produce if not limited by grid constraints. Marginal costs of hydro power are determined by so-called water values deduced from the EMPS model [6]. The European grid model used in the simulations consists of separate DC power flow data files covering the Continental, Nordic, UK and Ireland regions as defined by the European Network of Transmission System Operators for Electricity (ENTSO-E). The entire model consist of 141 nodes, 2222 branches, 56 HVDC cables, 54 generators and 152 wind farm clusters [1]. In order to study the main power flows in the system, each country has been divided into one or more zones, which consist of a set of generators and nodes according to their geographical location. Due to limited data available, all branches within a country have unlimited capacity except the Nordic countries and parts of Germany. Net transfer capacities (NTC) between countries, as given by ENTSO-E, are used as constraints in the power flow optimization. See Ref. [5] for further details. III. OFFSHORE GRID STRATEGIES In this paper, we have used PSST to investigate two different strategies for the development of the grid connection of offshore wind farms in the North Sea, namely: Radial Grid: Radial connection between each offshore wind farm and the main grid onshore and point to point HVDC connections between countries across the North Sea (see Figure 1a, 1c). Offshore Grid: A strategy based on the use of offshore nodes to build a meshed HVDC offshore grid (see Figure 1b, 1d). We have chosen the medium wind 23 TradeWind scenario[1], except for the load forecast data for which the N DE Operational Costs PSST (Mill e) Net-Op (Mill e) Radial Offshore Difference Combined high renewables and efficiency load demand scenario from EWEA[3] has been used instead. The grid design used in PSST for each strategy is shown in Figure 1a, 1b). These offshore grid designs have been determined by the Net- Op grid optimization tool [7], [8]. Net-Op is a transmission expansion planning tool for power systems with large shares of renewable energy sources like e.g. wind. Figures 1c, 1d), show the labels used for each country, the offshore wind farm clusters (O) considered in the Net- Op optimization and the corresponding Converter Substation (CVST) connecting the offshore HVDC cable to the main AC grid. Table I lists all the labels further used in the text. Several important differences between Net-Op and PSST should be mentioned: i) PSST includes detailed onshore grid topology (see Red lines and nodes in Figures 1a, 1b) whereas in Net-Op, countries are modeled as single nodes (see Figures 1c, 1d). Net-Op only includes net transfer capacity limits between countries but no internal grid constraints for each country; ii) Only the farthest offshore wind farms to shore have been considered in the Net-Op optimization for the radial and offshore grids. Additional wind farms closer to shore have only been considered in PSST as radially connected to land (see Figures 1a, 1b). iii) PSST does not include losses, whereas Net-Op considers losses at the HVDC cables and CVST. In the TradeWind medium wind scenario used [1], there is 32 GW of installed wind power, of which 9 GW is offshore wind. These numbers are in agreement with EWEA s [3] targets for the 23 medium scenario: 3 GW (18 GW onshore and 12 GW offshore). Note that EWEA s offshore wind target of 12 GW is higher than the 9 GW offshore wind used in this study. Our case study thus presents a relevant wind scenario study case in line with EU targets, with a more conservative offshore wind installed capacity. This study has addressed aspects such as the total socioeconomic benefit associated with each offshore grid strategy, the export/import power exchanges, offshore wind power generation, grid congestions and utilization of HVDC cable capacity. We present our results in the next section.

3 3 Reservoir level(%) 1 TABLE III INVESTMENT COSTS & BENEFIT Investment Costs Mill e Benefit Mill e Radial PSST Offshore Net-Op Difference WATER LEVELS OFFSHORE GRID.5 NO SE SF Fig. 2. Hydro reservoir levels: Blue curve for Norway (NO), Green curve for Sweden (SE), Red curve for Finland (SF) ACTUAL (MW) ACTUAL (MW) POTENTIAL (MW) 8 (a) WIND GENERATION OFFSHORE WIND GENERATION RADIAL WIND GENERATION POTENTIAL 8 B O IV. RESULTS 1) TOTAL COSTS: The operational cost found by both PSST and Net-Op are shown in Table II for both the radial and offshore grids. The operational costs found by PSST are larger than in Net-Op. This is due to the larger area modelled in PSST with respect to Net-Op. The investment costs associated with the radial and the offshore grid alternatives and the total benefit found are shown in Table III. The total benefit is defined as: Benefit = Operational Cost Difference Lifetime Factor + Investment Costs Difference. Difference is defined as Radial - Offshore. The Lifetime Factor for a lifetime of 3 years and 5% discount rate is 3 n=1 1/(1+.5)n = and it allows to compare the investment (today) with the operational savings accumulated throughout the lifetime of the grid. In both cases, the total benefit is found to be positive, showing the added value of the offshore grid with respect to the radial grid. Moreover, the larger benefit found in PSST compared to Net-Op indicates the importance of a detailed description of the grid structure for regions around the North Sea. High wind penetration in concentrated regions in and around the North Sea (e.g. Northern Germany) is likely to introduce flow bottlenecks in the grid. Our simulations indicate that an offshore grid will allow for better wind penetration and less grid bottlenecks than the radial grid case. We present more detailed power flow results further. 2) NORDIC HYDRO PRODUCTION, OFFSHORE WIND AND GRID CONSTRAINS: Figure 2 shows the simulated hydro reservoir level in the Nordic region for the offshore grid case. The hydro level for Norway (NO) is slightly higher at the end of the year than at the start of the year, while the opposite is observed for Sweden (SE) and Finland (SF). The simulated hydro reservoir level for the radial grid case is very similar to the results of Figure 2. The increase in reservoir levels around 6 is possibly due to the continued high wind generation in the surrounding countries in this period, see Figure 3. The wind situation causes grid congestions in central Europe, resulting in export of surplus wind power further Fig. 3. Offshore wind data: a) Wind production for the offshore grid case; b) Wind production for the radial grid case; c) Potential wind production from installed capacity; Dark blue curve for Belgian cluster, Green curve for German cluster, Red curve for British cluster, Light blue for Norwegian cluster and pink for Dutch cluster north. It is seen from Figure 3 that the wind power output is constrained both for the offshore grid case and the radial grid case (Figures 3a, 3b), when compared with the potential wind power which would have been realized if there were no limitations on power transfer (Figure 3c). Grid bottlenecks in the Continental European grid system prevent, for certain time periods during the year, wind power produced, e.g. in the German (Green line in Figures 3a, 3b) and Dutch (purple line in Figures 3a, 3b) wind farms clusters, to be utilized. This is reflected in the dips in the wind generation shown in Figures 3a, 3b. Wind congestion seems to be quite pronounced in the German wind cluster between s Figure 4 illustrates the relationship between the hydro production in Norway (NO) and the total offshore wind production in the North Sea. Figure 4a presents the hydro production for both offshore grid scenario and radial grid scenario during s 5-56 when the total North Sea offshore wind production is low. In this situation, hydro production in Norway is higher that the demand. Norway has, during those s, surplus production which can be exported to Continental Europe through HVDC cables. Note that around s 53 and 555, offshore production increases, slightly reversing this picture. In general, Figure 4a shows that for low wind production in the North Sea, hydro production in Norway follows the Norwegian demand profile quite closely. Therefore standard load-following balancing schedules would guarantee security of supply and efficient balancing reserve allocation in this situation. Figure 4b presents similar data for the next 6-66 s, when total North Sea offshore wind production is higher than the load demand in Norway. In this case we see that the Norwegian hydro production is substantially below

4 4 Power (MW) Power (MW) Fig. 4. x (a) NO Hydro Offshore NO Hydro Radial NO Load Offshore wind x NO Hydro Offshore NO Hydro Radial NO Load Offshore wind Norwegian hydro & load vs North Sea offshore wind the Norwegian demand due to the high wind penetration from the North Sea into the Norwegian grid. Also, hydro production variations are now much more correlated with wind variations. Balancing schedules and balancing reserve allocation should rather be controlled by the Net-Load = Load Wind in these situations, to efficiently provide security of supply. Figure 4 illustrates the connection between offshore wind production in the North Sea and hydro production in the Nordic region. As an illustration of the flow dynamics, we investigate the flow between the offshore grid HVDC links connecting the different wind farms (,,,, ) and the connections to the German and Dutch wind farms (, ) to their main land converter substations (CVST) points (DE CVST, N CVST ) for the above mentioned s h=(6, 66). Results are shown in Figure 5. We notice: For the following connections: (Figure 5a), (Figure 5e), (Figure 5c) and (Figure 5g), we observe that large offshore wind production at the German and British wind farms is re-directed towards the Netherlands and Norway. There are however some reversed power flow peaks which are correlated with the sudden reduction in wind power output at and showninfigure3. For the (Figure 5b) connection between the two largest producing offshore wind farms during this period, we observe that the flow direction changes regularly. This connection shows the ability of the offshore grid to redistribute the wind production in a flexible way. The usage of the German wind farm connector to land ( DE CVST ) is lower for the offshore grid case (blue curve in Figure 5d) than for the radial grid case (red curve in Figure 5d) for this period, whereas the usage of the Dutch wind farm connector to land increases ( N CVST, Figure 5h) for the offshore grid (blue curve) compared to the radial grid (red curve). This shows a redistribution of the wind power injection into the mainland grid; Injection around DE and DK seems to occurs more in the radial grid. On the other hand, wind penetration shifts more towards the Netherlands and Belgium in the offshore grid case (see also connection in Figure 5f). 3) UTILIZATION & FLOW RESULTS: Both the radial and optimal offshore grids increase the flexibility of the Power Flow (MW) DE N GB N (a) O O (e) O O B (f) O NO O 4 NO O (g) DE DE 2 N N 1 CVST O O CVST 4 DE DE [Rad] N N [Rad] CVST O O CVST 6 (h) Fig. 5. Example of flow results: For each connection A B, positive values mean flow from A to B: A B and negative values mean flow from B to A: A B transmission network as a whole. However, the optimal grid specifically aims to handle the variations of offshore wind power production on-site, therefore relieving the mainland grid of the congestions associated with high offshore wind generation. We show the duration diagrams for the usage of the different HVDC cables in Figures 6 and 7. For comparison, we present duration diagrams for the PSST model with and without simulated internal grid constrains in Germany. This comparison is quite important regarding wind penetration from the North Sea into the European grid, as the most important bottlenecks are likely to occur in the German grid due to the large presence of installed wind power in and around it. For completeness, we also present duration diagrams from the Net- Op model, where no grid constraints for the internal grid of each country are considered. In Table IV, yearly-averaged-flow values and utilization factors are presented for the main HVDC connections making up the offshore grid. Corresponding duration diagrams are presented in Figure 6. We notice that: The yearly-averaged data of Table IV, shows that offshore wind power, mainly from the German and British wind farms is redistributed South through the Netherlands and Belgium and North through Norway. Removal of the German internal constrains in the PSST model causes a higher flow towards DE. This is clear from the shift to the left of the green curves (without internal constrains) with respect to the blue curves (with internal constrains) for

5 5 N O (a) NO DK CVST CVST NO CVST (a) Power Flow (MW) N O (e) Power Flow (MW) DE CVST (e) B CVST N CVST (f) Fig. 6. Utilization offshore: PSST without DE internal constrains (green curves); PSST with DE internal constrains (blue curves); Net-Op (red curve); For each connection A B, positive values mean flow from A to B: A B and negative values mean flow from B to A: A B TABLE IV YEARLY-AVERAGED OFFSHORE GRID FLOW; UTILIZATIOF HVDC-LINKS IS GIVEN AS % OF MAXIMUM CAPACITY. HVDC MW HVDC MW HVDC MW DE N DE GB DE NO DE N DE GB DE NO 6.3 Sum Sum 124 Sum 2225 Util. 82.3% Util. 88.6% Util. 53.% GB N 1811 N B NO GB GB N 234 N B NO GB Sum 245 MW Sum Sum 1941 Util. 73.% Util. 69.4% Util. 69.3% the duration curves of the DE-connections in Figures 6a, b, c. Due to the meshed nature of the offshore grid, bottlenecks in the German grid directly affect the flow through the other offshore nodes, especially at the connections (,, Figures 6d, f), as seen by the shifts of the green curves (without internal constrains) with respect to the blue curves (with internal constrains). The agreement between the PSST duration curves (blue and green) and the Net-Op duration curves (red) in Figure 6 is rather good considering the differences between the two models, mentioned above. The duration curves for the Net-Op model (red lines in Figure 6) show many s with zero flow between the different offshore nodes. This occurs when the price difference Fig. 7. Utilization radial: PSST without DE internal constrains (green curves); PSST with DE internal constrains (blue curves); Net-Op (red curve); For each connection A B, positive values mean flow from A to B: A B and negative values mean flow from B to A: A B TABLE V YEARLY-AVERAGED RADIAL GRID FLOWS; UTILIZATIOF HVDC-LINKS IS GIVEN AS % OF MAXIMUM CAPACITY. CVST CVST MW CVST CVST MW NO DK NO GB 1142 NO DK NO GB 86.4 Sum Sum 22.4 Util. 81% Util. 47.7% NO DE 31.1 GB B 1331 NO DE GB B Sum Sum Util. 82.9% Util. 36.1% NO N NO N 28.8 Sum Util. 77.3% between different offshore nodes is less than the operational costs associated with HVDC cable and converter losses. This situation never occurs in PSST as the HVDC losses are not considered. In the case of a radial offshore grid, the HVDC cables are point to point connections between mainland converter substations (CVST) in the different countries. These CVST are also the only connection points of the offshore wind farms. The utilization of the HVDC cables in the radial grid is summarized in Table V and Figure 7. From these results we conclude:

6 6 TABLE VI YEARLY-AVERAGED FLOWS FOR NORNED, SKAGERRAK AND BRITNED; UTILIZATIOF HVDC-LINKS IS GIVEN AS % OF MAXIMUM CAPACITY. NorNed MW Skagerrak MW BritNed MW Offshore Offshore Offshore NO N NO DK 544 GB N NO N NO DK GB N Sum Sum Sum 843 Util. 89.6% Util. 96.7% Util. 83.4% Radial Radial Radial NO N NO DK GB N NO N NO DK GB N Sum Sum 97.8 Sum 842 Util. 94.9% Util. 95.6% Util. 84.2% UA SK SF SE SF RU UA RO SC RO SK PL SE PL SE NO NO N SC MC SV IT UA HU SK HU SC HU RO HU SV HR SC HR HU HR MC GR IT GR NO GB N GB IR GB IT FR GB FR P ES FR ES SE DK NO DK SE DE PL DE NO DE N DE L DE GB DE FR DE DK DE SK CZ PL CZ DE CZ IT CH FR CH DE CH SC BU RO BU GR BU SC BH HR BH N B L B GB B FR B SV AT IT AT HU AT DE AT CZ AT CH AT Electricity transfer [TWh] Fig. 8. Yearly exchange flows between countries: Red bars Radial grid case; Blue bars Offshore grid case Removal of the internal constrains in Germany causes a higher flow from NO towards DE (Figure 7b). In addition the flow from NO into N and GB is consequently reduced (Figures 7c, d respectively). The flow in the HVDC cables between NO DK and GB B is not substantially affected by the internal constrains in DE (Figures 7a, e respectively). The agreement between the PSST duration curves (blue and green) and the Net-Op duration curves (red) in Figure 7 is also rather good for the radial grid case. For completeness we show yearly averaged flow data for the already existing/planned HVDC cables considered in this study: NorNed (capacity 7MW), Skagerrak (capacity 95MW) and BritNed (cap 1MW) in Table VI. We find high utilization (>7%) for most of the HVDC cables analyzed in both radial and offshore grid cases. Finally we present the total power exchanges between countries for both offshore and radial grid strategies. The exchange flow data of Figure 8 shows: Trends/main flows remain, in general, basically the same. Exception are for NO DK and NO N, where the flow pattern changes substantially between the radial and the offshore grid cases. There is a higher benefit associated with the offshore grid (as shown in Table III). This is due to a better utilization of HVDC cables, i.e. more power exchange in the offshore grid than in the radial grid. This is clearly seen in Figure 8 by generally larger bars in the offshore grid case (blue) than in the radial grid case (red) for all countries around the North Sea. Power exchanges for the rest of countries far away from the North Sea remain basically unchanged. This demonstrates that the benefit of the offshore grid to central-north Europe does not come at the expense of worse power exchange conditions in other parts of Europe. V. CONCLUSION A comparison between two different grid expansion strategies for offshore wind farms in the North Sea has been presented. The total benefit of the offshore grid with respect to the radial grid is found to be 2.6 Billion Euro. This shows the value of the offshore grid in relieving flow bottlenecks in the grid, especially when high wind production occurs in the North Sea. We expect that our simulation might provide an optimistic limit for the utilization of both grid structures, and especially for the radial grid due to the absence of losses considered in the PSST model. Losses will make the power flow more constrained, therefore increasing the operational costs, but not necessarily the total benefit found. Further work including losses and improved distribution of onshore and offshore wind power is needed in order to identify needs for onshore grid reinforcements. Although this simulation case study indicates significant added value with the offshore grid structure with respect to total power system cost and performance, further studies in this direction are needed in order to establish sound strategies for (step-wise) development of offshore grids. ACKNOWLEDGMENT The authors would like to thank J. O. Tande and K. Uhlen for fruitful discussions. This work has been financed by NOWITECH FME centre ( and KMB project Deep sea offshore wind turbine technology. REFERENCES [1] EU, TradeWind EU-IEE project, [2] International Energy Agency (IEA), Energy Technology Perspectives: Scenarios & Strategies to 25, [3] European Wind Energy Association (EWEA), Pure Power: Wind Enery Scenarios up to 23, [4] European Wind Energy Association (EWEA), Oceans of Opportunity, [5] M. Korpås, L. Warland, J. O. Tande and K. Uhlen, Impact of increased wind integration on power flows and congestion costs in the European Transmission Network, Proceedings of the European Wind Energy Conference & Exhibition, PO.367, 29. [6] O. B. Fosso, A. Gjelsvik, A. Haugstad, B. Mo and I. Wangensteen, Generation scheduling in a deregulated system: The Norwegian case, IEEE Trans. Power Systems, 14(1):75-81, [7] T. Trötscher, M. Korpås and J. O. Tande, Optimal design of a subsea grid for offshore wind farms and transnational power exchange, Proceedings of the European Wind Energy Conference & Exhibition, 29; [8] T. Trötscher and M. Korpås,Optimal design of a subsea power grid in the North Sea, Proceedings of the European Offshore Wind Conference Exhibition, 29.