European energy policy goals: rivals or friends in ... - IEEE Xplore

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European energy policy goals: rivals or friends in transmission? David Bekaert. K.U.Leuven. ELECTA david.bekaert. @esat.kuleuven.be. Patrik Buijs.

European energy policy goals: rivals or friends in transmission? David Bekaert K.U.Leuven ELECTA david.bekaert @esat.kuleuven.be

Patrik Buijs K.U.Leuven ELECTA patrik.buijs @esat.kuleuven.be

Leonardo Meeus K.U.Leuven ELECTA leonardo.meeus @esat.kuleuven.be

Abstract-European energy policy strives towards an affordable, sustainable and secure energy supply. These three goals put strong demands on the entire value chain. The paper investigates how transmission grid planning, as the central element in this value chain, is influenced by these objectives. Especially it tries to examine how these objectives interact. It provides a first answer to the question whether the objectives are rivals or friends. To this extent a linear optimization model is set up. It combines an optimal power flow and optimal line capacities for the three policy goals and the combined multi-objective problem.

I.

INTRODUCTION

The European Union recently outlined its energy policy. Three major policy goals are put forward: affordability via a competitive market, sustainability and security of supply [1]. A holistic approach is needed and actions are required throughout the entire value chain. Here, the focus will be on how the threefold energy policy influences the planning of the transmission grid, the crucial backbone of this value chain. Each objective puts its own demands on the grid as illustrated in Fig. 1. Each objective itself is a major challenge. Moreover, at the same time interconnecting markets, connecting renewable energy sources (RES) and keeping the lights on is an even tougher job. Although the European Union believes these three targets strive to the same optimum [1], we believe that conflicts can arise when obtaining all three policy goals. This paper provides an insight in these interactions and potential conflicts. The aim is to analyze whether the impact on the transmission grid planning of the three objectives is the same or whether each objective requires a completely different grid. Are the same investments needed or do they at least aim towards the same direction, i.e. are they rivals or friends? On the one hand a tentative overview of areas of tension between the three objectives is presented. On the other hand, an optimization model is set up that allows comparing the optimal transmission grid investments and the optimal generation dispatch for each of the three policy goals separately and for the combined European policy. Whereas the relation between two policy goals is often analyzed, the contribution of this paper is to quantitatively adress the interaction between the three goals. Inspired by a model of Kirschen and Strbac [2] a trade off is made between extra investments in transmission capacity and dispatching more expensive generators. In the competitive case, optimal can be

Erik Delarue K.U.Leuven TME erik.delarue @mech.kuleuven.be

Ronnie Belmans K.U.Leuven ELECTA ronnie.belmans @esat.kuleuven.be

Fig. 1. The three-fold EU energy policy applied to transmission grids

understood as most cost-effective under the chosen constraints. Sustainability is modeled by adding priority dispatch of RES, which is also instructed by European directives. Reliability constraints enforce the grid to meet the N-1 criterion. The outline of the paper is as follows. In the second section, the three policy goals are confronted with each other in order to identify possible tension fields. In the third section the model is formulated to address the research question in a quantitative way. Results of the model are discussed in the fourth section. Finally, conclusions are drawn in the fifth section. II. CONFRONTING POLICY GOALS It is generally accepted that implementing the European energy policy requires transmission grid investments. For instance, the TEN-E program identifies crucial cross-border European grid investments [3]. The grid is far from static and should not be taken for granted. As a transmission investment often lasts for decades and is almost irreversible, investment inertia is huge. A clever transmission investment plan has to cope with different influences and mostly even with tradeoffs. The three main European policy goals have to be reached together and cannot be treated independently. Moreover, special effort and careful coordination are needed as several areas of tension can be identified. A. Security of supply – Competitiveness Before electricity sector liberalization took off, interconnections were primarily used for reliability purposes. Some long term contracts were available and were scheduled in a very clear and rather static way. Today, capacity on interconnections is traded amongst all market players and contributes to market integration. From a competitive

viewpoint, TSOs should maximize the capacity available for the market. Consequently, the power system is operated closer towards its security limits [4]. Ref. [5] describes another trade-off between competitiveness and reliability in a simple Wheatstone bridge configuration. On the one hand, adding an extra line to the network can increase the level of congestion in the network. On the other hand it increases reliability, as the extra line can be used in case of contingencies on other lines in the network.

III. MODEL DESCRIPTION In order to demonstrate these tensions between the different objectives a model is built up to investigate what the optimal grid is, given one of the policy goals explained in Fig.1 has to be reached. Optimal can be understood as most cost-effective under the chosen constraints. To analyze the effect of the different EU objectives on transmission system investments the results of five models are examined: ƒ Comp: the competitive case minimizing total transmission and generation dispatch costs ƒ Rel: the reliable case from a transmission grid point of view enforcing N-1 at minimal line cost ƒ Comp-Sust: the sustainable case requiring priority dispatch of the wind farms ƒ Comp-Rel: the competitive case taking also reliability constraints (N-1) into account ƒ Comp-Sust-Rel: the sustainable case taking also reliability constraints into account

B. Security of supply – Sustainability To operate a reliable transmission grid remains the TSO’s main duty. This is taken into account through the different timeframes a TSO is working in [6]. During investment planning a straightforward N-1 analysis is carried out, based on a base scenario considering future evolutions in demand and generation. Given the uncertainty in the generation market (who will build which power plant where and when?) and the fact that demand changes, statistical approaches are needed, which was not the case in the vertically integrated system. When the timeframe moves from years ahead to A. Formulation months or weeks more accurate data and facts, such as The basic idea behind the model is an optimal power flow planned outages and seasonal variations, can be added to the algorithm expanded with transmission investment costs [2]. base scenario in order to get a tighter security analysis. Only Instead of minimizing generation cost, the sum of generation days ahead or even just before real time, an accurate security cost and an annualized investment cost of the grid is analysis (e.g. N-1 expanded by known contingencies) taking minimized. Not only generation dispatch, but also the all relevant information into account, can be carried out. capacities of the different lines in the grid are a consequence It is generally acknowledged that RES have a huge impact of the decision variables. One can understand the proposed on the European electricity system [7]. Especially between problem as given a generation park and the rights of way the reliability aspect and a sustainable growth of generation between different nodes, which lines should be built and how conflicts can arise. As explained above a reliable operation of should generation be dispatched. the grid is based on a tight security frame. With a lot of RES, # periods # generators # lines ⎞ mostly intermittent in nature, this frame shifts towards the Min ⎛ Cg .Pg , generated + ∑ Cl .lengthl .capacityl ⎟ (1) ⎜ ∑ ∑ point of operation. Next to this aspect wind turbine parks are g l ⎝ p ⎠ often located far from load centers causing large (cross- Subject to: border) power flows [8]. 0 ≤ Pg , generated ≤ Pg ,capacity ∀p, g (2) PTDF .(net injections) ≤ capacityl ∀p, l (3) C. Competitiveness – sustainability To the extent competitive solutions can be defined as # buses ∀p (4) lowest-cost solutions and sustainability is interpreted as the ∑ net injections = 0 b greenest solution, competitiveness and sustainability may demandb = constant ∀p, b (5) have a conflict. On the level of the transmission grid, priority ∀l (6) dispatch of RES requires investments to be dimensioned on capacityl ≥ 0 the rated capacities of generators. This may lead to huge costs The competitive case (Comp) contains the equations as especially if RES are located in remote areas with a low load density, like for instance in Germany [8]. Additionally, the presented in (1)-(6) and is only the extended optimal power concentration of large wind farms in remote areas can create flow. If sustainability is required, the inequality constraint (2) temporarily large load flows. Besides grid stability effects, is changed into an equality constraint (7). By this change all generated power has to be accepted, i.e. priority dispatch. In these flows limit capacities for trade [7]. As RES often are intermittent in nature, the question arises fact a solution of this problem, gives an optimum for a whether it is economically justifiable to invest in the grid to combination of the both competitiveness and the accommodate the full rated capacity. It is concluded in [9] sustainability criterion (Comp-Sust). that it can be optimal from a wind farm investor point of view Pi , generated ≤ Pi ,capacity ⇒ Pi, generated = Pi ,capacity (7) to install a grid connection with a capacity smaller than the rated generating capacity of the wind farm.

In the reliability model (Rel) the goal of grid stability is fulfilled if the grid is N-1 secure. This is obtained by adding extra constraints to the competitive case. In the objective function generation costs are omitted. As such, the optimization determines the cheapest grid possible which is N-1 secure. The outage of each single line is considered as a contingency, except outages which isolate a part of the grid. These extra constraints are the same as in the basic formulation, but a new matrix with power transfer distribution factors (PTDF) and net injections are calculated for each constraining contingency. For each contingency it is checked if the constraints are binding. Formulation (1)-(6) is expanded with (8)-(9) for each constraining contingency c. PTDFc .(net injectionsc ) ≤ capacityl ∀p, l , c # buses

∑ net injections

c

=0

∀p, c

(8) (9)

b

B. Calibration The model is tested on a slightly modified IEEE 30 bus grid (Fig. 2) over four periods. Two generators are supposed to be wind farms with a simplified output duration curve based on [10] and given in Table 1. Other generators are always available at full capacity. Demand is supposed to be inelastic and is represented as fixed. It is displayed in italics in Fig. 2. It is scaled towards a realistic level compared to installed generation capacity. In line with the UCTE country average [11] total demand is set at approximately 60% of installed generation. Nodes with a wind farm have no local demand. Each period has the same demand pattern to keep results clear and comparable. Rated wind power generation capacity makes out 22% of the installed generation capacity. This is a challenging configuration, but it is in line with future wind power expansion plans. Today, Germany already has a wind power capacity level of about 19% [11]. The model often has to choose between adding extra transmission capacity to enable cheaper generation and dispatching more expensive generators. Therefore calibration of costs is of utmost importance. The cost of a typical line is 30 EUR/(MW.km) and is based on the cost of a three phase single 380kV line on flat land as reported in [12]. Wind farms are assumed to be connected by a five times more expensive line, for instance representing an offshore HVDC connection or high voltage cable [12]. Line lengths are derived from the line reactances in IEEE 30 bus model. Generation costs are implemented by using variable costs, i.e. fuel costs. Wind farms operate at zero cost and their output is perfectly correlated. The other generators have costs reflecting coal and CCGT fuel costs [13]. IV.

RESULTS

The results of the five models described in the previous section are given in Tables 2 to 5. From the results several lessons can be learned. First the focus is on general trends,

Fig. 2. The modified IEEE 30 bus test grid (loads in italic [MW]) TABLE 1 WIND POWER D URATION CURVE Period

1

2

3

4

Duration (hours)

1000

3000

3000

1760

Available output

100%

75%

30%

5%

next it is discussed to what extent the objectives are rivals or friends. Finally, a brief insight in the cost sensitivity of the models is given. A. Trends Firstly, the different models result in different costs. Looking at total costs in Table 2 Comp yields the best overall result. As the focus there is only on total cost minimization and sustainability and reliability are not enforced, this result is as expected. Costs in Comp-Sust are higher due to a more stringent set of constraints, i.e. the priority dispatch of the wind farms. Although less MW.km of lines is built, the line cost is higher compared to Comp. The underlying reason is twofold. Firstly, the higher cost per MW.km to connect the wind farms (lines 6-8 and 12-13) drives up the overall cost. Secondly, the results in Comp make clear that it is not cost efficient to build a line able to transport the full wind farm output even if the power itself comes at no cost. Lines 6-8 and 12-13 in the Comp model only have a capacity of about 75 MW, whereas the wind farms have a rated capacity of 100 MW. Although the maximum of wind power is used due to the priority dispatch, generation costs increase with more than 25% in Comp-Sust compared to Comp. In periods with low wind power output, more expensive generators have to be dispatched. In these periods the optimal generation dispatch differs from Comp as also the line capacities are different. In Rel only line costs are in the objective function, generation is dispatched as to minimize the number of MW.km. The minimum number of line costs is found when those generators are dispatched that are closest to the loads. Note that this is very dependent on the grid topology. In this

TABLE 2 SUMMARY OF RESULTS

Total cost (€)

Gen cost (€) Line cost (€) # MW.km

Comp

54,327,293

42,910,874

11,416,419

308,151

Comp-Rel

63,576,492

42,959,362

20,617,131

614,869

Comp-Sust

66,204,399

54,636,213

11,568,186

289,583

Comp-Sust-Rel

73,968,535

54,644,015

19,324,520

548,122

Rel

69,066,021

66,525,604

2,540,417

79,765

network the optimization results in a decrease of line costs of about 80% compared to Comp and Comp-Sust. The (expensive) lines connecting the wind farms have very small capacities, i.e. 2 and 7 MW. The focus on line costs causes generation dispatch to result in much higher generation costs, i.e an increase of 55% compared to Comp and 20% compared to Comp-Sust. Secondly, adding N-1 constraints to the competitive and the sustainable case, i.e. adding Rel to Comp and to Comp-Sust, largely affects the line costs but has no significant impact on generation costs and dispatch. Line costs increase with 7080% compared to the cases without N-1 constraints. Recall that outages isolating a part of the grid, e.g. lines connecting the wind farms, are not considered as a contingency. Thirdly, the combination of all models into the envisaged multi-objective problem Comp-Sust-Rel results in the most expensive scenario. The influences of both Sust and Rel can be seen in the cost figures. Line cost primarily increases due to the reliability constraints and generation costs increase due to the priority dispatch. B. Rivals or friends Formulating an answer on the question whether the three EU energy policy goals are rivals or friends from a transmission point of view starts with analyzing Tables 3 and 4. It is clear that no two models have the same line capacities. Taking into account the huge costs involved and today’s difficulty to erect transmission lines, these capacity differences urge for a correct implementation of the objectives from the start. However, different models can yield different results, but they can point towards the same direction. In Table 4 the different models are compared with regard to the line capacities. For lines with a capacity difference of more than 5 MW, the direction of the difference is investigated. If there are both lines with a lower as well as lines with a higher capacity, the compared models do not fully point in the same direction and trade-offs exist. These models are more thought of as being rivals. Models where only a capacity increase (or decrease) is necessary on every line are said to be friends. A first observation of Table 4 learns that most lines face an absolute capacity difference exceeding 5 MW when two models are compared. Note that there 40 lines in the network examined. Secondly, Table 4 confirms common sense that models with N-1 constraints exhibit higher capacities than models without these extra constraints.

Thirdly, comparison of the most extreme models (i.e. Comp, Rel and Comp-Sust) provides the most diverging results. Especially Comp and Comp-Sust seem to be the biggest rivals. The different generation dispatch due to prioritizing wind power output causes the grid to change. Finally, Table 4 reveals that comparing the extreme scenarios with the envisaged policy goals, i.e. Comp-Sust-Rel, TABLE 3 LINE CAPACITY IN DIFFERENT MODELS

Capacity (MW)

Line (from-to)

Line cost (€/(MW.km))

Comp

1-2

30

233

377

202

322

1-3

30

136

366

116

317

221

2-4

30

84

150

67

126

106

3-4

30

135

372

111

334

218

2-5

30

149

238

143

236

135

2-6

30

108

173

88

155

116

4-6

30

119

250

93

206

131

5-7

30

53

191

70

190

91

6-7

30

99

239

115

237

135

6-8

150

76

76

100

100

2 69

Comp- Comp- CompRel Rel Sust Sust-Rel 222

6-9

30

85

122

32

69

6-10

30

39

72

26

58

57

9-11

30

19

37

100

100

100

9-10

30

42

89

72

111

110

4-12

30

86

116

70

102

99

12-13

150

75

75

100

100

7

12-14

30

20

49

18

48

32

12-15

30

50

93

45

70

44

12-16

30

31

60

24

42

27

14-15

30

8

38

6

34

18

16-17

30

25

55

17

35

37

15-18

30

22

48

18

34

32

18-19

30

16

63

12

30

26

19-20

30

14

67

17

49

38

10-20

30

17

42

21

41

41

10-17

30

11

71

17

49

52

10-21

30

32

89

33

59

50

10-22

30

15

50

16

66

45

21-22

30

35

39

5

72

39

15-23

30

19

50

17

31

21

22-24

30

7

61

14

43

41

23-24

30

12

43

11

24

20

24-25

30

8

40

4

38

34

25-26

30

8

8

7

7

7

25-27

30

16

45

10

31

28

28-27

30

41

58

36

51

50

27-29

30

13

27

12

26

26

27-30

30

15

27

14

26

26

29-30

30

8

22

7

21

21

6-28

30

45

80

36

56

52

TABLE 5 SENSITIVITY ANALYSIS: CAPACITY (MW) OF LINES CONNECTING WIND FARMS (6-8 / 12-13) FOR D IFFERENT COST

# lines with cap(A) > cap(B)

# lines with cap(A) < cap(B)

Comp vs Rel

6

30

Comp vs Comp-Sust

17

8

Comp-Sust vs Rel

3

32

Comp vs Comp-Rel

0

36

Comp vs Comp-Sust-Rel

1

38

Comp-Sust vs Comp-Sust-Rel

0

36

Rel vs Comp-Sust-Rel

0

20

offshore costfactor

For lines with |cap(A)-cap(B)|>5MW

1

3

results in increasing the capacity of most lines, except for the comparison with Rel where only half of the lines needs an increased capacity. C. Cost sensitivities As stressed earlier, the calibration of the costs in the model is crucial. The cause of the conflicting results between Comp and Comp-Sust is the priority dispatch. The importance of the conflict can for instance be measured by the capacity of the lines connecting the wind farms. In Comp-Sust the capacity is by definition 100 MW, the maximal wind farm output. In Comp the capacity strongly depends on the line cost and the cost factor to account for offshore connections, but also on the cost of the other generators (Table 5). The capacities in Table 5 illustrate the importance of the calibration. However, the differences between Comp and Comp-Sust hold in many cases. The difference gradually disappears with increasing generation costs (other than wind) and with decreasing basic line costs, especially when lines connecting wind farms face the same costs than other lines.

5

7

Other generators cost range (€/MWh) 5 - 10

10 - 20

15 - 30

20-40

10

100/100 100/100 100/100 100/100

30

100/75

100/100

100/99

100/100

50

95/81

100/77

100/83

100/99

70

76/36

99/81

99/75

99/94

10

100/77

30

76/74

97/75

99/75

100/98

50

75/30

78/75

80/75

100/77

70

70/30

77/74

76/76

89/75

10

96/75

30

75/37

76/75

90/75

100/78

50

36/31

75/44

75/75

76/75

70

29/29

74/40

75/72

75/75

10

75/75

100/75

30

75/30

75/75

75/75

50

31/30

75/33

75/73

75/75

70

30/5

39/30

74/30

75/72

100/100 100/100 100/100

100/100 100/100 100/100

100/100 100/100 86/75

ACKNOWLEDGEMENT The authors are grateful for the support received from the K.U.Leuven Energy Institute. The research at the KU Leuven is performed within the framework of the research program ‘InterDisciplinaire Onderzoeksprogramma’s ’ (IDO). REFERENCES [1] [2] [3]

V. CONCLUSION The European Union’s multi-objective energy policy puts strong demands on the entire value chain. The transmission grid plays a crucial role in enabling these goals. However, several fields of tension between the different policy goals can be identified. If no special effort is done, it will be hard to reach the ultimate goal of an affordable, sustainable and secure energy supply. Although the benefits of the objectives (e.g. a clean planet, no black-outs) can be priceless, the cost side should not be neglected. Attaining goals in a least-cost efficient way is the best route to follow. Therefore, interactions between policy goals have to be studied especially where areas of tension exist. Subject to the limitations of the model and only applied to a small test grid, the results in this paper illustrate that special care and coordination is needed to integrate the three objectives in transmission planning. Especially the requirements for a sustainable and a competitive supply need to be closely fine-tuned.

basic line cost (€/(MW.km))

TABLE 4 COMPARISON OF LINE CAPACITIES IN DIFFERENT MODELS

[4] [5] [6] [7] [8] [9] [10] [11] [12] [13]

EU Commission, “Communication from the Commission to the European Council and the European Parliament - an energy policy for Europe (SEC(2007) 12)”, January 2007 D. Kirschen and G. Strbac, “Fundamentals of power system economics”, Wiley, 2004 Decision No 1364/2006/EC of the European Parliament and the Council of 6 September 2006 laying down guidelines for transEuropean energy networks and repealing Decision 96/391/EC and Decision No 1229/2003/EC D. Kirschen and G. Strbac, “Why investments do not prevent blackouts”, The Electricity Journal, Vol. 17, Issue 2, pp. 29-36, March 2004 S. Blumsack, L.B. Lave and M. Ilic, “The real problem with merchant transmission”, The Electricity Journal, Vol. 21, Issue 2, pp. 9-19, March 2008 NERC, “Reliability concepts”, Version 1.0.2, December 2007 ETSO, “European wind integration study (EWIS) Towards a successful integration of wind power into European electricity grids”, Final Report, January 2007 DENA, “Planning of the grid integration of wind energy in Germany onshore and offshore up to the year 2020”, Final Report, March 2005 S. Pattanariyankool and L.B. Lave, “Optimizing transmission from distant wind farms”, Carnegie Mellon Electricity Industry Center Working Paper CEIC-08-05, May 2008, unpublished Eltra, “Workshop on Electrical Design of Offshore Wind Installations”, Owen events, November 2000 , presentation UCTE, “System Adequacy Forecast 2008-2020”, January 2008 ICF Consulting, “Unit costs of constructing new transmission assets at 380 kV within the European Union, Norway and Switzerland”, Final report, prepared for the DG TREN/EU Commission, October 2002 A. Pellion, “Renewing energy production in Europe: an environmental, industrial and political challenge”, Fondation Robert Schuman, January 2008