Solar power in northern Scandinavia, its impact on the grid and methods to mitigate this impact

Sarah Rönnberg Luleå University of Technology

Sweden Sarah.ronnberg@ltu.se

Math Bollen Luleå University of Technology

Sweden Math.bollen@ltu.se

Abstract— This paper presents results from measurements of solar-power production in the north of Scandinavia; studies of the impact on the grid when larger amounts of solar power are installed, and methods to mitigate this grid impact. It is shown that solar power has limited contribution to reducing the peak loading of the grid. Large amounts of solar power will even increase the peak loading. Curtailment is shown to be an appropriate way of allowing more solar energy to be injected into the grid without additional grid investment. It is important however to use the right control method (“soft curtailment”) as otherwise production will decrease with increasing installed capacity. It is also shown in the paper that unacceptable voltage variations can occur when large installations are connected to weak parts of the grid. The availability of hourly metering data is an important contribution to integration studies.

Index Terms-- Smart grids, electric power distribution, solar power, curtailment, power quality, smart meters.

I. INTRODUCTION The NorthSol project studies the possibilities of producing electricity from solar power in the north of Sweden, Norway and Finland [1]. The project consists of the building of a number of test installations, measurements of solar-power production and power quality at those installations, study of the potential grid impact of large amounts of such installations, and the study of smart-grid methods to mitigate this impact. As part of the project, measurements with high time resolution have been obtained of active power, reactive power, rms voltage and harmonic voltage and currents for PV installations at one location in Northern Norway, several locations in Northern Sweden and one location in Northern Finland. The aim of these measurements is mainly to map the harmonic emission from the installations. Some early results were presented in [2].

The measurements of active and reactive power also allow a study of the impact of solar power on overload and overvoltage in the distribution grid. For this purpose, the measurements are combined with hourly consumption data. A large percentage of Swedish electricity customers are

equipped with hourly metering of their consumption.

II. OVERLOADING The maximum active power flow at a location with PV-

production will occur at times with maximum production and minimum consumption [3]. Measurements obtained between 23 February and 31 October 2012 have been used to study the risk of overloading and the possibilities of reducing this risk by using curtailment of production. Hourly metering data has been obtained from a detached house and from an office building both located in the North of Sweden. The house was heated with an electric heat pump; its highest hourly consumption during the measurement period was 6.7 kWh/h. The office building houses a local power company with a staff of approximately 60 persons and the highest consumption recorded during the period was 152kWh/h. The production from a solar power installation (20 kW installed capacity) located a few meters from the office building and approximately 80 km from the detached house, was obtained every hour over the same period. The maximum hourly production during the measurement period was 17.8 kWh/h. In Fig. 1, the production and consumption for the house are compared, where the production has been scaled such that its maximum value is equal to 5 kW, being more in line with the size of the consumption. The figure also shows the net consumption: consumption minus production. This is the flow between the customer and the grid and what impacts the grid.

Financial support from the European Commission, from the Swedish Energy Agency and from Skellefteå Kraft is gratefully acknowledged. The authors are with Luleå University of Technology, 931 87, Skellefteå, Sweden. M.H.J. Bollen is also with STRI AB, 417 55 Gothenburg, Sweden.

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978-1-4799-2984-9/13/$31.00 ©2013 IEEE

2013 4th IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), October 6-9, Copenhagen

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Time in days Fig. 1. Measured and scaled production from a solar-power installation (top); measured consumption from a detached domestic house (center) and calculated net consumption when the two are combined. The time axis runs from 23 February through 31 October

The correlation between production and consumption

obtained from the house is shown in Fig. 2. A strong positive correlation is most supportive for the grid because it will result in the production compensating the consumption, thus reducing the loading of the grid. Measurements for this case show that there is a mild negative correlation (-0.21) between production and consumption, i.e. high production is more likely to occur with low consumption. The correlation between the production and the office building during one year is slightly positive, 0.1 indicating a more suitable match between production and consumption.

Fig. 2. Consumption at a detached house versus production: hourly values obtained over the same period at locations close to each other

An important visual observation from the measurements is

that there can even be substantial amounts of solar-power production during periods of relatively high consumption (3 to 4 kW) but not during peak consumption (6 to 7 kW).

The solar production during periods of high consumption is not sufficient to reduce the peak loading of the grid, as is shown in Fig. 3. The highest consumption occurs when the solar production is zero, so that solar power does not reduce the peak loading of the grid.

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Fig. 3. Maximum loading of the grid as a function of the installed capacity of solar power with a domestic customer.

For installed capacity above 7.5 kW, the reserve flow becomes bigger than the maximum consumption. With installed capacity above 7.5 kW the risk of grid overload increases.

III. CURTAILMENT

To prevent overloading, a curtailment scheme can be used [4][5][6]. In such a scheme, the production of solar power is reduced whenever the net flow exceeds the limit. When the number of hours during which overload occurs is small, this can be a more economical solution that strengthening the grid to increase the hosting capacity. Alternative solutions, including energy storage, have been studied by many others as well, e.g. [7]. The two curtailment schemes studied in this paper are the following ones: � The production is reduced to zero once the net flow

exceeds the limit. This is referred to as “hard curtailment”.

� The production is reduced such that the net flow becomes equal to the limit (“soft curtailment”).

Both are to some extent extreme cases; the reality will be somewhere in between where improved control and communication will shift the results towards “soft curtailment”.

A. Domestic installation The impact of two such schemes on the annual power

production is shown in Fig. 4 for the domestic installation. The annual production has been calculated over the period 23 February through 31 October.

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Fig. 4. Annual production from solar power as a function of installed capacity, for hard curtailment (red circles) and for soft curtailment (green crosses).

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For installed capacity up to about 9 kW, the difference

between the two schemes is small and for neither of them is the loss of production a large amount. With a relatively simple scheme, the installed capacity can be increased without much loss of produced energy.

When the installed capacity exceeds 9 kW the hard curtailment scheme results in an actual reduction of the energy production. For a soft curtailment scheme the energy production still increases, but with diminishing returns.

The hosting capacity without curtailment, for this installation would be between 5 kW (the worst case assuming maximum production and minimum consumption) and 7.5 kW (according to Fig. 3), depending on the amount of risk that is acceptable. Even for hard curtailment, there is no significant impact of curtailment on the annual production up to about 9 kW installed capacity. For soft curtailment the reduction in annual production becomes noticeable around 11 kW. In most cases the largest system available on the market to day for a domestic customer is 10 kW but this could change in the future with more efficient PV-cells.

B. Commersial installation With an existing installation consisting of a 20-kW PV-

plant and an office building, both connected to a 500-kVA transformer there is at the present no risk of overloading the transformer. During the year the measurements took place the consumption of the office building was always higher than the production from the PV-plant so at no time did back feeding take place. The minimum value for the consumption measured was 22.4 kW which exceeds the maximum production. During one year, using measured values for the consumption (2011) and the production (2012), the need for curtailment due to overloading of the transformer occurred zero times as expected.

Assuming that additional panels are connected at the same location it is feasible to think that the production from those panels would be close to the production of the existing plant as they would be exposed to the same amount of irradiation. The impact from clouds partially shading the modules can likely be ignored for the hourly values. The highest loading of the transformer would occur at full production and zero load so theoretically the amount of PV that is possible to install would be at least 500 kW, where we assume zero reactive-power and nominal voltage. The power factor is close to zero during full production meaning that the active power can be considered equal to the apparent power.

Calculations of the potential need for curtailment based on the measurements from the aforementioned location are shown in Fig 5 and Fig 6. The maximum consumption measured during this timeframe was 152 kW. Based on this a maximum source size of 160 kW was used.

The calculations were made for hard curtailment as well as for soft curtailment. When the worst-case approach is used

and curtailment is not possible (this is sometimes referred to as “firm hosting capacity”), maximum production would be assumed to coincide with zero consumption. The hosting capacity would be 160 kW in that case and to connect a larger installation strengthening of the grid will be needed.

Fig 5 Amount of curtailed energy for hard curtailment (red solid) and soft curtailment (black dashed)

Using curtailment, there is no longer any limit to the

installed capacity set by the grid. Instead, the production will be curtailed whenever a risk of thermal overload occurs. For installed capacity below 200 kW no curtailment would be needed as can be seen in Fig 5. Installations significantly larger than 160 kW (the firm hosting capacity) can be connected with curtailment taking place only a small percentage of time. If hard curtailment would be used the amount of curtailed energy would increase fast, with an installed capacity of 400 kW the amount would reach 6.35 MWh/week. For soft curtailment the amount would be 1.7 MWh/week with a capacity of 400 kW.

In Fig 6 the amount of produced energy with hard and soft curtailment is shown. The produced energy will increase for increased installed capacity. If soft curtailment is used; the increase will decrease for levels above 200 kW but there is still an increase. If hard curtailment is used a point one will be reached where the produced energy will start to decrease as the installed capacity increases.

Fig 6 Amount of produced energy for hard curtailment (red solid) and soft curtailment (black dashed).

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As shown in Fig 6; the same amount of energy will be

produced with an installed capacity of 210 kW as with 270 kW if hard curtailment is used. For hard curtailment, the maximum production is obtained for an installed capacity around 250 kW. For larger installed capacity, the produced energy reduces.

C. Comparison A comparison was made between the two cases (domestic

and commercial installation). For the domestic case, the consumption from a detached house located not far from the PV-plant was combined with the production. In this case the consumption was scaled with a factor of 20 to give a better comparison to the consumption at the office building. The correlation between the production and the consumption of the detached house is slightly negative, -0.21, i.e. high production is more likely to occur at times with low consumption.

In Fig 7 the amount of produced energy for hard curtailment and soft curtailment is shown with the different consumption patterns (detached house and office building). When hard curtailment is used, the maximum production (for the combination PV and office building) is obtained for an installed capacity around 250 kW. This is reduced to 215 kW for the case combined PV and detached house. Both cases show a very similar relation between installed capacity and annual energy production. There are some differences however and especially for hard curtailment it is important to obtain data on local consumption.

Figure 7 Amount of produced energy for hard curtailment (red solid top)

and soft curtailment (black dashed top) when the production is combined with the consumption from a detached house and the amount of produced energy for hard curtailment (blue solid lower) and soft curtailment (green dashed lower) when the production is combined with the consumption from an office building

IV. OVERVOLTAGE Overloading of the distribution grid due to excessive net

production requires rather large amounts of installed power, but it is not impossible especially in suburban distribution networks where most of the customers do not have electric heating. (Electric heating and district heating are common in Sweden, the latter especially in the cities.) Overvoltage due to solar-power installations might occur already for small amounts of installed capacity. This is especially reported as a concern in rural domestic areas where the day-time consumption is low.

A. Voltage magnitude versus power production Measured relations between produced power (injected

current) and voltage are shown in Fig 8 for two locations. Especially for the location on the left high voltage variation occur at periods when the solar production is low. For installed power above 1100 Watt (5 A injected current) the maximum rms voltage will increase up to 106 % of nominal. The measurement shown on the right side in Fig 8 derives from a stage experiment representing a remote customer (1.11 ohm source impedance) with a 2.5 kW PV installation and no load connected.

Fig. 8. Relation between injected current from solar power and terminal voltage for two locations, Narvik, Norway (left); Skellefteå, Sweden (right).

For these two locations there is no risk for unacceptable

overvoltages; the maximum permissible voltage is 252 Volt in Sweden. But for remote rural locations, such risks can be substantial. Voltage magnitudes that exceed the limits set by standards are fairly easy to avoid with an inverter that disconnect when the voltage magnitude reach a pre-set value. This could however possible limit the yield from a plant and thereby making the depreciation time to long for PV to be a good investment.

B. Connection to a weak grid The combined measurements from the detached house and

the scaled (maximum is equal to 5 kW) production data was used to calculate the resulting voltage magnitude for a location with an assumed source resistance of 1 Ohm and nominal voltage of 230 V. A source resistance equal to 1 Ohm is seen as within the upper range of what is acceptable by most Swedish network operators. It was further assumed that the voltage, for zero net consumption, would be exactly equal to the nominal voltage (230 V).

The result is shown in Fig 9. The blue horizontal line corresponds to maximum permissible voltage in Sweden and

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the red horizontal line corresponds to the minimum.

Fig. 9. Resulting voltage magnitude when measured values of production and consumption for a detached house are used together with a source impedance of 1 ohm.

The voltage magnitude is highest during times with high production (spring and summer) and low consumption and at some instances the magnitude exceeds the limit. But as can be seen in Fig 9 the injection of active power also helps to keep the voltage magnitude above the minimum permissible level. The conclusion from the figure is that this customer most likely cannot be connected to a weak grid.

V. CONCLUSIONS There are concerns that the peak production (midday) and

peak consumption (mornings and evenings) happens at different times for homeowners. One solution might be to install the panels facing east and west instead of south. The net production would be lower but the production would happen at instances when the homeowners are more likely to use the energy and from a system perspective this might be a better solution. The production and consumption would take place close to each other and the system losses would be lower. To better match times with high production to times with high consumption will also reduce the risk of overloading.

It is shown that curtailment can be an effective method for avoiding grid overload due to solar power. Both soft and hard curtailment can be used for this, but hard curtailment will

result in large loss of energy production when the installed capacity increases. Above a certain amount of installed capacity, the energy production will even reduce when hard curtailment is used. With soft curtailment there is no such effect and the energy production will continue to increase with installed capacity. However the economic return on investment will become less with increasing installed capacity.

VI. REFERENCES

[1] H. Persson, Ö. Kleven, M. Norton and T. Boström, "Initial Results from a Grid-Connected 2-Axis Solar Tracking PV System at 65°N in Piteå, Sweden," in Proceedings of EUPVSEC 2012, Frankfurt, Germany, 2012

[2] S. Rönnberg, M. Bollen, A. Larsson, Grid impact from PV-installations in northern Scandinavia, Int. Conf. Electricity Distribution (CIRED), Stockholm, June 2013

[3] M. H. Bollen and F. Hassan, Integration of Distributed Generation in the Power System. Wiley-IEEE Press, 2011.

[4] M. Bollen, Y. Chen, N. Etherden, Risk analysis of alternatives to N-1 reserves in the network, Int. Conf. Electricity Distribution (CIRED), Stockholm, June 2013.

[5] N. Etherden, M.H.J. Bollen, Increasing the hosting capacity of distribution networks by curtailment of renewable energy resources, IEEE Trondheim Power Tech, June 2011.

[6] M. H. J. Bollen, The Smart Grid Adapting the Power System to New Challenges. Morgan & Claypool Publishers, 2011.

[7] N. Etherden, M.H.J. Bollen, Dimensioning of energy storage for increased integration of wind power, IEEE Transactions on Sustainable Energy, 2013, accepted for publication

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