Steps towards integration of PV-electricity into the GRID

Transcription

1 PROGRESS IN PHOTOVOLTAICS: RESEARCH AND APPLICATIONS Prog. Photovolt: Res. Appl. (2010) Published online in Wiley Online Library (wileyonlinelibrary.com) PAPER PRESENTED AT 25th EU PVSEC WCPEC-5, VALENCIA, SPAIN, 2010 Steps towards integration of PV-electricity into the GRID F. P. Baumgartner 1 *, T. Achtnich 1, J. Remund 2, S. Gnos 3 and S. Nowak 3 1 ZHAW Zurich University of Applied Sciences, School of Engineering, Institute Energy Systems a. Fluid-Eng., CH-8401Winterthur, Switzerland 2 Meteotest, Bern, Switzerland 3 NET Nowak Energie & Technologie AG, CH-1717 St. Ursen, Switzerland ABSTRACT The high growth rate of photovoltaic (PV) installations leads to the question about the consequences for grid integration and management. As a case study, we present an analysis of the first limits for the amount of PV electricity in the utility grid of the greater Zurich area. The first limit is found at an amount of 6% of the yearly electricity generation from PV, where the PV generation capacity begins to exceed the daytime increase of the load profile. This scenario assumes no changes of the daily constant base load generation. If the PV power is further increased to an amount of 10% of the overall electricity generation, about 8% of the PV electricity production could find no demand, starting with a surplus of PV production at noon at sunny weekends in summer time. This would reduce the nominal working hours of the PV plants by 8%, increasing the PV generation costs by the same factor. An amount of 17% of PV generation can be reached in the Zurich utility grid by storing the surplus of unused PV electricity as produced, by the widely available pumped hydro plants in the Swiss Alps. The 17% PV target would also be possible without storage, but it would require reducing the base load power production in favour of PV electricity generation. To further increase the amount of PV electricity generation above 20%, low cost storage means or changes of the load profile would be required. Copyright # 2010 John Wiley & Sons, Ltd. KEYWORDS grid integration; limit; nominal hours; performance *Correspondence F. P. Baumgartner, ZHAW Zurich University of Applied Sciences, School of Engineering, Institute Energy Systems a. Fluid-Eng., CH- 8401Winterthur, Switzerland. bauf@zhaw.ch Received 26 May 2010; Revised 6 August INTRODUCTION If at any time, there is no demand to consume or export electricity generated from photovoltaic (PV) systems, nor appropriate means of storage available, for example at noon in summer time, feeding PV electricity into the grid has to be blocked if the PV production is dominating at that time. We will face this load profile limit in well-developed PV utility grids long before we will see the upper limit due to limited space on rooftops or for other building integrated PV plants. The work presented here aims to quantify these limits for the electricity grids in Switzerland and to discuss issues and future needs to overcome some of the limitations [1,2,3,4]. Among one of the most advanced studies working on the integration of variable renewable energies in a larger utility grid is the Western Wind and Solar Integration Study in the USA [5]. In this study, based on the present cost scenario, wind power is the dominating source with a factor of six higher than the amount of solar electricity generation. The recent German grid integration study found a reduction of the needed base load power, by the combination of several variable renewable energy sources and an increase in peak power production, mainly by hydro. This study Copyright ß 2010 John Wiley & Sons, Ltd. 1

2 Steps towards integration of PV-electricity F. P. Baumgartner et al. analysed a 2020 scenario with 24% wind power production in combination with 7% of PV electricity generation [6]. In the study presented here, we will analyse high PV penetration rate scenarios, neglecting the amount of wind power in Switzerland, and the availability of stored hydro power in the mid term future. 2. METHOD The main question is, when the overall PV generation capacity exceeds the power load in a defined electricity grid. On the basis of the measured load profile in Zurich for 2008, several scenarios are developed to match this profile with large amounts of PV capacity. The second input data are measured irradiance characteristics from those parts of Switzerland, where the future grid connected, mainly roof top PV systems, will most likely be installed. During the scenario runs, the actually produced PV electricity is scaled with the measured irradiance values at the same time as the load characteristic was recorded. In this way, the results provide answers to find out which share of PV generation in the electricity production would have been possible if the supposed nominal PV power had been still installed in In the present study, no other additional renewable electricity generation sources, like wind, biomass or geothermal energy are taken into account. These will be taken into account in future work Load profile in the utility grid The current analysis is based on the load profile of the greater Zurich area, the largest final distributor in the Swiss utility grid. This 15 min load profile can be taken as an average for whole Switzerland. In the investigated year from October 2007 to September 2008, the overall consumed electricity was about TWh, with a maximum load of 1004 MW [7]. This is about 10% of the whole electricity consumption in Switzerland. The average load profile, required to supply about 1 million inhabitants, can be taken also as a typical profile for whole Switzerland with about the same overall yearly electricity consumption of around 7500 kwh per capita [8]. A typical weekly load profile is given in Figure 1, showing a maximum load at noon. The lowest consumption is evident not only on the weekend but also on the 1st of August, which is a national holiday in Switzerland. It can also be seen that in August, the daily maximum load is close to the yearly average load. The minimum at night goes down to about have of that value, which was taken as the typical base load limit (Table I). In wintertime at noon or in the evening, the maximum load is about 40% higher than the average power. The current electricity supply in Switzerland is separated into a daily constant base load, which is typically supplied by nuclear power plants and a smaller amount by run-of-river hydro power plants. The daily peak at noon and in the late afternoon is supplied by hydro storage power plants located in several parts of the Swiss 1 instantaneous Power/average Power Consumed Energy PV Yield Average Power Base Load Excess Energy Mon 28/07 Tue 29/07 Wed 30/07 Thu 31/07 Fri 01/08 Sat 02/08 Sun 03/08 Figure 1. Load profile in the greater Zurich utility area from 28th July to 3rd August 2008 and possible PV generation according to scenario A, with unchanged base load (yearly PV fraction 5%, see Table II).

3 F. P. Baumgartner et al. Steps towards integration of PV-electricity Table I. Sum of the global horizontal irradiance in the period given in kwh/m 2 (the selected regions are: ch, Swiss average; mi, Plateau central Switzerland; be, Bern area; zh, Zurich area; ti, southern Switzerland). ch mi be zh ti % 96% 97% 94% 104% Alps [8]. Today in Switzerland, 56% of the annual electricity is produced from hydro power. Of this amount, 49% is production from seasonal storage power plants, only 4% is produced by pumped hydro power plants and another 47% is generated in run-of-river hydro power plants [9]. The maximum power generated from pumped hydro presently sums up to 1.4 GW and will be strongly developed by another 4 GW over the next years [10]. Thus today, the maximum power of all pumped hydro plants is about 20% of the yearly average consumed power, a high value compared to other European countries. Due to the fact that in the next 5 years, the pumped hydro power capacity in Switzerland will be at least doubled, the assumption of an available 30% hydro power relative to the average consumed power was used in the following scenarios in Table II. The different PV scenarios shown in Table I, either leave the base load characteristic unchanged all the time (scenarios A) or reduce the production from conventional base load plants in favour of a prioritised PV power production (scenarios B). If the power produced from PV is higher than the actual demand, as it appears as excess energy in Figure 1 at noon on Sunday, storage or export to another grid can be taken into account. Otherwise, the production from PV systems has to be reduced, leading to lower nominal working hours and higher PV generation costs. To get use of the excess energy, storage is assumed, for example by the use of pumped hydro storage Solar input and PV output The analysis of the radiation data is based on ground measurements of MeteoSwiss. The 10 min data of the period October 2007 till September 2008 of 41 stations has been used. The 41 measurement stations (out of possible 72) have been selected to give a representative distribution of inhabited areas of Switzerland. Measurement stations on mountain passes and tops have been avoided. Nevertheless, the selection is somehow arbitrary and has not been weighted according to available roof area or population density (Figure 2). The stations have been grouped in five different regions: All sites, Plateau, Canton of Zurich, Canton of Bern (together with Jura and both Basels) and Canton of Ticino. For those areas, the area averages have been calculated. The 10 min data have been regridded with cubic splines to 15 min data to fit with the electrical load data. The use of real area averages based, e.g. on satellite data could show even more homogenous distribution than the averages of the chosen ground sites. The sum of the horizontal irradiance is given in Table II in each of the five analysed regions in Switzerland. These yearly averaged values show a standard deviation of 3.8%. In Figure 3, it can be found that the hourly scattering of the irradiance data appeared in one region will be nearly smoothed out if the average of the greater region is calculated. In the following analysis, the produced excess PV energy is plotted in the same mapping diagram as it is shown for the yearly solar irradiance in Figure 4, daily hours versus day in the year. The PV performance statistics of Switzerland for 2007 indicated that new PV plants larger than 20 kw achieved excellent yearly performance values of 1050 nominal hours, while PV plants installed before 2005 have about nominal hours [11]. Due to the fact that in the coming years, the quality and the uncertainty of nominal power of PV systems will be further improved, we Table II. Studied PV integration scenarios (P M average load power 689 MW; base load at 50% of P M ; 1 million inhabitants are supplied by that load profile within the greater Zurich area; overall efficiency of pumped hydro 80%) see also Figure 11. In scenarios A, PV electricity powers the difference between constant base load production and maximum load; in scenario B, the PV electricity is able to power up to full load assuming reduction of the present base load production. Explanation of abbreviations: A10s stands for scenario A with a 10% share of PV electricity of the overall yearly electricity consumption and s stands for using storage for the excess energy to maximum load (details see chapters 3.1 and 3.2). PV scenario Base load rel. to P M Max. storage rel. to P M (%) PV load mismatch losses (%) Nominal PV power rel. to P M Nominal PV power Wp/capita PV amount of overall electricity (%) A5 Constant A10 Constant A10s Constant A17s Constant B17 Reduced B30 Reduced B30s Reduced

4 Steps towards integration of PV-electricity F. P. Baumgartner et al. Figure 2. Solar input data. Figure 3. Measured global horizontal solar irradiance in Switzerland by MeteoSwiss stations in the period (left: Zurich region, right: average of all regions in Switzerland).

5 F. P. Baumgartner et al. Steps towards integration of PV-electricity Figure 4. Mapping of the global horizontal solar irradiance in Switzerland showing the average of the meteo stations given in Table I. estimated in this study an upper value of 1050 average yearly nominal hours. By the use of PV simulation tools and comparison with real measurements, the modified average performance ratio of each month was calculated and applied to the horizontal irradiance data. 3. RESULTS AND DISCUSSION Two groups of PV integration scenarios were calculated. Scenario A always adds the produced PV power to the fixed value of the base load. Thus, PV electricity offers the chance not to use the seasonal stored hydro power in the Swiss Alps, to fill the daily load peak at noon, or to export it at peak load prices. Scenario B gives PV electricity the priority to be fed into the grid at any time, according, for example to present legislation in several countries not only in Europe. We assume for this case the reduction of production from base load power plants, which in fact have to follow the rules of the transmission system operators (TSOs) and the grid operators embedded in the UCTE [12]. There, the coordination of the first, second and the tertiary control management is defined to compensate for small deviations between demand and for example excess of PV energy and guarantees a stable electricity supply across Europe. The simulation runs evaluate the produced PVoutput for each 15 min over the analysed 1 year period and enter the values in the balance load sheet, based on recorded 15 min load profiles in the greater Zurich area, as previously discussed. In Table II, all the scenarios are summarised and the final amount of PV electricity relative to the overall yearly electricity consumption is given. Even at a 5% PV penetration on top of the constant base load, the A5 scenario will lose about 1% of the possible PV production. This type of PV load mismatch losses, due to the fact that small additional PV production can exceed the load demand at some short periods in the year (Figures 5 7), can be compared with the other scenarios. These losses give the first limit of PV penetration without changing the base load management of the conventional power production of the grid as it is done in scenario B. Beside these full load scenarios, simulation runs are performed, by cutting off the feed-in of PVelectricity at the maximum available load in summer time. In scenario A10s and A17s and B30s this amount of PV energy is stored at noon and shifted into late afternoon or nighttime. These scenarios assume that, beside today s established solutions, other electricity storage system will likely be economically available in the future. Compressed air, batteries or hydrogen may be an option also in smaller decentralised systems connected to the grid. In Table II, the available maximum storage power is given relative to P M, the mean value of the yearly power consumption in the grid. The reduction of the yearly reached nominal working hours of the PV-plants will lead to an overall increase in PV generation costs Scenario A: PV powers on top of constant base load Scenario A will use the availability of the load difference between day and night in summer time to be powered by PV. Even a low 0.7% of PV penetration added to the

6 Steps towards integration of PV-electricity F. P. Baumgartner et al. 1 instantaneous Power/average Power Consumed Energy PV Yield Average Power Base Load Excess Energy Mon 28/07 Tue 29/07 Wed 30/07 Thu 31/07 Fri 01/08 Sat 02/08 Sun 03/08 Figure 5. Scenario A10 where excess energy emerges not only on the weekend. This energy may be stored by pumped hydro and shifted several hours later again into the grid with an overall efficiency of 80% (details see Table II). constant base load on Sunday 3rd August morning exceeds the load. In terms of losses and stability issues, this is negligible. At 5% PV penetration, the losses occurred on the weekend, like in May Figure 1. At 10% PV penetration, the losses also emerge on regular working days like July 31st in Figure 5. The occurrence of excess energy is limited to 15 days in scenario A5 and occurs in summer time according to Figure 6. A clear picture of the appearance of the excess energy over the year is given in Figure 7. If one compares this mapping with the irradiance mapping in Figure 4, a smaller amount of excess energy is found in the later afternoon, due to higher load at that time during the day. From an economic point of view, the yearly nominal hours of a PV plant, expressing the average time when the plant is working at nominal power, and the investment cost of the plant are the key figures of success. The increase of losses due to excess energy at higher PV penetration rates will lead to a reduction of the nominal hours as shown in Figure 8. The five investigated different regions in Figure 6. Occurrences of excess energy, given relative to the average electricity power P M by PV production during several days in the year; left: scenario A5 right: scenario A10 and scenario A10s, which store all the electricity with an excess energy smaller than 0.3 of P M with the rest defined as not produced or losses (see Figure 7).

7 F. P. Baumgartner et al. Steps towards integration of PV-electricity Figure 7. Occurrences of excess energy, relative to P M of scenario A5 left and A10 in the right plot in the yearly mapping time of day and day in the year (details of the scenarios see Table II). Switzerland, with their different solar irradiance situation, as shown in Table I, show a similar shape of the reduction characteristics. This graph also shows a small mitigation of variability of the solar irradiance at higher PV fractions where the averaged value over Switzerland, curve ch has a light smaller slope than an individual region (see Table I) Scenario B: PV powers full load In scenario B, whenever possible, PV powers the full load mainly at noon during summer time.(figure 9) This priority to feed the load including the base load within scenario B can increase the share of PV production by roughly 10% compared to scenario A. The mapping of the yearly excess energy shows that the daily time period of occurrence is also reduced by about one third compared to scenario A (Figures 7 and 10) Summary of reduction of nominal PV hours The cost per kwh of PV electricity has to be analysed according to the actual possible nominal working hours in a given meteorological region with a given load profile ch zh be mi ti nominal hours PV STC /P M PV solar fraction in % W PV /W load Figure 8. Reduction of the nominal hours of PV plants in the investigated grid operation area and operation year with constant base load and no regulation energy. The second set of characteristics shows the amount of needed PV power relative to the average power to fit the given PV penetration rate (details see Table II).

8 Steps towards integration of PV-electricity F. P. Baumgartner et al. 1 instantaneous Power/average Power Consumed Energy PV Yield Average Power Base Load Excess Energy Mon 28/07 Tue 29/07 Wed 30/07 Thu 31/07 Fri 01/08 Sat 02/08 Sun 03/08 Figure 9. Scenario B17 where excess energy emerges only on the weekend. This energy may be stored by pumped hydro and shifted several hours later again into the grid with an overall efficiency of 80% (details see Table II). Figure 11 summarises the scenarios in terms of nominal working hours. In the upper part of the graph, the nominal working hours of PV systems will be reduced by increasing the over all PV penetration rate. Thus the PV generation cost will be elevated by a similar amount. In the lower part of this figure, the needed nominal PV power is given relative to the PV penetration rate. The shown progressive slope of the characteristics of needed PV power to produce the proposed PV penetration rate indicates the decrease in overall production efficiency. This efficiency is higher for scenario B and may be further improved by additional short time storage Scenarios and cost trends One of the main questions is always which are the lowest cost options to deliver electricity to the customer at a certain time. To reach the A10 scenario, we have to compare the costs of further reducing the PV system price by 8%, to compensate for the load loss mismatch, with the costs to store 10% of the yearly produced PV electricity, according to Figure 11. Today, pumped hydro is cheaper, and state of the art batteries like lead acid or lithium ion are much more expensive than PV electricity costs. Therefore, a few countries like Switzerland or Austria Figure 10. Occurrences of excess energy, relative to P M of scenario B17 left and B30 in the right plot in the yearly mapping time of day and day in the year (details of the scenarios see Table II).

9 F. P. Baumgartner et al. Steps towards integration of PV-electricity A5 A10s A10 B17 A17s B30s B nominal hours PV STC /P M base load - no regulating energy base load - regulating energy no base load - no regulating energy no base load - regulating energy PV solar fraction in % W PV /W load 2 1 Figure 11. Reduction of nominal working hours summarising all scenarios in Table II; scenario A: PV on top of base load no regulating energy, scenario B: PV powers full load no regulating energy. have the highest potentials to reach PV penetration rates between 10 and 20%. This cost advantage can also be found in comparison with other locations with considerable higher solar irradiance values. Other effects and trends concerning the PV-limits are local wind production, limitation due to local weak grid conditions due to limiting cable cross-sections, the absence of adequate supply of balancing power in the grid management. Further improving the European grid infrastructure reducing the barriers of large distance electricity transport is also related to substantial costs as well as the development of smart grids. The fast developing PV sector will be further successful if important growth limiting factors are known and solutions to overcome the limits also outside the PV sector can be successfully developed. It is highly relevant within the PV sector itself that PV system engineering solutions focus on implementing electricity storage systems management into PV power electronics in combination with daily peak load shift features. Both sectors PV and storage technologies are highly emerging markets and therefore only a rough scheme of relevant aspects in cost development in the next decade and beyond is given here (Figure 12). 4. CONCLUSION AND OUTLOOK It was found that an amount of 10% of PV electricity is possible to be integrated into the utility grid in Switzerland, without the need for additional storage. For such an amount, the present base load power generation has not to be changed and 8% losses of not used PV electricity will occur, increasing the PV generation costs by that factor. PV penetration rates of up to 20% are possible without the need for storage, if base load power plants would have to give the production of PV power full priority. Both scenarios may increase their PV penetration rates by about 10% if cost effective storage, like pumped hydro is available for that purpose. These sorts of grid limitations will occur long before the limitation of available roof areas will be dominant. It can be expected that due to the availability of pumped hydro power in the Alps and the relative low amount of wind power, Switzerland and Austria will face 2010 PV generation costs at 100% feed into grid Limit day night peak 5 to 10% Additional storage costs daily Limit (storage) day night peak 10 to 20% 2025 Total household electricity price Limit PV roof top space 30% 2030 Figure 12. Principle scheme of the development process towards increasing the PV electricity amount in the electricity grid.

10 Steps towards integration of PV-electricity F. P. Baumgartner et al. some of the highest short term potentials of the share of PV electricity in the overall electricity production. Further work will be performed to evaluate the function of needed PV storage and storage time if the solar penetration rate should be further increased. On that base, the future available storage options should be discussed. ACKNOWLEDGEMENTS The support of the load profile data set from EKZ, Zurich and the support of the metrological data from MeteoSwiss are highly acknowledged. REFERENCES 1. SETfor2020, Solar photovoltaic electricity: a mainstream power source in Europe by 2020, EPIA report, Nowak S, Gnos S, Gutschner M. Würdigung der Kernaussagen des SETfor2020 Reports aus Schweizer Sicht, Initiative of the German Environmental Group DUH to work on the further development of the German Grid to increase the amount of Renewables; www. erneuerbare-ins-netz.de. 4. Baumgartner F. Integration of PV electricity into the Swiss grid ; Proceedings of the National PV Conference Switzerland; Feb Lew D. et al, NREL National Renewable Energy Lab, Goldon, CO, USA westwind or mercator.nrel.gov/wwsi; How do Wind and Solar Power Affect Grid Operations: The Western Wind and Solar Integration Study presented at the 8th International Workshop on Large Scale Integration of Wind Power and on Transmission Networks for Offshore Wind Farms, Bremen Germany October 14 15, Saint-Drenan Y. et. al; IWES Uni Kassel, Report Dec. 2009, Scenario 2020 Dynamic Simulation Germany;, Dynamische Simulation der Stromversorgung in Deutschland nach dem Ausbauszenario der Erneuerbaren-Energien-Branche. 7. Financial Report EKZ Elektrizitätswerke des Kantons Zürich; 2008/09; 8. Federal electricity statictis of Switzerland 2008, Bundesamt für Energie, Bern, Bestellnummer d/f / ; admin.ch/bundespublikationen. 9. Statistik der Wasserkraftanlagen der Schweiz, Status 1. Jan 2010; Bundesamt für Energie, Sektion Wasserkraft; pumped hydro plant Linthal/Glarus 1000MW added and will be operated in 2015; Newsletter der Kraftwerke Linth-Limmern AG j Mai 2010; Th. Hostettler; PV performance statistic Switzerland 2007, Bulletin SEV/VSE 8/2008 and Bulletin SEV/ VSE 5/2010 page Operation Handbook of the Union for the Co-ordination of Transmission of Electricity (UCTE) 2004; see alsohttp:// and