Resources adequacy Analysis of renewable generation variability - PowerPoint PPT Presentation

Resources adequacy – Analysis of renewable generation variability ING. MICHAELA LACHMANOVÁ FACULTY OF ELECTRICAL ENGINEERING, CZECH TECHNICAL UNIVERSITY IN PRAGUE 15TH IAEE EUROPEAN CONFERENCE 2017

Outline • Czech Republic – does it worth it? • Power sector and RES-E in the Czech Republic, solar boom • Resources adequacy – what is it? How can we measure it? • Methodology • Case study – 15 min RES generation in the Czech Republic • 15 min generation • 15 min gradients • Conclusion 2 9/6/2017

Czech Republic • 10 mio inhabitants • GDP - 192.92 billion US dollars (2016) • 1st in beer consumption in the world (3rd Austria) • Pilsner Urquell, Budweisser • Sport nation (Jaromir Jagr, Petra Kvitova) • 1989 – Velvet revolution (centrally planned economy) • 2003 – member of EU • Traditionally focused on heavy industry (Škoda auto, Paramo, Setuza) • Steel industry, petrochemical industry 3 9/6/2017

Czech power sector 1/2 4 9/6/2017

Czech power sector 2/2 • Nuclear and coal power • Heavy industry • Exporter • Overflows from Germany to Austria 5 9/6/2017

RES-E in Czech Republic • RES significantly increased in the last five years • 2010, 2011 solar boom (around 500 EUR/MWH FIT) • The highest share of PVE sources with an installed capacity over 1 MW • The highest share of wind sources with an installed capacity over 2 MW 6 9/6/2017

Aspects of RES integration • • Sustainable and secure energy High investment costs (recently lower) • • Protection of the environment Subsidies • • The limited supplies of fossil fuels and the High final electricity price • negative impact of their use on the Merit order effect • environment Intermittency • • Energy security - local independence on Low energy area concentration • energy sources Public opinion • • Social benefits of renewable energy. Traditional country Renewables are going to be more widely implemented – we should recognize how and focus on technical point of view – this paper focuses on basic characteristic of RES 7 9/6/2017

Resources adequacy Generation adequacy Capacity credit vs capacity factor • The ability of the generation in the power system to • Capacity factor is the ratio of generator actual output match the load on the power system at all times. over a period of time to its maximum generation capacity over the same period. • More broadly in long-time period, it is also about finding the optimal structure of sources for electricity • Capacity credit or capacity value of a generator is the generation taking into consideration all economic, amount of additional peak load that can be served by environmental and technical aspects of all types of that generator. sources. • Capacity factor and capacity credit are basic • For RES integration is crucial to analyze renewable characteristics of sources to determine the production and determine short term characteristics contribution of sources to generation adequacy. to determine contribution of RES to generation adequacy Short term variability analysis leads to calculation of sources covering hourly gradients of RES production – hourly (15 min) changes in generation 8 9/6/2017

Methodology • Statistical analysis of renewable generation • 15 min data • Mean, median, standard deviation, 95% confidence interval • Capacity factor 𝑞 𝑢 𝑑 = 𝑞 𝑗𝑜𝑡𝑢 • 15 min gradients • Mean, median, standard deviation, 95% confidence interval 𝑕 𝑢 = 𝑞 𝑢 − 𝑞 𝑢−1 9 9/6/2017

Case study – PVE, wind generation 1/2 • All wind generation in the Czech Republic, aggregated • All PVE generation in the Czech Republic, aggregated • 15 min data 1.7.2016, wind and solar production, 1.1.2016, wind and solar production, Czech Republic Czech Republic 1400 160 140 1200 Generation (MW) Generation (MW) 120 1000 100 800 80 600 60 400 40 200 20 0 0 00:00 01:15 02:30 03:45 05:00 06:15 07:30 08:45 10:00 11:15 12:30 13:45 15:00 16:15 17:30 18:45 20:00 21:15 22:30 23:45 00:00 01:15 02:30 03:45 05:00 06:15 07:30 08:45 10:00 11:15 12:30 13:45 15:00 16:15 17:30 18:45 20:00 21:15 22:30 10 9/6/2017

PVE, wind generation 2/2 – capacity factor Wind generation, Czech Republic (2016) PVE generation (Czech Republic (2016) 8000 100,00% 20000 100,00% 7000 80,00% 80,00% 15000 6000 FREQUENCY FREQUENCY 5000 60,00% 60,00% 10000 4000 40,00% 40,00% 3000 5000 2000 20,00% 20,00% 1000 0 0,00% 0 0,00% 0 106 212 318 424 530 636 742 848 954 1166 1060 1272 1378 1484 1590 1696 15 30 45 60 75 90 105 120 135 150 165 180 195 210 225 240 0 PRODUCTION (MW) PRODUCTION (MW) Wind generation PVE generation Minimum 0,000 0,000 Maximum 0,839 0,829 Mean 0,163 0,76 Standard deviation 0,171 0,187 95% confidence interval top 0,000 0,000 95% confidence interval bottom 0,474 0,425 11 9/6/2017

9/6/2017 15 min gradients 1/3 15 min gradient -0,015 -0,005 0,005 0,015 0,025 -0,02 -0,01 0,01 0,02 0 01.01.2016 00:15 01.01.2016 01:15 01.01.2016 02:15 01.01.2016 03:15 01.01.2016 04:15 01.01.2016 05:15 01.01.2016 06:15 01.01.2016 07:15 Wind (%) 01.01.2016 08:15 1.1.2016 01.01.2016 09:15 01.01.2016 10:15 01.01.2016 11:15 01.01.2016 12:15 PVE (%) 01.01.2016 13:15 01.01.2016 14:15 01.01.2016 15:15 01.01.2016 16:15 01.01.2016 17:15 01.01.2016 18:15 01.01.2016 19:15 01.01.2016 20:15 01.01.2016 21:15 01.01.2016 22:15 01.01.2016 23:15 15 min gradient -0,05 -0,04 -0,03 -0,02 -0,01 0,01 0,02 0,03 0,04 0,05 0,06 0 01.07.2016 00:00 01.07.2016 01:00 01.07.2016 02:00 01.07.2016 03:00 01.07.2016 04:00 01.07.2016 05:00 01.07.2016 06:00 01.07.2016 07:00 Wind (%) 01.07.2016 08:00 1.7.2016 01.07.2016 09:00 01.07.2016 10:00 01.07.2016 11:00 01.07.2016 12:00 PVE (%) 01.07.2016 13:00 01.07.2016 14:00 01.07.2016 15:00 01.07.2016 16:00 01.07.2016 17:00 01.07.2016 18:00 01.07.2016 19:00 01.07.2016 20:00 01.07.2016 21:00 01.07.2016 22:00 01.07.2016 23:00 12

15 min gradients 2/3 Wind gradient histogram PVE gradient histogram 25000 100,00% 25000 100,00% 90,00% 90,00% 20000 80,00% 20000 80,00% 70,00% 70,00% FREQUENCY FREQUENCY 15000 60,00% 15000 60,00% 50,00% 50,00% 10000 40,00% 10000 40,00% 30,00% 30,00% 5000 20,00% 5000 20,00% 10,00% 10,00% 0 0,00% 0 0,00% -0,15 -0,136 -0,122 -0,108 -0,094 -0,08 -0,066 -0,052 -0,038 -0,024 -0,01 0,004 0,018 0,032 0,046 0,06 0,074 0,088 Další 13 9/6/2017

15 min gradients 3/3 Wind generation PVE generation Minimum -0,148 -0,130 Maximum 0,140 0,087 Mean 0,000 0,000 Standard deviation 0,015 0,015 95% confidence interval top -0,025 -0,025 95% confidence interval bottom 0,025 0,025 14 9/6/2017

Conclusion • Maximum generation 0,83 wind, 0,829 PVE • Capacity factor is very low – 7,6% PVE, 16% wind • Hourly (15 min) gradients • Maximum values - Germany (-80%;88%) vs Czech Republic (-14%;8%) • Hourly variability is high • Hourly gradient is not as high – 3% • Following research – dimensioning of backup sources, demand response… 15 9/6/2017

Thank you for your attention! Ing. Michaela Lachmanová Department of Economy, Management, Humanities Faculty of Electrical Engineering Czech Technical University in Prague Michaela.lachmanova@fel.cvut.cz 16 9/6/2017