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S1E11

Stability Challenge: AI, Analytics&Maximizing PV Reliability with Gerhard Mütter TEB Podcast - S1E11

with Gerhard Mütter· NR· 1m

TL;DR

AI and analytics can enhance PV reliability and efficiency in energy systems.

Synopsis
Gerhard Mütter discusses the integration of AI and analytics in optimizing photovoltaic (PV) plants, emphasizing the importance of reliable forecasting and data analysis. He highlights the challenges and opportunities in the energy transition, particularly in Central and Eastern Europe, where regulatory frameworks and local engagement are crucial for success.

Key metrics

by the numbers · 8
  • 700 MW
    Ukrainian PV capacity
  • 4.5-5%
    Optimization improvement
  • 3 GW
    Indian PV plants optimized
  • 100 MW
    Free market sales optimization
  • 15-5%
    Forecast accuracy on clear days
  • 60%
    Austrian hydroelectric contribution
  • 11 tons
    Weight of 2 MW inverter
  • 8-11%
    PV production loss

Topics

5 tags
AI integrationPV optimizationData analyticsRegulatory challengesEnergy forecasting
Stats
Duration
1h 23m
Words
12.1k
Questions
25

Timeline

7 chapters
  1. Introduction of Gerhard Mütter

    Gerhard Mütter introduces his background and experience in renewable energy.

  2. Optimization of Ukrainian PV plants

    Mütter discusses optimizing 700 MW of PV capacity in Ukraine.

  3. Energy selling strategy in India

    Mütter explains how he optimized energy selling strategies for a 350 MW plant.

  4. Forecasting energy production

    Mütter highlights the importance of accurate forecasting for energy production.

  5. Austrian renewable energy landscape

    Mütter discusses Austria's reliance on hydroelectric power and renewable integration.

  6. Inverter specifications

    Mütter details the specifications of inverters used in renewable energy systems.

  7. Combining wind and solar

    Mütter discusses the benefits of integrating wind and solar energy systems.

Key insights

4 takeaways
  • 01

    AI enhances PV reliability

    Integrating AI can significantly improve the reliability and efficiency of photovoltaic systems.

  • 02

    Regulatory frameworks matter

    Effective regulatory frameworks are essential for facilitating energy transition in Central and Eastern Europe.

  • 03

    Local engagement is key

    Engaging local communities can mitigate challenges and enhance project acceptance.

  • 04

    Data analytics drives optimization

    Utilizing data analytics can lead to substantial improvements in energy production forecasting.

Pull quotes

2 quotes
  • The 700 megawatt got optimized 4 and a half 5% within the first years
    Gerhard Mütter
  • The 2 megawatt inverter have more the 2 megawatt inverter station have a weight of 11 tons
    Gerhard Mütter
Transcript1821 cuesClick a timestamp to jump
  1. So today in our episode 3 we have gear
  2. mud who doesn't like to be called a
  3. lecturer or professor because he has
  4. done he has done many others which
  5. includes doing integrating PV plants
  6. in many different part of the world
  7. doing a lot of work in the CE region and
  8. of course he would also CTO CTO for
  9. NR for a long period of time but I
  10. would let him introduce himself and then
  11. we go ahead.
  12. >> Okay.
  13. >>.
  14. >> Then let's start there.
  15. >> Let's start.
  16. >> Okay.
  17. I think I will not tell you my whole
  18. life because then the whole period will
  19. be over. But just give you a short
  20. idea of what it's been originally
  21. and that's done for you. I'm an
  22. automotive engineer. Then I started
  23. technical mathematics was then 25 years
  24. in computer graphics mainly focused
  25. on creating nice pictures of interior
  26. design and create an automatic generated
  27. sceneries on interior design which moved
  28. then to also renewables and since
  29. 2005 I'm more working for the renewables
  30. first as a product developer
  31. And then I started with my first
  32. part in Eastern Europe on supporting 700
  33. megawatt
  34. in Ukraine [clears throat] where part
  35. of them is on the island of Ka, part of
  36. them is in the area Odessa to the
  37. Romania border. So this is
  38. >> [snorts]
  39. >> Eastern Europe.
  40. >> Yeah.
  41. >> And the written in
  42. the topic. Yeah. And based on this
  43. there were challenges on having these
  44. plants under control and there I
  45. developed tools for really a lot of
  46. irregularities
  47. out of the out of the monitoring data
  48. and based on this the 700 megawatt
  49. got optimized 4 and a half 5% within the
  50. first years of my career of techn
  51. technical director that I was at that
  52. time. We then thought this idea of
  53. having analytics on based on monitoring
  54. data combined from my mathematical
  55. background with the renewable ones
  56. and created a product out of it. This
  57. product is now part of green power
  58. monitoring software and based on this I
  59. did looking at you as an Indian
  60. >> in your country optimization of
  61. across approximately 3 gawatt of plants
  62. and now counting here only that plants
  63. where I've been so I've been think six
  64. or seven times in the biggest plant of
  65. the world first in the first 100
  66. megawatt plant in Ukraine which is close
  67. to the airport of Cople
  68. on the island of Premier then the first
  69. gigawatt like the biggest plant in the
  70. world in BLA in Rajasthan.
  71. >>.
  72. >> and also the first gigawatt plant
  73. closed in one place which is in Korea
  74. but [snorts]
  75. approximately 3 or 4 hours south
  76. southeast of but in the center of India.
  77. Well, it well.
  78. >> I've been there for several times
  79. and there have been clients like
  80. Soft Bank who was the owner here 350
  81. megawatt of this gig plant
  82. >> and we optimized in this case we
  83. optimized their energy selling
  84. strategy on combining the weather
  85. forecast with the price that they get on
  86. the on because part of them they were
  87. selling on the on the free
  88. [clears throat] market. The part was the
  89. PPA like in India usual.
  90. >> Yeah.
  91. they made a part of saving on the
  92. on the free market 100 meg of this and
  93. I optimized here their accuracy of
  94. their forecast of their energy forecast
  95. bore forecast because the trick is if
  96. you if you sell exactly that energy that
  97. you have announced you get the best
  98. price.
  99. >> Yeah. If you if you produce more you
  100. get just a sheet on the top and if you
  101. produce less you have to buy on your
  102. price expensive additional energy.
  103. Mh. So the trick here was just to
  104. find out would the next day be close to
  105. that what is in India relatively often a
  106. clear sky day because on clear sky day
  107. you can predict a 15 minute exactly on 3
  108. to 5% exactly what you're producing if
  109. you have a cloudy day and then
  110. you have interruptions and you cannot
  111. predict 50 minutes plus minus what
  112. you're really producing [snorts]
  113. >> and so the trick It was there when we
  114. could see it [clears throat] on the
  115. weather forecast that there would be a
  116. clear sky day. We put our announcement
  117. on the top level of that what we
  118. predicted and on shitty days that we
  119. call them. we put our announcement on
  120. the lower one and we reduce based on
  121. this the prices for additional extra
  122. energy by 5%. And was it part of you
  123. being the independent consultant and
  124. going there and consulting the
  125. government or was part of some
  126. organization that you went there? it
  127. was it was during the this India tour
  128. we also were here talking with I
  129. don't know as a four fourdigit
  130. abbreviation of the Indian government
  131. that is that is taking care about the
  132. energy distribution in the country and
  133. here we did two of their plants a 10
  134. megawatt plant and a megawatt plant on
  135. from technical perspective I was only
  136. All of the time I was always focused on
  137. on the technical [clears throat]
  138. solutions. So all the political stuff
  139. that running behind was nice to see some
  140. politicians.
  141. >> Yeah.
  142. >> And to give them instantly to make
  143. technical sense to do something like
  144. this or what is to be expected or to
  145. discuss some on energy profiles
  146. because you have on the one hand the
  147. production profile on the other hand
  148. the profile of the market. So that was
  149. that was kind of nice. Yeah, we did we
  150. did something for this for this Indian
  151. government. I have some very friendly
  152. thoughts about them. They were
  153. trying to do but they are in a safe
  154. position. It's not the hard market
  155. >> centralized way.
  156. We like central
  157. >> central government. We like the
  158. centralized system.
  159. >> Yeah. [clears throat] Well, thank
  160. you, Kan for and first of all, I
  161. mean, what an introduction. So, it takes
  162. so much to get on our podcast.
  163. >> Yeah.
  164. >> Yeah. That you have to do so much work
  165. to get to fit.
  166. >> Yeah.
  167. It's just a matter of time.
  168. >> It's just a matter of time. I started
  169. this following the renewable
  170. ideas when I was at your age and my
  171. boys are at your age at the moment
  172. >> and they are still in the renewal
  173. project before now.
  174. >> Yeah.
  175. >> What a journey. But G just
  176. looking back it's been incredible
  177. journey but you said that you started
  178. your renewable journey back in 2005.
  179. 2005 I switched from from software
  180. to do something that I can grab because
  181. the part there were there were 25 years
  182. of doing more or less theoretical stuff
  183. from programming or coordinating a
  184. software company that I own at this time
  185. and it was quite interesting to not only
  186. to calculate the things and to show them
  187. nice pictures but really that then I did
  188. product management and developed
  189. ring solar thermal units and
  190. also setups for private household
  191. TV small PV units. So combining a small
  192. inverter, putting a set of cables,
  193. taking care that on your specific
  194. rooftop, you [clears throat] have the
  195. correct fixing system, the mounting
  196. systems that you need on every
  197. different tile that you have on your
  198. rooftop.
  199. You have you have different mounting
  200. systems. Yeah.
  201. >> Yeah. But it's very interesting. We
  202. were talking before the camera was on
  203. that your background was in the early
  204. stages of the AI, right? So
  205. >> it was it was in the I programmed I
  206. programmed the first in the in the
  207. 80s. I started [clears throat] when
  208. I first studied technical mathematics.
  209. did on the one hand the computer
  210. graphics on the other hand we were
  211. crazy about the algorithms of artificial
  212. intelligence creating the first
  213. neural networks on programming then in
  214. program lang program programming
  215. language yeah okay C is in the
  216. meantime C is still alive
  217. >> real software like I recorded
  218. >> so yeah I did I did some of the
  219. algorithms And there are also a few
  220. families I think you are now in this
  221. field where AI is in the market. you
  222. have on the eye. On the one hand, you
  223. have the algorithms that are simulating
  224. what your brain or trying to simulate
  225. what the brain is doing. That is and
  226. the other one is the interface to that
  227. and the interface is still a tricky
  228. situation.
  229. because on the interface you have
  230. to recognize
  231. what is going on and pattern
  232. recognition and also the modeling of
  233. the real world inside the computer is
  234. still a challenge. but I was also
  235. very amazed on being a part of
  236. that when we did the step from
  237. from the stupid black and white models
  238. that in the first days of
  239. computer science where where you have
  240. this binary situation. Okay, it is yes
  241. or no.
  242. >> And u in the meantime we have 256
  243. 256 shade of gray which you can
  244. represent. so the fuzzy logic were
  245. not black and white are the decision
  246. maker which is now used very
  247. intense on the artificial
  248. intelligence
  249. >> and compiling but the result and
  250. I'm I'm here also warning to my students
  251. when is the problem that you have is
  252. it is just compressing if you put
  253. in
  254. >> exactly
  255. >> yeah and that's the problem that
  256. you have if you follow EI where the
  257. database or the background is not
  258. verified by experts of the field where
  259. you use it and that's a different why u
  260. AI or if you take JP it is it is
  261. giving you word is like influencers
  262. are taking which is normally a
  263. compression of stupid things not
  264. everyone but there are there are for
  265. sure excuses on it but we have the
  266. advantage and on the other hand where
  267. artificial intelligence is working quite
  268. well. Take the example on detecting
  269. tumors on X-ray picture because there
  270. all the time every picture that is in
  271. the database and is quantified and
  272. classified. Here is the classifications
  273. is done by an expert
  274. >> and it's not done by anyone who says oh
  275. my py sister was jumping three times
  276. high on that so that must be the
  277. next for the whole world and here
  278. the results are really amazing and I
  279. in my later career when I was already
  280. in the renewables starting also
  281. >> from the from the path being the
  282. scientific committee of PVC
  283. I accompanied
  284. a PhD thesis in Portugal where a girl
  285. had to safely analyze 105 algorithms of
  286. [snorts] available in libraries like
  287. like the like you have at the moment
  288. usually Python libraries.
  289. >> Yeah. math lab is also one of
  290. these areas and she analyzed the
  291. usability.
  292. >> What year we are talking about
  293. >> what's
  294. >> what year was it?
  295. >> That was 200.
  296. >> Okay.
  297. >> Or or even 2020.
  298. >> Okay.
  299. >> So it was not not so long ago. Not so
  300. long ago. and she checked out this
  301. 105
  302. on predictive the sura production.
  303. the funny thing is this girl was from
  304. from Madaga where this island is
  305. famous for having a very fine structured
  306. local climate. So you have 500 m from
  307. one location a [clears throat] totally
  308. different climate. this is a small
  309. island in the Atlantic Ocean
  310. >> where the main wind mid direction is
  311. giving you because it is it goes
  312. out to 7 1, 700 1, 800 m
  313. and so the wind on the
  314. Atlantic gives a very fine segmented
  315. local climate. Each valley has different
  316. climate
  317. >> and that was amazing on checking
  318. out the quality of the algorithms.
  319. And there was during the work
  320. we classified it then to five groups on
  321. having neural networks more more than
  322. then on more on random
  323. numbers based
  324. >> okay
  325. >> Monte Carlo methodology and double
  326. checking we classified the test into
  327. five groups and the best result was done
  328. finally the final result of their
  329. PhD
  330. taking a top level algorithm based on
  331. fuzzy logic to decide which family of
  332. these five classes is the current case
  333. the best one
  334. >> and based on this we increased already
  335. the results I think by one or two%
  336. compared to the best to the average fit
  337. of the taking over five algorithms so
  338. this f logic on top of the artificial
  339. intelligence for select the real
  340. algorithms was an amazing result but
  341. also here the input have to be very
  342. clear and the expert who is using that
  343. artificial intelligence
  344. have to be in and should be an expert
  345. and then you get in this field and I
  346. think it is not only renewable energies
  347. you get then nice results
  348. >> nice every field
  349. >> in the in the in the meantime the
  350. second part is Then we are talking now
  351. here about the algorithm t part. The
  352. second part is the is the pattern
  353. recognition.
  354. >> So detect detect the difference and
  355. before we [clears throat] talked
  356. about the difference between cat and
  357. dogs
  358. >> where it is easier to detect this if you
  359. do not have a single slide but you have
  360. a movie out of it because the cat is
  361. moving much more smoother than the dog.
  362. Based on this you can detect
  363. C. You have the characteristics that are
  364. unique and you can then identify clear
  365. and the pattern recognitions you have in
  366. this algorithm is also the same topics
  367. detecting borders change of colors and
  368. based on this you can use them and
  369. classify and compress and data
  370. algorithms that are known already since
  371. 1990.
  372. >> Yeah. So in
  373. >> even before Yeah. Yeah. And it must be
  374. mind-blowing to see the evolution of AI
  375. when it started and
  376. where we are now. And in the AI field
  377. that you have seen in the field in
  378. renewable energies, you mentioned before
  379. something in
  380. in operation or maintenance or PV
  381. power plant for example. How do you see
  382. the AI and its role in renov?
  383. >> We have we have the same problems
  384. like you have in AI that means
  385. sheet in sheet out.
  386. >> so you have to clear clearly clearly
  387. segment and pre-ompress the data that
  388. you use for training your AI and you
  389. have a quite big variety on the
  390. monitoring data
  391. to detect this. So if you do not filter
  392. effects side effects out of it, you
  393. get the chaotic result and the result of
  394. any AI that you use on just stupid
  395. monitoring data is let's say limited
  396. >> it is it is limited it is most of the
  397. time it is marketing cake because it is
  398. not there is where is the border between
  399. statistics and AI. Yeah. so a lot of
  400. companies are also talking about
  401. their selecting and detecting fors on
  402. on AI and to be honest I was also
  403. one of them presenting and presenting
  404. things AI supported and but the main
  405. work is knowing what you're
  406. doing and figuring out I think in my
  407. lecture you have seen the simple
  408. things on having morning afternoon
  409. shares which is not necessary to put
  410. into AI but this simple calculation
  411. singiness and get the real sun position
  412. based on this this shadow is
  413. is not a fault this shadow is a is
  414. the daily position of the sun
  415. >> and you can skip it out if you don't
  416. filter it out and you just take the
  417. numbers or you're not aware that you
  418. are in the first row where you do not
  419. have the effect of the shadow because
  420. you are in the first row you can look
  421. poor into the sun. knowing what
  422. you're doing is here is here
  423. very much more interesting. Also, if
  424. you have different setups, you cannot
  425. use the same the same strategy on a
  426. flame power plant. than a power
  427. plant that is following the countryside
  428. a healing area
  429. >> because there every table looks into
  430. another direction and based on this
  431. you have you have different values
  432. and we have different characteristics.
  433. so taking u an AI algorithm that
  434. is trained on standard values on a
  435. flat area at the smooth climate and
  436. you put it then to a smaller power plant
  437. in the elves you get a bunch of force
  438. force. So that you have to filter out
  439. and based on that then it is limited
  440. but combining
  441. all the available technologies that
  442. are there makes sense. For instance,
  443. taking infrared pictures and based on
  444. the infrared pictures, classifying
  445. >> the patterns
  446. pattern classifying the patterns of the
  447. infrared pictures where a very
  448. clear difference between a broken cell
  449. and a broken diet because the broken
  450. diet or a diet is on a non location.
  451. It depends well if the model is oriented
  452. straight or or in landscape or or or
  453. portrait. But you have you have defined
  454. position where the location of
  455. the of the das is. And if this area is
  456. hot, you have and if the area is only
  457. one part hot, that that it is.
  458. And you can clear decide which
  459. kind of fault that that it is that it
  460. is also clear. If [clears throat] a
  461. quarter if a third of a model is
  462. in a different intensity than the
  463. other ones then quite clear
  464. what is the reason. So you can train you
  465. can train on that pattern and then you
  466. can classify
  467. and it helps you also to train
  468. if you have structural problem which is
  469. not very much in nowadays. there
  470. were a period around 2010 when the
  471. market on the PV
  472. >> exploded more or less.
  473. >> Yeah. 2010
  474. >> around 2010 plus minus 2 years 5 years
  475. and there was also the
  476. manufacturing was growing by amount of
  477. of models available on the market but
  478. the quality was not that perfect like it
  479. is now and also if you had to build
  480. bigger plants it was not possible to get
  481. from one manufacturer
  482. 10 megawatt
  483. or even more. Yeah. so today I your
  484. order without any problem is 100 but
  485. okay since week you had but
  486. >> had a good manufacturing at that time
  487. and even now right for
  488. >> PD they had they had manufacturer some
  489. friends of mine in the meantime they
  490. do other jobs but there one one or two
  491. manufact
  492. special ones are still glass gas
  493. models are for they have purpose for
  494. building integration
  495. for small frames. This they're still in
  496. Austria something but these big series
  497. >> we do not have the capacities here
  498. >> the this big factories in China and
  499. there will change but the problem was
  500. you have not you have the quality and
  501. sometimes it can happen that
  502. structural problems occur in the in the
  503. power and for that artificial
  504. intelligence is quite interesting. So
  505. your structural problem you have some
  506. patterns that are coming up. You take
  507. draw pages or you take these patterns
  508. from from the from the monitoring data
  509. more or less backtrack to the to the
  510. location where it is or you can follow
  511. up the growth rate of the
  512. phone and based on this you can then
  513. you would be able to coordinate let's
  514. say model replacement or any warranty
  515. cases. In these cases it makes sense
  516. to dig but these are single cases. in
  517. single cases and in the meantime the
  518. quality of the models are
  519. more or less perfect compared to 2010 to
  520. 2015 or let's say 2008 to 2015 2007
  521. after 2019 I have not seen any major
  522. quality problems in the big plants that
  523. I've visited or have operated but at
  524. this time there were already plants
  525. operating since 2010. We're at the end
  526. of the lifetime on some parts was
  527. visible.
  528. >> Yeah.
  529. >> We last week we were talking with
  530. Alexander Fisher, your friend.
  531. >> He has done a lot of stuff at his
  532. home making it I would say energy
  533. transition family.
  534. what kind of TV does he install?
  535. It was PV in the roof, the
  536. [clears throat] heat pump, electrical
  537. vehicle and house insulation.
  538. >> I remember
  539. >> and we believe you also have done
  540. something similar in your house like you
  541. would.
  542. >> Yeah.
  543. >> Would you like to share something?
  544. >> There is there is not very much to
  545. share. I have in a nice location. I'm
  546. sorry that you that I have now work
  547. here. So otherwise next time next time
  548. you will come
  549. I live I have the privilege to
  550. live out in the countryside and in a
  551. bit bigger area than usual last year.
  552. and for sure I have I have a few kil
  553. [clears throat]
  554. on TV on my on FL rooftop integrated
  555. and I drive an electric car. Yes.
  556. because I like it. Yeah.
  557. >> Do you have what kind of car do you
  558. have?
  559. >> Don't worry about it. It's a bit ugly,
  560. but don't worry about it.
  561. it's it's a it's a nice electric car
  562. and I tried also hybrid electric car
  563. before electric cars were there and
  564. I like the combination I like the
  565. smooth driving u and for sure the
  566. way have to go into into electric
  567. driving
  568. but it have to be combined with
  569. with that what is available on the
  570. market so that I can tell you the
  571. difference between an European electric
  572. car and that was the initial real
  573. electric car to name Tesla here which
  574. is a nice electric car had a lot of
  575. power but you cannot keep it on the
  576. European roads because the
  577. it is it is made for California
  578. highway and not for our curvy
  579. roads here. So that's that's but
  580. the way of aging it is no noise
  581. it is no it is no pollution or
  582. limited pollution or making the rubber.
  583. Now, how do you feel about like
  584. diesel being still the primary carrier
  585. for a lot of for a lot of vehicle in
  586. Austria still?
  587. I'm I am originally an automotive
  588. engineer and I know the technical
  589. issues inside. it is a philosophical
  590. discussion but from from from a vital
  591. perspective from also from having
  592. clean environment [clears throat] it
  593. makes absolutely sense to switch
  594. but the main the main advantages are
  595. not that I would say it's it's more
  596. on it's the next generation of
  597. comfort it is a and the next
  598. generation of comfort means also less
  599. noise which is important especially
  600. in cities and in
  601. villages not to disturb anyone. by
  602. the cars I think the pollution values of
  603. the of the
  604. small cars are reduced significantly
  605. >> in the [clears throat] last 20 years.
  606. it is it is different on
  607. countries where you coming from where
  608. nobody is checking out what is coming
  609. out of the of the exhaust. Hey, I have
  610. to tell you I have to tell you G that in
  611. Delhi you cannot drive a diesel car
  612. after 10 years and they're making it
  613. tougher to buy car you have to pay more
  614. taxes. So for it would for me it was
  615. very interesting
  616. >> but the interesting are the taxes in
  617. daily for instance they are gas driven
  618. yeah and that there's a lot of the
  619. pollution reduction of daily but this
  620. is a different it's a different world.
  621. Yeah. No but the cars that that we
  622. that we have here
  623. for sure there is there is there is
  624. pollution. We do not have this dance
  625. 11 rows in one direction and
  626. no we do we do not have this and I
  627. think the transition should be even
  628. more to public transport. Yeah,
  629. >> we have we have here and Austria is
  630. here a really nice example. I'm really
  631. 200 km out of out of me and I'm coming
  632. with the train.
  633. >> Yeah,
  634. >> because it's more comfortable.
  635. >> and it is even faster because the
  636. train is allowed to drive for 20 230.
  637. I'm here in less than 2 hours and
  638. from my office to here to the
  639. university.
  640. >> we love train. We went to Amsterdam by
  641. train last week.
  642. >> Yeah, my train.
  643. >> Yeah.
  644. >> Okay, then. Yeah, I've been also
  645. traveling with Indian railways. So,
  646. >> how did you like it?
  647. >> Okay, let's talk another
  648. [clears throat]
  649. It was an experience. That's Let
  650. That's Let's And I was, as you can
  651. expect, I was in the highest class. It
  652. was an experience.
  653. >> I will not miss it, but I will not do
  654. it. What did the delay the train?
  655. >> The one was one trip was the amazing
  656. distance of close 400 kilometers in
  657. Rajasthan.
  658. >>.
  659. >> From daily out to Rajasthan
  660. there the trip was 10 hours for 400
  661. kilometers. So really nice. that's
  662. what you to do in Austria in two. Okay.
  663. This that's less than the NSR do in 2
  664. hours now.
  665. >> Yeah. [snorts]
  666. So that that was that was amazing. And
  667. the other one was the high speed
  668. coming from from from Bopal up to up
  669. to day from I think in Kia I was there.
  670. [snorts] Yeah. the last the last 200
  671. kilometers and the train was amazing 120
  672. kilometers and everyone
  673. at the high speed but a lot of
  674. people I imagine when I was coming back
  675. from
  676. from the desert I you need you
  677. do not need a bodyguard in India
  678. because the people are all friendly but
  679. I needed a bodyguard to come to my car
  680. to make the wave free to
  681. [clears throat] the car because there
  682. was so many people when the train was
  683. arriving there.
  684. >> Okay. Getting getting our focus back to
  685. Austria after your experience in India.
  686. >> Is that how how do you see the Austrian
  687. landscape like you have been here
  688. for many years and you're from upper
  689. Austria but like the Austrian
  690. landscape for last 30 years. How you
  691. seeing the energy system changing here?
  692. I think the energy system in Austria is
  693. a very lucky one. we have we have
  694. a quite wide range of renewables
  695. starting last 100 years even where we
  696. used the relatively big rivers
  697. to produce our main energy or my main
  698. electricity to be honest.
  699. we have on the other hand the
  700. big where a lot of water is running is
  701. coming down and supporting
  702. I think about more than 60% don't ask me
  703. about the precise number but more than
  704. 60% is just water coming down from
  705. the mountains. there's a quite
  706. lucky situation that we are and to fill
  707. up the rest with renewables
  708. [clears throat] on at least on the
  709. electricity sector
  710. independent
  711. is technically possible.
  712. Yeah,
  713. >> that's that's the situation and I'm
  714. working one of my best guide is the
  715. Austrian vill
  716. and they will reach this 100% on
  717. renewable electricity for their trains
  718. quite soon. I'm supporting them
  719. currently for combining big PV plants
  720. with supporting the electricity of
  721. the train and they start now also to
  722. combine wind farms and connect
  723. them directly to the line of the
  724. train
  725. >> with this inverter that you say that is
  726. not 50
  727. >> 16.7 yes we have and it is one phase so
  728. it's a single phase
  729. >> and based on this The inverter is
  730. quite bigger than the normal one.
  731. >> Yeah.
  732. >> Because you have to you have the bigger
  733. coils and you have the bigger
  734. capacitors. because of the high
  735. current you have only one phase.
  736. >> Just an idea.
  737. The 2 megawatt inverter have more the 2
  738. megawatt inverter station have a weight
  739. of 11 tons which is not necessary and
  740. you are below one tone. if you take
  741. the 50 Hz compare if you take the
  742. PKS SMA 1 megab station it is without a
  743. transformer
  744. without transformer the part is below
  745. one tone
  746. >> or around and here we have 11 tons and
  747. no transformers
  748. >> so that's that's that's the situation
  749. but supporting the train directly is
  750. impressive and on the Austrian landscape
  751. Okay. there is there are some
  752. other power plants. U
  753. >> yeah are there any like new development
  754. project that is going on that worth
  755. mentioning?
  756. >> I do not even even the gas power
  757. plants are in the way to used very
  758. limited.
  759. >>. M so we can we can based on this
  760. lucky situation where we are
  761. >> and the same is in Switzerland
  762. >> based in this lucky situation we are
  763. able to do this
  764. neighbor countries do not have this
  765. lucky situation if you take Germany for
  766. instance they have to they have to do a
  767. lot on distribute their big
  768. available wings the northern part of the
  769. country the mountains in the south
  770. are the rest of the mountains, not the
  771. main part like Austria and Switzerland.
  772. >> Yeah.
  773. >> Yeah. So they have they have nearly no
  774. riverside power but they have they have
  775. no pump storage in the higher mountains
  776. like we have.
  777. >> So what next for Austria in terms of
  778. deparbonization industries right
  779. we still need to address in
  780. Austria the industry. Yeah, but the
  781. industry is located
  782. on few locations and especially
  783. the main the steel industry in
  784. in leads they have developed extremely
  785. I remember when I was grown up in the
  786. 70s last century u and you and you went
  787. to lead
  788. I've never seen it before I was an alien
  789. >>
  790. >> competitive
  791. >> that but it was in the 70s and
  792. you we had a lot of death on
  793. on the effects of the pollution and
  794. then they reduced the sulfur
  795. in the pollution by the
  796. regulations and the industry so the air
  797. is clean in Austria in the meantime.
  798. I know a friend of mine who is
  799. responsible for the historical building
  800. here in Indiana in Vienna.
  801. >>.
  802. >> And this nice green
  803. rooftops built from copper, but you need
  804. them that they get green. You have this
  805. copper and this this orange
  806. >> orange black color at the initial
  807. state and then you need the sulfur
  808. from the air that it getting green and
  809. they have problems that the historical
  810. buildings when they change the rooftops
  811. get not does not get this nice green
  812. because there is no sulfur anymore in
  813. the air. So they remain with the copper
  814. natural
  815. >> they yeah maximum it goes to black from
  816. any other pollution rest but it get it
  817. doesn't get green anymore.
  818. >> Wow.
  819. >> They are they are taking they are taking
  820. the green copper from from parts
  821. that are not visible and put it out
  822. on the visible and reuse it on
  823. the visible part because [clears throat]
  824. the air is so clean in the meantime.
  825. That's the advantage of using the
  826. renewals and not
  827. >> blowing anything out. But the industrial
  828. the industrial
  829. pollution is simpler to be to get
  830. under control. You can you get no permit
  831. to start anything before you do not
  832. fulfill the strong regulations that we
  833. have here. So here we are based on this
  834. we are we are very lucky lucky and
  835. coming back to India where you have
  836. the problem that most of the pollution
  837. is coming from small local fires
  838. where where a lot of people
  839. [clears throat] are burning anything
  840. that is not allowed to be burned but you
  841. will never put into a controlled
  842. power plant like we have here in Vienna
  843. for instance the
  844. >> yeah they you
  845. >> but there this is a controlled situation
  846. the pollution is really limited to that
  847. what the content of the material that
  848. you burn [clears throat] usually
  849. provides.
  850. >> But the way should go into having all
  851. all that you need on energy in a
  852. controlled way so that you have no no
  853. pollution coming out from that the
  854. households are cleaning here. Austria is
  855. in a lucky situation also.
  856. >> the way to heat pump is just the
  857. next logical one. But we do send
  858. since
  859. I've done it on also renewable is
  860. is wood firing if you do it controlled
  861. and controlled wood firing for
  862. households is also a possibility. I do
  863. not I did even not follow this idea.
  864. I was originally by myself.
  865. I'm having now my second heat pump. I
  866. already did 1993
  867. he pump to support my house.
  868. >> Wow.
  869. >> Because I have and it worked 30 years
  870. without any problems and the problem was
  871. a buffer at the end of the lifetime but
  872. not the heat pump itself.
  873. >> I changed it last year. Yeah.
  874. >> And they have and the quality is now
  875. labelizing the electric five and my
  876. type of heat. Were you able to get the
  877. individual heat pump back then? Like
  878. >> Yeah. Yeah. That was legal on the
  879. market.
  880. >> Okay. [clears throat]
  881. >> That was no problem.
  882. >> Yeah,
  883. >> that was no problem.
  884. >> And because I think it now it's
  885. getting back in that people want
  886. individual heat pumps and that heat pump
  887. suppliers have become and was it a
  888. boiler?
  889. >> Yeah, that the boiler is afterwards. So
  890. you heat up with the heat pump
  891. >> the water put it in the boiler and the
  892. boiler the boiler is your buffer
  893. >> and on the on the energy heat transition
  894. coming back to that the buffer is
  895. now the battery
  896. >> should be the battery because you
  897. produce the cleanest energy that you
  898. can produce electricity for sure you
  899. take a support that is not writing your
  900. bill so no one is sending you a bill
  901. from oil or gas
  902. or even for wood firing. Yeah. So,
  903. you are independent from that. So,
  904. you can you have stable situation of
  905. your energy input which is wind, which
  906. is [clears throat] water, which is
  907. direct sun usage. And you buffer it.
  908. >>.
  909. >> And you deliver it when the client
  910. requires it. The startup was for sure
  911. setting up the market, growing up the
  912. market by setting up subsidies which
  913. Germany was really famous
  914. >> and the market all you can eat
  915. have to digest everything and that's the
  916. situation where we are now in this
  917. energy transition where we have now
  918. balance the energy and provide it to the
  919. client when he requires it.
  920. >> Yeah. So
  921. you are an energy expert you were
  922. all professor but you are a consultant
  923. energy expert in the field. So I want to
  924. ask you this solution that you mentioned
  925. before we started the when you can
  926. combine different technologies
  927. in order to address to optimize the
  928. infrastructure usage
  929. >> and then to storage and to supply the
  930. energy when it's needed to tackle
  931. this challenge which is the D car which
  932. It's everywhere. So
  933. >> yeah. Okay.
  934. >> What is this?
  935. >> Let's let's talk about it. we have we
  936. have I think we have it all over all
  937. over Europe and some countries are more
  938. developed, some countries are more
  939. lucky. The main pattern is the
  940. same. We have a transition to renewable
  941. energies where we have energy available
  942. when the wind is blowing and we have
  943. energy available on the renewables when
  944. the sun is shining which is a problem
  945. in the night
  946. [snorts]
  947. >> on the one yeah wind is also going in
  948. the night. So u based on this is quite
  949. quite fine. the next one is the
  950. energy is leading to an to a
  951. different time. and the other problem
  952. is that you have to bring the energy to
  953. the client. So bringing the energy to
  954. require a grid [clears throat]
  955. and the grid is to be dimensioned on
  956. when the most energy is available. it
  957. has to support the whole power and
  958. here is
  959. a big gap in between thinking about
  960. power and energy. power is that what
  961. you get on let's say in a strong strike
  962. >> instantly
  963. >> in but you but if you take less power
  964. but over a longer time you transport the
  965. same energy.
  966. >>.
  967. >> So the trick is to have the energy
  968. more or less distributed or provided
  969. when the client and the client can
  970. also be on the power but the grid.
  971. >> Okay.
  972. >> Yeah. when the when the client
  973. require this
  974. >> all you have have to do and on the
  975. solar server it is quite easy is to
  976. take the energy when you have it. Okay,
  977. the sun is shining it's heating up your
  978. water and you take the energy to your
  979. personal consumption when you need it.
  980. So when do you need your hot water? When
  981. you want to shower there are two types
  982. of showering one in the morning the
  983. other in the afternoon. So, or when when
  984. you're when you're cooking or
  985. cleaning your your dishes, then you
  986. need your your hot water or you take
  987. your water for heating up the room or
  988. reducing the temperature a bit, mixing
  989. it up into the frozen.
  990. >>.
  991. >> U that's so on that renewable system,
  992. you can do everything local. You take
  993. the water as a buffer, you have 2, 000 m
  994. storage on a private house. You have a
  995. few square meter on your on your rooftop
  996. on a certain server collector. you
  997. have some copper lime sometimes and this
  998. the system is working independently
  999. without any any pollution. it's
  1000. consuming a few
  1001. >> [snorts]
  1002. >> a small part of electricity for a for
  1003. the pumps that's you cannot do this on
  1004. on you can do this but it is quite
  1005. interesting to have it on areas
  1006. Denmark did a lot of that they have
  1007. they have distributed heating system on
  1008. on taking care about renewables this is
  1009. a good example but the world is a
  1010. bit different the whole world and the
  1011. energy that we can use in most cases and
  1012. the biggest energy is for sure
  1013. electricity. So the key is here
  1014. taking the patterns that have been
  1015. successful for many years for
  1016. even decor
  1017. situation that the battery prices are
  1018. going down. They are going they are at
  1019. at an exact level. that also from the
  1020. economical perspective it gets
  1021. attractive and we have a lot of
  1022. connections to the grid [clears throat]
  1023. from PV plants from wind farms
  1024. where this is only partially needed. So
  1025. one of the things is why not
  1026. combining two different things that have
  1027. different production profiles and
  1028. using it on the same connection point.
  1029. I've appreciated in my in my lesson just
  1030. an example here of Austria. we
  1031. have the south of Fienna a lot of
  1032. successful
  1033. wind [clears throat] where this wind has
  1034. a profile that it is running here. It is
  1035. blowing more in winter. it is blowing
  1036. more in the early morning and late
  1037. afternoon. And
  1038. if you take the solar impact, the
  1039. solar impact is more at high noon when
  1040. the wind is more or less quiet. It is
  1041. more in the summer season than in the
  1042. winter season. when the wind is
  1043. silent. So why not connect these two
  1044. together? Because on the one hand they
  1045. were the produc of the winter. I need my
  1046. 1 megab or whatever the on
  1047. connection. on the other hand
  1048. >> on the other hand or 8 megawatt or
  1049. whatever. Yeah. And on the other hand
  1050. the PV plant I need my grid connect for
  1051. 1 megawatt because 2 hours a day I
  1052. have concern and I can produce really 1
  1053. MHz. Yeah. And nobody thinking about the
  1054. borders when the wind is not blocked
  1055. full power part but only partial then
  1056. the wind connection is maybe blocked for
  1057. 70% 40% even 60%. U and why not fill
  1058. up at this time when the sun is usually
  1059. shining [clears throat] adding
  1060. additional power on the same connection
  1061. point
  1062. >> the same connection point
  1063. >> on the same connection point and oh man
  1064. I'm I'm losing a lot of this of my
  1065. energy and it is so expensive the
  1066. real number is here in this area we
  1067. did it on simulating three or four
  1068. years exactly on 5 minute resolution and
  1069. the result is you are between 8 and 11%
  1070. of the PV production which is which is
  1071. half of the wind production because wind
  1072. is running during the night also.
  1073. >> and it is delivering 2, 000
  1074. kilowatt hours per kilowatt power
  1075. connected. Yeah. Roughly. And the V8
  1076. [clears throat] is, 1, 200 but on filling
  1077. up but you have 8, 000 hours in here.
  1078. Hey, sorry. So even connecting the same
  1079. dimension of PB on a on a feeding point
  1080. of
  1081. defined [snorts] of a defined level in
  1082. this case it was 14 megawatt but I
  1083. did it also with 100 megawatt scenario
  1084. it's it's the same proportion it's the
  1085. same and the amazing part is if you
  1086. have if you add a battery to
  1087. bridge
  1088. 4 or 8 hours you go down to a loss that
  1089. is below 1% of the whole energy
  1090. production. So adding a battery of 8
  1091. hours to a setup using the full power
  1092. of the wind farm and using the same size
  1093. or even double the size on PV adding it
  1094. on the same feeding point. You do not
  1095. have to add anything on the grid but you
  1096. have a five times higher
  1097. >> energy
  1098. not five times but three times three
  1099. times higher energy transition on the
  1100. same point not not one screw additional
  1101. necessary on wind
  1102. >> yeah wind solar battery
  1103. makes up to 60 67 70% usual usage of
  1104. the of the feeding point where wind is
  1105. up to 20 25%.
  1106. And solar is even is even 30 50%.
  1107. So, 000, 000
  1108. full load hours.
  1109. >>.
  1110. >> Of 8, 800
  1111. 800 hours a year. you blow
  1112. over the line from from so this is
  1113. this is a
  1114. an attractive approach. and the
  1115. next one is put such an environment
  1116. close to a connection point. We have for
  1117. instance a gas power plant. We have gas
  1118. power plants with 30 with a few hundred
  1119. megawatt where wind area is around
  1120. and the and the lines to this connection
  1121. point are not you don't have to change
  1122. too much on the grid. So this is a this
  1123. is a possibility
  1124. to edit and coming back to your
  1125. initial questions would it would it
  1126. be interesting for Eastern Europe and
  1127. here it's clear for sure this is the
  1128. solution to provide
  1129. developing countries which are not at
  1130. that high energy level like we are we
  1131. have to fill up and keep it alive
  1132. >> here here in Austria more or less and
  1133. the energy growth rate is not
  1134. that
  1135. >> high
  1136. >> not that high like you have in emerging
  1137. countries where economy
  1138. >> can take any example of a country like
  1139. where it could be applicable.
  1140. >> take take Romania, Bulgaria for
  1141. instance, they have their their [snorts]
  1142. I think they are the classical ones for
  1143. for Eastern Europe. They are countries
  1144. with a lot of sun. taking Romania
  1145. from the Black Sea there is an
  1146. attractive wind profile. They have they
  1147. have really attractive wind but they
  1148. have good read.
  1149. >> Yeah.
  1150. >> Yeah. So having here some kind of
  1151. strategic
  1152. situation and here coming back to
  1153. India where I put the 400 K line KV
  1154. line from big cities to the desert
  1155. putting their gigaw
  1156. of PV and supporting there the growth
  1157. the energy ha that the big cities
  1158. have and support the big cities to
  1159. support at least
  1160. during the day and you have also
  1161. collected the energy growth is
  1162. then also to support your air
  1163. conditioning systems which is a nice
  1164. profile running parallel to the sun.
  1165. >> Yeah.
  1166. >> Yeah. but there is a limited there
  1167. is limited additional infrastructure
  1168. required
  1169. to pass this challenge and that
  1170. that is interesting for sure for
  1171. Romania Bulgaria where they have some
  1172. areas with big cities if you take
  1173. Romania
  1174. >> they won't have to invent it on the
  1175. on trade modernization or create
  1176. infrastructure because it can you can
  1177. already feed it into the existing the
  1178. existing is I'm I'm not aware about the
  1179. details there. I think Alex and is
  1180. here much better. But from from the
  1181. basics.
  1182. >> Yeah.
  1183. >> From from the basics maybe there are
  1184. there is there is you can discuss about
  1185. requirements but from the basics
  1186. putting [snorts]
  1187. strong lines to the to the areas of
  1188. industry. Putting strong lines to the
  1189. cities and go out on the countryside
  1190. and you have and they have enough
  1191. countryside. and put heavy PV and
  1192. and wind farms and put anywhere local to
  1193. the to the feeding point that you do not
  1194. over overrun
  1195. the long lines. put put
  1196. batteries on the on the entrance of
  1197. the of the line. make a big
  1198. transportation to the areas where the
  1199. energy is required and put also
  1200. additional batteries close to the client
  1201. to fulfill their their their profiles.
  1202. and then you get rid of the problems
  1203. where especially Germany is crying
  1204. about this because they have PV on a lot
  1205. of private households
  1206. >> and during during the noon hours
  1207. PV is producing more than Germany is
  1208. requiring
  1209. >> so they have negative prices. Yeah. So
  1210. they the market price on is
  1211. then negative. and you have You
  1212. didn't have to pay to deliver your
  1213. energy, which is a problem on the
  1214. power bus. Yeah.
  1215. >> But it's good for storage.
  1216. >> It's good for storage. It's it's
  1217. extremely for storage because
  1218. on storage you can exactly compensate
  1219. this this problem because you take the
  1220. energy.
  1221. >>.
  1222. >> when the sun is shining, put it into
  1223. the storage and keep it there until the
  1224. market is requiring it.
  1225. >> Yes.
  1226. >> And based on this, you can you can
  1227. compensate. I'm not a friend of this
  1228. battery only fence where we're just
  1229. dealing with it's called the duck
  1230. curve where it looks like a duck up and
  1231. down. Yeah. where the price is down
  1232. when the sun is shining and the price is
  1233. up in the morning and afternoon hours
  1234. when everyone is at home
  1235. and a lot of electricity is required in
  1236. the private household. And there are
  1237. some bumps in some areas when the
  1238. industry is retiring but the industry
  1239. is a different chapter and can be
  1240. handled locally or this special
  1241. elate solutions but or if you take it
  1242. all over the country you have to take
  1243. care about this and this is quite
  1244. interesting to take here the battery
  1245. and I don't like the guys who who just
  1246. say, "Okay, we have the dark curve. We
  1247. have this low prices
  1248. in the
  1249. >> [clears throat]
  1250. >> in the early morning when the
  1251. riverside power plants, gas power
  1252. plants, cold fire power plants are
  1253. running because you can stop them and
  1254. run them and also the nuclear power
  1255. plants you cannot run and stop them
  1256. like you want." So the price they
  1257. are fitting in and the price is going
  1258. down. Then there's D coming down during
  1259. a sunny day especially on weekends
  1260. when the industry is not consuming the
  1261. price is going to negative then they are
  1262. buying the negative price the at cheap
  1263. times and selling it. it helps for
  1264. sure it helps for sure. it is it is
  1265. money making
  1266. but I think it is a too narrow engine
  1267. the because after sometimes when a lot
  1268. of people are recognizing this
  1269. everyone wants to play this game and
  1270. then you have got this benefit because
  1271. the gap is still not not enough. You
  1272. have you do not have to forget you need
  1273. also some fees for getting
  1274. transportation over over the grid and
  1275. between selling and buying you have
  1276. still a grid fee and if the gap between
  1277. maximum and minimum price is less than
  1278. the grid fee then you can smash your
  1279. battery because you don't make money
  1280. with it. So this is this is a temporary
  1281. aspect where you get nowadays when the
  1282. dark curve is extremely the dark curve
  1283. is b at the moment as TV and wind are
  1284. still growing is the dark curve
  1285. expanding at the moment.
  1286. >> Yeah. No, it's a canyon canyon curve.
  1287. It's not dark.
  1288. >> It's not like a canyon.
  1289. >> It's a canyon curve. Okay, that's nice.
  1290. [clears throat] I will I will remember
  1291. this in my next lecture
  1292. to Kenya curve.
  1293. at the moment at the moment but it is
  1294. visible it is v visible that within the
  1295. next 5 10 years whatever this
  1296. curve gets flattened and banned
  1297. >> u if you have a poor battery use
  1298. >> you can smash it because you
  1299. cannot by only using this gap of the
  1300. price it is not enough but by using it
  1301. or having a having it as a storage to be
  1302. prepared when you when you use it
  1303. it makes absolutely sense.
  1304. [clears throat] There are also ideas on
  1305. putting on putting the
  1306. batteries [snorts] of electricity of
  1307. of electric cars as a public buffer.
  1308. But this is from the regulatory from the
  1309. regulatory side it is really really
  1310. tricky because you want to drive a car
  1311. when you want to drive but when
  1312. electricity is not required [snorts] and
  1313. yeah
  1314. >> just talking about you
  1315. mentioned Romania and Bulgaria. So just
  1316. getting back to the whole CE region and
  1317. what do you think like the other
  1318. challenges that you see in their
  1319. energy transition?
  1320. >> I think I think the
  1321. there is a development but it is
  1322. still a challenge is the regulatory side
  1323. that I remember the first days when I
  1324. was working for Romanian projects.
  1325. it was extremely problem on the
  1326. corruption to get the permits.
  1327. >>.
  1328. >> There to get to get permits it was
  1329. that is getting significantly better in
  1330. the last years. So they are successful
  1331. working against corruption but I
  1332. remember 2008 2010
  1333. setting up for the stupid 20 megawatt
  1334. which is nothing
  1335. that a 20 megawatt plant in the
  1336. area of tisha
  1337. we have to come with we should have come
  1338. with cash money to get it permit.
  1339. Yeah. and we escalated it and this
  1340. guy was for sure fired but we did not
  1341. get the permit anyhow because on the
  1342. next level they didn't want that
  1343. anyone was getting fired.
  1344. >> that was that was a problem. it
  1345. is it is getting better. the regulatory
  1346. side is for sure
  1347. a problem then the development of the of
  1348. the grid is not fast enough.
  1349. >> Yeah.
  1350. >> but especially on compensating
  1351. the extension of the grid which is quite
  1352. necessary but it is not necessary only.
  1353. So this can be compensated by having
  1354. and then here the regulatory is the
  1355. problem that it takes
  1356. it doesn't recognize fast enough that
  1357. the feeding point is the point of
  1358. interest and not the production. So if
  1359. you have if you have a main farm and you
  1360. put up a PV and you say I use the same
  1361. filling point then they make it still
  1362. from the regulatory side not from they
  1363. make it still at two different point and
  1364. get the permit also it's technically
  1365. possible so here but I think this
  1366. should be possible to talk with the
  1367. regulatory side to understand that the
  1368. energy behind the meter should be
  1369. provided by whatever you have And even
  1370. if you extend it to hydrogen, if it
  1371. is a big if it's a big plant, you can
  1372. also extend it and produce hydrogen
  1373. there and use the hydrogen where you
  1374. need where you need for instance
  1375. higher temperature or where you need
  1376. where you need gas for industry purpose
  1377. on production. Yeah, there you can
  1378. there you can extend this model and I'm
  1379. talking here about industrial dimension
  1380. not about private household because
  1381. private household is nice but and it
  1382. is also that you can talk if you with
  1383. your neighbor about how many things
  1384. you have here
  1385. advantage and everything localized
  1386. but on industrial dimension you
  1387. should go
  1388. taking peak units combine it behind
  1389. the meter and distribute it like the
  1390. client and the client can be integrated
  1391. requires it. Yeah.
  1392. >> beforehanded this interview we were
  1393. talking to you and we were discussing
  1394. leafrogging for developing markets. what
  1395. what kind of leafrogging that you see in
  1396. the Eastern Europe because they don't
  1397. need to do everything that maybe
  1398. Scandinavia has done or Netherlands has
  1399. done. What where do you see them doing
  1400. leaprogging in and a new transition?
  1401. I think there is no need on
  1402. these countries to set up a lot of
  1403. gas power plants for grid
  1404. [clears throat] balancing.
  1405. >>.
  1406. that that step which was done with
  1407. Austria
  1408. was done can be compensated
  1409. by renewable power plants if they
  1410. are really set up on having really
  1411. enough battery having
  1412. [clears throat] reliable wind direction.
  1413. I'm talking here about units above
  1414. 100 megab.
  1415. >>. [clears throat]
  1416. >> Yeah. But one
  1417. 500 megawatt connections setting up such
  1418. things can be done using
  1419. renewables 100%.
  1420. and having it also from from the
  1421. public perspective also economical
  1422. with [snorts] no
  1423. no fuel costs.
  1424. You have you have no no primary no cost
  1425. of primary energy..
  1426. >> You have only the infrastructure and
  1427. the capex and the operational part
  1428. where the operational part is
  1429. let's say it is for sure challenging in
  1430. in these countries to have
  1431. enough electricity that you can educate
  1432. them on the local requirements. You can
  1433. people people are willing to learn on
  1434. on the local requirements. so if you
  1435. have if you have ski people who are able
  1436. to transfer
  1437. the knowledge how to operate the PV
  1438. plant
  1439. >> it is not a problem way is different
  1440. it's a different one but wind which
  1441. which is higher speed but with less
  1442. services
  1443. then from from then on with less
  1444. services than on PE
  1445. And there is there are not so many
  1446. the possibilities and then then on PV pl
  1447. you fight with the big numbers of
  1448. equipment that you have where you should
  1449. take care about that the big number of
  1450. equipment is stimuli and life at the
  1451. high level. Yeah. So repairing an
  1452. inverter or replacing an inverter
  1453. should be possible by your local team or
  1454. by a team that is close to your company
  1455. and not to ask someone in Sweden or
  1456. another in Germany to jump and to
  1457. repair it which is on a link to a
  1458. different u different high quality
  1459. label. They have single spots where it
  1460. is required to have high quality
  1461. services.
  1462. on Pine you have amount a huge
  1463. amount of models you have huge amount of
  1464. cables and a lot of possibilities that
  1465. someone locally breaks down but doesn't
  1466. disturb the power
  1467. >> also just
  1468. >> just discussing a bit about the
  1469. technical knowhow in these countries how
  1470. how how do you think how prepared are
  1471. they for the challenges that are
  1472. coming their way
  1473. >> I think I'm on
  1474. on the big challenges meaning
  1475. setting up the grid there is
  1476. enough experience in all Europe and
  1477. there are some specialized companies who
  1478. are doing it.
  1479. >>.
  1480. >> and they and they can expand and
  1481. transfer their knowledge and then sing
  1482. projects and when the projects are done
  1483. there will be there will be no
  1484. bigger problems. winter as I already
  1485. said it's it's usual that the
  1486. manufacturer is setting up a service
  1487. team and by growing of the manufacturer
  1488. the service team is growing in parallel
  1489. so this the individual service
  1490. turbines is managed by the
  1491. structure of the market itself
  1492. >> u on PV on PV there is there is
  1493. some challenge because you need some
  1494. people there but this can also be
  1495. handled on having local electrician
  1496. u and educating and training people on
  1497. the local services that are necessary.
  1498. Not everyone in the PV plant have to be
  1499. fully educated PhD on electro
  1500. technical. so you can you can train
  1501. you can tell them which people
  1502. which parts of the are let's say
  1503. dangerous and the dangerous zones means
  1504. the switch gears and the
  1505. big inverters on if you have big
  1506. inverters can be handled by experts
  1507. and the rest can be done by people that
  1508. you can really get from the local area.
  1509. They're creating sound jobs. Not not
  1510. very much to be honest. Yeah. we are
  1511. talking here about 10 15 people on
  1512. the 50 megawatt plant. Yeah.
  1513. >> That that makes sense that you that
  1514. you support them. You have to take care
  1515. about about grass cutting. If you
  1516. have problems you have to take care
  1517. about cleaning the models and some
  1518. countries more, some countries less.
  1519. >> Yeah.
  1520. you have to take care that all the
  1521. wear out can be handled by
  1522. cycling. You have to do some some
  1523. checks. These are the jobs that are
  1524. necessary but you can't the service
  1525. aspect is quite low and not so
  1526. much challenging. So I would say that
  1527. the transition
  1528. is manageable is manageable on
  1529. the on the grid operator side. I think
  1530. the growth rate on distributing
  1531. the people are they have enough
  1532. people sent out to international
  1533. universities so that the education
  1534. for these experts that you need for
  1535. training staff and so on.
  1536. is giving companies that are doing
  1537. energy trainings will grow with their
  1538. local teams. There is a lot of eco
  1539. company jobs that are necessary on
  1540. on the legal side for instance. The
  1541. legal side is quite tricky there. It
  1542. needs much more than and all the
  1543. managing side for
  1544. >> was there any more challenges apart from
  1545. corruption in some part that you failed
  1546. obtaining permits?
  1547. >> Yeah. Okay. Getting getting the permits
  1548. is it is it crucial? Well
  1549. then the normal technical
  1550. issues that you have that you have
  1551. no clear profile about what is under
  1552. the ground
  1553. >> so that the ground is not working and
  1554. you have to add concrete on locations
  1555. where you didn't expect that that the
  1556. ramic was not working that it did not
  1557. have smooth information about what is
  1558. what is below the ground that were for
  1559. sure challenges on erecting
  1560. getting
  1561. yeah some on some areas problems with
  1562. others from the local people.
  1563. >>.
  1564. >> But that is also in the meantime managed
  1565. by if you make communication to the to
  1566. the people around
  1567. it is working. There is a nice
  1568. example but it is from India where we
  1569. where we had broken models and save
  1570. and distortions from from
  1571. people of the village around and the
  1572. original owner was blowing up the
  1573. security stuff which is creating jobs
  1574. and the real solution was just giving
  1575. the people from the village around jobs
  1576. on taking care of cleaning the models
  1577. which was a problem in this location and
  1578. as soon as the people of the village
  1579. around had jobs in the plants to clean
  1580. the models at the lower price than
  1581. the security
  1582. >> just taking care about
  1583. >> for the community
  1584. >> but the Yeah. But the single
  1585. job is cheaper than than a security
  1586. guy. Yeah.. [snorts]
  1587. >>
  1588. then the security was no longer
  1589. necessary because the people said okay
  1590. my auntie and my and my cousin are
  1591. working there and they took care from
  1592. the village that no one is getting into
  1593. the power plant and destroying anything
  1594. and based on this this is
  1595. communicate with the with the area where
  1596. we are then this problems of the
  1597. local people you can handle. But if
  1598. you if you just I'm the big money
  1599. spender and I put two millions models in
  1600. the desert and not taking care about
  1601. who is around if you integrate
  1602. [clears throat] them you can you can
  1603. handle them but that was the 12
  1604. challenges. also I remember in
  1605. Romania this is no longer an issue. They
  1606. the people are used
  1607. >> they're used to it.
  1608. >> They are used to that. They are they
  1609. they know it. Safet is for sure a
  1610. problem when when you
  1611. have anything that looks like it is
  1612. expensive
  1613. and can be can be used on
  1614. so as long as you as you do not have
  1615. fans around. but in the meantime the
  1616. motors prices are so low that even
  1617. stealing models doesn't and during
  1618. and the safe of cables is only
  1619. interesting when the cables are really
  1620. available
  1621. during the construction days. If
  1622. you have anything expensive copper cable
  1623. under the ground already safeties is
  1624. a
  1625. big effort. Yeah. You also have
  1626. considerable experience in Hungary,
  1627. right? Or
  1628. >> in Hav I is one of the countries I'm
  1629. missing. Czech Republic, Slovakia.
  1630. >> but do you think like the
  1631. countries you can put them in one
  1632. bucket?
  1633. >> No. No. Every country, every country
  1634. here is different. Jake is
  1635. for instance from all the all all the
  1636. Eastern European countries. the most
  1637. developed
  1638. there you have you have for sure
  1639. you have to fight with the
  1640. bureaucratism..
  1641. >> but on the other end there is also
  1642. a growing lobby who is who is
  1643. taking care that renewable energies
  1644. have have an position on the
  1645. political decisions and they are
  1646. considered but based on the
  1647. development of these countries for
  1648. instance in the Czech Republic you have
  1649. a lot of small power plants instituted
  1650. all over the country with a lot of mixed
  1651. up stuff. Yeah.
  1652. >> So [clears throat] having here a bigger
  1653. portfolio is challenging as you have
  1654. a lot of small plants distributed
  1655. all over the country where this this
  1656. effects that I told before putting
  1657. battery on it and deliver it
  1658. and use it like a big power plant
  1659. doesn't work that smooth.
  1660. >> Yeah. but they on the other hand very
  1661. very well developed. you have a lot of
  1662. of good educated people and have
  1663. not the problem to find people to
  1664. service you. but on the other hand
  1665. you have then to manage it very
  1666. effective because the prices of the
  1667. main power is based on the better
  1668. education higher Slovakia
  1669. is closed around is very
  1670. distributed closed around Bratislava
  1671. similar developed like like Czech
  1672. Republic if you go on the border port
  1673. Ukraine you are closer to the country
  1674. that you
  1675. working with the white countryside
  1676. with not very much population, not
  1677. very much infrastructure.
  1678. >> Hungary, sorry I cannot I have no
  1679. personal experiences also not all the
  1680. former Ukrainian countries and Romanian,
  1681. Bulgaria
  1682. are similar but different in
  1683. details. These are big countries. They
  1684. have the good sun. They have some
  1685. local centers among around the big
  1686. cities. and the rest is big
  1687. countryside which you can use for
  1688. producing the energy.
  1689. >> so taking care about this
  1690. structure it is manageable.
  1691. on the end you have also the
  1692. legislation at least centralized
  1693. compared to central Europe for sure a
  1694. bit chaotic but they [clears throat] are
  1695. on a way that is getting better and it's
  1696. getting clearer and they see their
  1697. chance and that makes it quite
  1698. interesting.
  1699. >> Yeah. sorry the time of flight
  1700. we know that we have your all businesses
  1701. today so maybe we can continue with
  1702. the final thoughts or how we in the
  1703. future. Wow. Yeah.
  1704. >> I'm surprised, but
  1705. >> yeah, we just we just want to ask you a
  1706. couple of final questions. You want to
  1707. go ahead? from my side I would like
  1708. to know as a tech technical expert how
  1709. do you see the future and the developing
  1710. of the renewal energy technologies in
  1711. the next years and
  1712. the role of the innovation in this
  1713. field. I think they the role of
  1714. innovation is here the in the
  1715. integration of already existing
  1716. u innovations in other fields and the
  1717. trick on the renewables is thinking out
  1718. of the local box of the experts I'm
  1719. fighting at PBC always PB guys who
  1720. think they are the most famous in the
  1721. world which is
  1722. >> clear they are experts in their field
  1723. and they are for sure on their field the
  1724. most famous but the most famous thing is
  1725. to produce u electricity for everything
  1726. for everyone and so you have to think
  1727. about the border.
  1728. thinking about the border combining
  1729. things that are existing like I told you
  1730. wind combining wind with battery and
  1731. with PV and battery and even on
  1732. the bigger ones adding the hydrogen
  1733. as a as as combined centers but the
  1734. same is also on technology
  1735. on the development. So u using
  1736. artificial intelligence by all the
  1737. criticism that I brought out from the
  1738. technical perspective but using it
  1739. where it makes sense on pattern
  1740. recognition to detect for the
  1741. analysis it makes absolutely sense on
  1742. analyzing the big data that you have
  1743. a PV plant have a few million a real PV
  1744. plantion models in a in a few hundred
  1745. thousand of strings finding out which
  1746. one is working should
  1747. have to be optimized in a in a big one
  1748. and here selecting and filtering
  1749. out what is a fault what is a what is a
  1750. cloud. Yeah.
  1751. >> so that you do send out on every
  1752. cloud technician to measure if a motor
  1753. is broken on a fuel and that but using
  1754. these technologies that are available
  1755. making it simpler to be handled.
  1756. also for forecast AI is
  1757. at least an indicator if you it's an
  1758. indicator it's not it's it's not the
  1759. final tool yet
  1760. >> but it is an indicator taking care about
  1761. more precise forecast is a wide
  1762. field on combining thinking out
  1763. of the box and using the things
  1764. that are already available on the market
  1765. and combining would be the key in
  1766. the next time and using it on
  1767. industrial dimension.
  1768. >> Okay.
  1769. >> And finally G what do you think about
  1770. the energy bridge and our initiative to
  1771. understand the central and eastern
  1772. European energy system better? I'm I'm
  1773. really amazed about that what you're
  1774. doing here u because that could
  1775. get this especially the knowledge
  1776. that is not there. The knowledge is
  1777. there on industrial institution like
  1778. we have here on the university u on
  1779. international institutions like we
  1780. have here on the University of Vienna
  1781. in our master. We have people all all
  1782. over the world that are contributing and
  1783. not only sharing their experience but
  1784. also sharing the experience from you
  1785. in Chile to you in India and talking
  1786. in Vienna
  1787. that's that's necessary and
  1788. I think especially on this transition
  1789. taking taking out putting expert
  1790. together on the stakeholder of the
  1791. executing part is interesting. Don't
  1792. forget the lawyers and discuss with them
  1793. from the technical perspective to
  1794. simplify the laws because this is one of
  1795. the challenges that we have inside our
  1796. technical problems.
  1797. >> We already have a lawyer in our
  1798. pipeline to discuss next.
  1799. >> Yeah. Because because they have they
  1800. have to take care that the that the
  1801. rules are simplified but user energy
  1802. Yeah. So yes, just to highlight that you
  1803. made the same master program that we are
  1804. finishing and you were classmate with
  1805. with Alexander Fisher.
  1806. >> So we are very happy to having you here.
  1807. It has been a pleasure and I don't
  1808. know I think that we were lack of time
  1809. so maybe we can repeat it in the future
  1810. >> to discuss other interesting topics
  1811. and
  1812. I think that that's all for today.
  1813. >> Yeah. And we will be meeting you in May
  1814. in our conference
  1815. >> for sure.
  1816. >> Thank you very much.
  1817. >> Thank you all and follow us. Don't
  1818. forget to subscribe the channel and
  1819. join us to keep learning about the
  1820. energy transition in central and eastern
  1821. Europe.