100% Carbon-Free Energy System: Can We Still Keep the Lights On?

Jul 26, 2021 14:49 · 8462 words · 40 minute read

hi everyone we are gonna wait for a few minutes for people to join and we will start the webinar at probably 1202. thanks so much for being here once again we’re just going to wait like another minute uh for everyone to join then we’ll get started so thanks for being here and hang tight all right i’m doing it we’re gonna start okay welcome everybody to this bonus new mexico smart grid center summer webinar um it’s 100 percent carbon free energy system can we still keep the lights on with dr jiang all the way from clarkson university in new york um i’m brittany van der werff the communication and outreach special specialist for new mexico established program to stimulate competitive research uh new mexico epscor.

epscor is a nationwide program funded by the national science foundation and i’ll be your host for today’s webinar along with my partner in crime isis serna our website administrator who will be working behind the scenes to make it all flow smoothly so a few housekeeping things before i begin i want to let you know that if you have questions at any point please type them in the q a box and isis will politely interrupt dr jean and read them out loud i also want to take a hot second to tell you about the epic webinar training lineup we have for you this fall in august we kick off with dustin allen systems and network analysts at the new mexico state office who who will be presenting python fundamentals with data analysis and visualization on the 25th from noon to 1.

if you ever wanted to learn python now is the time uh then in september we will hear from about research from dr wang from um nmsu school of engineering and he is also a new new mexico smart grid center heckled faculty hire finally in october we will learn about the research of dr xiao at an assistant professor at new mexico new mexico tech department of electrical engineering and also a new new mexico smart grid center higher uh registration info can be found on our website as always okay now that’s out of the way with that i’d like to introduce our presenter for today um dr jean we uh who was recommended by the aforementioned dr wang from nmsu dr jiang is an assistant professor in the ece department at clarkston university prior to joining clarkston in 2020 he was a power systems engineer at ge global research center in new york there dr jiang led a ge team to investigate long duration storage for renewable grid integration and participated in design of ge products including distributed energy resource management system flexible large power transformers and converter-based distributed generation dr jiang earned his phd from washington state university in 2016 and his research interests include renewable integration and energy digitalization thank you so much for being here dr jiang please begin whenever you are ready all right thanks so much um for the introduction here uh let me share my screen can you see my screen okay all right thank you for the introduction again um welcome to this talk here um today i just wanted to talk share some of my experience of uh when we are moving towards the 100 percent carbon free energy system can we still keep the lights on um this is this is very interesting to me that the reason is uh now we are more and more more and more dependent on the electricity and keeping the lights on is almost the number one priority for our daily life i just cannot imagine um we have the lights out uh the experience i had yesterday that we have uh the storm here yesterday and then um the electricity supply to the water house was out and then basically i was not i don’t have water supply for four hours this drove me crazy because i cannot cook and cannot take a shower so that just shows how important the electricity um to our daily life so giving that a background i just want to share a little bit of my view on this topic and hope that i will give you some information you can get something here um before i talk about the uh how to keep the lights on i just want to quickly um describe my background here um brittany already introduced my um experience here just want to give it a little bit more details here so basically i got my phd from washington state university and then uh my whole phd program was about outage for both the transmission grid and also distribution grid and also i have been working on the ge uh distribution management system for the smart city testbed um before i graduate so they because of that and then i very naturally and then i i transfer uh you know to ge to continue working in that direction but um surprisingly after i went to ge you know my all my focus was on renewable integration and also the product design to improve the greater resiliency the resiliency is almost equivalent to to say we need to keep the lights on under the extreme events basically resiliency is is miniature keep the lights on so in that part in the week i continue to work on some of the technology related to outage then in 2020 in 2020 i came to clarkson um i have been focusing on the the data analytics so basically now we have more and more data and how to use the data to um for the decision making power system um you you guys will have the next um seminar on the uh python learning for the data and then analytics and the visualization i would say i wish i could be the student here so i can have the chance to to learn but unfortunately i cannot but i i hope that you you can you can you can learn that and then you can you can see that what we are doing here in the power grid also quite rely on the data analytics and the visualization and the other part is i also focus on the grid operation under uncertainty uh latter part is more about driven by the renewable integrated into the grid you your your renewable is very uncertain means you have a lot of variability your forecasting has a lot of uncertainty how do you operate your grid uh consider uncertainty that’s another um direction that i’m focusing on but definitely i’m also considering i’m also continuing the work of outage related work there in the storage related work that has what i have been working on um since day one while i was in the phd program so basically that’s my um some of some of my experience uh i also wanted to briefly introduce where i’m from and the the power engineering program at my university which is clarkson university on the the the top left top figure is the where we are located if you look at clarkson is in new york state and indeed people always questioning um is in new york city or is where in new york and i have been asked i asked this question a lot of times and indeed the clarkson is in upstate new york um indeed is very close to the border between the u.

s and canada um people from the clarkson usually go to ottawa or montreal instead of go to new york city um if you look at the distance it’s very obvious and it takes us about one and a half hours to go to ottawa it takes a about two hours to go to montreal but it takes us about six hours to go to new york city so this is the weird clarkson it is uh this is the uh our campus in in the summer um we have a center we established a power system engineering center in 2018.

currently the core members we have we have five faculties uh in pub the purity in power system uh pure uh power engineering we also have um a coordinator because the the center is funded by basically by the clarkson in collaboration with the industry um we have quite a lot of the members basically we serve the industry in the northeast part of the country clarkson has a long history of power engineering uh it’s a strength for clarkson and we trying to continue that route and wanted using our expertise and experience to build a grid of the future um that’s basically the where we are um where we are and my uh my experience so now let’s jump into some of the uh information regarding the generation max in new mexico because we when we’re trying to hit the target of 100 percent carbon free we also need to know where we are i quickly look at a look at the data from the energy information administration that is a u.

s agent it looks to me now uh in new mexico um the energy the generation capacity compensation it looks like this this data maybe is a little bit dated uh the data seems like it’s from 2019 but definitely that give us a good reflect of where we are in new mexico for the general electricity roughly 30% of capacity is from coal it’s coal and the 37% is natural gas and the wind accounts for 23% solar 80% um it looks to me that new mexico is pretty dry and then the the hydro is only less than one percent this is based on the generation capacity and then if you look at the electricity electricity basically is energy from the energy perspective the coal that generates 42 percent of electricity from new york uh for new mexico state uh and the natural gas generate about 34% of the electricity in your new mexico state the wind and the solar the capacity-wise they have about 31% but in terms of electricity they account for 24% of electricity for for new mexico state it definitely did very um it looks like we have a lot of work to do to really transform the grid from the where we are to 100 percent carbon free one of the definitely one of the things we need to do is that get rid of the coal coal power the power plants there that’s you can do look at that capacity-wise of 30% percent the energy-wise of 42% that will lead to a dramatic change of the energy space um people may also say the natural gas is also generating the carbon dioxide in so um i look at data seems like in currently in the u.

s about 62 percent of the natural gas they are not equipped with the carbon capture technologies there in other words uh during the transition to 100 carbon free energy system and other work we need to do is to run it either you um retire the gas power plants or you need to invest into the carbon capture to make sure the natural gas will be carbon free with all of that the the need of the technology or the investment or exchange of the generation max it’s just another angle to show that we really really need a lot of engineering for the great decoration in new mexico that has been also reflected by the um the goal um the goal for uh the max code it i think the the legislators set up the goal that by 2030 uh 50% will be the electricity will be from the renewable and by 2045 and it should hit the target of 100% um if you look at the um currently the the renewable compensation in the u.

s uh here is where we are in the next few decades this is where we will go to um just one thing i want to point out here is um here is a percentage in other words if you look at the percentage now the hydro is about 34 percent in the renewable excuse me we have we have a question sorry um from anthony franklin why no nuclear? um even the new clear for forfeit here for for the uh for the renewable or the nuclear for the generation max um anthony both okay so this data it seems the new mexico does not have nuclear or nuclear is very small that’s what i find from the data from the uia data there he says he sees it now and then that’s a very good question indeed i like that question why not nuclear indeed currently nuclear is carbon neutral you’re right and um currently i think in the US we have about ten percent of uh generation uh electricity from nuclear uh the nuclear has the challenge is for the large-scale nuclear and the flexibility is very it so basically nuclear is not as flexible and then they usually, traditionally we use a nuclear to serve the base load and also the waste of the nuclear power plants it’s always a concern so for the large-scale nuclear power plants basically is not favored from the policy provider and also from the market prosperity i’ve seen it’s because the nuclear is serving the base load in other words the nuclear should be running constantly at an almost constant output but because the generation system is transforming to a high penetration renewal driven dominated energy system the system will need a lot of flexibility but the flexibility cannot be supplied by the nuclear that created the challenge to maintain the secure operation of the power grid with high renewables now in the nuclear space a lot of momentum is trying to design a smaller nuclear is more flexible we call it the small scale the nuclear technology i would say the technology now is still in the development phase has not really changed the game yet um but i will envision if the small scale uh nuclear power plants the new technology will come into the become mature coming to the market i think the renewable uh composition will be somehow be changed by that uh but the condition is we have to have the mature technology and with a lot of flexibility to really accommodate the variability and uncertainty of the renewable i hope that answered your question it did he said thank you uh no more questions right now okay great oh i forgot to wear it where i was but anyway um so you if you look at the um the renewable profile here um um so in the next few decades solar and wind will continue to ramp up hydro i would say hydro is still considered a very key component for the renewable future um indeed in new york state we have about 24% of electricity from hydro and that we are the new york power authority thinks hydro facilities will be a key enabler for new york to hit a 100 percent carbon free electricity grade um so if you look at the um this is the front of the the employment um this is the data is in 2019 um in the elect electric power generation employment the employment increased by 4.

8 percent the transmission the distribution storage uh sector the employment increased by 3. 5% this is just another angle to show that when we are uh transforming the power grid and the demand for workforce is definitely increasing that makes a strong demand of power engineers or engineers in energy space and luckily i saw i i dig into the literatures i saw one statistics for ieee so this is the ieee transaction on power at pert test and the system basically that’s the top one journal in the ieee on power engineering and i i i started in new mexico state the name is here uh this is a rigorous program it’s the fundamental to to develop the workforce um for the uh new mexico state or the country to really hit the target 50% renewable by 2030 and 100 by 2045.

20:57 - um so when the power grid is transformed is transformed into you know renewable dominated power grid uh another concern is a blackouts uh that has been um the the the effects of the black house has been shown by the texas blackout you know this year in the winter but generally speaking um because of a blackout it costs the u. s economy about more than 100 billion dollars per year because of the outage and also they have some statistics um shows by each state what’s the annual business losses are from the grid province i’ll definitely be from new mex new mexico is uh i would say is less impact um by the audigies or greater problems uh but if you look at the uh other state like california or texas or florida illinois or new uh new york uh we are highly impacted by outages, real problems um one example is hurricane sandy uh in 2011.

so if you look at hurricane sandy in 2011 uh the new jersey and the whole new uh northeastern part of the country has been hit pretty hard um so we have a lot a lot of people lost the electricity supplied by that and then the outage lasts for quite a few days that has a very big impact on the energy policy for all all the states here in the most eastern part so the electricity i usually say electricity is usually like taken for granted until until we are experiencing blackouts so the blackouts definitely is a very very important topic when we are transforming the grid into the 100% renewable um let me just quickly review what happened in the texas blackout from there we can see why we have the blackout what should we should do to really keep the lights off so in february 24th uh february 14 2021 to february um the 19, 2021 another time period uh the freezing cold weather had the texas region including new mexico if you look at the the map here i’m pretty sure that maybe you know some of your experiments that extremely cold weather in the winter um here is just a recap of what happened there so on february 14 the aircraft is the system operator in texas already seen that they already project that because the cold weather they may experience the shortage of reserve but they didn’t project that there are so many generators tripled offline including wind um so this is what happened in the early morning of february uh 15 and then at so this is the 12 12, 12 a.

m they saw that the reserve is less than three gigawatt and then they say we need to do the energy conservation but unfortunately even you do the energy conservation um you can still not maintain the reserve margin there because the the cold weather tripped off the gas power plants so at 1:20 a. m they issued uh emergency operation level three that’s the highest level basically they said there is no way for me to do anything to keep the lights on i have to do the load shedding so in that time they do the rotating outage for almost 11 gigawatt load 11 gigawatt load that’s a lot of customers um i think the whole new mexico the piccolo the property is around it’s about it’s about this number that means uh you basically cover the power supply to a whole new macro state and then during the road um during the rolling outage so if you look at the the generation um the outage due to the extreme cold weather there so this is the uh published by the earcup is the system operator to uh for the taxes you can see that the the scale here is gigawatt gigawatt it’s a huge number um so the 15 and the 16 uh around the 52 gigawatt generation triple offline because the extremely cold weather and then if you look at the composition the majority leading factor is natural gas and also wind so i would say the wind definitely played a role here because the uh cold weather not a leader to the uh running blackout if you look at some of the data here in texas the peak demand is 75 gigawatts roughly and then the whole the total generation capacity they have is about 107 gigawatt and then they have a generation outage like about 52 gigawatt if you do a single map here uh using the 107 gigawatt minus 52 gigabyte then you get about 55 gigabyte so 55 gigawatt generation definitely is way lower than your demand right so that’s one of the key features in power system we almost need to keep the balance um of between the generation and load to maintain the frequency in other words your generation is is way short than the demand then they have to do the lotion so uh in that in uh february 15 february 16 they shed about 20 gigawatts load um to maintain the reliable operation of the grid um if you look at the root cause of the blackout it’s the insufficient generation humidity due to extremely cold weather but if you go deeper into that if you go to really report from the aircut it’s because the cold weather makes the um the gas delivery system not working so your gas cannot be delivered to the uh gas-fired power plants and the um the wind turbine does not have the has the uh winterization um technologies so they freeze out they cannot generate electricity anymore so extreme events or extremely cold weather definitely lead to the running blackout in texas 20 gigawatt a lot of shedding is a lot that’s basically double the electricity the demand in whole new mexico state then we look at the 2020 the california the ruining black cow um the root cause is is totally opposite in 2020 in the summer um the extreme heat um heavier western coast and then including the california um so california experience the one why in 30 years weather events and then the climate change in this event heatwave really extended across the western united states indeed new mexico is also impacted by the hidden way so for the california if you look at the load curve so this is the load curve and then you look at the peak here definitely mean the load is larger than a typical year because the high demand is from the heatwave in this in the meantime the heat wave also um they the heat wave also make the thermal generators less efficient we know that thermal generators they uh depends on the ambient temperature uh the efficiency and also the capacity uh the max the limitation the generation limitation will be impacted by the ambient temperature generally speaking the thermal generators they can their limitation a megawatt limitation will be larger in winter but it’s less in the summer because the the higher ambient temperature and also because the uh the heat wave then you have the smokes the solar generation uh is decreased and also the california experience the drought they don’t have sufficient hydro generation so it’s a lot of factor lead to the rolling black car in texas um the if we summarize that it is it’s the imbalance between the generation and the low the heat wave increased the demand and the warsaw decreasing the generation not lead to the running blackout in texas if we summarize the two iranian black house in texas in in california you can see that um in texas they have 52 gigawatt generation is offline and the california solar generation decreases gas turbine decrease load increase for both scenarios and the impact is a lot of 4.

  1. 5 million in texas houses are lost to power and in in california roughly one gigawatt load um no shedding are was executed and the impact the taxes won is up to four days outage for some of the customers for the california um the outage was um less so but people will say you know we pay a lot of electricity bills we will make sure that system has sufficient generation to meet the demand that is should be done should it be planned in the design of the power grid why we have not prevent this kind of blackouts or say if we have a blackout what should we do indeed i have to claim that the engineering practice for the energy system are really really challenging by the extreme events to keep the lights on in other words the engineering practice in the power industry has not considered all the scenarios that uh of the energy system all the scenario including the extreme events or cascading failures of a power grid so that’s uh that’s the uh the practice indeed we can say we can always always improve the engineering products that’s right and how to improve the engineering products and also considering the cost that’s the other thing we need to keep in mind but how to design and operate the grid in a more cost effective way to keep the lights on while hitting the target 100% carbon-free that is our goal um if you look at the um historically the blackouts in the u.

s uh i just listed some very typical i would say signature blackouts in the u. s history um the most famous one i would say one of the most famous one it was 1965 that’s the northeastern blackout indeed the new york was heavily impacted by that uh that’s almost uh four or five decades ago 30 million customers are affected indeed because of this blackout that lead to the installation of a remote terminal unit that’s the substation measurement sensors and also energy management system energy management system ad for the trans bulk power system uh management system um in the control room yeah so what is because of blackout people realize that we need to have more visibility into the grid operation so that’s one of the um very signature blackout in the u.

s history now we look at the 2003 north eastern black house that blackout costs about 45 million uh customer lost electricity that drives to further investment into the grid people uh the industries want to have more visibility into your grid what caused it and they put a lot of investment into the phasor management unit that is about two decades ago now we look at the on 2011 2012 in that time period the U. S. has been impacted by a lot of hurricanes extremely events like hurricanes and and a thunderstorm like that and then about that impact so the you i would say this blackout or related transmission grid  but in roughly one decade ago that extreme events have impact the distribution grid about 4.

2 million people are affected and then one decade ago people bring the resiliency into our table and say we really really need to need to design a resilient power grid and then in 20 on 20 and 21 now we have the control blackouts about 4. 2 million customers are affected and what will come out from this we need to see but i’m pretty sure um the renewable somehow uh when we are doing the transition of the paragraph into 100% renewable we need to keep the blackouts into our mind and how can we keep the lights on when we do the energy transformation so i i always call the blackouts it’s a wake up call for a change of breadth especially the change of the policy changing the new standard, change of the engineering practice for us um if you look at the root cause of backup um there are so many reasons to cause the blackout uh in the taxes in california it’s the extreme cold weather extremely hot weather um if we cut categorize that into the top 10% root cause of blackout there or outages there the number one is a natural disaster including the extreme cold or hot weather as we talked about the second root cause is the motor vehicle accident so basically someone uh hit a poll um and knocked down the the power line that caused the costly outage and the warsaw the third one is the equivalent of failure basically i need to say that in the u.

s the power grid was uh was designed to build was the majority probably was in 1960s or 70s from 50s 60s and 70s in that three decades so the transmission line has been there for 50 years the power plants i would say power plant probably is fairly newer but the transformers and the transmission lines have been there for a few decades the average transmission transformers in the transmission grid the average age is about 27 years just imagine how old they are basically your father designed the power grid now you are still using the the same power grid your father designed but that all of that no matter is the natural disasters it’s the motor vehicle accidents or equipment failures or is it the falling trees no matter what so usually the system operators is sitting at the control room they don’t know what is going on there they don’t understand they don’t know if you are experienced experiencing an outage until you notify the system operator either by calling them say i have outage you know you need to take some action to fix it or some the some sensors at your house can detect there’s outage and send a notification to the control room to notify the system operator that you have a power outage so no matter what what root cause it is the system system operators relies on the technology to estimate where the outage is where the problem is for example if there’s a file or if there’s a uh the poll knocked down they need to predict what where the problem is so they can dispatch the crew to patrol in order to come here on site to fix it so we call that as outage management um before i go on i just want to see uh uh isis do you see any questions no questions at this time.

all right um feel free to answer questions and i would be more than happy to answer any questions there if there is so here i just wanted to you know go into some of the technology that i have been working on um the the first part is the audit management of the electrical power division systems um while talking about the distribution grade the audience management basically when you have a power outage either you call you pick up your phone call to to to notify the um the system operator saying you have outage or the smart meter at the warehouse will report outage um i need to talk about the currently in the us the energy meters we are using so energy meters are nothing new but depends on technology we have three categories one is the uh the traditional matter we call the standard meter uh about 2000 um the automation um we try to increase the automation in the into the power grid and then roughly in 2000 we started in the U.

S. we started deploy the AMR it called automatic meter reading meter but that is not a small meter and in the last decade we have seen a lot of installation smart meters compared to different technologies basically the standard meter needs uh the the utility will need to come dispense some um some people here to come into your backyard to read the meters how much energy you consume that every month that’s manually basically we call the manual meter the AMR meter basically is called automatic meter reading uh what they do is uh they have a one-way communication that instead of coming to your backyard they just need to drive a car along the road and to ping your meter and to read the energy consumption or detect if there’s any issue or outage in your house now the smart meter is we call it smart because you have the two-way communication it has more um capability they they they report the data energy consumption every 15 minutes or every hour uh beyond that if your house experience outage it can send a notification to the system operator automatically uh i look it up the the profile in new mexico state currently uh the majority of your customers in new mexico stay is still the standard meter that’s about account for about 62 percent and then about 20 12% of the customers it’s using the smart meters uh this number is for the us roughly about now i think about 100 million smart meters have been installed in the U.

S. so because of the smart meters you’re going to see that now the system operators has the visibility into the residential or commercial so basically in the customers energy consumption because the data originally the standard meter can give you the manner to give you the data one data point per month now the smart meter gives the data every 15 minutes so the meter uh i think the the the volume of the data is is hundreds uh tens of hundreds uh tens two hundred times the data volume so that data give you more information so my research for on this topic is trying to use the smart meter data to help the outage management in other words we use smart meter data to help the system operators to infer where the problem is say the the poll that was knocked down or the squirrel like uh you know jump into the the lines there to create a shortage whatever and then if you look at the uh this is the distribution grid um this is the schematics um so this is a substation you know the uh from the substation from the feeders you go to the the fuses for protection then you go to the student transformers they serve the house if there’s outage for example if there is a file here then you trip open the recloser then all the customers downstream will experiment outage then the smart meters will report the audit you send a notification to the system operator the system operator using that notification try to infer um where the file is and what happened there so the question is that how do you use the meter data to infer the audio scenario also i need to note that in addition to the smart meters we have along the feeder level we also have remote file indicators we also have the automatic over closures like that so the feeder level sensor together with the smart meter how did you use the data to for the decision making for the system operators so i um if you look at the um of the outage management issue and then you need to you don’t know what happened in the scenario you try to uh infer the most credible out of the scenario supported by the evidence the meter data there and then you also need to constrain the physical rules the physical rules means basically considering the physical property of your system for example your protection is coordinated basically when there is a fault downstream of protection your protection is expected to activate you also want uh has the other constraints saying the faulty indicators send the notifications only when the file indicator is upstream of the file the follow location like that and then you give all the all the constraints you try to infer using the data from the meters either the smart meters or the feeder level meters you try to infer which outage is narrow of default location and also the activated protection is the most incredible but indeed that is you don’t know what happened there you don’t know the ground truth but what you can do is purity data driven or evidence driven try to infer these scenarios there so in the optimization perspective you put an objective function you put a lot of constraints there you try to solve the object optimization but indeed because you don’t know how many files are there if there is if any meter is uh is uh failed or any meter male functioned you know in other words we don’t know the uncertainty of the meter theta then we propose using the hypothesis testing in other words i don’t know what it or how many issues are there in the system i can put a hypothesis assume how many issues there for each of the assumed scenario we run the optimization try to improve the efficiency of the analytical model so the immediate model is the challenge is that we there a lot of non linearity and also computational complexity in the local optimality and then we propose using to have multiple hypotheses methodologies so you generate a hypothesis you collect all the evidence from the smart meters or feeder level meter data together you design the optimization model consider all the constraints your remote file indicator should be about upstream of the file location your smart meter audio report should be downstream of the activated uh protections there like that and then you run the optimization model you for each of the hypotheses you determine you calculate the credibility of this hypothesis in other words you you try to rank the credibility for each hypothesis then using the credibility you infer which audit scenario is the most credible supported by the evidence you connected from the smart meters or other sensor uh sensors around the feeder now we tested this uh the technology uh using the the real world feeders uh this is from the um the the washington state um this is the simplified schematics of that and then we have the scenarios there uh we uh we generate eight hypotheses for each above that is we run the optimization we determine the which device protection activated where the fault is we calculate how many small meters are aligned with the determined all these scenarios and the credibility we can see that for this one for the other half either hypotheses we can see that different hypothesis will have are have different credibility credibility we rank the credibility we find the most credible one using that hypothesis result you infer the audit scenarios so basically we infer what happened in the outage using the data this is a very in line with what we do in this room where we have the distribution management system we use the data we leverage the data we try to infer what happened we call it data analytics in the power system um so this is the distributing grid for transmission for transmission now i would say it’s it’s very similar but the transmission is way more complex than the distribution if you look at this transmission transmission basically the transmission line in the substations in the substation because the substation automation we have a lot of sensors installed into the substation that includes the digital relays the uh phasor management units and then other ieds like all the meters there and then for transmission the protection principle is totally different because the transmission grid is way more complex for each of the components in power system we have a dedicated production scheme to protect the component the reason is one transmission transformers will cost you quite a number of million dollars so if there is any events let’s say there is a fault within the transformer you want to trip open the circuit breaker to isolate the transformer transformers as soon as possible usually that is done within one or two seconds so that it we have a very soft um you know dedicated protection to protect a great asset there so usually for transmission grid uh for grid asset we have the main protection this uh the primary backup protection secondary uh progression trigger failure progression all the purpose is trying to isolate the fog as soon as possible and considering the abnormality and security of your protection schemes so at the substation you have the pmus you have other device ieds or digital relays you also have the sequential event recorder that basically to try and record what happened in the substation uh did your uh digital relay trip did your uh circuit uh breaker opened did your pmu that recorded the data like that they all will record in the sequential uh event recorder now the problem is how for the system operator we don’t have we don’t have um engineers in every substation the system operators in the control room they rely on the alarms for the data from the sensors to infer what happened which transmission line filed it which protections it’s triple open like that so the user they use the data using the data analytics technology plus the domain knowledge of power engineering try to infer what happened there we call the event diagonals for transmission so basically you have the grid of data you have sensor data you’re considering all the domain knowledge of the protection and the system there you try to infer where uh which component is filed it where’s the failure of the circular banker if there is any failure or malfunction of the relays or if there is a missing or incorrect alarms like that so we call that even the diagnosis um so here is just one example a file that happens in line 3 and then this circuit breaker keeps triple open but this circuit breaker did not instead the second secondary backup protection at location circuit breaker one second break two second flavor 15 the circular vapor top they took the oven to answer the file then this is the event this is this um alarm we get and then using the analytical model there we infer what happened there uh at what time the the fault occurs and at which component filed it um which protection relay tripped open or failured and is there any other time type issues with circuit breaker electron so what we’ve done for here is we propose the analytic model to handle the complex scenarios with the abnormalities but then um given the time i will i will go a little bit quick here as what if the cascading events leading to a system-wide blackouts in other words what if your uh abnormality or files has not been isolated by the protection or the the the issues propagate into the in the in the grid that is what exactly happened in 2003 one spread blackout um so when we have a widespread blackout what do we need to do we call the power system restoration what is a power system restoration basically you have someone dedicated to the black star units you use net a black star unit you try to crank the network and also the generators you try to restore bring back the transmission line and also the generators back into normal operation um step-by-step so we call the generator restoration system restoration that loaded restoration if you look at the the pictures basically you are using one uh the dedicated generation unit we call the black star unit you try to crank the network step by step we call the restoration there and then indeed that effort was from the 2003 the the westbrook blackout and then after it was put some initiative to design the software there uh it takes a long time to really design uh develop the tools there indeed one of the tool is defined by i would i wouldn’t say purely by me but started from me and um now uh they tested the work with the um the teenagers across the world for for this technology i do have a small uh video here to um to show it’s a small a very quick plan to show that the tool here but it’s not a toy it’s more about the background why we need to do that how the tour is helping the industry restoring power to the electric grid after a total shutdown this ability to black start the grid is something all grid operators plan and practice for and it’s one capability they hope to never use a black start involves using designated power plants known as black start units that can start without the help of the grid as these units return to service grid operators methodically connect electric load and other generators to restore the system through prescribed steps while the concept of a black start has generated oh sorry discussion following the extreme winter weather impacts in texas restoring electric service in the state did not require a black start that’s because the grid is designed to withstand disturbances without leading to a blackout grid operators must anticipate and mitigate a number of scenarios from severe weather to natural disasters to cyber attacks to an electromagnetic pulse the electric power research institute works with utilities around the world to harden their systems plan to mitigate the impacts of extreme events and expedite power restoration while some estimated that restoring the texas system from black start could have taken months the black start of a de-energized but functional energy system would have taken a matter of hours or at most a few days epri’s approach to black start planning consists of two primary components empress optimal blackstar capability tool finds the best location of blackstar resources those that power on first as well as the sequencing across the grid to restore priority loads and non-black star generators this identifies the ideal black star strategy assuming all resources are available as the circumstance so given a time i will not oh i should just stop sharing the spring sorry um given the time i will not go to the details of the all the videos here um so so this is basically the tool and also we tested it for like using the duke energy systems there’s some results there uh given the time i will not go to too much details here but then when we are looking about the transformation of the grid into the future and then we we are really have the challenges here in addition to the challenges that we have been talking about in the last decade no inertia from the renewable variability and uncertainty from the renewables i think the most challenging one is engineering engineering practice and the controllers in the system now currently we have they are all based on the conventional generator resources so that create i would say the most challenging part for the transformation of the grid um now this is the uh some of the uh the yeah sorry dr john it looks like we actually have a question from anthony um what is um and so i was gonna interject you have two minutes left maybe you can use the two minutes to answer uh questions does that work for you yes okay um because this has been a fantastic presentation thank you so much um anthony’s question is um what are the biggest obstacles currently facing you in your work and what are some of the future challenges you anticipate? right i think that’s a fantastic question i think the challenge one is how do you understand the value of the data now from the grid and then this understand the value and the second is that how do you design the technology based on the the data combined with the domain knowledge to really untap the value of the data um for me one of the challenges is that i sometimes i cannot get really the the data that i want for my study but from the technology perspective the challenge is how did you design the technology to really take the challenge um based on the grid.

59:03 - awesome what a succinct and on-point answer thank you um this has been an absolutely fantastic presentation i um there are not enough people in academia that present like you do so thank you thank you thank you for being here um i’m gonna i’m gonna quick close this out um since i don’t see any other questions and take over the screen so i can show this yes thank you um thank you again doctor we’ve got someone in the okay cool um thank you dr jiang once again for being so generous with your time um this is an absolutely fascinating topic and one that’s as you know at the core of our project’s research mission so this presentation was quite a treat for us and and for those of us who are non-experts in the field it was fantastic um before we sign off i just want to thank my partner in crime and dr wang for suggesting dr jiang as a webinar speaker because he was fantastic um so thank you thank you for presenting.

thank you for having me here and i think of all the students who attend our faculties attend this seminar if you if you have any questions feel free to reach out and then you can easily look out look at my information website and i will be more than happy to um keep the conversation going there and keeping in in touch with you this has been a great day thank you so much and don’t forget everybody to join us again in august for python fundamentals data analysis and visualization with dustin allen um until next time have a great great afternoon everybody.