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Well, it’s heading that way more rapidly than almost every other US state already. And it’s reaping the benefits of lower retail price and higher grid reliability.This is from the Electric Reliability Council of Texas (ERCOT). 18% of the electricity generated in Texas in 2017 was from solar and wind, with a lot more being built.What’s been the result? Flat and declining electricity rates for consumers compared to the US average per EIA statistics.That 1% of solar has signed deals to triple by the end of 2020. Wind generation has signed deals to increase by 40%.Let’s call it 29% of all electricity by the end of 2020. If the rate of deployment persists, and there’s no reason to believe it won’t as wind and solar are cheaper than operating existing nuclear and coal plants, Texas could be 100% renewable in under 20 years.Oh, and the ERCOT point is interesting because Texas is at about 20% renewables now with zero grid instability issues. In fact, Texas grid stability has increased substantially from 2012 to today. It was dead last in 2012 and now it’s 34th in terms of reliability. An unstable grid is becoming stable as more renewable energy is added to it in a nice inverse of the anti-renewable FUD.References:Texas Got 18 Percent of Its Energy from Wind and Solar Last YearTexas Ranks Last in Electrical Power Reliabilityhttps://www.usnews.com/news/best-states/rankings/infrastructure/energy

You have to remember that Abbott is a lying weasel, who is also the Governor of a state that has refused to spend the money that other states did in order to ruggedize their power systems against bad weather.Abbott first came to my attention when, as Attorney General of Texas, he dropped the case TX was pursuing against Donald Trump and Trump University on behalf of the “students” they defrauded, at about the same time he received a large donation to campaign to run for Governor.More recently, he was in the news for threatening to secede from the Union over Trump’s loss in the Presidential election, and again helping his AG try to bring suit against Pennsylvania for voting for Biden.Having explained why I expect nothing good from Abbott, let me say a little about why Texas is having power issues.Most states subscribe to a national electrical grid. That allows a state which is having trouble to get some help from neighboring states. Normally, this happens invisibly, so we don’t hear about the problems in the first place. It is part of benefit of being part of a large country.But, in order to make the risk sharing tolerable, the national grid has standards of ruggedization that it requires member states to meet. Texas decided that it was big enough not to need the help, so they “saved” themselves the expense of ruggedizing their network, and stayed off the national grid.Part of the standard would have required that the water pumps and heat exchangers which are an integral part of the process of turning heat into electricity in a gas or coal fired plant, and especially at nuclear plants, would have to be engineered to work under very cold conditions. Texas decided not to bother.So now, when it suddenly gets cold, as part of the climate change that they deny is happening, their coal, gas and nuclear plants stop generating. (Ironically, the solar and wind generators have degraded far less than the coal, gas and nuclear plants.)He can’t say, our gas fired plants planned poorly, they didn’t invest in the weather resistant systems we now need, because that would make it seem like it was the fault of the petroleum energy companies. And they fund most of his campaigns.And he can hardly admit that a big part of the problem is Texas’ notorious libertarian independence and refusal to adhere to standards some outside “scientists” (engineers, actually) wanted to impose.And he really can’t admit that a deeper reliance on solar and wind power would have made this problem less severe.Blame must be laid.And the only convenient place to lay it is on the Green New Deal, with its emphasis on renewable energy.Don’t look for honesty from Governor Abbott. Look for expedience.Q: Why did the governor of Texas, Greg Abbott, say that wind and solar are causing Texas residents to lose power during the winter 2021 cold snap?

Incremental change is one of the most powerful forces in the universe.AI isn’t doing much today to advance renewable energy, but that’s changing. AI holds terrific promise to advance renewables, and more and more people are recognizing the potential of AI. It likely won’t do so in “sexy” ways, but it can enable advancements on several fronts at once. The big ones are 1) grid integration & smart grid technologies and 2) forecasting (see also this link), but these aren’t the only interesting applications.*In this post, I’ll talk mostly about why AI hasn’t made a big impact on the deployment of renewables thus far. In future posts, I’m hoping to write more about how and why it’s going to transform renewables.As hot as AI has been, it hasn’t made inroads into the renewables space in any substantial way. There are several reasons for this, but the main one comes down to the basics of energy economics.At a fundamental level, energy is a commodity that is produced and consumed. Unlike fossil fuels, renewable energy is not extractive. But renewables still obey the basic rules of economics. In other words, the renewable energy industry’s core business is similar to any commodity business: profit is the result of producing something at the lowest possible cost and selling to others at a higher price.As such, renewables actually includes a few separate market segments:Residential - think rooftop solar; this includes sales to individual, residential consumers. These are the smallest, highest-cost systems.Commercial and industrial - companies and industrial players will often purchase renewable energy for their own use. Typically, these players prefer to buy energy via power purchase agreements (PPAs) rather than to own and operate their own renewable power plants. In the US, C&I renewables mostly refer to wind and solar.Utility-scale - producers of renewable energy build power plants and sell either the plants or the energy to electricity utilities (the specifics depend on the rules of the electricity market you’re in - ERCOT in Texas looks different than CAISO in California). These utilities then turn around and sell the electricity to consumers. Utility-scale projects are the largest and cheapest per unit of energy produced, but because they’re so big, they take years and millions of dollars to build and operate.At this scale, geothermal and hydroelectric join the club. When you’re going to invest a ton of money in building a hefty power plant, building massive hydro plants or the occasional geothermal is often the most attractive option. Generally, a small scale hydro or geothermal plant doesn’t make much financial sense, to say nothing of the environmental, legal and political hurdles.In both the US and worldwide, the utility-scale segment dominates the solar and hydro markets. I don’t have good stats on wind, but I’ll go out on a limb and intuit that it’s basically the same. Econ 101 will tell you that the larger a plant becomes, the less it costs per unit of energy because the fixed costs can be spread across a wider base. So, utility scale typically produces the lowest cost of energy, and lowest cost usually wins the day in a commodity market.Here’s why this matters for AI:At the utility scale, both producers and consumers are large companies that are highly focused on energy as a commodity. Utilities want to buy renewable energy as cheaply as possible, and producers want to make clean energy as cheaply as possible. For the same reasons as above, making something cheaper means achieving the largest possible economies of scale.What this means is that utilities - the biggest purchasers of renewable energy - are often massive, slow-moving, stodgy entities. Similarly, renewable energy producers “win” by reducing their manufacturing expenses and making the cheapest possible goods. It’s not impossible for big companies to innovate - GE is a good example of a huge company that’s done a lot in renewables, e.g. wind - but it tends to be harder.The same is largely true of renewable energy producers. China - the undisputed world leader in low-cost manufacturing and building massive things with cheap labor - dominates the hydro and solar markets (the biggest wind companies are actually not all Chinese).Hydroelectrity is not easily productized; you can’t really export a hydro dam. But you can export lots and lots of solar panels and wind turbines. This means that producing energy is a brutal, cutthroat business. The high margins of yesteryear are a thing of the past, and low cost rules the day.Bottom line: when everyone is focused on making things cheaply, there’s not a lot of time and money left to focus on innovative measures like AI. On the demand side: hiring qualified data scientists and AI practitioners is expensive, and being a “cost center” at a big manufacturing company or a utility is a tough step for executives to take.Moreover, most executives at these companies don’t really understand AI and don’t have a clear sense of its value. It’s not that they aren’t interested; part of my job at both solar companies I’ve worked for is to help senior executives stay abreast of emerging and disruptive technologies. I like to think I did a good job at this. But what I found is that it’s a tough sell for any executive to say, “Give me a million dollars and two years to build a center of excellence for AI and data science”, no matter how compelling a picture you paint of the ROI. When a company is preparing to lay off workers and close plants because it’s facing a ton of competition from cheap Chinese products, an executive who suggests something like that is going to be laughed out of the room.On the supply side, AI is in high demand and so are qualified practitioners. If you have a choice between working at a hot startup making big $$$ and doing sexy things, or working for an electricity utility where the entire company culture is focused on low cost…well, it’s not a hard choice.This is the status quo today. But change is coming.Disclaimer: I’m aware that I didn’t answer the second part of the question, about how AI can benefit renewables and fight climate change. That’s coming, too.I’ve noticed quite a few questions on Quora recently about how “hot technologies” - AI, machine learning, and advanced analytics - can affect renewables. I’m not an expert in AI, per se, but working for a solar energy startup requires me to stay “in the know” on important trends and to make clear to executives how disruptive technologies matter for renewable energy. Moreover, the intersection of advanced technologies and renewables is a Big Deal™.So, for the rest of May, I’ll be writing a lot more about the potential for AI and machine learning to advance renewables. I’ll try my best to “pull back the curtain” and write accessibly for those who might not be on the cutting edge, but who want to learn more. If these topics interest you, please feel free to A2A me and I’ll do my best to share what I’ve learned “from the field.”*Two examples of the cool stuff: 1) smart devices for operations & maintenance/O&M, and 2) AI+computer vision for labor analytics and labor cost reduction.Here’s a picture of a generally impractical but really cool-looking PV array. AI will be just as cool, but much more practical!