Combined heat and power: the economics?

This data-file models the energy economics of a combined heat and power installation, to provide electricity and heating behind the meter, in lieu of purchasing electricity from the grid. The economics are strong, especially for larger units.

CO2 emissions can also be reduced by 5-30%compared to purchasing power from the grid, due to high efficiency capturing and using exhaust heat in CHPs.

Economic sensitivities can be stress-tested, including to power prices, gas prices, thermal efficiencies and system sizes (examples below).

The full model also contains granular cost data, c100 rows of operational data for CHP systems and our full notes from the technical literature.

One hundred years of innovation: global patent filings from 1920?

This data-file breaks down the number of patents that have been filed globally since 1920, across 150 different categories, to illustrate the pace of technological progress, across each industrial sub-segment.

The data are also sub-divided by geography, across the US, China and Japan, which are contrasted in c30 charts. Depressingly, the US’s share of global patent filings has recently declined back toward all time lows, while a vast acceleration has seen China filing 70% of all global patents.

China’s lead is also widening in 135 out of 150 patent categories in our data-set. This may suggest trade tensions are on course to accelerate further. It also holds implications for policymakers, as Western decarbonization must be balanced with industrial competitiveness.

CO2 concentrations in industrial exhaust streams?

The aim of this data-file is to compile CO2 concentrations in industrial exhaust streams, as a molar percentage of flue gas. This matters for the costs of CO2 separation (e.g., the amine process).

Costs will generally be c10-15% lower to separate out CO2 in middling processes such as blast furnaces and cement plants, compared to lower concentration processes such as coal and combined cycle gas plants.

Costs of separating CO2 from ambient air will be an order of magnitude higher again (at least c4-6x, as costs rise linearly as concentrations fall by each order of magnitude).

Most promisingly, some CO2 is already purely concentrated (e.g., after pre-treating natural gas before LNG liquefaction; or after separating out industrial hydrogen from SMR in the refining, ammonia, chemicals and blue hydrogen industries). These be the most promising options for CCS.

Energy transition technologies: the pace of progress?

This data-file aggregates 20 different TSE patent screens, to assess the pace of progress in different energy technologies. Our short, 3-page summary note on the findings is linked here.

Lithium batteries are most actively researched, with 8,300 patents filed in 2019 ex-China. Autonomous vehicles and additive manufacturing technologies are accelerating fastest, with 10-year patent filing CAGRs of 22% and 53% respectively.

Wind and solar remain heavily researched, but the technologies are maturing, with patent activity -36% and -76% from peak, respectively. The steepest deceleration of interest has been in fuel cells and biofuels, declining at -10% pa and -7% since 2009.

It remains interesting to compare the pace of progress within sub-industries; for example, more supercapacitor patents were filed in 2019 than nuclear patents; while hydraulic fracturing patents remain the most intense focus area within conventional oil and gas.

Vestas: where’s the IP?

This data-file aggregates 2,000 patents filed by Vestas and compares them with 15,000 patents filed by its competitors. This allows us to conclude that Vestas likely has an edge in wind technology.

Vestas’s largest turbines are currently 10MW, smaller than the monster 12-15MW turbines making headlines from GE and Siemens. This is because Vestas’s focus is elsewhere, and not simply on the largest nameplate capacity.

Vestas’s patents focus on reliability, operability, digital monitoring, ease of installation, ease of maintenance and the longevity of turbines. It leads the industry by 20-100% on these categories. A steady stream of patents is also being filed to improve manufacturing methods.

Our insights, charts and data are contained in the data-file.

Vehicle costs: cars, SUVs, hybrids, EVs and hydrogen?

This data-file quantifies the cost per mile of vehicle ownership for different categories of vehicles. Our methodology looks across the prices of 1,200 second hand vehicles, to correlate how the re-sale value of each make and model degrades per mile that has accumulated on its odometer (chart above).

Hybrids and basic passenger cars are most economical. Trucks and SUVs are 2x more costly. EVs are another 25% more costly again, and will have lost c60% of their value after 100,000 miles. Hydrogen cars have the highest costs and will have lost over 90% of their value after 100,000 miles (chart below).

Underlying data are shown in the input tab across ten makes and models, to see how the re-sale value of each vehicle degrades with mileage. This may help you appraise what a particular second hand purchase “should” cost (example below) if you are among the many non-drivers considering a vehicle purchase as a result of the COVID crisis.

 

Refinery membranes: where’s the IP?

This data-file reviews over 1,000 patents to identify the technology leaders aiming to use membranes instead of other separation processes (e.g.,  distillation) within refineries.

Covered companies in the screen include Air Liquide, Air Products,  Aramco, BASF, BP, Chevron,  Dow, ExxonMobil, GE, Honeywell, IFP, MTR, Praxair, Shell, WR Grace and Zeon. A brief overview is prented for each company, along with a summary of their recent patent filings, and all the underlying details.

Operational data are also presented for two interesting cases: Exxon’s recent refinery membrane breakthrough (chart below) and Air Products’s PRISM membranes for hydrogen separation.

A database of historical commodity prices and disruptions

This data-file aggregates long-term historical prices of commodities going back to 1800, and running up until 1970, predominantly in the US, using academic records and census data.

Covered commodities include bricks, coal, copper, cotton, nails, rock oil, steel rails, sugar, turpentine, whale oil, wheat and wood. A combined profile of all of these commodities is aggregated in the index above.

In particular, we focus in upon the disruption of whale oil as a lighting fuel and the disruption of wood as a heating fuel, using granular data into pricing and demand. Our conclusions are presented in a research note linked here.

Tesla: where’s the IP?

This data-file compiles all of Tesla’s patents, classifies them across 1,000 patent families, and describes their innovations.

Our conclusion is that Tesla holds less patented IP than rival auto-companies. However, where it has filed patents, it is more focused on pure EV technologies, such as batteries, electric circuitry, electric propulsion and digital features (chart above).

Patent filings since 2019 have focused on big data/digital technologies, solar and improved batteries (including novel electrolyte systems using lithium fluorates, borates and other improved additives).

Fiscal incentives for US decarbonization?

This data-file tabulates fiscal incentives that exist to abate CO2, across individual categories in the energy transition, based on current legislation in the United States.

In each case, we have calculated the implied cost to abate CO2,  under the various policies, as measured in dollars per ton ($/ton). Included in the file are Production Tax Credits, Blenders Tax Credits, Investment Tax Credits, Equipment Tax Credits and Section 45Q.

Our view is that the current system is overly-complex and arbitrary. It provides large incentives for specific technologies that happen to have policy support, and no incentives (or small incentives) for other technologies that could make a larger decarbonization impact at a much lower cost.