Wind Turbine Power Generation & The Science of Emergence

I’d like to continue piggy-backing on my previous posts about localized data and control with an entry-level post about wind forecasting as it relates to energy production and energy markets. 

Wind prediction is part of our local, nightly newscast and the principles guiding it are scientific standards: low pressure persuaded by distant bodies of water make wind.  This is nothing new.  What is new, however, is the hyper near-term prediction of wind velocity, angle, density, etc. for the use in wind farm design and operation.  Day-out forecasts have long been available for these purposes, but several firms now offer data-analytics software (i.e. LIDAR) and turbine blade hardware that can make real-time predictions of incoming wind several thousand feet away.  Micro adjustments are then made to blade pitch and the like so as to better capture the energy within the wind.  This ability is not necessarily new as many newer turbine blades incorporate design that exploits complex hydrodynamic principles, but adapting them to further increase production is still ongoing. This is very similar to the use of automated flight stabilizing flaps used on commercial aircraft.   The below video is a quick, anecdotal example.

What’s more, I believe the concept of Emergence used in Science could also compliment the refined efficiency of large farms.  Emergence is the concept of self-organization without leadership.  Fire-flies, ants, fish, and the like use it to build complex societies and coordinate movement without the aid of central command.  It’s the same reason why some neighborhoods within a city sprout and gentrify quickly.  One unique shop or venue opens up and passerby’s stop.  Soon enough, people come to view the venue, start new venues, move, multiply, grow, etc. until a new neighborhood has formed with new character all without official direction.  I’m leading to the point that wind farms can benefit from this concept too. 

A farm built in such a way so as to capture wind data from the front-facing turbines could then communicate valuable data backwards to the “school” of turbines stacked behind it just as fish do effectively letting them "see" and adjust to wind in real-time.  Farms could make quick, forward-looking micro adjustments to harvest the best catch.  Assuring every installation of wind generation has more up-time is critical to making it a viable node within the larger generation/transmission system.  Independent System Operators will be able to consider using this power more regularly and at better prices with these increased efficiencies instead of it currently being relegated to generation for nighttime load.

A Final Dash of Salt…

This post isn’t a rant into the awesomeness of wind power.  Instead it’s an extension of my recent theme on data-driven, networked energy production and consumption.  I look at any opportunity to turn passive technologies (i.e. wind) into active and controllable ones.

Has Distributed Generation (DG) Reached a Fall-line in the Utility Industry?

In follow-up to my previous post about the Internet of Things, I’d like to discuss one of the most prominently affected industries and a topics: Utilities and Distributed Generation (DG).

When Edison first performed Direct Current (DC) transmission of electricity, the concept of DG was the paradigm of electric consumption: consume electrons near where they’re produced.  Consumption remained this way for a small amount of time before Alternating Current (AC) allowed the gap between generation and consumption to literally widen.  Today, this model is even more evident as most consumers cannot even speculate as to where their electrons come from.  However, several evolving forces have renewed interest in this classic concept and reinforced the possibility of DG becoming a valuable energy alternative for Industrial, Commercial, and even Residential consumers.  It is being seriously evaluated by many agencies and utilities around the country.

                Utility administration must craft their perspective on this topic as it will be continually discussed in this and several upcoming decades.  First, they should settle upon why not to embrace this concept, which includes fundamental power production and distribution issues such as power quality.   Utilities traditionally discourage multiple generation sites on the account of power quality.  The introduction of various generation points, times, sources, voltages, etc. greatly affect the physics of producing and transmitting “good” power: load factor, voltage, harmonics, etc.  In many cases, DG directly erodes the effects of the natural Economies of Scale traditional to electricity generation and the very reason Centralized Generation (CG) exists.  On a purely mathematical basis, increasing DG, at least in 2012, will make CG less efficient.   Classic Economics assures us the most efficient player should always produce the appropriate good/services, which has so far been demonstrated by the AC generators of the last 100 years.  Interestingly, this paradigm is now also driving a resurgence of DG discussions across the spectrum of Utility customers. 

                There are increasing instances when the actual consumer of electrons may be able to produce them more efficiently than a centralized Utility and as such each Utility must render an opinion on why to embrace the concept.  Micro-generation technologies such as turbines, battery storage, PV, bio-reactors, etc. allow for this.  Utility point of view sometimes changes as they begin to run the numbers on Avoided-cost.  If the harm of DG on power quality and planning can be minimized, it may be more efficient to allow for DG, thus making the avoided-cost component an immeasurable real-time stat to monitor.  This is generally in contradiction to most people’s thinking of big Utilities in that many believe they simply want to sell as much electricity as possible just as any other business would.  In reality, Utilities want to sell the right amount of power, which is a delicate dance between bulk and efficiency.  So does DG stand a realistic chance amongst evolving fuel and technology prices?

                Real potential exists for DG to gain noticeable traction right now largely due to two macro trends.  First, the advancement of micro or hyper-local generation technologies across the Utility customer spectrum makes on-site generation economical.  Second, the real-time and decision-making power of a data-driven economy and energy marketplace make micro control and connection realistic.  The Classic Economics referenced prior state that the most efficient player should produce any given service/good, but this fundamental decision process has never been widely applicable to energy generation and consumption.  Energy has always been dumb.  The data-driven information revolution and the implementation of data analysis, real-time control, and networking technologies make it possible for Generators and Consumers to interact, which is a new element to the Utility industry.  DG can generate when most efficient while CG reduces peaking-plants and vise versa.  These are the data trends that are flipping a 100-year old Monopoly on its head and should surely become action-items on any utility CEO’s desks if they aren’t already.

 A Final Dash of Salt…

 Data-driven energy generation and consumption: the biggest change to the utility industry since AC

transmission?  I think so!

Extra Reading…

Check out the sections on the changing nature of risk.

http://www.ferc.gov/legal/fed-sta/exp-study.pdf