Exploiting the Inverse Capacity-Rate Relationship in a Stochastic

Setting

Control Algorithm Development for Hybrid Energy Storage in Renewable Energy Applications

Advisors:Prof. Craig Arnold, Prof. Warrant PowellSami Yabroudi

In a Nutshell…

• To make alternative energy viable in a closed system, need to make storage functional and efficient.

• To store with varying supply and demand (i.e. in the real world), use multiple complimentary storage devices.

• To decide where to allocate energy to and where to use it from at a given time, use Approximate Dynamic Programming.

The Big IdeaWith StorageDevices:Every storage device has its own power and capacity applications. Pick the one that matches your needs.

INVERSE CAPACITY-RATE RELATIONSHIP!!!!!!!

But what if…

…energy supply and demand are stochastic?

• What if you wanted to power a house using a standalone wind turbine system, and • What if the wind changes speed and direction, sometimes blowing a little,

sometimes blowing a little more, sometimes blowing A LOT, and sometimes not blowing at all, and

• What if the family inside the house has an energy demand that changes significantly over the course of the day, unpredictably.

Translation to the vernacular: What if everything in the world behaves normally?

Battery Rate and Specific Capacity• Charge, discharge rate measured in power

per unit mass or volume (or money), or C rate, which is a percentage of total capacity– Ex: A battery charging at .1 C would take 10

hours to charge

• The more charge/discharge current you draw (or try to draw), the more ohmic and kinetic overpotential you have, as well as ohmic loss– Charge Voltage:

– Discharge Voltage:

• The higher the current on a battery, the more permanent (and bad) chemical changes you make to the battery.– “Gassing”

• Ragone Plot: Most Batteries prefer to operate below 1-2 C, and reach their absolute limit below 10 C.

(Summarize)

Electrochemical (i.e. “Ultra”) Capacitors• Energy stored between porous electrode and electrolyte,

and across separator• ~3-10 Wh/kg• ~200-2000 W/kg

– @ 95% discharge efficiency

• Same rate effects as batteries, but for much higher rates

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Other STSES Devices

• Compressed Air Energy Storage (CAES)

1 = cooler2 = compressor3 = air4 = clutch5 = generator/motor6 = power supply7 = turbine8 = combustor9 = fuel10 = valve11 = air storage cavity

• Flywheels

• Superconducting Electromagnetic Energy Storage (SMES)

Inverse Capacity-Rate Relationship both between classes of devices and within each class

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So now we have the problem:The Inverse Capacity-Rate Relationship in a

Stochastic Setting

But Wait! More device behaviors than just capacity, rate.

• Self Discharge– (Very, very) generally,

higher rate devices have more self-discharge

• Frequency, rise-time, fall-time effects– Irrelevant when using a 10 second time interval

Hope that I’m not out of time…

• Hopefully, I have conveyed the motivation for the project

• No time to get into the algorithm methodology development– Can outline the requirements though……….

Requirements of a Methodology for Storage Control Algorithms

• Must not depend on specific transition functions

• Must be dynamic with regards to the number of devices

• Must satisfy objective– Long run objective: maximize storage and usage

efficiency to minimize amount of storage needed– MCC objective: maximize the amount of energy

stored before time T

The End