1. 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 Powell Sami Yabroudi

2. 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.

3. The Big Idea With Storage Devices: Every storage device has its own power and capacity applications. Pick the one that matches your needs. INVERSE CAPACITY-RATE RELATIONSHIP!!!!!!!

4. 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?

5. 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)

6. 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 (Skip)

7. Other STSES Devices Compressed Air Energy Storage (CAES) 1 = cooler 2 = compressor 3 = air 4 = clutch 5 = generator/motor 6 = power supply 7 = turbine 8 = combustor 9 = fuel 10 = valve 11 = air storage cavity Flywheels Superconducting Electromagnetic Energy Storage (SMES) Inverse Capacity-Rate Relationship both between classes of devices and within each class (Skip)

8. 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

9. 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……….

10. 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

11. The End